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| 1 | Optimizing submerged arc welding using response surface methodology, regression analysis, and genetic algorithm显示文摘The weld quality is significantly affected by the weld parameters(arc voltage, welding current, nozzle to plate distance and welding speed) in the submerged arc welding(SAW). Bead-on-plate welds were performed on stainless steel plates by automated SAW machine. The experimental data were collected in accordance with the response surface methodology(RSM). In addition to RSM, the regression analysis was performed to set up inputeoutput relationships in the SAW process. It was found that weld parameters define the geometry of weld bead and determine the mechanical properties of the joint. The influence of the input variables on weld bead geometry is represented as graphs. It was found that an increment in voltage increases the bead width but decreases the bead height, whereas the current increment result-in an increment in bead height and no change in bead width. The bead width and height decrease with the increment in the welding speed. With an increment in the nozzle-to-plate distance, bead width decrease, but bead height increases. The value of bead hardness increases with the increment in current but the increment in voltage and travel speed does not have a significant influence on the bead hardness. The predictions from the mathematical model developed and the corresponding experimental results are having a fair agreement. Further, the genetic algorithm(GA) is also used for predicting the weld bead geometry. | Ajitanshu Vedrtnam Gyanendra Singh Ankit Kumar | 2018 | Defence Technology(防务技术)2018，14，3： | 7 |
| 2 | Development of intelligent computing expert system models for shelf life prediction of soft mouth melting milk cakes 显示文摘 | Goyal Sumit Goyal Gyanendra Kumar | 2011 | International Journal of Computer Applications2011，25，9： | 1 |
| 3 | Plasma Homocysteine level and its clinical correlation with type 2 diabetes mellitus and its complications显示文摘 | Satyendra Kumar Sonkar Gyanendra Kumar Sonkar Deepika Soni Dheeraj Soni Kauser Usman | 2014 | International Journal of Diabetes in Developing Countries2014，，： | 1 |
| 4 | Central post-stroke pain: Current evidence 显示文摘 | Kumar Gyanendra Soni Chetan Rasiklal | 2009 | Journal of the Neurological Sciences2009，284，12： | 1 |
| 5 | Penumbra, the basis of neuroimaging in acute stroke treatment Current evidence 显示文摘 | Gyanendra Kumar Munish Kumar Goyal Pradeep Kumar Sahota | 2013 | Journal of the Neurological Sciences2013，10，1： | 1 |
| 6 | Cascade Artificial Neural Net- work Models for Predicting Shelf Life of Processed Cheese显示文摘 | Sumit Goyal Gyanendra Kumar Goyal | 2013 | Joumal of Advances in Information Technology2013，4，2： | 1 |
| 7 | Miliary nodules due to secondary pulmonary hemosiderosis in rheumatic heart disease显示文摘Pulmonary hemosiderosis is defined as the clinical and functional consequence of iron overload of the lungs,which usually occurs due to recurrent intra-alveolar bleeding.It can manifest as miliary mottling and should be entertained in the differential diagnosis of patients presenting with miliary nodules on chest radiography,especially those with mitral stenosis.The management of secondary pulmonary hemosiderosis secondary to valvular heart disease includes valvuloplasty and/or valve replacement.The radiological opacities may disappear with successful treatment of the underlying valvular disease in many patients.However,they may persist with no physiological impairment to the patient.Here,we present a 32-year-old man with mitral stenosis who presented with fever and miliary shadows on chest radiography,which was ultimately diagnosed as secondary pulmonary hemosiderosis. | Gyanendra Agrawal Ritesh Agarwal Manoj Kumar Rohit Venkat Mahesh Rakesh Kumar Vasishta | 2011 | World Journal of Radiology2011，3，2： | 1 |
| 8 | Telomere Length Attrition, a Marker of Biological Senescence, Is Inversely Correlated with Triglycerides and Cholesterol in South Asian Males with Type 2 Diabetes Mellitus显示文摘 | Alison L. Harte Nancy F. da Silva Michelle A. Miller Francesco P. Cappuccio Ann Kelly Joseph P. O’Hare Anthony H. Barnett Nasser M. Al-Daghri Omar Al-Attas Majed Alokail Shaun Sabico Gyanendra Tripathi Srikanth Bellary Sudhesh Kumar Philip G. McTernan Tos | 2012 | Experimental Diabetes Research2012，，： | 1 |
| 9 | Artificial Humming Bird Optimization with Siamese Convolutional Neural Network Based Fruit Classification Model显示文摘Fruit classification utilizing a deep convolutional neural network(CNN)is the most promising application in personal computer vision(CV).Profound learning-related characterization made it possible to recognize fruits from pictures.But,due to the similarity and complexity,fruit recognition becomes an issue for the stacked fruits on a weighing scale.Recently,Machine Learning(ML)methods have been used in fruit farming and agriculture and brought great convenience to human life.An automated system related to ML could perform the fruit classifier and sorting tasks previously managed by human experts.CNN’s(convolutional neural networks)have attained incredible outcomes in image classifiers in several domains.Considering the success of transfer learning and CNNs in other image classifier issues,this study introduces an Artificial Humming Bird Optimization with Siamese Convolutional Neural Network based Fruit Classification(AMO-SCNNFC)model.In the presented AMO-SCNNFC technique,image preprocessing is performed to enhance the contrast level of the image.In addition,spiral optimization(SPO)with the VGG-16 model is utilized to derive feature vectors.For fruit classification,AHO with end to end SCNN(ESCNN)model is applied to identify different classes of fruits.The performance validation of the AMO-SCNNFC technique is tested using a dataset comprising diverse classes of fruit images.Extensive comparison studies reported improving the AMOSCNNFC technique over other approaches with higher accuracy of 99.88%. | T.Satyanarayana Murthy Kollati Vijaya Kumar Fayadh Alenezi E.Laxmi Lydia Gi-Cheon Park Hyoung-Kyu Song Gyanendra Prasad Joshi Hyeonjoon Moon | 2023 | Computer Systems Science & Engineering2023，47，11： | 1 |
| 10 | Depletion of Reduced Glutathione, Ascorbic Acid, Vitamin E and Antioxidant Defence Enzymes in a Healing Cutaneous Wound显示文摘 | Arti Shukla Anamika Mohan Rasik Gyanendra Kumar Patnaik | 1997 | Free Radical Research1997，，2： | 1 |
| 11 | Microwave -assisted, solvent -free, parallel syntheses and elucidation of reaction mechanism for the formation of some novel tetraaryl imidazoles of biological interest显示文摘 | Prashantha Kumar B R Gyanendra Kumar Sharma S Srinath | 2009 | Journal of Heterocyclic Chemistry2009，46，2： | 1 |
| 12 | 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 |
| 13 | Metaheuristics Based Node Localization Approach for Real-Time Clustered Wireless Networks显示文摘In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,etc.At the same time,proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks.This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization(IM-EECNL)approach for real-time wireless networks.The proposed IM-EECNL technique involves two major processes namely node localization and clustering.Firstly,Chaotic Water Strider Algorithm based Node Localization(CWSANL)technique to determine the unknown position of the nodes.Secondly,an Oppositional Archimedes Optimization Algorithm based Clustering(OAOAC)technique is applied to accomplish energy efficiency in the network.Besides,the OAOAC technique derives afitness function comprising residual energy,distance to cluster heads(CHs),distance to base station(BS),and load.The performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency.A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio(PDR)of 0.985. | R.Bhaskaran P.S.Sujith Kumar G.Shanthi L.Raja Gyanendra Prasad Joshi Woong Cho | 2023 | Computer Systems Science & Engineering2023，44，1： | 0 |
| 14 | 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 |
| 15 | Deep Learning Enabled Disease Diagnosis for Secure Internet of Medical Things显示文摘In recent times,Internet of Medical Things(IoMT)gained much attention in medical services and healthcare management domain.Since healthcare sector generates massive volumes of data like personal details,historical medical data,hospitalization records,and discharging records,IoMT devices too evolved with potentials to handle such high quantities of data.Privacy and security of the data,gathered by IoMT gadgets,are major issues while transmitting or saving it in cloud.The advancements made in Artificial Intelligence(AI)and encryption techniques find a way to handle massive quantities of medical data and achieve security.In this view,the current study presents a new Optimal Privacy Preserving and Deep Learning(DL)-based Disease Diagnosis(OPPDL-DD)in IoMT environment.Initially,the proposed model enables IoMT devices to collect patient data which is then preprocessed to optimize quality.In order to decrease the computational difficulty during diagnosis,Radix Tree structure is employed.In addition,ElGamal public key cryptosystem with Rat Swarm Optimizer(EIG-RSO)is applied to encrypt the data.Upon the transmission of encrypted data to cloud,respective decryption process occurs and the actual data gets reconstructed.Finally,a hybridized methodology combining Gated Recurrent Unit(GRU)with Convolution Neural Network(CNN)is exploited as a classification model to diagnose the disease.Extensive sets of simulations were conducted to highlight the performance of the proposed model on benchmark dataset.The experimental outcomes ensure that the proposed model is superior to existing methods under different measures. | Sultan Ahmad Shakir Khan Mohamed Fahad Al.Ajmi Ashit Kumar Dutta L.Minh Dang Gyanendra Prasad Joshi Hyeonjoon Moon | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 16 | DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems显示文摘The exponential growth of data necessitates an effective data storage scheme,which helps to effectively manage the large quantity of data.To accomplish this,Deoxyribonucleic Acid(DNA)digital data storage process can be employed,which encodes and decodes binary data to and from synthesized strands of DNA.Vector quantization(VQ)is a commonly employed scheme for image compression and the optimal codebook generation is an effective process to reach maximum compression efficiency.This article introduces a newDNAComputingwithWater StriderAlgorithm based Vector Quantization(DNAC-WSAVQ)technique for Data Storage Systems.The proposed DNAC-WSAVQ technique enables encoding data using DNA computing and then compresses it for effective data storage.Besides,the DNAC-WSAVQ model initially performsDNA encoding on the input images to generate a binary encoded form.In addition,aWater Strider algorithm with Linde-Buzo-Gray(WSA-LBG)model is applied for the compression process and thereby storage area can be considerably minimized.In order to generate optimal codebook for LBG,the WSA is applied to it.The performance validation of the DNAC-WSAVQ model is carried out and the results are inspected under several measures.The comparative study highlighted the improved outcomes of the DNAC-WSAVQ model over the existing methods. | A.Arokiaraj Jovith S.Rama Sree Gudikandhula Narasimha Rao K.Vijaya Kumar Woong Cho Gyanendra Prasad Joshi Sung Won Kim | 2023 | Computers, Materials & Continua2023，，3： | 0 |
| 17 | Pharmacological, Ethnomedicinal, and Evidence-Based Comparative Review of Moringa oleifera Lam.(Shigru) and Its Potential Role in the Management of Malnutrition in Tribal Regions of India, Especially Chhattisgarh显示文摘Moringa oleifera Lam.(Shigru)(Moringaceae family) is a traditional medicine used for control of diabetes, obesity, asthma, and cardiac,liver, gastrointestinal, infective, and brain disorders, such as depression and Alzheimer's disease. In Ayurvedic literature, Shigru is among few drugs having Balya(nourishing) as well as Medohara(antiobesity) property. This review focuses on valid connections between the properties documented in ancient literature and current pharmacological knowledge of Moringa, including pharmacological actions, phytochemistry,botanical description, and how Moringa can tackle malnutrition in India, especially Chhattisgarh. All information about M. oleifera was obtained from electronic scientific databases such as PubMed, Web of Science, Scopus, ScienceDirect, Elsevier, Google Scholar, Traditional Knowledge Digital Library, and Indian Traditional Books(Ancient Ayurveda literatures, The Wealth of India, and The Ayurvedic Formulary of India), postgraduate/doctoral thesis, and googling the keyword M. oleifera. M. oleifera have anti-oxidant, antimicrobial, anti-diabetic,anti-obesity, anti-inflammatory, cardioprotective, hepatoprotective, neuroprotective, gastroprotective, wound-healing properties and it can potentially tackle malnutrition. This review describes the key information related to botanical description of M. oleifera, phytochemistry,pharmacological actions, clinical studies, toxicological studies, better utilization as food therapeutics, and ethnobotanical and evidence-based comparative review of M. oleifera. M. oleifera can effectively tackle malnutrition in India, especially Chhattisgarh. The authors emphasize the need for future in-depth ethnopharmacological lead-based research and clinical studies to expand M. oleifera pharmacological activities,clinical efficacy, and safety. | Kishor Sonewane Sharda Swaroop Chouhan Mariappan Rajan Nagendra Singh Chauhan Om Prakash Rout Awanish Kumar Gyanendra Singh Baghel Prashant Kumar Gupta | 2022 | World Journal of Traditional Chinese Medicine2022，8，3： | 0 |
| 18 | Acute onset clozapine-induced hyperglycaemia: A case report显示文摘Clozapine is an atypical antipsychotic which is described to have higher efficacy among all available antipsychotic medications. Clozapine is reserved especially for resistant schizophrenia due to its side effects. Clozapine-induced metabolic syndrome and hyperglycaemia are common longterm side effects and are responsible for increased mortality in patients with schizophrenia. In this case, a patient with resistant schizophrenia was presented with acute-onset hyperglycaemia and delirium with the use of clozapine within a week. Withdrawal of clozapine in the patient led to the improvement in delirium and hyperglycaemia without the use of any hypoglycaemic agent. This case s叩ports the notion that in certain cases clozapine can induce hyperglycemia through possible direct pathophysiological mechanisms within a shorter time frame. | Pradeep Kumar Dheerendra Kumar Mishra Nimisha Mishra Sunil Ahuja Gyanendra Raghuvanshi Vijay Niranjan | 2019 | General Psychiatry2019，32，2： | 0 |
| 19 | Optimized Load Balancing Technique for Software Defined Network显示文摘Software-defined networking is one of the progressive and prominent innovations in Information and Communications Technology.It mitigates the issues that our conventional network was experiencing.However,traffic data generated by various applications is increasing day by day.In addition,as an organization’s digital transformation is accelerated,the amount of information to be processed inside the organization has increased explosively.It might be possible that a Software-Defined Network becomes a bottleneck and unavailable.Various models have been proposed in the literature to balance the load.However,most of the works consider only limited parameters and do not consider controller and transmission media loads.These loads also contribute to decreasing the performance of Software-Defined Networks.This work illustrates how a software-defined network can tackle the load at its software layer and give excellent results to distribute the load.We proposed a deep learning-dependent convolutional neural networkbased load balancing technique to handle a software-defined network load.The simulation results show that the proposed model requires fewer resources as compared to existing machine learning-based load balancing techniques. | Aashish Kumar Darpan Anand Sudan Jha Gyanendra Prasad Joshi Woong Cho | 2022 | Computers, Materials & Continua2022，，7： | 0 |
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