Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.
In today’s fast-paced digital world, generative AI, especially OpenAI’s ChatGPT, has become a game-changing technology with significant effects on education. This study examines public sentiment and discourse surrounding ChatGPT’s role in higher education, as reflected on social media platform X (formerly Twitter). Employing a mixed-methods approach, we conducted a thematic analysis using Leximancer and Voyant Tools and sentiment analysis with SentiStrength on a dataset of 18,763 tweets, subsequently narrowed to 5655 through cleaning and preprocessing. Our findings identified five primary themes: Authenticity, Integrity, Creativity, Productivity, and Research. The sentiment analysis revealed that 46.6% of the tweets expressed positive sentiment, 38.5% were neutral, and 14.8% were negative. The results highlight a general openness to integrating AI in educational contexts, tempered by concerns about academic integrity and ethical considerations. This study underscores the need for ongoing dialogue and ethical frameworks to responsibly navigate AI’s incorporation into education. The insights gained provide a foundation for future research and policy-making, aiming to enhance learning outcomes while safeguarding academic values. Limitations include the focus on English-language tweets, suggesting future research should encompass a broader linguistic and platform scope to capture diverse global perspectives.
In this study, the development of rinnenkarren systems is analyzed. During the field studies, 36 rinnenkarren systems were investigated. The width and depth were measured at every 10 cm on the main channels and then shape was calculated to these places (the quotient of channel width and depth). Water flow was performed on artificial rinnenkarren system. A relation was looked for between the density of tributary channels and the average shape of the main channel, between the distance of tributary channels from each other and the shape of a given place of the main channel. The density and total length of the tributary channels on the lower and upper sections of the main channels being narrow at their lower end (11 pieces) and being wide at their lower end (10 pieces) of the rinnenkarren systems were calculated as well as their average proportional distance from the lower end of the main channel. The number of channel hollows was determined on the lower and upper sections of these main channels. It can be stated that the average shape of the main channel calculated to its total length depends on the density of the tributary channels and on the distance of tributary channels from each other. The main channel shape is smaller if less water flows on the floor for a long time because of the small density of the tributary channels and the great distance between the tributary channels. In this case, the channel deepens, but it does not widen. The width of the main channel depends on the number and location of the rivulets developing on channel-free relief. The main channel becomes narrow towards its lower end if the tributary rivulets are denser and longer on the upper part of the main rivulet developing on the channel-free, plain terrain and their distance is larger compared to the lower end. The channel hollows develop mainly at those places where the later developing tributary channels are hanging above the floor of the main channel. Thus, the former ones are younger than the latter ones. It can be stated that the morphology of the main channels (shape, channel hollows, and width changes of the main channel) is determined by the tributary channels (their number, location and age).
Efficient access to tourist spots is necessary for enhancing the overall travel experience, especially in urban environments. This study investigates the accessibility of key tourist spots in Budapest through different transportation modes (e.g., walking, cycling, and public transport) across various time intervals. Using spatial-temporal travel time maps and detailed statistical analysis, the research highlighted significant differences in how these modes connect tourists to their attractions. Cycling stands out as the most efficient transportation option, providing rapid access to a wide range of tourist spots, while public transport ranks second. However, the study also reveals disparities in accessibility, with central areas being well-served, while outer ones, especially in the northwest, remain less accessible. These findings highlight the need for targeted transportation improvements to ensure that all areas of the city are equally reachable. The results offer valuable insights for urban planners and policymakers aiming to enhance tourism infrastructure and improve the visitor experience in Budapest.
