CuO–TiO_(2) based self-powered broad band photodetector

An efficient room-temperature self-powered,broadband(300 nm–1100 nm)photodetector based on a CuO–TiO_(2)/TiO_(2)/p-Si(100)heterostructure is demonstrated.The CuO–TiO_(2)nanocomposites were grown in a two-zone horizontal tube furnace on a 40 nm TiO_(2)thin film deposited on a p-type Si(100)substrate.The CuO–TiO_(2)/TiO_(2)/p-Si(100)devices exhibited excellent rectification characteristics under dark and individual photoillumination conditions.The devices showed remarkable photo-response under broadband(300–1100 nm)light illumination at zero bias voltage,indicating the achievement of highly sensitive self-powered photodetectors at visible and near-infrared light illuminations.The maximum response of the devices is observed at 300 nm for an illumination power of 10 W.The response and recovery times were calculated as 86 ms and 78 ms,respectively.Moreover,under a small bias,the devices showed a prompt binary response by altering the current from positive to negative under illumination conditions.The main reason behind this binary response is the low turn-on voltage and photovoltaic characteristics of the devices.Under illumination conditions,the generation of photocurrent is due to the separation of photogenerated electron-hole pairs within the built-in electric field at the CuO–TiO_(2)/TiO_(2)interface.These characteristics make the CuO–TiO_(2)/TiO_(2)broadband photodetectors suitable for applications that require high response speeds and self-sufficient functionality.

Software Defect Prediction Using Hybrid Machine Learning Techniques: A Comparative Study

When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross-project software defect prediction is elaborated through an innovative hybrid machine learning framework. The proposed technique combines an advanced deep neural network architecture with ensemble models such as Support Vector Machine (SVM), Random Forest (RF), and XGBoost. The study evaluates the performance by considering multiple software projects like CM1, JM1, KC1, and PC1 using datasets from the PROMISE Software Engineering Repository. The three hybrid models that are compared are Hybrid Model-1 (SVM, RandomForest, XGBoost, Neural Network), Hybrid Model-2 (GradientBoosting, DecisionTree, LogisticRegression, Neural Network), and Hybrid Model-3 (KNeighbors, GaussianNB, Support Vector Classification (SVC), Neural Network), and the Hybrid Model 3 surpasses the others in terms of recall, F1-score, accuracy, ROC AUC, and precision. The presented work offers valuable insights into the effectiveness of hybrid techniques for cross-project defect prediction, providing a comparative perspective on early defect identification and mitigation strategies. .

HV Process Model of Software Development

Software Development Life Cycle (SDLC) is one of the major ingredients for the development of efficient software systems within a time frame and low-cost involvement. From the literature, it is evident that there are various kinds of process models that are used by the software industries for the development of small, medium and long-term software projects, but many of them do not cover risk management. It is quite obvious that the improper selection of the software development process model leads to failure of the software products as it is time bound activity. In the present work, a new software development process model is proposed which covers the risks at any stage of the development of the software product. The model is named a Hemant-Vipin (HV) process model and may be helpful for the software industries for development of the efficient software products and timely delivery at the end of the client. The efficiency of the HV process model is observed by considering various kinds of factors like requirement clarity, user feedback, change agility, predictability, risk identification, practical implementation, customer satisfaction, incremental development, use of ready-made components, quick design, resource organization and many more and found through a case study that the presented approach covers many of parameters in comparison of the existing process models. .

Prevention and treatment of hypoxia-induced colorectal cancer damage in albino Wister rats

Background:In the early metastasis of colon cancer,cancer cells detach,migrate,and infiltrate surrounding tissues,including lymph vessels and blood vessels.Tumor heterogeneity arises from both tumor cells and distinct microenvironments.Maldistribution of blood vessels,creates hypoxic regions within the tumors,fostering cancer stem cell-like properties due to reduced oxygen and nutrient supply.Under hypoxia,tumor cells shift to a glycolytic pathway,producing more lactic acid that acidifies the microenvironment and leads to unstable heart rate variability(HRV)factors,weight disparity,and a higher incidence of aberrant crypt foci(ACF).These hypoxic-induced parameters promote cancer cell invasion,increase radiation resistance,and facilitate cancer cell migration.Methods:In this study,we induced hypoxia-preneoplastic colon damage in albino Wister rats by administrating 1,2-dimethyl hydrazine(DMH).After successfully creating a hypoxic environment in albino Wister rats,resulting in preneoplastic colon damage,we randomly allocated Wistar albino rats into seven groups,each containing 8 animals,and conducted a 6-week study.Group 1-Normal control(administered 1 mM EDTA+saline,2 ml/kg/day,p.o.);group 2-Toxic control(administered DMH,30 mg/kg/week,s.c.);group 3-Standard treatment(DMH,30 mg/kg/week,s.c.for 6 weeks),followed by 5-fluorouracil and Leucovorin(25 mg/kg each on 1^(st),3^(rd),7^(th),and 10^(th) days,i.p.after 6 weeks administration of DMH);group 4-Low dose of P1(DMH,30 mg/kg/week,s.c.+P1,2 mg/kg,i.v.,weekly for 3 weeks);group 5-High dose P1(DMH,30 mg/kg/week,s.c.+P1,4 mg/kg,i.v.,weekly for 3 weeks),group 6-Low dose of P2(DMH,30 mg/kg/week,s.c.,+P2,2 mg/kg,i.v.,weekly for 3 weeks),group 7-High dose of P2(DMH,30 mg/kg/week,s.c.,+P2,4 mg/kg,i.v.weekly for 3 weeks).Results:DMH-treated rats exhibited alterations in HRV factors,weight disparity,elevated gastric pH,increased total acidity,a higher incidence of ACF,and changes in antioxidant markers(TBARs,SOD,catalase,GSH).Brightfield microscopy at 40x magnification revealed the presence of large crypts within aberrant crypt foci in the toxic control group.Conclusion:Treatment groups P1 and P2 containing triazine derivatives initiated proteasomal degradation of Hypoxia Inducible Factor-1α(HIF-1α)by activating Prolyl Hydroxylase(PHDs)pathways.HIF-1αunder a hypoxic environment is responsible for activating a multitude of genes involved in angiogenesis,metastasis,invasiveness,pH changes,metabolic reprogramming,stem cell maintenance,resistance to radiation,and downstream regulation of the immune system.Treatment with P1 and P2 groups helped minimize the ACF count and restored HRV factors,weight disparity,pH levels,total acidity,and oxidative balance.Our findings emphasize the potential role of 1,2,4-triazine derivatives in suppressing hypoxia-induced colon carcinogenesis.

Nested Levels of Hybrid Cryptographical Technique for Secure Information Exchange

Data security is a very important part of data transmission over insecure channels connected through high-speed networks. Due to COVID-19, the use of data transmission over insecure channels has increased in an exponential manner. Hybrid cryptography provides a better solution than a single type of cryptographical technique. In this paper, nested levels of hybrid cryptographical techniques are investigated with the help of Deoxyribonucleic Acid (DNA) and Paillier cryptographical techniques. In the first level, information will be encrypted by DNA and at the second level, the ciphertext of DNA will be encrypted by Paillier cryptography. At the decryption time, firstly Paillier cryptography will be processed, and then DAN cryptography will be processed to get the original text. The proposed algorithm follows the concept of Last Encryption First Decryption (LEFD) at the time of decryption. The computed results are depicted in terms of tables and graphs.

Photoluminescence behavior and visible light photocatalytic activity of ZnO,ZnO/ZnS and ZnO/ZnS/α-Fe_2O_3 nanocomposites

In order to achieve effective, economic, and easily achievable photocatalyst for the degradation of dye methyl orange（MeO）, ZnO, ZnO/ZnS and ZnO/ZnS/α-Fe2O3 nanocomposites were prepared by simple chemical synthetic route in the aqueous medium. Phase, crystallinity, surface structure and surface behavior of the synthesized materials were determined by X-ray diffraction（XRD） and Brunauer-Emmett-Teller analysis（BET） techniques. XRD study established formation of good crystalline ZnO, ZnO/ZnS and ZnO/ZnS/α-Fe2O3 nanomaterials. By using intensity of constituent peaks in the XRD pattern, the compositions of nanocomposites were determined. From the BET analysis, the prepared materials show mesoporous behavior, type Ⅳ curves along with H4 hysteresis. The ZnO/ZnS/α-Fe2O3 composite shows the largest surface area among three materials. From the UV-visible spectra, the band gap energy of the materials was determined. Photoluminescence spectra（PL） were used to determine the emission behavior and surface defects in the materials. In PL spectra, the intensity of UV peak of ZnO/ZnS is lowered than that of ZnO while in case of ZnO/ZnS/α-Fe2O3, the intensity further decreased. The visible emission spectra of ZnO/ZnS increased compared with ZnO while in ZnO/ZnS/α-Fe2O3 it is further increased compared with ZnO/ZnS. The as-synthesized materials were used as photocatalysts for the degradation of dye MeO. The photo-degradation data revealed that the ZnO/ZnS/α-Fe2O3 is the best photocatalyst among three specimens for the degradation of dye MeO. The decrease of intensity of UV emission peak and the increase of intensity of visible emission cause the decrease of recombination of electrons and holes which are ultimately responsible for the highest photocatalytic activity of ZnO/ZnS/α-Fe2O3.

Evaluating the Impact of Prediction Techniques: Software Reliability Perspective

Maintaining software reliability is the key idea for conducting quality research.This can be done by having less complex applications.While developers and other experts have made signicant efforts in this context,the level of reliability is not the same as it should be.Therefore,further research into the most detailed mechanisms for evaluating and increasing software reliability is essential.A signicant aspect of growing the degree of reliable applications is the quantitative assessment of reliability.There are multiple statistical as well as soft computing methods available in literature for predicting reliability of software.However,none of these mechanisms are useful for all kinds of failure datasets and applications.Hence nding the most optimal model for reliability prediction is an important concern.This paper suggests a novel method to substantially pick the best model of reliability prediction.This method is the combination of analytic hierarchy method(AHP),hesitant fuzzy(HF)sets and technique for order of preference by similarity to ideal solution(TOPSIS).In addition,using the different iterations of the process,procedural sensitivity was also performed to validate the ndings.The ndings of the software reliability prediction models prioritization will help the developers to estimate reliability prediction based on the software type.

Integrating Blockchain Technology into Healthcare Through an Intelligent Computing Technique

The blockchain technology plays a significant role in the present era of information technology.In the last few years,this technology has been used effectively in several domains.It has already made significant differences in human life,as well as is intended to have noticeable impact in many other domains in the forthcoming years.The rapid growth in blockchain technology has created numerous new possibilities for use,especially for healthcare applications.The digital healthcare services require highly effective security methodologies that can integrate data security with the availablemanagement strategies.To test and understand this goal of security management in Saudi Arabian perspective,the authors performed a numerical analysis and simulation through a multi criteria decision making approach in this study.The authors adopted the fuzzy Analytical Hierarchy Process(AHP)for evaluating the effectiveness and then applied the fuzzy Technique forOrder of Preference by Similarity to Ideal Solution(TOPSIS)technique to simulate the validation of results.For eliciting highly corroborative and conclusive results,the study referred to a real time project of diabetes patients’management application of Kingdom of Saudi Arabia(KSA).The results discussed in this paper are scientifically proven and validated through various analysis approaches.Hence the present study can be a credible basis for other similar endeavours being undertaken in the domain of blockchain research.

Estimating the Impact of COVID-19 Pandemic on the Research Community in the Kingdom of Saudi Arabia

Ever since its outbreak inWuhan,COVID-19 has cloaked the entireworld in a pall of despondency and uncertainty.The present study describes the exploratory analysis of all COVID cases in Saudi Arabia.Besides,the study has executed the forecastingmodel for predicting the possible number of COVID-19 cases in Saudi Arabia till a defined period.Towards this intent,the study analyzed different age groups of patients(child,adult,elderly)who were affected by COVID-19.The analysis was done city-wise and also included the number of recoveries recorded in different cities.Furthermore,the study also discusses the impact of COVID-19 on the economy.For conducting the stated analysis,the authors have created a list of factors that are known to cause the spread of COVID-19.As an effective countermeasure to contain the spread of Coronavirus in Saudi Arabia,this study also proposes to identify the most effective Computer Science technique that can be used by healthcare professionals.For this,the study employs the Fuzzy-Analytic Hierarchy Process integrated with the Technique for Order Performance by Similar to Ideal Solution(F.AHP.TOPSIS).After prioritizing the various Computer Science techniques,the ranking order that was obtained for the different techniques/tools to contain COVID-19 was:A4>A1>A2>A5>A3.Since the Blockchain technique obtained the highest priority,the study recommends that it must be used extensively as an efficacious and accurate means to combat COVID-19.

A Systematic Review on the Internet of Medical Things:Techniques,Open Issues,and Future Directions

IoT usage in healthcare is one of the fastest growing domains all over the world which applies to every age group.Internet of Medical Things(IoMT)bridges the gap between the medical and IoT field where medical devices communicate with each other through a wireless communication network.Advancement in IoMT makes human lives easy and better.This paper provides a comprehensive detailed literature survey to investigate different IoMT-driven applications,methodologies,and techniques to ensure the sustainability of IoMT-driven systems.The limitations of existing IoMTframeworks are also analyzed concerning their applicability in real-time driven systems or applications.In addition to this,various issues(gaps),challenges,and needs in the context of such systems are highlighted.The purpose of this paper is to interpret a rigorous review concept related to IoMT and present significant contributions in the field across the research fraternity.Lastly,this paper discusses the opportunities and prospects of IoMT and discusses various open research problems.

Usability Evaluation Through Fuzzy AHP-TOPSIS Approach: Security Requirement Perspective

Most of the security strategies today are primarily designed to provide security protection,rather than to solve one of the basic security issues related to adequate software product architecture.Several models,frameworks and methodologies have been introduced by the researchers for a secure and sustainable software development life cycle.Therefore it is important to assess the usability of the popular security requirements engineering(SRE)approaches.A significant factor in the management and handling of successful security requirements is the assessment of security requirements engineering method performance.This assessment will allow changes to the engineering process of security requirements.The consistency of security requirements depends heavily on the usability of security requirements engineering.Several SRE approaches are available for use and each approach takes into account several factors of usability but does not cover every element of usability.There seems to be no realistic implementation of such models because the concept of usability is not specific.This paper aims at specifying the different taxonomy of usability and design hierarchical usability model.The taxonomy takes into account the common quality assessment parameters that combine variables,attributes,and characteristics identified in different approaches used for security requirements engineering.The multiple-criteria decision-making(MCDM)model used in this paper for usability evaluation is called the fuzzy AHP-TOPSIS model which can conveniently be incorporated into the current approach of software engineering.Five significant usability criteria are identified and used to evaluate the six different alternatives.Such strategies are graded as per their expected values of usability.

Measuring the agricultural sustainability of India:An application of Pressure-State-Response(PSR)model

Analyzing agricultural sustainability is essential for designing and assessing rural development initiatives.However,accurately measuring agricultural sustainability is complicated since it involves so many different factors.This study provides a new suite of quantitative indicators for assessing agricultural sustainability at regional and district levels,involving environmental sustainability,social security,and economic security.Combining the PressureState-Response(PSR)model and indicator approach,this study creates a composite agricultural sustainability index for the 14 mainstream agro-climatic regions of India.The results of this study show that the Trans-Gengatic Plain Region(TGPR)ranks first in agricultural sustainability among India's 14 mainstream agro-climatic regions,while the Eastern Himalayan Region(EHR)ranks last.Higher livestock ownership,cropping intensity,per capita income,irrigation intensity,share of institutional credit,food grain productivity,crop diversification,awareness of minimum support price,knowledge sharing with fellow farmers,and young and working population,as well as better transportation facilities and membership of agricultural credit societies are influencing indicators responsible for higher agricultural sustainability in TGPR compared with EHR.Although,the scores of environmental sustainability indicators of EHR are quite good,its scores of social and economic security indicators are fairly low,putting it at the bottom of the rank of agricultural sustainability index among the 14 mainstream agroclimatic regions in India.This demonstrates the need of understanding agricultural sustainability in relation to social and economic dimensions.In a nation as diverse and complicated as India,it is the social structure that determines the health of the economy and environment.Last but not least,the sustainability assessment methodology may be used in a variety of India's agro-climatic regions.

Integrity Assessment of Medical Devices for Improving Hospital Services

The present study examines the various techniques being used to maintain the integrity of the medical devices,and develops a quantitative framework to list these in the sequence of priority.To achieve the intended objective,the study employs the combined procedure of Fuzzy Analytic Network Process(ANP)and Fuzzy Technical for Order Preference by Similarities to Ideal Solution(TOPSIS).We selected fuzzy based decision making techniques for assessing the integrity of medical devices.The suggested methodology was then used for classifying the suitable techniques used to evaluate the integrity of medical devices.Different techniques or the procedures of integrity assessment were ranked according to their satisfaction weights.The rating of the options determined the order of priority for the procedures.As per the findings of the study,among all the options,A1 was assessed to be the most likely option.This means that the integrity of medical devices of A2 is the highest amongst all the chosen alternatives.This analysis will be a corroborative guideline for manufacturers and developers to quantitatively test the integrity of medical devices in order to engineer efficacious devices.The evaluations undertaken with the assistance of the planned procedure are accurate and conclusive.Hence instead of conducting a manual valuation,this experimental study is a better and reliable option for assessing the integrity of the medical devices.

Hesitant Fuzzy-Sets Based Decision-Making Model for Security Risk Assessment

Security is an important component in the process of developing healthcare web applications.We need to ensure security maintenance;therefore the analysis of healthcare web application’s security risk is of utmost importance.Properties must be considered to minimise the security risk.Additionally,security risk management activities are revised,prepared,implemented,tracked,and regularly set up efficiently to design the security of healthcare web applications.Managing the security risk of a healthcare web application must be considered as the key component.Security is,in specific,seen as an add-on during the development process of healthcare web applications,but not as the key problem.Researchers must ensure that security is taken into account right from the earlier developmental stages of the healthcare web application.In this row,the authors of this study have used the hesitant fuzzy-based AHP-TOPSIS technique to estimate the risks of various healthcare web applications for improving security-durability.This approach would help to design and incorporate security features in healthcare web applications that would be able to battle threats on their own,and not depend solely on the external security of healthcare web applications.Furthermore,in terms of healthcare web application’s security-durability,the security risk variable is measured,and vice versa.Hence,the findings of our study will also be useful in improving the durability of several web applications in healthcare.

Impact Assessment of COVID-19 Pandemic Through Machine Learning Models

Ever since its outbreak in the Wuhan city of China,COVID-19 pandemic has engulfed more than 211 countries in the world,leaving a trail of unprecedented fatalities.Even more debilitating than the infection itself,were the restrictions like lockdowns and quarantine measures taken to contain the spread of Coronavirus.Such enforced alienation affected both the mental and social condition of people significantly.Social interactions and congregations are not only integral part of work life but also form the basis of human evolvement.However,COVID-19 brought all such communication to a grinding halt.Digital interactions have failed to enthuse the fervor that one enjoys in face-to-face meets.The pandemic has shoved the entire planet into an unstable state.The main focus and aim of the proposed study is to assess the impact of the pandemic on different aspects of the society in Saudi Arabia.To achieve this objective,the study analyzes two perspectives:the early approach,and the late approach of COVID-19 and the consequent effects on different aspects of the society.We used a Machine Learning based framework for the prediction of the impact of COVID-19 on the key aspects of society.Findings of this research study indicate that financial resources were the worst affected.Several countries are facing economic upheavals due to the pandemic and COVID-19 has had a considerable impact on the lives as well as the livelihoods of people.Yet the damage is not irretrievable and the world’s societies can emerge out of this setback through concerted efforts in all facets of life.

Atrocious Impinging of COVID-19 Pandemic on Software Development Industries

COVID-19 is the contagious disease transmitted by Coronavirus.The majority of people diagnosed with COVID-19 may suffer from moderate-tosevere respiratory illnesses and stabilize without preferential treatment.Those who are most likely to experience significant infections include the elderly as well as people with a history of significant medical issues including heart disease,diabetes,or chronic breathing problems.The novel Coronavirus has affected not only the physical and mental health of the people but also had adverse impact on their emotional well-being.For months on end now,due to constant monitoring and containment measures to combat COVID-19,people have been forced to live in isolation and maintain the norms of social distancing with no community interactions.Social ties,experiences,and partnerships are not only integral part of work life but also form the basis of human evolvement.However,COVID-19 brought all such communication to a grinding halt.Digital interactions have failed to support the fervor that one enjoys in face-to-face meets.The COVID-19 disease outbreak has triggered dramatic changes in many sectors,and the main among them is the software industry.This paper aims at assessing COVID-19’s impact on Software Industries.The impact of the COVID-19 disease outbreak has been measured on the basis of some predefined criteria for the demand of different software applications in the software industry.For the stated analysis,we used an approach that involves the application of the integrated Fuzzy ANP and TOPSIS strategies for the assessment of the impact of COVID-19 on the software industry.Findings of this research study indicate that Government administration based software applications were severely affected,and these applications have been the major apprehensions in the wake of the pandemic’s outbreak.Undoubtedly,COVID-19 has had a considerable impact on software industry,yet the damage is not irretrievable and the world’s societies can emerge out of this setback through concerted efforts in all facets of life.

Throughflow and g-jitter effects on binary fluid saturated porous medium

A non-autonomous complex Ginzburg-Landau equation （CGLE） for the finite amplitude of convection is derived, and a method is presented here to determine the amplitude of this convection with a weakly nonlinear thermal instability for an oscillatory mode under throughflow and gravity modulation. Only infinitesimal disturbances are considered. The disturbances in velocity, temperature, and solutal fields are treated by a perturbation expansion in powers of the amplitude of the applied gravity field. Throughfiow can stabilize or destabilize the system for stress free and isothermal boundary conditions. The Nusselt and Sherwood numbers are obtained numerically to present the results of heat and mass transfer. It is found that throughfiow and gravity modulation can be used alternately to heat and mass transfer. Further, oscillatory flow, rather than stationary flow, enhances heat and mass transfer.

Managing Security-Risks for Improving Security-Durability of Institutional Web-Applications: Design Perspective

The advanced technological need,exacerbated by the flexible time constraints,leads to several more design level unexplored vulnerabilities.Security is an extremely vital component in software development;we must take charge of security and therefore analysis of software security risk assumes utmost significance.In order to handle the cyber-security risk of the web application and protect individuals,information and properties effectively,one must consider what needs to be secured,what are the perceived threats and the protection of assets.Security preparation plans,implements,tracks,updates and consistently develops safety risk management activities.Risk management must be interpreted as the major component for tackling security efficiently.In particular,during application development,security is considered as an add-on but not the main issue.It is important for the researchers to stress on the consideration of protection right from the earlier developmental stages of the software.This approach will help in designing software which can itself combat threats and does not depend on external security programs.Therefore,it is essential to evaluate the impact of security risks during software design.In this paper the researchers have used the hybrid Fuzzy AHPTOPSIS method to evaluate the risks for improving security durability of different Institutional Web Applications.In addition,the e-component of security risk is measured on software durability,and vice versa.The paper’s findings will prove to be valuable for enhancing the security durability of different web applications.

Cyber Security Analysis and Evaluation for Intrusion Detection Systems

Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the world.Machine learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and security issues.It is crucial in offering a proactive security system in the field of cybersecurity.In real time,cybersecurity protects information,information systems,and networks from intruders.In the recent decade,several assessments on security and privacy estimates have noted a rapid growth in both the incidence and quantity of cybersecurity breaches.At an increasing rate,intruders are breaching information security.Anomaly detection,software vulnerability diagnosis,phishing page identification,denial of service assaults,and malware identification are the foremost cyber-security concerns that require efficient clarifications.Practitioners have tried a variety of approaches to address the present cybersecurity obstacles and concerns.In a similar vein,the goal of this research is to assess the idealness of machine learning-based intrusion detection systems under fuzzy conditions using a Multi-Criteria Decision Making(MCDM)-based Analytical Hierarchy Process(AHP)and a Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS).Fuzzy sets are ideal for dealing with decision-making scenarios in which experts are unsure of the best course of action.The projected work would support practitioners in identifying,prioritising,and selecting cybersecurityrelated attributes for intrusion detection systems,allowing them to design more optimal and effective intrusion detection systems.

Blockchain and Artificial Intelligence Applications to Defeat COVID-19 Pandemic

The rapid emergence of novel virus named SARS-CoV2 and unchecked dissemination of this virus around the world ever since its outbreak in 2020,provide critical research criteria to assess the vulnerabilities of our current health system.The paper addresses our preparedness for the management of such acute health emergencies and the need to enhance awareness,about public health and healthcare mechanisms.In view of this unprecedented health crisis,distributed ledger and AI technology can be seen as one of the promising alternatives for fighting against such epidemics at the early stages,and with the higher efficacy.At the implementation level,blockchain integration,early detection and avoidance of an outbreak,identity protection and safety,and a secure drug supply chain can be realized.At the opposite end of the continuum,artificial intelligence methods are used to detect corona effects until they become too serious,avoiding costly drug processing.The paper explores the application of blockchain and artificial intelligence in order to fight with COVID-19 epidemic scenarios.This paper analyzes all possible newly emerging cases that are employing these two technologies for combating a pandemic like COVID-19 along with major challenges which cover all technological and motivational factors.This paper has also discusses the potential challenges and whether further production is required to establish a health monitoring system.