In recent times amount of data is increasing rapidly and analysis of data is a must to come up with business decisions, predictions etc. It’ s not just text are numbers which has to be stored properly. Data Types these days varies from images, video, social media data, surveys to blogs etc. When this is the case its mandatory to deal with Bigdata and to safeguard those Bigdata. Technologies available in Bigdata and Bitcoin helps us in achieving this. Bigdata technologies helps in storing the unstructured data effectively and processing of such voluminous data is taken care of. Hashing algorithms are used in Blockchain to keep the data safe. Hashing algorithms like SHA 256 are used to make it more secure. Its almost not possible to break the data available in Blockchain. Let’ s try to secure the data even more using encryption algorithms to make sure that proper data is used for analysis etc.

Objective: This study analyzes the effects of lifestyle, nutrition, and diets on the status and risks of apparent (symptomatic)COVID-19 infection in Iranian families. Materials and Methods: A relatively extensive questionnairesurvey was conducted on more than 20, 000 Iranian families(residing in more than 1000 different urban and rural areas in theIslamic Republic of Iran) to collect the big data of COVID-19 and develop a lifestyle dataset. The collected big data included therecords of lifestyle effects (e. g. nutrition, water consumptionresources, physical exercise, smoking, age, gender, health and disease factors, etc. ) on the status of COVID-19 infection infamilies (i. e. residents of homes). Therefore, an online selfreported questionnaire was used in this retrospective observationalstudy to analyze the effects of lifestyle factors on the COVID-19risks. The data collection process spanned from May 10, 2020 toMarch 19, 2021 by selecting 132 samples from more than 40different social network communities. Results: The research results revealed that food and water sources, which contain some natural hypomethylating agents, mitigated the risks of apparent (symptomatic) COVID-19 infection. Furthermore, the computations on billions of permutations ofnutrition conditions and dietary regime items, based on the data collected from people’, s diets and infection status, showed thatthere were many dietary conditions alleviating the risks ofapparent (symptomatic) COVID-19 infection by 90%. However, some other diets tripled the infection risk. Conclusion: Some natural hypomethylating agents in food, water, and environmental resources are against the spread and risks ofCOVID-19.

The intensity of the changes in cyberspace and its according diversity of insecurity and the need to respond to the current threats of this space, especially the strategic position of the services and information available in this space, have necessitated the need for a model for strategic management of this space's security. On the other hand, having environmental information, both indoor and outdoor, especially with regard to the speed of their changes and the need for accurate information, allows us to manage security in the Bigdata of this space. Understanding the environment for selecting the right strategies in all strategic management models is part of the model. Cyber-space Bigdata, in addition to providing real-time cyber-space information, enables complete assessment and identification of the environment. In this study, the final model was implemented using ISO 31000 standard framework. In this standard, the risk assessment section was extracted with regard to the macro features of the data available in cyberspace. The risk values in each of the extracted components of cyberspace security by using Bayesian conditional probability functions and using Poisson distribution modulated Markov model by combining Markov cycle with Poisson probability density function and its conditional functions in Bayesian network, Extracted from large cyberspace data, risk assessment was performed. The implementation of ISO 31000 standard was also completed in the formulation of risk management strategies by applying elements extracted from studies on strategic management and risk management models. Finally, the model is simulated with an example of a cyber threat scenario on social networks.

Smart city has shown a new form of life development in recent years and has been proposed as an effective approach to better urban management. Conceptually, in these types of cities, the interactions between the new technologies, the new organizations and the new constructive cities of smart cities have been integrated into the social and technical system. The goal of smart city is to realize the integration of urban business, transportation, water, energy and other urban subsystems through the integration and analysis of data collected through sensors and information and communication technology (ICTs). In this paper, a hybrid structure is proposed using cloud computing and cloud processing and Internet technology for development and management of smart cities and urban planning. In addition, an assessment of sensor development and analysis, and the purpose of building smart cities as well as supporting technologies in these types of cities have been investigated. The present study aims at defining and reviewing large data and objects of the Internet and cloud computing, and identifying existing challenges and constraints. The proposed model structure has 3 layers: the first layer has the task of collecting large data sources and producing content. The second layer is responsible for linking and enhancing sensors and managing data and data processing using the Hadoop architecture. The third layer is responsible for applications and how to use the results and analytical data. The implementation of this system involves various stages of generating, collecting, integrating, classifying, processing, calculating and deciding information. Based on the information and analysis collected and the architecture of the system in question, the system uses Hadoop single-player in Ubuntu 14. 04 LTS. It has been developed with 3. 2 GHZ x4 processors and 4 GB of memory. Ultimately, this article has created a new way in the Internet context of objects, where data is gathered from different geographic locations using devices and sensors, and it uses a new system designed and cloud computing services in a city to analyze and cause smart decision making for smart city management and welfare of citizens.

The purpose of this paper is to localise cloud based e-HRM adoption model in knowledge base SMEs by using the Technology, Organization and Environment (TOE) framework. While many studies have predominantly looked at cloud computing adoption determinants in general, few is known about specific cloud services such as cloud base e-HRM, which is the main subject of this paper. This study was conducted as a mixed method research. In the qualitative part, based on the TOE framework, a semi-structured interview conducted between 3 domain experts, i. e. the technology, organization, environment domains. In the interviews the questions were whether the determinants are valid in developing countries business ecosystem or not? The interviews continued until heoretical saturation. Then based on the findings of the interview, a questionnaire designed and final users of cloud base e-HRM answered it. There were 168 valid questionaires which were used to examine the fitness of model. The findings indicate that factors such as relative advantage, uncertainty, complexity, compatibility in technology domian, physical location, competitive pressure, industry, market, supplier computing support in environment domain and top management support, organizational readiness, prior technology experience in organization domain were the TOE factors to be significant in cloud based e-HRM adoption model. The findings of this study have important implications to the research community, managers and providers of information and communication technologies (ICT), to have a better road map and strategies for adopting cloud computing.

Digital entrepreneurship marketing ecosystem as a new form of business organization that uses effective resources. Investigating the studies and previous studies, the researchers first extracted the concepts, but due to the non-relevance of some of the factors extracted to the current state of Iran's retail retailers, using the two methods of interviewing and Delphi, experts were used. . The research method is a qualitative and quantitative mixture and is considered as an objective, developmental, and applied goal. Firstly, through an interview with 18 experts, the components were identified. The initial model was then developed by 12 Internet Retailers Managers and 3 Academic Experts 98 Indicators and 25 Concepts of the digital entrepreneurship marketing ecosystem of Internet Retail Companies. In the third step, in order to confirm the initial model, experts were interviewed and managers of the Internet retailer were interviewed and classified by exploratory factor analysis method. Based on the results, external factors, internal, values, and casting actors constructed the final model. The final model provides new concepts for product development through interactive investment, integrated channels, Bigdata, sustainable services, shared economies, Prosumer, and the existence of various actors.

With the development of a new stage of the industrial revolution, the importance of digitalization of business development tools is growing. The purpose of this article is to study the applied aspects of digital marketing tools usage for business development in the B2C market. To achieve the purpose and objectives of the study general and special methods are used: comparative analysis of the results of economic and statistical surveys, method of expert assessments by questionnaires using a 5-point Likert scale. The concordance coefficient was used to determine the consistency of the experts' opinions taking into account the related ranks in method of expert assessments. According to the results of the research, it is established that the Ukrainian business of the B2C sector was actively mastering digital marketing tools. The analysis of penetration level of digital technologies in the development of trade business showed the emergence of basic conditions for updating marketing tools to influence the B2C market. There is a rapid coverage rate of multi-purpose use of the Internet among consumers and businesses, gradual growth of digital skills among practitioners, positive dynamics of development of interactive services in the trade sphere. However, the level of use of the retail businesses websites remains low in many spheres of customer service. An important trend of the current development stage of the consumer market is the usage of business Internet platforms designed for mass dissemination of information. Effective marketing channels of interaction with consumers include social media (social networks, blogs or microblogs, websites with multimedia content, knowledge sharing tools), websites, e-shops, and sales via mobile devices. According to the results of expert evaluation, foreground digital technologies, which are able to bring business to a qualitatively new level of interaction with consumers and the provision of trade services have been identified. These are artificial intelligence and cognitive technologies, Bigdata, Internet of Things (IoT), and cloud computing. The structural and logical scheme of research of digital marketing tools is used for business development which includes two stages is offered. In the first stage, trendwatching, benchmarking and evaluation of internal opportunities for the use of digital marketing tools are performed. In the second stage, three components of digital readiness of business are defined: technological, competence, institutional. The obtained results form the basis of further research to determine the priorities of adaptive digital business behavior for the productive use of existing digital opportunities.