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| 1 | Influence of metham sodium on suppression of collar rot disease of peanut, in vitro antibiosis, siderophore production and root colonization by a fluorescent Pseudomonas strain FPO4显示文摘 | DILEEP C KUMAR B S | 2000 | Indian Journal of Experimental Bi- ology2000，38，12： | 1 |
| 2 | Induction of systemic resistance against fusarial wilt in pigeon pea through interaction of plant growth promoting rhizobacteria and rhizobia显示文摘 | S. Dutta A.K. Mishra B.S. Dileep Kumar | 2007 | Soil Biology and Biochemistry2007，，2： | 1 |
| 3 | Application of polymerase chain reaction for detection of Vibrio parahaemolyticus associated with tropical seafoods and coastal environment显示文摘 | Dileep V Kumar H S Kumar | 2003 | Letters in Applied Microbiology2003，36，6： | 1 |
| 4 | Convenient approach to 3,4-diarylisoxazoles based on the Suzuki cross- coupling reaction 显示文摘 | Kumar JS Dileep Ho MM Leung JM | 2002 | Advanced Synth Cat2002，344，10： | 1 |
| 5 | Synthesis and characterization of crystallizable anorthite-based glass for a low-temperature cofired ceramic application显示文摘 | DILEEP KUMAR C J SUNNY E K RAGHU N | 2008 | J Am Ceram Soc2008，91，2： | 1 |
| 6 | Curcumin: a potential candidate for matrix metalloproteinase inhibitors显示文摘 | Dileep Kumar Manish Kumar Chinnadurai Saravanan Sushil Kumar Singh | 2012 | Expert Opinion on Therapeutic Targets2012，，10： | 1 |
| 7 | A Novel Method Based on UNET for Bearing Fault Diagnosis显示文摘Reliability of rotating machines is highly dependent on the smooth rolling of bearings.Thus,it is very essential for reliable operation of rotating machines to monitor the working condition of bearings using suitable fault diagnosis and condition monitoring approach.In the recent past,Deep Learning(DL)has become applicable in condition monitoring of rotating machines owing to its performance.This paper proposes a novel bearing fault diagnosis method based on the processing and analysis of the vibration images.The proposed method is the UNET model that is a recent development in DL models.The model is applied to the 2D vibration images obtained by transforming normalized amplitudes of the time-series vibration data samples into the corresponding vibration images.The UNET model performs pixel-level feature learning using the vibration images owing to its unique architecture.The results demonstrate that the model can perform dense predictions without any loss of label information,generally caused by the sliding window labelling method.The comparative analysis with other DL models confirmed the superiority of the UNET model which has achieved maximum accuracy of 98.91%and F1-Score of 99%. | Dileep Kumar Soother Imtiaz Hussain Kalwar Tanweer Hussain Bhawani Shankar Chowdhry Sanaullah Mehran Ujjan Tayab Din Memon | 2021 | Computers, Materials & Continua2021，，10： | 1 |
| 8 | Induction of systemic resistance against fusarial wilt in pigeon pea through interaction of plant growth promoting rhizobacteria and rhizobia显示文摘 | Dutta S Mishra A K Dileep Kumar B S | 2008 | Soil Biology & Biochemistry2008，40，： | 1 |
| 9 | Potential for improving pea production by coinoculation with fluorescent Pseudomonas and Rhizobium显示文摘 | Dileep Kumar B S Berggren I Martensson A M | 2001 | Plant and Soil2001，229，： | 1 |
| 10 | Critical care practice in India:Results of the intensive care unit need assessment survey(ININ2018)显示文摘BACKGROUND A diverse country like India may have variable intensive care units(ICUs)practices at state and city levels.AIM To gain insight into clinical services and processes of care in ICUs in India,this would help plan for potential educational and quality improvement interventions.METHODS The Indian ICU needs assessment research group of diverse-skilled individuals was formed.A pan-India survey'Indian National ICU Needs'assessment(ININ 2018-I)was designed on google forms and deployed from July 23rd-August 25th,2018.The survey was sent to select distribution lists of ICU providers from all 29 states and 7 union territories(UTs).In addition to emails and phone calls,social medial applications-WhatsApp™,Facebook™and LinkedIn™were used to remind and motivate providers.By completing and submitting the survey,providers gave their consent for research purposes.This study was deemed eligible for category-2 Institutional Review Board exempt status.RESULTS There were total 134 adult/adult-pediatrics ICU responses from 24(83%out of 29)states,and two(28%out of 7)UTs in 61 cities.They had median(IQR)16(10-25)beds and most,were mixed medical-surgical,111(83%),with 108(81%)being adult-only ICUs.Representative responders were young,median(IQR),38(32-44)years age and majority,n=108(81%)were males.The consultants were,n=101(75%).A total of 77(57%)reported to have 24 h in-house intensivist.A total of 68(51%)ICUs reported to have either 2:1 or 2≥:1 patient:nurse ratio.More than 80%of the ICUs were open,and mixed type.Protocols followed regularly by the ICUs included sepsis care,ventilator-associated pneumonia(83%each);nutrition(82%),deep vein thrombosis prophylaxis(87%),stress ulcer prophylaxis(88%)and glycemic control(92%).Digital infrastructure was found to be poor,with only 46%of the ICUs reporting high-speed internet availability.CONCLUSION In this large,national,semi-structured,need-assessment survey,the need for improved manpower including;in-house intensivists,and decreasing patient-tonurse ratios was evident.Sepsis was the most common diagnosis and quality and research initiatives to decrease sepsis mortality and ICU length of stay could be prioritized.Additionally,subsequent surveys can focus on digital infrastructure for standardized care and efficient resource utilization and enhancing compliance with existing protocols. | Rahul Kashyap Kirtivardhan Vashistha Chetan Saini Taru Dutt Dileep Raman Vikas Bansal Harpreet Singh Geeta Bhandari Nagarajan Ramakrishnan Harshit Seth Divya Sharma Premkumar Seshadri Mradul Kumar Daga Mohan Gurjar Yash Javeri Salim Surani Joseph Varon 无 | 2020 | World Journal of Critical Care Medicine2020，9，2： | 1 |
| 11 | Environmental concems of underground coal gasification显示文摘 | IMRAN Muhammad KUMAR Dileep KUMAR Naresh | 2014 | Renewable and Sustainable Energy Reviews2014，31，： | 1 |
| 12 | Induction of systemic resistance against fusarial wilt in pigeon pea through interaction of plant growth promoting rhizobacteria and rhizobia显示文摘 | DUTTA S MISHRA A K DILEEP KUMAR B S | 2008 | Soil Biology and Biochemistry2008，40，2： | 1 |
| 13 | Induction of systemic resistance against fusarial wilt in pigeon pea through interaction of plant growth promoting rhizobacteria and rhizobia显示文摘 | S. Dutta A.K. Mishra B.S. Dileep Kumar | 2007 | Soil Biology and Biochemistry2007，，2： | 1 |
| 14 | Passive Damping Characteristics of Carbon Epoxy Composite Plates显示文摘 | Dileep Kumar K V V Subba Rao | 2016 | 材料科学与工程(中英文A版)2016，6，1： | 1 |
| 15 | Synthesis and characterization of crystallizable anorthite-based glass for a low-temperature cotired ceramic application显示文摘 | Dileep Kumar C J Sunny E K Raghu N | 2008 | JAmCeram Soc2008，91，2： | 1 |
| 16 | Environmental concerns of underground coal gasification显示文摘 | Muhammad Imran Dileep Kumar Naresh Kumar | 2014 | Renewable and Sustainable Energy Reviews2014，31，： | 1 |
| 17 | Fault Detection and Identification Using Deep Learning Algorithms in Induction Motors显示文摘Owing to the 4.0 industrial revolution condition monitoring maintenance is widely accepted as a useful approach to avoiding plant disturbances and shutdown.Recently,Motor Current Signature Analysis(MCSA)is widely reported as a condition monitoring technique in the detection and identification of individual andmultiple Induction Motor(IM)faults.However,checking the fault detection and classification with deep learning models and its comparison among them selves or conventional approaches is rarely reported in the literature.Therefore,in this work,wepresent the detection and identification of induction motor faults with MCSA and three Deep Learning(DL)models namely MLP,LSTM,and 1D-CNN.Initially,we have developed the model of Squirrel Cage induction motor in MATLAB and simulated it for single phasing and stator winding faults(SWF)using Fast Fourier Transform(FFT),Short Time Fourier Transform(STFT),and Continuous Wavelet Transform(CWT)to detect and identify the healthy and unhealthy conditions with phase to ground,single phasing and in multiple fault conditions using Motor Current Signature Analysis.The faults impact on stator current is presented in the time and frequency domain(i.e.,power spectrum).The simulation results show that the scalogram has shown good results in time-frequency analysis for fault and showing its impact on the energy of current during individual fault and multiple fault conditions.This is further investigated with three deep learning models(i.e.,MLP,LSTM,and 1D-CNN)for checking the fault detection and identification(i.e.,classification)improvement in a three-phase induction motor.By simulating the three-phase induction motor in various healthy and unhealthy conditions in MATLAB,we have collected current signature data in the time domain,labeled them accordingly and created the 50 thousand samples dataset for DL models.All the DL models are trained and validated with a suitable number of architecture layers.By simulation,the multiclass confusion matrix,precision,recall,and F1-score are obtained in several conditions.The result shows that the stator current signature of the motor can be used to detect individual and multiple faults.Moreover,deep learning models can efficiently classify the induction motor faults based on time-domain data of the stator current signature.In deep learning(DL)models,the LSTM has shown better accuracy among all other three models.These results show that employing deep learning in fault detection and identification of induction motors can be very useful in predictive maintenance to avoid shutdown and production cycle stoppage in the industry. | Majid Hussain Tayab Din Memon Imtiaz Hussain Zubair Ahmed Memon Dileep Kumar | 2022 | Computer Modeling in Engineering & Sciences2022，，11： | 1 |
| 18 | Application of polymerase chain reaction for detection of Vibrio parahaemolyticus associated with tropical seafoods and coastal environment显示文摘 | Dileep V Kumar HS | 2003 | Lett Appl Microbiol2003，36，6： | 1 |
| 19 | 水介质中药物-AOT混合物的温度依赖的混合胶束化行为(英文)显示文摘The mixed micellization behavior of an amphiphilic antidepressant drug amitriptyline hydrochloride(AMT)in the presence of the conventional anionic surfactant sodium bis(2-ethylhexyl)sulfosuccinate(AOT)was studied at five different temperatures and compositions by the conductometric technique.The critical micelle concentration(cmc)and critical micelle concentration at the ideal state(cmcid)values show mixed micelle formation between the components(i.e.,drug and AOT).The micellar mole fractions of the AOT(X1)values calculated using the Rubingh,Motomura,and Rodenas models show a higher contribution of AOT in the mixed micelles.The interaction parameter(β)is negative at all temperatures and the compositions show attractive interactions between the components.The activity coefficients(f1and f2)calculated using the different proposed models are always less than unity indicating non-ideality in the systems.TheΔGmΘ values were found to be negative for all the binary mixed systems.However,ΔHmΘ values for the pure drug as well as the drug-AOT mixed systems are negative at lower temperatures(293.15-303.15 K)and positive at higher temperatures(308.15 K and above).TheΔSmΘ values are positive at all temperatures but their magnitude was higher at T=308.15 K and above.The excess free energy of mixing(ΔGex)determined using the different proposed models also explains the stability of the mixed micelles compared to the pure drug(AMT)and surfactant micelles. | RUB Malik Abdul ASIRI Abdullah M KUMAR Dileep AZUM Naved KHAN Farah | 2014 | 物理化学学报2014，30，4： | 1 |
| 20 | Environmental concerns of underground coal gasification显示文摘 | IMRAN Muhammad KUMAR Dileep KUMAR Naresh | 2014 | Renewable and Sustainable Energy Reviews2014，31，： | 1 |
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