درخت حوزه‌های تخصصی

Scientific sources demonstrate different attitudes of researchers to cryptocurrencies because they treat them as a category of currency, virtual money, commodity, etc. Accordingly, the relation to the valuation and risk of cryptocurrency as an investment object is different. The purpose of the article is to identify cryptocurrency value formation factors and determine the risks of investing in cryptocurrency. Cryptocurrency is simultaneously considered a currency, an asset with uncertain income, and a specific product, the price of which is determined by the energy costs for mining new cryptocurrency blocks. Thus, the paper examines the risks of investing in cryptocurrency from several positions. First, the study identifies the factors of formation of the value and risk of cryptocurrency as ordinary money based on comparing cryptocurrency with traditional money. Unlike traditional money, cryptocurrency is not tied to the economic performance of a particular country; also, central banks do not control or regulate their mining. Instead, the cryptocurrency emissions depend on the computational capacity of the equipment used for their mining. As a financial asset, cryptocurrency can be a “financial bubble” because their value increasing often exceeds the cost of mining. On the other hand, given the emergence of cryptocurrency as a phenomenon of the information economy, the paper analyses the impact of specific technical features (cryptographic hashing algorithm, the complexity of creating new blocks, the technology of verification of mining operations, etc.) on the risk of investing in cryptocurrency assets.

In recent years, Blockchain technology has been recognized as one of the most important new technologies affecting businesses and society, with a very bright future ahead. This technology is known as one of the most critical technologies of industry 4. Given that Blockchain technology is a new concept, before implementing it, the organization must understand it and be prepared to accept it; otherwise, the organization will incur irreparable damages. The main purpose of this study is to provide a framework within which organizations can evaluate their readiness to implement Blockchain technology. For this purpose, after a library study and systematic literature review, this study provided the initial research framework using the meta-synthesis method. Finally, the Lawshe model was applied to validate the proposed framework for the organization's readiness to implement Blockchain technology. Based on the findings, the final established framework included seven main dimensions, including Blockchain-based business strategy, operations of a distributed system, culture, people in Blockchain decentralized network, decentralized governance, technology, and Blockchain-based product traceability. Besides, 37 main criteria affected these dimensions, which can help companies increase the level of Blockchain technology readiness. Finally, this framework was used to measure the readiness of an airline company. According to the results of the analysis, Blockchain-based business strategy, culture, and Blockchain-based product traceability showed a medium level of readiness. Moreover, none of the main dimensions of Blockchain technology readiness were sufficiently prepared in this case study. This paper suggests practical recommendations to improve the level of Blockchain technology readiness for the managers

The study of path loss propagation is of high importance in telecommunication, for optimizing the efficiency of wireless communication networks. In this paper, four path loss propagation models; free space path loss (FSPL) model, Okumura model, Okumura-Hata model, and COST 231-Hata model were compared. The models were compared using measurement data from Choba, Port Harcourt, Nigeria. The data is gotten from a 4G walk test using two mobile applications. The first mobile application Network, Signal Info (version 5.68.07), was used to acquire the received signal strength in and the distance between the BTS antenna and the mobile antenna. While the second mobile application, G-NetTrack Lite (version 14.8), was used to map out the track path followed during the test. Choba, the study area, is a coastal suburban area with map coordinates 4.8941° N, 6.9263° E. The measured distance range was from 0.09 km to 0.45 km, and a path loss range of 69dB to 81dB. While the BTS and mobile antenna heights were 32 m and 1m respectively, with a carrier frequency of 800MHz. BTS transmission power of 23 dBm was assumed, based on 3GPP eNodeB recommendations. A graph comparison of the studied models showed that Okumura-Hata model and COST 231-Hata model had the closest predictions to the measured path loss. The need for better path loss models for 4G and 5G propagations was observed