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 usage of cybersecurity is growing steadily because it is beneficial to us. When people use cybersecurity, they can easily protect their valuable data. Today, everyone is connected through the internet. It’s much easier for a thief to connect important data through cyber-attacks. Everyone needs cybersecurity to protect their precious personal data and sustainable infrastructure development in data science. However, systems protecting our data using the existing cybersecurity systems is difficult. There are different types of cybersecurity threats. It can be phishing, malware, ransomware, and so on. To prevent these attacks, people need advanced cybersecurity systems. Many software helps to prevent cyber-attacks. However, these are not able to early detect suspicious internet threat exchanges. This research used machine learning models in cybersecurity to enhance threat detection. Reducing cyberattacks internet and enhancing data protection; this system makes it possible to browse anywhere through the internet securely. The Kaggle dataset was collected to build technology to detect untrustworthy online threat exchanges early. To obtain better results and accuracy, a few pre-processing approaches were applied. Feature engineering is applied to the dataset to improve the quality of data. Ultimately, the random forest, gradient boosting, XGBoost, and Light GBM were used to achieve our goal. Random forest obtained 96% accuracy, which is the best and helpful to get a good outcome for the social development in the cybersecurity system.

Over the last few decades, countries in the South have been undergoing rapid urbanization, as if to make up for lost time. Sub-Saharan Africa is characterized by a very low urbanization rate compared to0 the rest of the world. Although the African continent reached its urban transition in 2015, Niger remains by far the least urbanized country, with a rate of 17%. The city of Niamey is the main urban center, with an estimated population of 1,449,801 hbts in 2023, spread over an area of around 33,100 ha. The aim of this study is to analyze the spatial expansion of the city of Niamey from 1984 to 2023. The main data used in this study are raster images from the United States Geological Survey (USGS), vector data from Open Sources Map (OSM) and GoogleEarth, secondary data from the National Institute of Statistics (INS) and field observation. This study enabled us to conclude that between 1984 and 2023, the city of Niamey underwent very strong spatial expansion. The city grew from 4,690 ha to 33,100 ha, i.e. 28,410 ha absorbed in 39 years, with exceptional growth between 2014 and 2023, when the urban area doubled. Its population has risen from 397,437 at the time of the 1988 general population and housing census to an estimated 1,449,801 in 2023 (INS), an increase of 1,052,364 in 35 years. Between these two dates, population density fell from 87.7 to 43.8 inhabitants/km², i.e. half that of 1984. This spatial expansion has resulted in unprecedented peri-urbanization.

Access to clean water and improved sanitation are basic elements of any meaningful discourse in rural development. They are critical challenges for achieving sustainable development over the next decade. This paper seeks to examine the strategies for improving access to clean water and sanitation in Nigerian rural communities. Hypothetically, the paper states that there is no significant relationship between access to clean water and sanitation and the attainment of Sustainable Development Goal 6 in Nigeria. The paper leverages Resilience Theory. The survey research design was adopted, and primary data was obtained from a sample size of 250 respondents, proportionally drawn from the 10 wards in Obanliku local government area of Cross River State. The chi-square statistical technique was to test the hypothesis. The result shows that the calculated value of Chi-square (X²) is 24.4. Since the P-value of 21.03 is less than the level of significance (0.05), the null hypothesis was rejected and the alternate accepted. The study concludes that there is a significant relationship between access to clean water and sanitation and the attainment of Sustainable Development Goal 6 in Cross River State, Nigeria. it recommends the need for more commitment on the part of government and international donor agencies in expanding access to clean water and improved sanitation in Nigeria.

The xanthorrhiza species of the genus Arracacia belongs to the Apiaceae family and is known for its ability to generate tuberous reservoir roots that are harvested annually and marketed fresh in South American countries such as Colombia, Brazil, Venezuela, Peru, Bolivia and Ecuador. In Colombia, arracacha is planted mainly in 15 departments and the regional cultivars are differentiated by the color of the leaves, petiole and tuberous root, the best known being amarilla común or paliverde, yema de huevo, and cartagenera. There are studies that have characterized regional materials by applying a limited number of descriptors, but they do not allow knowing the morphology and phenotypic differentiation of each one; therefore, their definition and characterization constitute a support in breeding programs that allow the efficient use of the genetic potential and increase the knowledge about the diversity of cultivars. Phenotypic characterization and description of three cultivars was performed during two production cycles (2016 and 2018) in two phases (vegetative and productive) applying 74 morphological variables (42 qualitative and 32 quantitative) organized in seven groups of variables: plant, leaf, leaflet, petiole, propagule, stock and tuberous root. A factorial analysis for mixed data (FAMD) was performed, which incorporated a multivariate analysis with all variables and identified 11 discriminant variables, 8 qualitative and 3 quantitative, which can be used in processes of characterization of arracacha materials. A morphological description of each cultivar was made, which means that this is the first complete characterization study of regional arracacha materials in Colombia.

Technical Pedagogical Content Knowledge (TPACK) encompasses teachers’ understanding of the intricate interplay among technology, pedagogy, and subject matter expertise, serving as the essential knowledge base for integrating technology into subject-specific instruction. Over the decade, advancements in information technology have led to the consistent application of the TPACK framework within studies on instructional technology and technology-enhanced learning, significantly advancing the evolution of contemporary teacher education in technology integration. In this paper, we utilize the Teaching and Learning Knowledge of Subjects Based on Integrated Technology (TPACK) framework to administer a questionnaire survey to teacher trainees at Chinese colleges and universities. This survey aims to evaluate the current status of their integrated technology-based subject teaching and learning knowledge. Based on the research findings, we propose strategies aimed at enhancing the educational technology integration knowledge of students pursuing integrated technology courses in colleges and universities. Furthermore, we integrate the smart classroom setting to develop a comprehensive TPACK-integrated model teaching framework. Our final objective is to offer valuable references for the progress of modern teaching skills among education students in higher education institutions.