|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Optimization of flotation variables for the recovery of hematite particles from BHQ ore显示文摘The technology for beneficiation of banded iron ores containing low iron value is a challenging task due to increasing demand of quality iron ore in India. A flotation process has been developed to treat one such ore, namely banded hematite quartzite (BHQ) containing 41.8wt% Fe and 41.5wt% SiO2,by using oleic acid, methyl isobutyl carbinol (MIBC), and sodium silicate as the collector, frother, and dispersant, respectively. The relative effects of these variables have been evaluated in half-normal plots and Pareto charts using central composite rotatable design. A quadratic response model has been developed for both Fe grade and recovery and optimized within the experimental range. The optimum reagent dosages are found to be as follows: collector concentration of 243.58 g/t, dispersant concentration of 195.67 g/t, pH 8.69, and conditioning time of 4.8 min to achieve the maximum Fe grade of 64.25% with 67.33% recovery. The predictions of the model with regard to iron grade and recovery are in good agreement with the experimental results. | Swagat S. Rath Hrushikesh Sahoo B. Das | 2013 | International Journal of Minerals,Metallurgy and Materials2013，20，7： | 7 |
| 2 | Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review显示文摘The paper reviews and extends an emerging body of theoretical results on deep learning including the conditions under which it can be exponentially better than shallow learning. A class of deep convolutional networks represent an important special case of these conditions, though weight sharing is not the main reason for their exponential advantage. Implications of a few key theorems are discussed, together with new results, open problems and conjectures. | Tomaso Poggio Hrushikesh Mhaskar Lorenzo Rosasco Brando Miranda Qianli Liao | 2017 | International Journal of Automation and computing2017，14，5： | 6 |
| 3 | Potential of (18)~F-FDG-PET as a valuable adjunct to clinical and response assessment in rheumatoid arthritis and seronegative spondyloarthropathies显示文摘AIM: To evaluate the role of fluorine-18-labeled fluorodeoxyglucose positron emission tomography (18F-FDG PET) in various rheumatic diseases and its potential in the early assessment of treatment response in a limited number of patients. METHODS: This study involved 28 newly diagnosed patients, of these 17 had rheumatoid arthritis (RA) and 11 had seronegative spondyloarthropathy (SSA). In the SSA group, 7 patients had ankylosing spondylitis, 3 had psoriatic arthritis, and one had non-specific SSA. Patients with RA were selected as per the American College of Rheumatology criteria. One hour after FDG injection, a whole body PET scan was performed from the skull vertex to below the knee joints using a GE Advance dedicated PET scanner. Separate scans were acquired for both upper and lower limbs. Post-treatment scans were performed in 9 patients in the RA group (at 6-9 wk from baseline) and in 1 patient with psoriatic arthropathy. The pattern of FDG uptake was analysed visually and quantified as maximum standardized uptake value (SUVmax) in a standard region of interest. Metabolic response on the scan was assessed qualitatively and quantitatively and was correlated with clinical assessment. RESULTS: The qualitative FDG uptake was in agreement with the clinically involved joints, erythrocyte sedimentation rate, C-reactive protein values and the clinical assessment by the rheumatologist. All 17 patients in the RA group showed the highest FDG avidity in painful/swollen/tender joints. The uptake pattern was homogeneous, intense and poly-articular in distribution. Hypermetabolism in the regional nodes (axillary nodes in the case of upper limb joint involvement and inguinal nodes in lower limb joints) was a constant feature in patients with RA. Multiple other extra-articular lesions were also observed including thyroid glands (in associated thyroiditis) and in the subcutaneous nodules. Treatment response was better appreciated using SUVmax values than visual interpretation, when compared with clinical evaluation. Four patients showed a favourable response, while 3 had stable disease and 2 showed disease progression. The resolution of regional nodal uptake (axillary or inguinal nodes based on site of joint involvement) in RA following disease modifying anti-rheumatoid drugs was noteworthy, which could be regarded as an additional parameter for identifying responding patients. In the SSA group, uptake in the affected joint was heterogeneous, low grade and nonsymmetrical. In particular, there was intense tendon and muscular uptake corresponding to symptomatic joints. The patients with psoriatic arthritis showed intense FDG uptake in the joints and soft tissue. CONCLUSION: 18F-FDG PET accurately delineates the ongoing inflammatory activity in various rheumatic diseases (both at articular and extra-articular sites) and relates well to clinical symptoms. Different metabolic patterns on FDG-PET scanning in RA and SSA can have important implications for their diagnosis and management in the future with the support of larger studies. FDG-PET molecular imaging is also a sensitive tool in the early assessment of treatment response, especially when using quantitative information. With these benefits, FDG-PET could play a pivotal clinical role in the management of inflammatory joint disorders in the future. | Vishu Vijayant Manjit Sarma Hrushikesh Aurangabadkar Lata Bichile Sandip Basu | 2012 | World Journal of Radiology2012，4，12： | 5 |
| 4 | Decolourization of Methyl Orange using Fenton-like mesoporous Fe 2 O 3 –SiO 2 composite显示文摘 | Niranjan Panda Hrushikesh Sahoo Sasmita Mohapatra | 2010 | Journal of Hazardous Materials2010，，1： | 1 |
| 5 | Mechanical and impact performance of three-phase polyamide 6 nanocomposites显示文摘 | LAURA G JAMES N HRUSHIKESH A | 2015 | Materials and Design2015，66，： | 1 |
| 6 | Decolourization of Methyl Orange Using Fenton-Like Mesoporous Fe203 SiO2 Composite 显示文摘 | NIRANJAN P HRUSHIKESH S SASMITA M | 2011 | 185: 359-3652011，185，： | 1 |
| 7 | Decolourization of Methyl Orange using Fenton-like mesoporous Fe2O3-SiO2 composite 显示文摘 | Niranjan Panda Hrushikesh Sahoo Sasmita Mohapatra | 2011 | Journal of Hazardous Materials2011，185，： | 1 |
| 8 | Decolourization of methyl orange using Fenton-like mesoporous Fe203 - SiO2 composite 显示文摘 | Niranjan Panda Hrushikesh Sahoo Sasmita Mohapatra | 2011 | Journal of Hazardous Materials2011，185，： | 1 |
| 9 | Decolourization of Methyl Orange using Fenton-like mesoporous Fe203-SiO2 composite 显示文摘 | Niranjan Panda Hrushikesh Sahoo Sasmita Mohapatra | 2011 | Hazard Mater2011，185，1： | 1 |
| 10 | Microstructure evolution of AI-Si-10Mg in direct metal laser sintering using phase-field modeling显示文摘Direct metal laser sintering (DMLS) has evolvedas a popular technique in additive manufacturing, whichproduces metallic parts layer-by-layer by the application oflaser power. DMLS is a rapid manufacturing process, andthe properties of the build material depend on the sinteringmechanism as well as the microstructure of the buildmaterial. Thus, the prediction of part microstructures dur-ing the process may be a key factor for process optimiza-tion. In addition, the process parameters play a crucial rolein the microstructure evolution, and need to be controlledeffectively. In this study, the microstructure evolution ofA1-Si-10Mg alloy in DMLS process is studied with the helpof the phase field modeling. A MATLAB code is used tosolve the phase field equations, where the simulationparameters include temperature gradient, laser power andscan speed. From the simulation result, it is found that thetemperature gradient plays a significant role in the evolu-tion of microstructure with different process parameters. Ina single-seed simulation, the growth of the dendriticstructure increases with the increase in the temperaturegradient. When considering multiple seeds, the increasingin temperature gradients leads to the formation of finerdendrites; however, with increasing time, the dendrites joinand grain growth are seen to be controlled at the interface. | Jyotirmoy Nandy Hrushikesh Sarangi Seshadev Sahoo | 2018 | Advances in Manufacturing2018，6，1： | 0 |
| 11 | Detection of Alzheimer’s Disease Progression Using Integrated Deep Learning Approaches显示文摘Alzheimer’s disease(AD)is an intensifying disorder that causes brain cells to degenerate early and destruct.Mild cognitive impairment(MCI)is one of the early signs of AD that interferes with people’s regular functioning and daily activities.The proposed work includes a deep learning approach with a multimodal recurrent neural network(RNN)to predict whether MCI leads to Alzheimer’s or not.The gated recurrent unit(GRU)RNN classifier is trained using individual and correlated features.Feature vectors are concate-nated based on their correlation strength to improve prediction results.The feature vectors generated are given as the input to multiple different classifiers,whose decision function is used to predict the final output,which determines whether MCI progresses onto AD or not.Our findings demonstrated that,compared to individual modalities,which provided an average accuracy of 75%,our prediction model for MCI conversion to AD yielded an improve-ment in accuracy up to 96%when used with multiple concatenated modalities.Comparing the accuracy of different decision functions,such as Support Vec-tor Machine(SVM),Decision tree,Random Forest,and Ensemble techniques,it was found that that the Ensemble approach provided the highest accuracy(96%)and Decision tree provided the lowest accuracy(86%). | Jayashree Shetty Nisha P.Shetty Hrushikesh Kothikar Saleh Mowla Aiswarya Anand Veeraj Hegde | 2023 | Intelligent Automation & Soft Computing2023，37，8： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员