Danger Class Research Articles

Influence of meteorological factors on the moisture content of fine forest fuels: responses of fire danger class to different microclimates on the example of European beech (Fagus sylvatica L.) stands

Abstract Due to the increased number of forest fires, a detailed examination and knowledge of the effects of the microclimatic conditions of forests is currently significant. The study carried out in Arboretum Borova hora (Slovak Republik), investigates the influence of meteorological factors (air temperature, relative humidity), the value of the Angström index, and the danger class of the Angström index on the moisture content of fine fuel at the edge of a beech forest stand, but also in its interior. We tested three working hypotheses: a) meteorological conditions differ significantly between the edge and the interior of the beech forest, b) the moisture content of fine fuel is higher in the beech forest interior than at the forest edge, c) the Angström index fire danger class is higher at the edge of the beech forest than in its interior. We created a calibration curve that was also used to measure the humidity of beech leaves with the help of the ME 2000 hygrometer. Our results show that edge beech stands are significantly more susceptible to fires, lower air humidity and fine fuel moisture content, and higher air temperatures than forest interiors. From our point of view, the microclimate is considered the main factor that explains the difference between the vegetation structure of the forest edge and the forest interior.

Точка росы как основа оперативного показателя лесопожарной опасности

The problem of preventing forest fires and timely mobilization of extinguishing agents is particularly acute in the Irkutsk Region, where forests cover considerable areas. The use of classical indices for assessing forest fire danger does not always provide accurate results in the operational planning of fire extinguishing measures. The aim of this study is to develop a simple and effective indicator for predicting the occurrence of forest fires. The forestries of the Irkutsk Region, which were most severely affected by forest fires, were chosen as the object of this study. In the course of the study, it has been necessary to solve a number of problems, such as assessing the adequacy of the existing methods, developing a more accurate and simple indicator for local conditions, establishing the algorithm for calculating and the scale for assessing the fire danger class. As the initial data, the publicly available data from the meteorological observations archives and the data from the Remote Monitoring Information System of the Federal Forestry Agency (ISDM-Rosleskhoz) have been used. The methods of cluster analysis and correlation and regression analysis have been applied. The dependence of the number of forest fires on weather conditions in sparsely populated areas has been revealed. The frequency of the cycles of the number and area of forest fires is 3–4 years. Various options for calculating the accumulated dewpoint deficit for predicting the number and area of forest fires have been considered. The closest correlation has been found for the indicator calculated over 10 days. Foreign experience in assessing fire danger according to weather conditions having been analyzed, an assumption has been made about the potential partial use of the Australian FFDI index. In the calculations, a satisfactory result has not been achieved. Therefore, it has been proposed to use the accumulated dew-point deficit over 10 days as an indicator of forest fire danger. The number of forest fires is described through the quadratic dependence on this indicator. A scale for assessing fire danger, adapted to the scale based on the Nesterov index, has been developed. For practical use, the calculation algorithm in MS Office Excel has been described, which makes it possible to apply the proposed indicator in the forestries of the Irkutsk Region. The indicator based on the accumulated dew-point deficit over 10 days will make it possible to check the state of forest fire danger according to weather conditions in accordance with the developed scale using the described algorithm and the macro for calculation in MS Excel.

The composition of avalanche hazard maps with the help of ArcGIS on the base of geomorphological analysis for the mountainous areas of Chernivtsi region

An analysis of the geomorphological factors of avalanche formation in the mountains of Chernivtsi region has been. With the use of ArcGis, a geomorphological analysis has been carried out and classes of avalanche danger were identified. An avalanche danger map for the mountainous territory of the Chernivtsi region has been constructed. Territories with increased avalanche risk have been identified, thanks to GIS technologies, the areas of territories with certain classes of avalanche danger have been calculated. A description of the territories with the highest classes of avalanche danger has been carried out. Keywords: avalanche hazard, relief, underlying surface, spatial analysis, GIS technology.

The Risk-Level Change of Dam Break Due to the Population Growth in the Dam Downstream

This research intends to evaluate the risk-level change of dam break due to the number of population growth rates in the dam downstream. The number of population growth rates in the dam downstream area causes the number of populations that is impacted by disaster risk. In this research, there is conducted the danger class classification of dam failure based on the increasing number of population growth rates. In this research, there is conducted a class classification about the dam failure based on the increasing of population growth rate. The methodology is started from data collecting such as PMF design flood that is used for analyzing the dam break to be obtained the flood boundary of the dam downstream area, Map of the Digital Elevation Model that is for knowing the topography of the dam downstream area, population data which is obtained from BPS that is for knowing the population growth rate so it can predict the population number until the life time of the reservoir, and the land use data that is for knowing the population growth rate in the downstream dam area so it can be known the development of residence until the life time of reservoir. Then there is carried out the evaluation and assessment, which is based on the number of risk populations. The result show that there are 6 dams with very high danger level of the downstream damage level and the classification assessment of dams is extreme such as the dams of Bintang Bano, Rotiklot, Napungette, Lolak, Kuwil, and Pandanduri. However, the other four dams also show a very high danger level but in the assessment classification of dam is high (not extreme) such as the dams of Batu Nampar, Kengkang, Sepit, and Jangkih Jawa. The result is hoped can predict the danger classification of dam failure during the life time of the reservoir. Additionally, it can give input to the policymaker in determining the risk classification of dam failure. Moreover, it can be as one of the inputs in developing the risk classification model of dam failure.

Recycling of municipal waste in crop production as condition for reducing the toxicological load on ecosystems

In the period from 2013 to 2020, in all regions of Russia, there was an increase in household waste by 4.5-6.9 times an average. The study has identified that the properties of some wastes allow using them in economic sphere; it predetermines the interest in wastes as a secondary material resource. Some waste can be used as a fertilizer material and a substance for soil formation. It has to be considered that waste use can cause a number of serious negative processes, affecting all components of the ecosystem. Moreover, the polluting strength depends on the chemical composition of waste and the regulations for waste use. The purpose of the study is a geoecologic assessment of the resource potential of household waste in Orel in order to determine the possibility of their subsequent use in the region’s agriculture. The authors have presented the results of a ten-year monitoring of the resource potential of sewage sludge. According to chemical and biological components determined by the analyses, the examined waste belongs to IV, V classes of danger to the environment. It proves that they can serve as an organomineral fertilizer for the biological reclamation of disturbed lands.

Influence of the composition of atmospheric air pollution on genotoxic effects in the buccal epithelial cells in children

Introduction. This publication presents the third fragment of a comprehensive multi-parameter pilot study to create a methodology for assessing the open-air odor’ impact on human’s adaptive potential. The pilot study was carried out in the little town (50 thousands of inhabitants), mainly the food industry and agro-industrial complex work, but enterprises of 1-2 classes of danger are absent. Air emissions from operating enterprises have a specific odor that causes complaints of inhabitants. Materials and methods. The effects of genome instability (EGI) in children attending kindergartens located at a distance of 1.7-5.9 km from enterprises - the primary sources of odor - were assessed. EGI was determined non-invasively using a micronucleus test on exfoliating cheek epithelial cells. The epitheliocytes from 112 children of 5 -7 years old were examined simultaneously with a collection of atmospheric air samples from the walking areas of the kindergartens which the examined children attended. These atmospheric air samples were taken for gas chromatography-mass spectrometric determination of their chemical composition. Results. Seventy-eight chemical compounds belonging to different classes of chemicals were identified in the air samples. The groups of children from different kindergartens did not differ statistically in any of the 13 assessed indicators of the cytome analysis of the buccal mucosa epithelium cells, and the levels of genotoxic and toxic effects did not go beyond the average expected values presented in literature and our studies for differents groups of comparison. High-level and statistically significant direct correlations between the total content of air pollutants with proven genotoxic activity and the two main indicators of the micronucleus test on cheek epithelial cells: the frequencies of cells with micronuclei and cells with accepted apoptotic bodies were revealed. No correlation was found between summarized levels of the detected chemicals limited concentrations and the results of cytome analysis of children’s buccal epithelial cells. Limitations. correct formation of groups for examination, the severity of the criteria for cytotome analysis and identity of cytogenetic effects identification in the course of cytotome analysis by different researchers. Conclusion. The effects of genome instability in the buccal epithelial cells in children were shown to be mainly associated with the presence of substances with proven mutagenic, carcinogenic and neogenic activities, but not with the total excess of hygienic standards for the content of chemical compounds in the air.

Fire Danger on Jambi Peatland Indonesia based on Weather Research and Forecasting Model

Monitoring drought related to peat fire danger is becoming essentials due to the adverse impacts of peat fires. However, the current monitoring is mostly based on station data and has not yet covered all parts of peatlands. This research was carried out to initiate a spatial monitoring for peat fire, particularly in Jambi province. Our approach was simple by integrating Weather Research Forecasting (WRF) output with a drought-fire model. This research aims to: (i) calibrate rainfall, air temperature and soil moisture data from WRF output; and (ii) analyze temporal drought related to fire danger. A drought-fire model known as Peat Fire Vulnerability Index was applied with daily inputs of WRF output at 5km resolution, which were comprised of rainfall, air temperature, and soil moisture. The results showed that calibration reduced rainfall magnitude, and slightly increased the maximum air temperature and soil moisture. The calibration performance was good as shown by a very low percent bias (less than ±5%), and lower error (RMSE=16.5; MAE=9.5). Our analysis showed that drought triggered by El Niño in 2015 had escalated extreme fire danger class by 38% compared to normal year (2018). This has been confirmed by a low variation of proportion of extreme class during July-August 2015. The results suggested that integrating spatial global climate data will benefit to the improved drought-fire model by providing spatial data. The results are expected to be a reference on drought and peat fires mitigation action.

Monitoring of forest conditions during fire danger

A variety of information on forest ecosystem can be obtained by using remote sensing techniques nowadays. The use of space data of forest monitoring is economically beneficial, because it allows to quickly obtain objective information needed by forest users to solve practical problems. Satellite data provides wide coverage of forest lands, high accuracy of results, and high frequency of received data. Space images of the territory of Ovruch district of Zhytomyr region of Ukraine were selected for the study in the summer of 2020. The definition of the rock composition is carried out by methods of the guided classification, namely Bayesian classifier. It is found that 70% of forests are pine, the aspen, hornbeam, birch, alder and ash breeds of tree are found in smaller numbers. In Ukraine according to statistical data for 2000-2020, 51,4 thousand hectares of forest plantations were damaged and destroyed by forest fires. Therefore, objective and timely information on the fire effects is necessary for the solving a wide class of applied problems of forestry. Determining the area of damaged forests is an important task in assessing the ecological and the economic damage caused to forest management by forest fires. In the work technologies for defining the forest area, in which the fire occurred, are reviewed using the space images of Landsat 8 sattelite. For detecting burned areas and levels of damage a normalized NBR pre and post fire index and DNBR index are used. For forecasting forest fires a mathematical model based on Bayesian theorem and a quarterly thematic map with classes of fire danger are created. To check the accuracy of the results of the projected model, a combination of the thematic map with a fire layer of the defined areas is carried out. This software product is flexible and versatile enough, it can be easily adapted to use not only for the determination of burned forest lands, but also for other territories.

Матіс Є. О. АНАЛІЗ ПРОГРАМНОГО ЗАБЕЗПЕЧЕННЯ ОЦІНКИ ЕКОЛОГІЧНОСТІ ОБ’ЄКТІВ НАВКОЛИШНЬОГО ПРИРОДНОГО СЕРЕДОВИЩА

The increase of ecofriendlyness and safety of technologies and estimation of their influence on a natural environment are based on many principles: study of technological processes and exposure of sources of formation of harmful substances. On the quantitative estimation of receipt of contaminents in the environment, normative requirements, sanitary-hygienic descriptions; feasibility study, technological regulations, maximum possible level of physical influences, on the classes of wastes danger. Maximum possible concentration of harmful substances in the air, water objects; methodologies, estimations of influence at the environment, project and operating data; on the complex estimation of ecofriendlyness of technologies. The actual research and practice task of ecological estimation is development of the informatively-algorithmic providing of evaluation of ecofriendlyness and unconcern of industrial objects on the basis of improvement of theoretical, methodical positions of complex ecological analysis. Thus, the development of methodological support for solving the problem of assessing the environmental friendliness of enterprises is relevant for the Environmental Quality Management of the environment, aimed at improving the information and algorithmic component of studying the level of environmental safety of system objects. Modern information systems for assessing the safety of natural and manmade objects are based on methods of risk analysis, product life cycle analysis, and forecasting the consequences of negative impacts on environmental components and public health. All the software tools discussed in the article are used for closed-cycle economics, life cycle assessment, building certification, sustainable design, ErP and environmental design directives, environmental product declarations, environmental information technologies, product carbon footprint, environmental footprint, product impact on the environment, resource and energy efficiency and water footprint.

Adaptive Artificial Intelligent Technique to Improve Acquisition of Knowledge in the Educational Environment

It is now possible to make the logical thinking of humans, computer-controlled robots, and technology on the educational Environment platform by using artificial intelligence. These method-based robotic systems begin replacing human resources in all industries, which helps resolve various characteristic difficulties that include emotional skills, creative thinking, cognitive, and depletion in the educational platform. The Adaptive Artificial Intelligence Technique (AAIT) has been refined in this study to fulfill the learning objective of increased higher-order learning and skill acquisition in the Educational Environment. It enables more intelligent decision-making by taking into account all essential aspects of a company. As a result, big data plays a crucial role in today’s businesses. A powerful tool for proactive and automated management when combined with artificial intelligence (AI). Saving time and money by automating and optimizing routine tasks may be possible for your business with the right AI technology. Productivity and operational efficiencies will be increased. Use cognitive technologies to make faster business decisions. Therefore, the learning achievement model (LAM) and Risk Student Model (RSM) are established on the educational environment platform. As well as optimizing interpersonal resilience, the Learning Achievement Model is also utilized to increase innovative abilities in the Educational Platform. In the Danger Class Diagram, the Estimation Algorithm reduces the risk of learning failure, enhances cognition, and deprives the recognizing platform. Experiments and simulations are conducted to determine the reliability of the proposed framework based on the accuracy, F-Means, Sensitivity, specificity, and Performance (SSP).

A Priority-Based Tag Identification Protocol for the Large-Scale RFID System

Radio Frequency Identification (RFID) technology has been widely deployed in IoT-enabled applications because of its cheapness, simultaneous multi-item-identification, and strong information storage capability. In a large-scale RFID system, all tags belong to different groups according to the item-associated brand, value, or danger class. However, the existing works assume that groups equally share the maximum identification efficiency 36.8% under the optimal parameter settings. This letter proposes a Priority-based Tag Identification (PTI) protocol for RFID systems. In PTI, the high priority group enjoys a higher identification efficiency than the low priority groups. This is achieved by using the priority queue technique, which enables the reader to detect the tags with the highest priority and only allows them to respond to the reader. Our experiments show that due to the benefit of priority queues, the maximum slot efficiency of the PTI protocol can be improved to 78.9%.

An improved drought-fire assessment for managing fire risks in tropical peatlands

Peatlands transformation in Indonesia has caused immense ecological and environmental degradation. Land use conversion has changed this natural carbon sink to a drought- and fire-prone ecosystem. Public awareness to tackle the drought and fire risk in peatlands has led to the development of drought-fire index. Current knowledge states that both climate and hydrology have a strong influence on drought-induced fire in tropical peatlands, yet the role of soil hydraulic properties in controlling the drying of peats remains unclear. This study develops an improved drought-fire index for tropical peatlands, called the Peat Fire Vulnerability Index, by incorporating groundwater and soil water retention information. We tested the new index on two peatland regions in Kubu Raya and Batanghari, Indonesia, to assess fire danger. We monitored daily rainfall, groundwater tables, and soil moisture from 2018 to 2019 on eight stations in the peatlands. Our model was calibrated against the observed drought index of two stations, and the results were verified with actual fire events through daily fire hotspots and fire burned areas in the other six stations. Results showed that soil-hydrological properties influenced the moistening and drying of peats through capillarity. Our model showed good performance in assessing fire danger during the calibration period, as indicated by three employed statistical metrics: the RMSE-standard deviation ratio (RSR = 0.57), Kling-Gupta Efficiency (KGE = 0.81), and percent bias (PBIAS = 1%). For verification, all observed fire events fell in high and extreme fire danger classes predicted by PFVI. Further, our findings revealed the importance of the groundwater table as a threshold of fire events. The high fire danger class was mostly found when groundwater table dropped below 40 cm, and burned areas only occurred when the groundwater table was below 60 cm. These findings suggest that our drought-fire index can be used as a peat fire risk management tool, and its application may minimize fire risks in tropical peatlands.

Efficiency evaluation of the weighted mean calculation of the forest fire hazard class

Nowadays, cost-optimization of aerial patrolling plays a key role in the context of limited aerial forest protection funding. Forest Fire Danger Class is the main indicator that regulates the work of forest fire services. Usually, it’s calculated by the nearest weather station data. Some information systems use the mean of several nearby weather stations to estimate large areas, such as the surveyed area of aerial forest protection. The idea of using the mean weighted index with the weather stations weighting factor is not new. Even though, this idea isn’t widespread due to the calculation complexity and questionable efficiency in practice, this study proposes a scientifically substantiated method of quantitative comparison of two approaches and the direct calculation method of the economic impact when transition to using the mean weighted Forest Fire Danger Class calculation algorithm. The first time such an indicator was used to obtain derivatives of analytical information products. A long-term analysis of forest fire rate showed that the weighted mean of the Forest Fire Danger Class value is 6.7% greater in correlation with the number of forest fires than the usual mean value. The use logarithmic transformation of the forest fire occurrence frequency and population density allows statistical criteria to be reasonably used.

Fire Danger Harmonization Based on the Fire Weather Index for Transboundary Events between Portugal and Spain

Portugal and Spain have a cross-border cooperation protocol on wildfires response for a buffer strip of 25 km for each side of the border. In spite of the success of this collaboration, there are issues to be improved, since Portuguese and Spanish authorities use different methodologies to assess the daily fire danger. A methodology to harmonize fire danger and its interpretation by the Portuguese and Spanish Civil protection authorities in the transboundary buffer strip area is hereby presented. The fire danger index used is the Canadian Fire Weather Index (FWI), which requires input from meteorological data and gives an indication of fire intensity. The fire danger class is an important decision support tool for preventing and fighting wildfires. Since the meaning of FWI values change from region-to-region according to its specific characteristics, a calibration process was performed based on statistical data of the daily FWI values, the number of fires and burned area between 2005 and 2013. The results of the FWI calibration and harmonization of the data for the five danger classes minimizes the fire danger discrepancies across the border. This methodology has the potential to be reproduced in other areas.

Study of acute toxicity of the drug Homeovox

Relevance. Assessment of acute toxicity is a necessary stage of preclinical research of a tablets Homeovox homeopathic. The aim of present research is study of acute toxicity Homeovox. Methods. Homeovox was administered once orally and intraperitoneally to mice and rats in the maximum possible volumes for each of the administration methods and for each animal species, at the highest possible concentrations. Equivalent volume of 1 % starch solution was administered to animals of the control groups. Euthanasia and pathoanatomical dissection were performed 14 days after drug administration. Periods of animals intoxication with a detailed description of the observed clinical picture were registered. Results. The median fatal doses were not identified because Homeovox did not cause death of animals at introduction of the maximum allowable volumes and maximum allowable concentrations. The morphological view of the internal organs, detected during pathoanatomical dissection of all experimental animals, did not differ from that observed in control animals. Conclusion. It was determined that Homeovox at oral and intraperitoneal introduction concerns to practically non-toxic substances. According to classification Sidorov KK this homeopathic tablets may be related to 5th toxicity class. According to GOST 12.1.007-76 Homeovox may be related to 4th danger class.

Weather-related thresholds for wildfire danger in a Mediterranean region: The case of Greece

The objective of the following paper is to identify weather-related thresholds for wildfire danger, i.e., the potential extent of fire, based on local weather conditions. The target area is Greece, a wildfire prone Mediterranean country which experienced on average 2000 wildfires annually over the last two decades. Initially, the Fire Weather Index (FWI) component of the Canadian Fire Weather Index (FWI) System (FWI System) adopted by the European Forest Fire Information System (EFFIS), is evaluated with respect to its wildfire danger predictive ability. Hence, weather and wildfire data at municipality level and on a daily basis, for the period 2000–2016 are exploited. The analysis showed that the FWI thresholds proposed by EFFIS for assessing the level of fire danger in Europe are too low for the case of Greece and, therefore, are not representative of the country's fire weather conditions. Two statistical approaches, cluster analysis and non-linear least-squares regression, are subsequently applied to determine the most appropriate FWI thresholds for discrete levels of wildfire danger. The results are presented in 4 sets of FWI thresholds and they are further evaluated on the basis of verification measures. All sets of FWI thresholds were found to significantly improve the predictability of wildfire danger compared to the EFFIS fire danger class thresholds. In particular, two of them were found to meet selected performance requirements for a balanced predictive performance, namely a reduced overestimation of wildfire danger and increased reliability in danger classification. The results are expected to have significant practical implications for wildfire prevention and risk mitigation strategies implemented by the forest fire control agencies of the country.

Landscape-geochemical preconditions and regularities of toxic elements distribution on “Oleshkivski pisky” military training site territory

It is characterized main features of landscape-geochemical structure of “Oleshkivski pisky” military range. It is analysed special aspects of military training activity influence on the of soils and plants contamination level with heavy metals. Sampling scheme for studying of heavy metals migration features, with respect to landscape structure of the territory is substantiated. Special features of heavy metals distribution in soils at different distances from firing positions within military range have been determined. It is investigated distribution and accumulation of I and II danger class heavy metals in soil and vegetational cover of the military training site. The regularities of spatial distribution of mobile and potentially accessible forms of heavy metals are determined. It was defined that content of heavy metals in three movable forms are represented in the following geochemical units, mg/kg: in acid soluble form – Mn > Zn > Pb > Cu > V > Ni > Co > Cd; in exchangeable form – Mn > Zn > Pb > V > Co = Ni > Cu > Cd; in water soluble form – Mn > Zn > Pb = V > Co > Ni > Cd > Cu.
 It is presented studies results on accumulation intensity and the nature of distribution of gross and mobile heavy metals forms in soil space and on their migration in the soil profile. The dominant technogenic geochemical unit was extracted: Cd > Hg > Pb > Cu > Zn > Ni > V > Co > Mn. Landscapes with maximum polyelement contamination have been identified. Landscape-geochemical map of “Oleshkivski pisky” military training site territory was drawn, relying on own field and experimental materials. Migration dynamics of Ni, Zn, Cu, V, Pb and other heavy metals mobile forms in the soil profile of soddy underdeveloped sandy soil during 2015–2019 under impact contamination levels has been determinated. The peculiarities of heavy metals mobile forms absorption in typical plant species of the military range territory during 2015–2019 vegetation periods were clarified.

Performance enhancement techniques for traffic sign recognition using a deep neural network

An advanced traffic sign recognition (ATSR) system using novel pre-processing techniques and optimization techniques has been proposed. During the pre-processing of input road images, color contrasts are enhanced and edges are made clearer, for easier detection of small-sized traffic signs. YOLOv3 has been modified to build our traffic sign detector, since it is an efficient and effective deep neural network. In this YOLOv3 modifications, grid optimization and anchor box optimization were done to optimize the detection performance on small-sized traffic signs. We trained the system on our traffic sign dataset and tested the recognition performance using the Mean Average Precision (MAP) on the Korean Traffic Sign Dataset (KTSD) and German Traffic Sign Detection Benchmark (GTSDB). We used the bisection method for selecting the optimum threshold of confidence score to reduce false predictions. Our ATSR system is capable of recognizing Prohibitory, Mandatory, and Danger class traffic signs from road images. ATSR can detect small-sized traffic signs accurately along with big-sized traffic signs. It shows the best recognition performance of 98.15% on the challenging KTSD (the previously reported best performance was 90.07%) and 100% on the GTSDB. Result comparisons show that ATSR significantly outperforms ITSR, TS detector, YOLOv3, and D-patches, on KTSD.

İŞYERİ TEHLİKE SINIFLARINA GÖRE ÇALIŞANLARIN GÜVENLİK İKLİMİ ALGILARININ İNCELENMESİ

The aim of this study is to determine whether the perceptions of safety climates differ according to hazard classes. A total of 223 participants from three selected workplaces representing different hazard classes were reached and analyzed. According to the results of the analyzes, the perception of the safety climate is significantly different according to the hazard classes. Participants in the workplaces belonging to the less dangerous class perceived their workplace as safer. As the danger class increases (very dangerous class) it has been determined that employees perceive their workplaces less secure. In addition, the perception of safety climate differs significantly from gender and position in the firm. The safety climate of the female employees was higher than the perceptions of the male employees. The safety climate of the managers was higher than the perceptions of the employees. In the education variable; the perceptions of secondary school and associate degree graduates have higher safety climate perceptions. Finally, in the age variable; employees under 30 years of age had the highest perception of safety climate.

АНАЛІЗ ІСНУЮЧИХ ПРОГРАМНИХ КОМПЛЕКСІВ ДЛЯ РОЗРАХУНКУ ЧАСУ ЕВАКУАЦІЇ ЛЮДЕЙ ПІД ЧАС ПОЖЕЖІ

В статті розглядаються існуючі програми для розрахунку часу евакуації людей під час пожежі. Розглянуто наукові роботи з вивчення моделей руху людей під час евакуації з приміщень з використанням різних методів математичного розрахунку. Проведений порівняльний аналіз існуючих програмних комплексів в області розрахунків. Наведено порівняльний аналіз математичних методів закономірностей руху людей під час пожежі у програмних продуктах. Дано висновок щодо функціональності досліджуваних програмних комплексів.