Arapbaev Ruslanbek Nurmamatovich

Background: Digital literacy, education, and human right of internet are also hampered in rural areas keeping the rural people more backward in the technological advancement and not providing them better chance of socioeconomic development. The opportunity of implementing the new 5G technologies can give the new perspective in the elimination of such disparities manifested through the improvement of the connection, the decrease of latency, and the increase of data transfer rates. This research study established that the adoption of 5G for coverage in rural areas is challenged by technical, economic and policy factors. Objective: The article aims at analyzing the technical, economic, and social aspects of 5G technology in the rural context in order to identify such problem the development of appropriate solutions for infrastructure costs, spectrum availability, and consumers. In pursuing this goal, the research seeks to develop practical recommendations on enhancing deployment strategies to increase Internet access where it is scarce. Methods: The study therefore used an exploratory, theoretical-evaluative, and finally empirical approach that involved quantitative modeling, case studies, and key informant interviews. Latency, data throughput, and coverage stand as the most significant factors which were tested using network simulation. Level of cost was used to determine economic feasibility while data for qualitative analysis were obtained from a survey of policymakers and telecom operators, and focus group discussion with rural community leaders. Results: In the case of 5G, the implementation of the system led to a 75% reduction in latency, a 600% improvement in the data throughput, and a 300% increase in coverage area. This finding revealed that the partnerships as a deployment model were the most effective as they resulted to a 58%ROI and lowered infrastructure costs. Conclusion: The study reaffirms the innovation of 5G to rural areas and develops agriculture, healthcare services, and educational systems. Policies, investments in the right areas, optimal management of the available spectrum and engaging with the communities as required should be a key focus for deployment to be just.

  Background: Quantum computing has brought in all new paradigm for computational processing providing unparallel ability for data analysis. Considering worldwide data production is expected to exceed 180 trillion zettabytes by 2025 the utilization of the conventional computing framework hampers the real-time processing of data. People consider quantum computing, which uses principles of quantum mechanics to solve problems 100 and 1,000 times faster than classical computing.   Objective: The article looks at quantum computing and its relevance to real time data analytics to determine its relevance, hence its impact, by the year 2025. It is worthwhile to emphasize the comparison of quantum algorithms with traditional approaches to dealing with extensive, data-centered workloads in various fields.   Methods: A comparison was made on quantum versus classical computing algorithms based on criteria such as, the flow rate, precision, and flexibility. Data sets provided by the finance stream, including real-time stock analysis, supply chain and logistics, genomic sequencing from the healthcare domain were used. Over 10 million simulation experiments were performed to gain trends and insights into the operational problems for quantum simulation.   Results: The study establishes differences in the efficiencies of these two approaches, with quantum algorithms speeding up particular tasks as much as a hundred times higher than classical algorithms and almost 15% of the error rate being decreased if quantum error correction modes were used. In scalability tests it was shown that quantum systems could process data sets larger than 10 terabytes with little slowdown, compared to a classical system, which reduced efficiency by as much as 30%. However, in present day quantum hardware, processing the capability is limited and problems arise with regards the error correction protocol.   Conclusion: Quantum computing, on the other hand, has an unconventional prospect of real-time data analytics to operate at high efficiency and big scale on data-bound concerns. However, much progress is required in the way of bettering coherence times and reducing exacting error rates, crucial advances for total realization of quantum potentialities by 2025