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| 1 | A simple way to identify insulin resistance in non-diabetic acute coronary syndrome patients with impaired fasting glucose显示文摘 | Sayantan Ray Ashit Bairagi Santanu Guha Satyabrata Ganguly Debes Ray Ashis Basu Anirban Sinha | 2012 | Indian Journal of Endocrinology and Metabolism2012，，8： | 1 |
| 2 | An Enantioselective synthesis of the antifungal agent(2R,3R)-2-(2,4-difluorophenyl)-3-(methylsulfonyl)-1-(1,2,4-triazol-1-yl)-2-butanol显示文摘 | Frank B Ashit K G Viyyoor M | 1995 | Synlett1995，，11： | 1 |
| 3 | Role of lithology, weathering and precipitation on water chemistry of lakes from Larsemann Hills and Schirmacher Oasis of East Antarctica显示文摘Schirmacher Oasis and Larsemann Hills areas represent two different periglacial environments of East Antarctica. Schirmacher Oasis is characterized by a vast stretch of ice-shelf in the north and East Antarctic Ice Sheet(EAIS) to its south. Whereas, in Larsemann Hills area the northern and north-western boundary is coastal area and EAIS in the southern part,exhibiting polar lowland between the marine and continental glacial ecosystems. Physico-chemical parameters of water samples from different lakes of both of these two distinct locations are quite contrasting and have indicated influence of lithology, weathering, evaporation and precipitation. The lake water chemistry in Larsemann Hills area is mainly governed by the lithology of the area while Schirmacher lakes exhibit influence of precipitation and rock composition. All major ions of lake waters indicate balanced ionic concentrations. The atmospheric precipitation has significantly modified the ionic distributions in the lakes and channels. Carbonation is the main proton supplying geochemical reactions involved in the rock weathering and this is an important mechanism which controls the hydrochemistry. The lake water hydrochemistry differs widely not only between two distant periglacial zones but also within a short distance of a single periglacial entity, indicating influence of territorial climate over hydrochemistry. | Rajesh ASTHANA Prakash K SHRIVASTAVA Hari B SRIVASTAVA Ashit K SWAIN Mirza Javed BEG Amit DHARWADKAR | 2019 | Advances in Polar Science2019，30，1： | 1 |
| 4 | Intraoperative Localization of Insulinoma and Normal Pancreas Using Invisible Near-Infrared Fluorescent Light显示文摘 | Joshua H. Winer MD Hak Soo Choi PhD Summer L. Gibbs-Strauss PhD Yoshitomo Ashitate MD Yolonda L. Colson MD PhD John V. Frangioni MD PhD | 2010 | Annals of Surgical Oncology2010，，4： | 1 |
| 5 | Enantioselective syntheses of carbocyclic ribavirin and its analogs: linear versus convergent approaches显示文摘 | Rongze Kuang* Ashit K Ganguly* Tze-Ming Chan Birendra N Pramanik David J Blythin Andrew T McPhail Anil.K Saksena | 2000 | Tetrahedron Letters2000，，49： | 1 |
| 6 | Near-infrared fluorescence imaging of thoracic duct anatomy and function in open surgery and video-assisted thoracic surgery显示文摘 | Yoshitomo Ashitate Eiichi Tanaka Alan Stockdale Hak Soo Choi John V. Frangioni | 2011 | The Journal of Thoracic and Cardiovascular Surgery2011，，1： | 1 |
| 7 | Predictors of adequacy of arteri ovenous fistulas in hemodidysis patients显示文摘 | PaulE Miller Ashit TolwaniC TolwaniC etal | | 0，，： | 1 |
| 8 | Upregulation of solu ble vascular endothelial growth factor receptor type1 by endogenous prostacyclin inhibitor coupling factor 6 in vascular endotheli al cells: a role of acidosis induced c-Src activation 显示文摘 | Echizen T Osanai T Ashitate T | 2009 | Hyper tensRes2009，32，3： | 1 |
| 9 | Overex-pression of coupling factor6causes cardiac dysfunction under high-salt diet in mice显示文摘 | ASHITATE T OSANAI T TANAKA M | 2010 | J Hypertens2010，28，11： | 1 |
| 10 | Inflammatory pseudotumor of the spleen in a 6-year-old child:a clinieopathologic study显示文摘 | Ashit Sarker Mary Davis Caroline An | 2003 | Arch Pathol Lab Med2003，127，3： | 1 |
| 11 | Use of extremely high specific activity xylanase in ECF and TCF pulp bleaching显示文摘 | ASHIT K S COOPER A ADOLPHSON R B | 2000 | Tappi2000，83，8： | 1 |
| 12 | Overexpression of coupling factor 6 causes cardiac dysfunction under high-salt diet in mice 显示文摘 | Ashitate T Osanai T Tanaka M | 2011 | J Hypertens2011，28，11： | 1 |
| 13 | Overexpression of coupling factor 6 causes cardiac dysfunction under high-salt diet in mice 显示文摘 | Ashitate T Osanai T Tanaka M | 2010 | J Hypertens2010，28，11： | 1 |
| 14 | Use of an extremely high specific activity xylanase in ECF and TCF pulp bleaching显示文摘 | Ashit K Shah Coop A Ryan B Adolphson | 2000 | Tappi2000，83，8： | 1 |
| 15 | A closed- form nenural network for discriminatory feature extration from high - dimensional data显示文摘 | Ashit talukder David casasent | 2001 | Neural networks2001，，14： | 1 |
| 16 | Use of extremely high specific activity xylanase in ECF and TCF pulp bleaching显示文摘 | Ashit K Shah A Cooper Ryan B Adolphson | 2000 | Tappi2000，83，8： | 1 |
| 17 | Optimal Deep Learning Enabled Statistical Analysis Model for Traffic Prediction显示文摘Due to the advances of intelligent transportation system(ITSs),traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control,navigation,route mapping,etc.The traffic prediction model aims to predict the traffic conditions based on the past traffic data.For more accurate traffic prediction,this study proposes an optimal deep learning-enabled statistical analysis model.This study offers the design of optimal convolutional neural network with attention long short term memory(OCNN-ALSTM)model for traffic prediction.The proposed OCNN-ALSTM technique primarily preprocesses the traffic data by the use of min-max normalization technique.Besides,OCNN-ALSTM technique was executed for classifying and predicting the traffic data in real time cases.For enhancing the predictive outcomes of the OCNN-ALSTM technique,the bird swarm algorithm(BSA)is employed to it and thereby overall efficacy of the network gets improved.The design of BSA for optimal hyperparameter tuning of the CNN-ALSTM model shows the novelty of the work.The experimental validation of the OCNNALSTM technique is performed using benchmark datasets and the results are examined under several aspects.The simulation results reported the enhanced outcomes of the OCNN-ALSTM model over the recent methods under several dimensions. | Ashit Kumar Dutta S.Srinivasan S.N.Kumar T.S.Balaji Won Il Lee Gyanendra Prasad Joshi Sung Won Kim | 2022 | Computers, Materials & Continua2022，，9： | 1 |
| 18 | An Optimization Approach for Convolutional Neural Network Using Non-Dominated Sorted Genetic Algorithm-Ⅱ显示文摘In computer vision,convolutional neural networks have a wide range of uses.Images representmost of today’s data,so it’s important to know how to handle these large amounts of data efficiently.Convolutional neural networks have been shown to solve image processing problems effectively.However,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher accuracy.This technique is time consuming and requires a lot of work and domain knowledge.Designing a convolutional neural network architecture is a classic NP-hard optimization challenge.On the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and inconvenient.Various approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random selection.To address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized hyperparameters.This study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN model.In addition,different types and parameter ranges of existing genetic algorithms are used.Acomparative study was conducted with various state-of-the-art methodologies and algorithms.Experiments have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature. | Afia Zafar Muhammad Aamir Nazri Mohd Nawi Ali Arshad Saman Riaz Abdulrahman Alruban Ashit Kumar Dutta Badr Almutairi Sultan Almotairi | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 19 | Design of QoS Aware Routing Protocol for IoT Assisted Clustered WSN显示文摘In current days,the domain of Internet of Things(IoT)and Wireless Sensor Networks(WSN)are combined for enhancing the sensor related data transmission in the forthcoming networking applications.Clustering and routing techniques are treated as the effective methods highly used to attain reduced energy consumption and lengthen the lifetime of the WSN assisted IoT networks.In this view,this paper presents an Ensemble of Metaheuristic Optimization based QoS aware Clustering with Multihop Routing(EMOQoSCMR)Protocol for IoT assisted WSN.The proposed EMO-QoSCMR protocol aims to achieve QoS parameters such as energy,throughput,delay,and lifetime.The proposed model involves two stage processes namely clustering and routing.Firstly,the EMO-QoSCMR protocol involves crossentropy rain optimization algorithm based clustering(CEROAC)technique to select an optimal set of cluster heads(CHs)and construct clusters.Besides,oppositional chaos game optimization based routing(OCGOR)technique is employed for the optimal set of routes in the IoT assisted WSN.The proposed model derives a fitness function based on the parameters involved in the IoT nodes such as residual energy,distance to sink node,etc.The proposed EMOQoSCMR technique has resulted to an enhanced NAN of 64 nodes whereas the LEACH,PSO-ECHS,E-OEERP,and iCSHS methods have resulted in a lesser NAN of 2,10,42,and 51 rounds.The performance of the presented protocol has been evaluated interms of energy efficiency and network lifetime. | Ashit Kumar Dutta S.Srinivasan Bobbili Prasada Rao B.Hemalatha Irina V.Pustokhina Denis A.Pustokhin Gyanendra Prasad Joshi | 2022 | Computers, Materials & Continua2022，，5： | 0 |
| 20 | Autonomous Unmanned Aerial Vehicles Based Decision Support System for Weed Management显示文摘Recently,autonomous systems become a hot research topic among industrialists and academicians due to their applicability in different domains such as healthcare,agriculture,industrial automation,etc.Among the interesting applications of autonomous systems,their applicability in agricultural sector becomes significant.Autonomous unmanned aerial vehicles(UAVs)can be used for suitable site-specific weed management(SSWM)to improve crop productivity.In spite of substantial advancements in UAV based data collection systems,automated weed detection still remains a tedious task owing to the high resemblance of weeds to the crops.The recently developed deep learning(DL)models have exhibited effective performance in several data classification problems.In this aspect,this paper focuses on the design of autonomous UAVs with decision support system for weed management(AUAV-DSSWM)technique.The proposed AUAV-DSSWM technique intends to identify the weeds by the use of UAV images acquired from the target area.Besides,the AUAV-DSSWM technique primarily performs image acquisition and image pre-processing stages.Moreover,the Adam optimizer with You Only Look Once Object Detector-(YOLOv3)model is applied for the detection of weeds.For the effective classification of weeds and crops,the poor and rich optimization(PRO)algorithm with softmax layer is applied.The design of Adam optimizer and PRO algorithm for the parameter tuning process results in enhanced weed detection performance.A wide range of simulations take place on UAV images and the experimental results exhibit the promising performance of the AUAV-DSSWM technique over the other recent techniques with the accy of 99.23%. | Ashit Kumar Dutta Yasser Albagory Abdul Rahaman Wahab Sait Ismail Mohamed Keshta | 2022 | Computers, Materials & Continua2022，，10： | 0 |
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