This study aims to explore the link and match policy through industrial classes and its impact on the competence and employability of Vocational High School (VHS) graduates. The importance of this research is to address the gap between education and industry by assessing the effectiveness of industrial classes in improving the skills and employability of VHS graduates. Horison Industrial Class (HIC) in 4 schools, namely: (1) SMKN 57 Jakarta, 2 batches of Hospitality expertise programs; (2) SMKN 6 Yogyakarta, there are 3 batches of Hospitality expertise programs; (3) SMKN 6 Semarang, there are 2 batches of Hospitality expertise programs; (4) SMKN 2 Semarang. This research emphasizes the important role of industry involvement and commitment in aligning the curriculum with industry needs. The field findings show that the implementation of the link and match policy through industrial classes significantly affects the quality of learning in VHS. The study also highlights the influence of government support and industry associations in ensuring the successful implementation of industrial classes. Student participation in industry classes directly enriches their learning experiences by allowing them to engage in direct practice in a real work environment. These findings can contribute to the implementation of policies and regulations in the field of education, especially in the context of vocational education. The findings of this study can also be applied to vocational students to improve the quality of graduates in order to meet the qualification standards of employees in companies or industries.

UAVs, also known as unmanned aerial vehicles, have emerged as an efficient and flexible system for offering a rapid and cost-effective solution. In recent years, large-scale mapping using UAV photogrammetry has gained significant popularity and has been widely adopted in academia as well as the private sector. This study aims to investigate the technical aspects of this field, provide insights into the procedural steps involved, and present a case study conducted in Cesme, Izmir. The findings derived from the case study are thoroughly discussed, and the potential applications of UAV photogrammetry in large-scale mapping are examined. The study area is divided into 12 blocks. The flight plans and the distribution of ground control point (GCP) locations were determined based on these blocks. As a result of the data processing procedure, average GCP positional errors ranging from 1 to 18 cm have been obtained for the blocks.

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.

To achieve sustainable development, detailed planning, control and management of land cover changes that occur naturally or by human caused artificial factors, are essential. Urban managers and planners need a tool that represents them the information accurate, fast and in exact time. In this study, land use changes of 3 periods, 1994-2002, 2002-2009, 2009-2015 and predictions of 2009, 2015 and 2023 were assessed. In this paper, Maximum Likelihood method was used to classify the images, so that after evaluation of accuracy, amount of overall accuracy for images of 2013 was 85.55% and its Kappa coefficient was 80.03%. To predict land use changes, Markov-CA model was used after assessing the accuracy, and the amount of overall accuracy for 2009 was 82.57% and for 2015 was 93.865%. Then web GIS application was designed via map server application and evoked shape files through map file and open layers to browser environment and for design of appearance of website CSS, HTML and JavaScript languages were used. HTML is  responsible for creating the foundation and overall structure of webpage but beautifying and layout design on CSS. 

China’s annual government work report (GWR) contains terms with Chinese characteristics (TCC), reflecting unique policy frameworks. Translating these terms into English poses significant challenges due to cultural disparities between China and the West. This paper examines the English translation methods used for such terms, using the 2020 GWR as a case study, aiming to provide valuable insights for future translation practices.