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Varna-based optimization:a novel method for capacitated controller placement problem in SDN

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Frontiers of Computer Science 2020年第3期14卷 87-111页

作者： ashutosh kumar SINGH Saurabh MAURYA Shashank SRIVASTAVA Department of Computer Science&Engineering Motilal Nehru National Institute of Technology AllahabadAllahabad 211004U.P.India

Recently,software defined networking(SDN)is a promising paradigm shift that decouples the control plane from the data *** can centrally monitor and control the network through softwarization,i.e.,*** controllers are a necessity of current SDN based *** multiple controllers in an optimum way is known as controller placement problem(CPP).Earlier,solutions of CPP only concentrated on propagation latency but overlooked the capacity of controllers and the dynamic load on switches,which is a significant factor in real *** this paper,we develop a novel optimization algorithm named varna-based optimization(VBO)and use it to solve *** the best of our knowledge,this is the first attempt to minimize the total average latency of SDN along with the implementation of TLBO and Jaya algorithms to solve CPP for all twelve possible *** experimental results show that TLBO outperforms PSO,and VBO outperforms TLBO and Jaya algorithms in all scenarios for all topologies.

关键词： SDN controller placement CPP latency VBO

Security Attacks in Named Data Networking: A Review and Research Directions

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Journal of Computer Science & Technology 2019年第6期34卷 1319-1350页

作者： Naveen kumar ashutosh kumar Singh Abdul Aleem Shashank Srivastava Department of Computer Science and Engineering Motilal Nehru National Institute of Technology Allahabad Prayagraj 211004India

Contents such as audios,videos,and images,contribute most of the Internet traffic in the current *** content sharing is a tedious *** existing security solutions do not secure data but secure the communicating *** data networking(NDN)secures the data by enforcing the data publisher to sign the *** user can verify the data by using the public key of the *** is resilient to most of the probable security attacks in the TCP/IP model due to its new ***,new types of attacks are possible in *** article surveys the most significant security attacks in NDN such as interest flooding attacks,cache privacy attacks,cache pollution attacks,and content poisoning *** attack is classified according to their behavior and discussed for their detection techniques,countermeasures,and the affected *** article is an attempt to help new researchers in this area to gather the domain knowledge of *** article also provides open research issues that could be addressed by researchers.

关键词： named data networking(NDN) interest flooding attack cache privacy attack cache pollution attack content poisoning attack

Ethanol steam reforming study over ZSM-5 supported cobalt versus nickel catalyst for renewable hydrogen generation

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Chinese Journal of Chemical Engineering 2019年第3期27卷 677-684页

作者： ashutosh kumar Ram Prasad Yogesh Chandra Sharma Department of Chemistry Indian Institute of Technology (Banaras Hindu University) Varanasi Department of Chemical Engineering & Technology Indian Institute of Technology (Banaras Hindu University) Varanasi

The renewable hydrogen generation through ethanol steam reforming is one of the anticipated areas for sustainable hydrogen generation. To elucidate the role of Ni and Co with ZSM-5 support, catalysts were prepared by wet impregnation method and ethanol steam reforming(ESR) was performed. The catalysts were characterized by HR-XRD, ATR–FTIR, HR-SEM, TEM with SAED, EDAX, surface area analyzer and TPR. It had shown complete ethanol conversion at 773 K, but the selectivity in hydrogen generation was found higher for 10% Ni/ZSM-5 catalyst as compared to 10% Co/ZSM-5. The 10% Ni/ZSM-5 catalyst has about 72% hydrogen selectivity at temperature 873 K. It indicates that Ni is a more sustainable catalyst as compared to Co with ZSM-5 support for ESR. The C_2H_4 was found major undesirable products up to 823 K temperature. Nevertheless, the 10% Ni/ZSM-5 catalyst had shown its stability for high temperature(873 K) ESR performance.

关键词： Ethanol steam reforming Zeolite Hydrogen Renewable energy Catalyst

Medical Data Clustering and Classification Using TLBO and Machine Learning Algorithms

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Computers, Materials & Continua 2022年第3期70卷 4523-4543页

作者： ashutosh kumar Dubey Umesh Gupta Sonal Jain Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Institute of Engineering and Technology JK Lakshmipat UniversityJaipurIndia

This study aims to empirically analyze teaching-learning-based optimization(TLBO)and machine learning algorithms using k-means and fuzzy c-means(FCM)algorithms for their individual performance evaluation in terms of clustering and *** the first phase,the clustering(k-means and FCM)algorithms were employed independently and the clustering accuracy was evaluated using different *** the second phase,the non-clustered data obtained from the first phase were preprocessed with *** was performed using k-means(TLBO-KM)and FCM(TLBO-FCM)(TLBO-KM/FCM)*** objective function was determined by considering both minimization and maximization ***-clustered data obtained from the first phase were further utilized and fed as input for threshold *** benchmark datasets were considered from theUniversity of California,Irvine(UCI)Machine Learning Repository for comparative study and *** are breast cancer Wisconsin(BCW),Pima Indians Diabetes,Heart-Statlog,Hepatitis,and Cleveland Heart Disease *** combined average accuracy obtained collectively is approximately 99.4%in case of TLBO-KM and 98.6%in case of *** approach is also capable of finding the dominating *** findings indicate that TLBO-KM/FCM,considering different computational measures,perform well on the non-clustered data where k-means and FCM,if employed independently,fail to provide significant *** different feature sets,the TLBO-KM/FCM and SVM(GS)clearly outperformed all other classifiers in terms of sensitivity,specificity and ***/FCM attained the highest average sensitivity(98.7%),highest average specificity(98.4%)and highest average accuracy(99.4%)for 10-fold cross validation with different test data.

关键词： K-means FCM TLBO TLBO-KM TLBO-FCM TLBO-KM/FCM machine learning algorithms

Epidemiology of lung cancer and approaches for its prediction:a systematic review and analysis

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Chinese Journal of Cancer 2016年第9期35卷 455-467页

作者： ashutosh kumar Dubey Umesh Gupta Sonal Jain Institute of Engineering and Technology JK Lakshmipat UniversityNear

Background: Owing to the use of tobacco and the consumption of alcohol and adulterated food, worldwide cancer incidence is increasing at an alarming and frightening rate. Since the last decade of the twentieth century, lung cancer has been the most common cancer type. This study aimed to determine the global status of lung cancer and to evaluate the use of computational methods in the early detection of lung ***: We used lung cancer data from the United Kingdom(UK), the United States(US), India, and Egypt. For statistical analysis, we used incidence and mortality as well as survival rates to better understand the critical state of lung ***: In the UK and the US, we found a significant decrease in lung cancer mortalities in the period of 1990–2014, whereas, in India and Egypt, such a decrease was not much promising. Additionally, we observed that, in the UK and the US, the survival rates of women with lung cancer were higher than those of men. We observed that the data mining and evolutionary algorithms were efficient in lung cancer ***: Our findings provide an inclusive understanding of the incidences, mortalities, and survival rates of lung cancer in the UK, the US, India, and Egypt. The combined use of data mining and evolutionary algorithm can be efficient in lung cancer detection.

关键词：肺癌流行病学系统预测早期检测临界状态进化算法数据挖掘

Thermoelectric properties of high-entropy rare-earth cobaltates

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Journal of Materiomics 2023年第1期9卷 191-196页

作者： ashutosh kumar Diana Dragoe David Berardan Nita Dragoe ICMMO(UMR CNRS 8182) University of Paris-SaclayOrsay91405France

High-entropy concept introduced with a promising paradigm to obtain exotic physical properties has motivated us to explore the thermoelectric properties of Sr-substituted high-entropy rare-earth cobaltates i.e.,(LaNdPrSmEu)_(1-x)Sr_(x)CoO_(3)(0≤x≤0.10).The structural analysis of the samples,synthesized using the standard solid-state route,confirms the orthorhombic structure with the Pbnm space *** Seebeck coefficient and electrical resistivity decrease with rising Sr concentration as well as with an increase in *** multiple A-site ions in high-entropy rare-earth cobaltates result in an improved Seebeck coefficient(α)compared to La_(0.95)Sr_(0.05)CoO_(3),associated with a decrease in the Cosingle bondOsingle bondCo bond angle,which further enhances the power *** random distribution of cations at the rare-earth site results in a significant lowering of phonon thermal *** a result,a maximum figure of merit(zT)of 0.23 is obtained at 350K for(LaNdPrSmEu)_(0.95)Sr_(0.05)CoO_(3),which is one of the highest values of zT reported at this temperature for oxide *** study shows promise to decouple thermoelectric parameters using the high-entropy concept in several materials.

关键词： materials. temperature. entropy

Performance Estimation of Machine Learning Algorithms in the Factor Analysis of COVID-19 Dataset

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Computers, Materials & Continua 2021年第2期66卷 1921-1936页

作者： ashutosh kumar Dubey Sushil Narang Abhishek kumar Satya Murthy Sasubilli Vicente García-Díaz Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjabIndia Workday Integration Architect Huntington ColumbusOHUSA Department of Computer Science University of OviedoOviedoSpain

Novel Coronavirus Disease(COVID-19)is a communicable disease that originated during December 2019,when China officially informed the World Health Organization(WHO)regarding the constellation of cases of the disease in the city of ***,the disease started spreading to the rest of the *** this point in time,no specific vaccine or medicine is available for the prevention and cure of the *** research works are being carried out in the fields of medicinal and pharmaceutical sciences aided by data analytics and machine learning in the direction of treatment and early detection of this viral *** present report describes the use of machine learning algorithms[Linear and Logistic Regression,Decision Tree(DT),K-Nearest Neighbor(KNN),Support Vector Machine(SVM),and SVM with Grid Search]for the prediction and classification in relation to *** data used for experimentation was the COVID-19 dataset acquired from the Center for Systems Science and Engineering(CSSE),Johns Hopkins University(JHU).The assimilated results indicated that the risk period for the patients is 12–14 days,beyond which the probability of survival of the patient may *** addition,it was also indicated that the probability of death in COVID cases increases with *** death probability was found to be higher in males as compared to *** with Grid search methods demonstrated the highest accuracy of approximately 95%,followed by the decision tree algorithm with an accuracy of approximately 94%.The present study and analysis pave a way in the direction of attribute correlation,estimation of survival days,and the prediction of death *** findings of the present study clearly indicate that machine learning algorithms have strong capabilities of prediction and classification in relation to COVID-19 as well.

关键词： COVID-19 linear and logistic regression DT KNN SVM SVMwith grid search

Poly(ADP-ribose) polymerase inhibition reveals a potential mechanism to promote neuroprotection and treat neuropathic pain

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Neural Regeneration Research 2016年第10期11卷 1545-1548页

作者： Prashanth Komirishetty Aparna Areti Ranadeep Gogoi Ramakrishna Sistla ashutosh kumar Department of Pharmacology and Toxicology National Institute of Pharmaceutical Education and Research (NIPER)-Hyderabad BalanagarIndia Department of Biotechnology National Institute of Pharmaceutical Education and Research (NIPER)-Guwahati Assam India Pharmacology Division Indian Institute of Chemical Technology (IICT) Hyderabad India

Neuropathic pain is triggered by the lesions to peripheral nerves which alter their structure and function. Neuroprotective approaches that jimit the pathological changes and improve the behavioral outcome have been well explained in different experimental models of neuropathy but translation of such strategies to clinics has been disappointing. Experimental evidences revealed the role of free radicals, especially per- oxynitrite after the nerve injury. They provoke oxidative DNA damage and consequent over-activation of the poly（ADP-ribose） polymerase （PARP） upregulates pro-inflammatory pathways, causing bioenergetic crisis and neuronal death. Along with these changes, it causes mitochondrial dysfunction leading to neu- ronal apoptosis. In related preclinical studies agents that neutralize the free radicals and pharmacological inhibitors of PARP have shown benefits in treating experimental neuropathy. This article reviews the in- volvement of PARP over-activation in trauma induced neuropathy and therapeutic significance of PARP inhibitors in the experimental neuropathy and neuropathic pain.

关键词： neuropathic pain poly(ADP-ribose) polymerase neuroinflammation oxidative stress bioenergeticcrisis

Emerging industrial applications of microalgae:challenges and future perspectives

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Systems Microbiology and Biomanufacturing 2021年第4期1卷 411-431页

作者： Aswathy Udayan ashutosh kumar Pandey Pooja Sharma Nidhin Sreekumar Sunil kumar CSIR-National Environmental Engineering Research Institute(CSIR-NEERI) Nehru MargNagpurMaharashtra 440020India Accubits Invent Accubits Technologies Inc.ThiruvananthapuramKerala 695004India

Microalgae are unicellular photosynthetic organisms that have been recently attracted potential interests and have applications in food,nutraceuticals,pharmaceuticals,animal feed,cosmetics,and biofertilizers *** are rich in a variety of high-value bioactive compounds which have potential benefits on human health and can be used for the prevention and curing of many disease *** scale-up and safety issues remain a major challenge in the commercialization of microalgal products in a cost-effective ***,techniques have been developed to overcome these challenges and successfully selling the products derived from microalgae as food,cosmetics and pharmaceutical *** are rich in many nutrients and can be used for the production of functional food and nutraceuticals,safety and regulatory issues are major concerns and extensive research is still needed to make microalgae a commercial success in the *** practical difficulties are involved in making the microalgal food industry commercially *** present review focuses on the industrial applications of microalgae and the challenges faced during commercial production.

关键词： Microalgae Functional foods Nutraceuticals Pharmaceuticals Cosmetics