This paper proposes a novel and secure blockchain hyperledger sawtooth-enabled consortium analytical model for smart educational accreditation credential evaluation. Indeed, candidate academic credentials are generated, verified, and validated by the universities and transmitted to the Higher Education Department (HED). The objective is to enable the procedure of credential verification and analyze tamper-proof forged records before validation. For this reason, we designed and created an accreditation analytical model to investigate individual collected credentials from universities and examine candidates’ records of credibility using machine learning techniques and maintain all these aspects of analysis and addresses in the distributed storage with a secure hash-encryption (SHA-256) blockchain consortium network, which runs on a peer-to-peer (P2P) structure. In this proposed analytical model, we deployed a blockchain distributed mechanism to investigate the examiner and analyst processes of accreditation credential protection and storage criteria, which are referred to as chaincodes or smart contracts. These chaincodes automate the distributed credential schedule, generation, verification, validation, and monitoring of the overall model nodes’ transactions. The chaincodes include candidate registration with the associated university (candidateReg()), certificate-related accreditation credentials update (CIssuanceTrans()), and every node’s transactions preservation in the immutable storage (ULedgerAV()) for further investigations. This model simulates the educational benchmark dataset. The result shows the merit of our model. Through extensive simulations, the blockchain-enabled analytical model provides robust performance in terms of credential management and accreditation credibility problems.

Distributed forecasting of agriculture commodity prices has an attractive research perspective that delivers active breakthrough analysis of the rapid fluctuations in pricing forecasts for participating stakeholders without being manually dispatched lists. The increased use of an efficient forecasting mechanism for the agriculture information management of generated records and processing creates emerging challenges and limitations. These include new government mandates and regulations, the price of land for expansion, forecasting the growing demand for commodities, fluctuations in the global financial market, food security, and bio-based fuels. Building and deploying distributed dynamic scheduling, management, and monitoring systems of agricultural activities for commodity price forecasting and supply chains require a significant secure and efficient approach. Thus, this paper discusses a collaborative approach where two different folds are demonstrated to cover distinct aspects with different objectives. A metaheuristic-enabled genetic algorithm is designed to receive day-to-day agricultural production details and process and analyze forecast pricing from the records by scheduling, managing, and monitoring them in real-time. The blockchain hyperledger sawtooth distributed modular technology provides a secure communication channel between stakeholders, a private network, protects the forecasting ledger, adds and updates commodity prices, and preserves agricultural information and node transactions in the immutable ledger (IPFS). To accomplish this, we design, develop, and deploy two distinct smart contracts to register the system’s actual stakeholders and allow for the addition of node transactions and exchanges. The second smart contract updates the forecasting commodity pricing ledger and distributes it to participating stakeholders while preserving detailed addresses in storage. The simulation results of the proposed collaborative approach deliver an efficient E-agriculture commodity price forecast with an accuracy of 95.3%. It also maintains ledger transparency, integrity, provenance, availability, and secure operational control and access of agricultural activities.

This article aims to analyze the relationship between the threat of ransomware and new effective counteraction principles for law enforcement agencies to utilize. Moreover, it contemplates on how specific behavior of persons can help reduce the threat of being infected with this malicious software. It establishes that certain changes made in society's mentality towards their computer and network systems can significantly reduce the consequent damages of ransomware attacks. The manuscript uses a qualitative research approach and the analysis of variance (ANOVA), including an F-test, which defines major challenges in ransomware. This is the first empirical research piece which uses this type of data and approach for the analysis of current threats in global ransomware security. The article suggests that the main challenge is the systematic growth of ransomware connected to illegal businesses and the inattentive actions of casual users. The research paper proposes the implementation of global ransomware counteraction principles on the base of challenges that are present now and the prospects of rising threats in the future. In addition, the manuscript analyzes the trends of the last 2-years of attacks to find and determine new ways of successfully counteracting it for optimal innovative regional development.

The COVID-19 pandemic has led many governments to impose restrictive measures that have contributed to a decline in the demand for goods and services, leading to an economic crisis. This study proves a novelty that implies a rise in the capitalization of renewable energy companies during the coronavirus pandemic. The study is based on the hypothesis that, at a time of economic crisis, the prospect of investing in clean energy has increased, through the need to protect the environment and ensure clean air. The analysis provided additional results that there is an inverse relationship between two economic indicators of firms, namely, the percentage change in profitability and capitalization of firms between 2020 and 2021. Analysis of data from companies included in TRBC Industry Name Renewable Fuels provided numerical results that show an average increase in firms’ capitalization of 86%. The study uses analysis techniques such as covariance and correlation. The results show an increase in capitalization of renewable energy companies by 150%, while there is a decrease in income by 2%. However, the capitalization of fossil fuel companies has increased, with an average growth rate of 35%. This situation in the fossil energy market is that company revenues fell by 32% while capitalization increased by 35%. It proves a bubble in the non-renewable energy market. This paper suggests that the period of coronavirus infection has seen a slowdown in economic growth in many countries around the world, but a switch to renewable energy will help improve the quality of life of the population and ensure economic growth.

The goal is to consider the problems and prospects for the development of enterprises in agricultural sector. Methods – analysis and synthesis, determination of absolute and relative indicators, abstract-logistical, economic-statistical. Results – the authors note the main features of agricultural production: high capital intensity, long payback period, low profitability, seasonality, dependence on natural and climatic conditions. Enterprises are insufficiently provided with modern technology, social infrastructure is poorly developed, soil fertility is declining, level of income of the rural population is much lower to income in other industries. At present, effective programs on development of agro-industrial complex and support for agricultural producers have been developed in the republic. The article presents data on the number of registered producers of agricultural products in the Republic of Kazakhstan: legal entities, individual entrepreneurs, peasant (private) farms, households. The volumes of gross output of agricultural goods, production of livestock products in Kazakhstan, cattle products sales in slaughter weight for all categories of farms are shown. It was revealed that for some types of food, dependence on imports remains: meat and milk processing products, poultry meat, vegetables and fruits. The main directions of development of AIC are substantiated: measures to ensure food security; digitalization and robotization; attraction of domestic and foreign investments; application of the achievements of selection and breeding work in the livestock industry; strengthening scientific potential by improving training of highly qualified personnel. Conclusions – specifics of modern economic entities is their broad specialization: the presence of several workshops for heat treatment, sterilization and preparation for sale. There are also highly specialized agricultural enterprises, which as a rule, are producing one type of product, for example, dairy farms, greenhouses, nurseries.