Archives for Technical Sciences最新文献

The aim of this study is to identify and map the zones of different vulnerability to flash floods based on the geospatial analysis of natural conditions in the Porečka River basin (Republic of Serbia). The analysis covers the catchment area of the Porečka River (493.82 km2 ). Geospatial analysis was conducted using GIS software (QGIS 3.18). The Flash Flood Potential Index (FFPI) was used to determine the terrain's predisposition to flash floods, where the input data for determining the value of the index were the values of the following coefficients: the terrain slope, the type of geological substrate, the way of land use, and the bareness of the terrain.

The analysis determined that 50.43% of the total territory of the basin belongs to the class of high and very high susceptibility to flash floods, and when looking at the length of watercourses in the basin, that percentage is 81.94%. The results of this study clearly indicate the advantages of using modern GIS technologies in the land use and risk management. Geospatial analysis is of particular importance in the field of managing regions that stand out as particularly vulnerable to some natural disasters. 

Vehicle classification is a crucial task owing to vehicles' diverse and intricate features, such as edges, colors, shadows, corners, and textures. The accurate classification of vehicles enables their detection and identification on roads and facilitates the development of an electronic tollcollection system for smart cities. Furthermore, vehicle classification is useful for traffic signal control strategy. However, achieving accurate vehicle classification poses significant challenges due to the limited processing time for real-time applications, image resolution, illumination variations in the video, and other interferences. This study proposes a method for automated automobile detection, recognition, and classification using statistics derived from approximately 11,000 images. We employ SURF-based detection and different classifiers to categorize vehicles into three groups. The Traffic Management System (TMS) is crucial for studying mobility and smart cities. Our study achieves a high automobile classification rate of 91% with the medium Gaussian Support Vector Machine (SVM) classifier. The paper's main objective is to analyze five object classifiers for vehicle recognition: Decision Tree, Discriminant Analysis, SVM, K-Nearest Neighbor Classifier (KNN), and Ensemble Classifier. In the discussion section, we present the limitations of our work and provide insights into future research directions.

Tourism is one of the most developed industries in the world that is continuously growing. It has many different shapes and types with many different factors that affect its success. Over the years, tourism has changed. The new era of tourism is trying to put focus on present environmental problems such as the amount of waste, the use of natural resources and the pollution that it produces as a result of different activities. In this paper, the effect of natural and artificial resources on the development of three types of ecotourism is observed on the area of Semberija and Majevica in Bosnia and Herzegovina. Types of tourism that were research are: cultural and heritage tourism, spa (healing) tourism and recreational tourism. All these types have a great presence on the observed area. The distribution and attendance of the three types of tourism mentioned above is largely dependent on natural elements, such as water and forest areas, which can have both a positive and a negative effect on its development. On the area of Semberija and Majevica, types of tourism largely depend from the location and its surrounding.

The main goal of this research is to examine thermal comfort in the central area of Belgrade (Serbia), over a period of 30 years (1991-2020). The Universal Thermal Climate Index (UTCI) was used as a measure for evaluating outdoor thermal comfort (OTC). The obtained results were considered separately for each season, as well as at the annual level. The analysis was carried out on the basis of an extensive database, which included hourly values (7h, 14h, 21h CET) of meteorological parameters, as well as their average daily, minimum, and maximum values.

The obtained values of UTCIs show a positive growth trend during all four seasons. A significant increase in the annual values of UTCIs was also recorded. Four of five years with the highest average UTCIs were recorded in the last decade of the survey, more precisely in the period 2015-2020. The years that stand out for the frequency of record spring, autumn and winter UTCIs values are 2017, 2018, 2019 and 2020. On an annual level, minimum UTCI value has rising trend of 0.099°C/year, while at maximum UTCI value, that trend is 0.081°C/year.

The effects of corruption in urban development and urban affairs management in several south Asian countries are examined through a series of specific, distinctive, and provocative cases for which the data is more readily available. The stories and themes provide a starting point for analyzing corruption as a symptom and factor of underdevelopment, affecting efforts to use and allocate scarce resources for a higher quality of life in cities. It shows how corruption stifles imaginative and creative solutions to urban challenges while increasing future revenue sources. 3Ps has provided a chance for the public section to look at various funding expertise and options from the business sector to prepare the public infrastructure. On the other hand, governments in the source of budget limitations and other competing demands for state sources can’t supply each citizenry’s infrastructure. Besides, the private sector has been considered a better resource manager, and the government should concentrate on policymaking. Where P3s are put to fair use, the advantages are immense. Unfortunately, vulnerable to bribery. This is the case; whatever benefits 3P offers in reducing the urban infrastructure deficit may be eroded due to corruption, which could lead to an increase in construction or facility costs.’ rehabilitation. Secondly, a PPP process marred by corruption could lead to inferior construction substances. One of the fund’s big chunks will be diverted to the public officials’ bribing via the project company. Thirdly, a corrupt process could compromise officials’ integrity that has been charged with accountability for inspecting and approving construction works.

The paper defines choice of the optimal excavation method for ore deposits, which are characterized by general irregularity due to their origin, occurrence and different content of the usable minerals. In such complex conditions, the choice of the excavation method is defined according to: the natural characteristics of the deposit and according to the techno - economic parameters of the comparison methods and the methods of multi-criteria optimization.