The technological development and growth of the telecommunications industry have had a great positive impact on the education, health, and economic sectors, among others. However, they have also increased rivalry between companies in the market to keep and acquire new customers. A lower level of market concentration is related to a higher level of competitiveness among companies in the sector that drives a country’s socioeconomic development. To guarantee and improve the level of competition, it is necessary to monitor the concentration level in the telecommunications market to plan and develop appropriate strategies by governments. With this in mind, the present work aims to analyze the concentration prediction in the telecommunications market through recurrent neural networks and the Herfindahl-Hirschman index. The results show a slight gradual increase in competition in terms of traffic and access, while a more stable concentration level is observed in revenues.

Urban facilities and services are essential to human life. Access to them varies according to the geographical location of the population, whether urban, peri-urban or rural, and according to the modes of transport available. In view of the rapid development of peri-urban areas in developing countries, questions are being asked about the ability of the inhabitants of these areas to access these facilities and services. This study examines the ability of the inhabitants of Hêvié, Ouèdo and Togba, three peri-urban districts of Abomey-Calavi in the Republic of Benin, to access commercial, educational, school and health facilities. To this end, we have adopted a GIS-based methodology. It is a combination of isochronal method and accessibility utility measurement. The isochrones were produced according to the main modes of travel recorded on the study area and over a time t ≤ 20 min divided into intervals of 05 min. Analysis of the data enabled us to understand that the main modes of travel adopted by residents are walking, motorcycle and car. Access to educational and health facilities is conditioned by the mode of travel used. Access to commercial and entertainment facilities in t ≤ 20 min is not correlated with the modes of transport used.

Natural Protected Areas (NPAs) are critical for biodiversity conservation and ecological balance. These areas are not only refuges for wildlife but also pivotal in promoting sustainable tourism. Geoparks, a unique subset of NPAs, emphasize geological heritage, offering distinctive educational and recreational opportunities. This article explores the significance of Geoparks in Portugal for geotourism and assesses the accessible digital communication strategies of Portuguese Geoparks, emphasizing the analysis of pedagogical concerns. The study highlights the importance of online engagement in enhancing visitor experiences and promoting sustainable tourism practices.

The article investigates trade flows between the Shanghai Cooperation Organization (SCO) member-states and Belarus before the upcoming Belarus’ joining the organization. The export flows of the countries are modeled using a power function based on the time data. The results of the qualitative and quantitative analysis of foreign trade between the organization and the Republic of Belarus are presented, as well as the quantitative forecast of the prospects open to Belarus in connection with its joining the organization based on three original scenarios using econometric models. The results of the study show that Belarus has certain promising sectors of foreign economic activity, which can contribute to an increase in income from trade. It was found that the integration of the country will have a positive effect on increasing the volume of trade turnover with the participating countries, while in order to maintain sustainable economic growth of the country, domestic development of production should remain a priority, as evidenced by the obtained parameter estimates for the factors. An assessment of potential economic effects can be used to make a decision on whether a country should join an international organization. In particular, based on the assessments in our study in trade with Russia the expected increase in Belarus exports upon joining the Shanghai Cooperation Organization will constitute an increase of nearly 5%, exports to Kazakhstan are expected to increase by almost 75%, and to India and China by almost 90%. In the context of reshaping of international associations and organizations, the problems and issues raised in the study become even more relevant.

The proposed research work encompasses implications for infrastructure particularly the cybersecurity as an essential in soft infrastructure, and policy making particularly on secure access management of infrastructure governance. In this study, we introduce a novel parameter focusing on the timestamp duration of password entry, enhancing the algorithm titled EPSBalgorithmv01 with seven parameters. The proposed parameter incorporates an analysis of the historical time spent by users entering their passwords, employing ARIMA for processing. To assess the efficacy of the updated algorithm, we developed a simulator and employed a multi-experimental approach. The evaluation utilized a test dataset comprising 617 authentic records from 111 individuals within a selected company spanning from 2017 to 2022. Our findings reveal significant advancements in EPSBalgorithmv01 compared to its predecessor namely EPSBalgorithmv00. While EPSBalgorithmv00 struggled with a recognition rate of 28.00% and a precision of 71.171, EPSBalgorithmv01 exhibited a recognition rate of 17% with a precision of 82.882%. Despite a decrease in recognition rate, EPSBalgorithmv01 demonstrates a notable improvement of approximately 14% over EPSBalgorithmv00.

The purpose of Vehicular Ad Hoc Network (VANET) is to provide users with better information services through effective communication. For this purpose, IEEE 802.11p proposes a protocol standard based on enhanced distributed channel access (EDCA) contention. In this standard, the backoff algorithm randomly adopts a lower bound of the contention window (CW) that is always fixed at zero. The problem that arises is that in severe network congestion, the backoff process will choose a smaller value to start backoff, thereby increasing conflicts and congestion. The objective of this paper is to solve this unbalanced backoff interval problem in saturation vehicles and this paper proposes a method that is a deep neural network Q-learning-based channel access algorithm (DQL-CSCA), which adjusts backoff with a deep neural network Q-learning algorithm according to vehicle density. Network simulation is conducted using NS3, the proposed algorithm is compared with the CSCA algorithm. The find is that DQL-CSCA can better reduce EDCA collisions.