Frequency Analysis Method Research Articles

Comparison of different quantile delta mapping schemes in frequency analysis of precipitation extremes over mainland Southeast Asia under climate change

This study investigated the frequency analysis of precipitation indices of maximum daily precipitation amount (Rx1day), maximum 5-day cumulative precipitation amount (Rx5day), and maximum length of consecutive dry days (CDD) using various bias-correction schemes over mainland Southeast Asia (MSEA). The bias-correction schemes were based on quantile delta mapping (QDM) with different strategies in selecting the data series, including monthly correction (MC), annual correction (AC), peak correction using annual raw data (PCRAW), and annual correction using extreme-index data series (ACEX). Two regional climate model (RCM) outputs from CORDEX-SEA and APHRODITE rainfall datasets were used as modelled and observed data for methodology verification. The study first compared four frequency analysis methods based on generalized extreme value (GEV), Gumbel (GB), Log-Pearson Type III (LP3), and Lognormal (LOGN) distributions, at 9 selected sites over MSEA, and found that LP3 was the best choice for frequency analysis for the study region. Then, the study compared the four bias-correction schemes at both individual sites and all grids over the entire MSEA and indicated that the PCRAW was the best performer in terms of bias-correction for frequency information. Finally, the study gave an ensembled projection of future extreme indices with 200-yr return based on seven CORDEX-SEA RCMs and suggested a general increasing trend of all indices over MSEA. The study explored the effect of uncertainty originated from adopting various bias-correction schemes in mapping future frequency of precipitation indices and is valuable in revealing the spatiotemporal distribution of precipitation extremes over large areas under climate change which is important for flood/drought risk assessment and adaptation planning.

Frequency Analysis of the Nonstationary Annual Runoff Series Using the Mechanism-Based Reconstruction Method

Due to climate change and human activities, the statistical characteristics of annual runoff series of many rivers around the world exhibit complex nonstationary changes, which seriously impact the frequency analysis of annual runoff and are thus becoming a hotspot of research. A variety of nonstationary frequency analysis methods has been proposed by many scholars, but their reliability and accuracy in practical application are still controversial. The recently proposed Mechanism-based Reconstruction (Me-RS) method is a method to deal with nonstationary changes in hydrological series, which solves the frequency analysis problem of the nonstationary hydrological series by transforming nonstationary series into stationary Me-RS series. Based on the Me-RS method, a calculation method of design annual runoff under the nonstationary conditions is proposed in this paper and applied to the Jialu River Basin (JRB) in northern Shaanxi, China. From the aspects of rationality and uncertainty, the calculated design value of annual runoff is analyzed and evaluated. Then, compared with the design values calculated by traditional frequency analysis method regardless of whether the sample series is stationary, the correctness of the Me-RS theory and its application reliability is demonstrated. The results show that calculation of design annual runoff based on the Me-RS method is not only scientific in theory, but also the obtained design values are relatively consistent with the characteristics of the river basin, and the uncertainty is obviously smaller. Therefore, the Me-RS provides an effective tool for annual runoff frequency analysis under nonstationary conditions.

Результаты опроса руководителей объектов в области управления системой обеспечения пожарной безопасности

Introduction. The article presents the results of a survey of facility managers in the field of fire safety management. The survey was conducted to assess the capabilities of the manager in the field of managing the fire safety system To do this, a survey was conducted of the heads of organizations (persons responsible for ensuring fire safety) in terms of their organizational activities in the field of ensuring fire safety. The task of the work is to identify the features of the managerial activity of the facility manager (the person responsible for ensuring fire safety) in the field of managing the fire safety system in order to detail the management problems that have developed in this area. Methods. To conduct the survey, the method of individual questioning was used. To process the obtained results, the method of frequency analysis was applied using the SPSS software package. Results. The data obtained made it possible to identify the social portrait of the head of the facility, to assess his level of qualification, both in the field of fire safety and in the field of managing the fire safety system. The features of the organization of activities in the field of management of the fire safety system are revealed. Methods are proposed in terms of forming an extended structure of the control system, built so that at each stage of the life cycle of the building, the facility manager can obtain a quantitative description of the fire safety state of the facility and a set of alternatives if such a state requires intervention. Conclusion. The factors influencing the assessment of the state of the controlled system and the manager's awareness of the level of fire safety are determined. The problems faced by the head of the facility in the management of fire safety in the organization are identified. Fire safety management has been reduced to the level of monitoring the performance of fire protection systems. Methods for solving the existing problem of managing the fire safety system are proposed. Keywords: fire safety, management, survey, fire safety system, head of the object of protection.

Reading Online Romance Novels Is Related To Chinese Readers' View of Love

Chinese online romance novels are novels aimed at female readers, which describe the love between women and men. Many young Chinese readers understand that novels have many conventions of plot, but they still engage with the perfect love between handsome men and beautiful women. This leads to a question: is reading romance novels related to Chinese people's concept of love? We cannot prove that there is a causal relationship between online romance novels and readers' view of love. Although many previous studies have been conducted on the influence of literary works on readers' values, some people read online romance novels as they agree with the views of love in the novels. In addition, we have not found research on the relationship between online romance novels and people's views of love. Our research hopes to make up for the lack of research on online romance novels as a genre. For our research, we collected 175 questionnaires. Using the method of frequency analysis, we analysed the specific characteristics of the participants in the study. After this, in accordance with the recommendations of reliability analysis and validity analysis, we used chi-square analysis and variance analysis to deal with the categorical and quantitative data, respectively. We found that people who read online romance novels look forward to marriage more than those who dislike the genre. People who often read online romance novels are more likely to value having common preferences with their partner when pursuing a romantic connection. People who read online romance novels are more worried that their partners may abandon them as a result of physical disability than those who have not read online romance novels. The aim of this paper is to demonstrate that many women who read romance novels have immature views on love.

Research on the Connotation and Development Path of Mission Education for Chinese College Students in the New Era

This paper studies the connotation and development path of mission education for Chinese college students in the new era. Using the mission descriptions of 50 colleges and universities selected from the top 100 colleges and universities in China on the website of “China Education Online” as the research object, the research method of text frequency analysis and cluster analysis is used to search for key phrases, refine key words and form the connotation categories of mission education by clustering, and the mission education system is constructed, which includes world mission, national mission, political party mission, social mission, college mission, discipline mission and talent mission. Through the process of searching key phrases, refining key words and forming mission education connotation categories by clustering, we constructed a mission education system for Chinese college students in the new era, which includes global mission, national mission, political party mission, social mission, college mission, discipline mission and talent mission, and explored the development path of mission education for Chinese college students based on seven mission categories.

ДИНАМИКА ИНТЕГРАЦИОННОГО ВЗАИМОДЕЙСТВИЯ В ФОРМАТЕ СОЮЗНОГО ГОСУДАРСТВА БЕЛАРУСИ И РОССИИ НА СОВРЕМЕННОМ ЭТАПЕ: ФАКТОРЫ ВНЕШНЕЙ СРЕДЫ

The article is devoted to issues of the integration cooperation between Russia and Belarus within the framework of the Union State in the context of external influence at the present stage. It highlights the dynamics in the matter in the period from May 2020 to October 2021. In an applied research based on the methods of event analysis, frequency and thematic content analysis, the authors systematized the external challenges and threats articulated by the member countries of the Union State that hinder RussianBelarusian integration. They revealed specifics of the reaction of key actors to external influence in the context of the internal political situation and union construction. The interest of Russia and Belarus in building mutually beneficial cooperation and deepening integration is emphasized. The authors draw their main conclusion on a recognition of the catalyzation in the Union State integration interaction in the current period. Its driver was largely the negative impulses coming from the external environment. They also contribute additional mobility and instability to the motivation of internal actors and agents. Effective prevention, suppression and minimization of emerging risks are combined with overcoming existing gaps in the internal and external dimensions of the integration process.

Relationship between gender and subjective well-being: survey of married couples

Subjective well-being refers to people’s experience and self-reported measures about the quality of their lives, cognitive evaluation of social and economic activities. This evaluation depends on different factors, like income, standards of living, mood, adaptability, expectation on job-to-pay ratio. The importance of gender in this process cannot be underestimated. Based on data obtained by a sociological survey we examined 75 Altai Krai's married couples responses to determine gender differences in subjective well-being, using a multi-step procedure involving methods of frequency and correlation analysis, the method of studying the relationship between categorical variables. Our results reveal several gender differences, which greatly appear in expectations on a job-to-pay ratio.

Avaliação da estabilidade primária em implantes com diferentes tratamentos de superfície por meio da análise de frequência de ressonância

The prerequisites for success in Implantology, in addition to osseointegration, are obtaining and maintaining implant stability. Much research has been done regarding the surface treatment of implants in order to enhance and shorten the osseointegration time. This gave rise to the concept of hydrophilicity, which influences the level of contact between a biomaterial and the cells present in the tissue where it is inserted. The aim of this study was to evaluate the stability coefficient (ISQ) of two different surfaces of dental implants, one hydrophobic (Neoporos) and the other hydrophilic (Acqua), through the method of resonance frequency analysis (AFR) using Osstell (Integrations Diagnostics, Gothenburg, Sweden). Four implants (3.75 x 9.0 mm, hybrid design with cylindrical body and conical apex and morse taper connection) were inserted in the posterior region of the maxilla with two different surface treatments, one of which was treated with acid etching and blasting (hydrophobic surface – Neoporos - Neodent, Curitiba, Brazil) and another treated similarly to the previous one, but stored in sodium chloride for protection (hydrophilic surface - Acqua - Neodent, Curitiba, Brazil). ISQ measurements (performed in the mesial, buccal, distal, occlusal, and palatal of the implants) were performed in the postoperative T0 (0 days), T1 (40 days), and T2 (90 days). The results allowed us to conclude that, in the present study, there were no significant differences between the means of ISQ of implants with a hydrophilic surface versus implants with a hydrophobic surface, through the AFR.

Generalized Transient-Squeezing Transform: Algorithm and Applications

Time–frequency analysis (TFA) methods can characterize the instantaneous frequency (IF) features of nonstationary signals by constructing the time-domain signal model. However, the traditional TFA methods are ineffective for transient signals that are discontinuous in the time domain and characterized by sharp frequency variation. Therefore, this article proposes a new TFA method called generalized transient-squeezing transform (GTST) to process transient signals by constructing a signal model in the frequency domain. First, the generalized group delay (GD) estimation is calculated based on the frequency-domain signal model. Then, the generalized transient-squeezing operator is constructed by iterative operations. Finally, the time–frequency (TF) energy is rearranged according to the constructed operator. The GTST provides a more compact TF representation (TFR) of the transient signal while maintaining reversibility. Numerical validation shows that the proposed method has higher TF concentration and accuracy in analyzing transient signals compared with other advanced TFA methods. Experimental validation shows the effectiveness of the proposed method in practical transient signal analysis.

Frequency-Domain Energy-Concentrated Synchrosqueezing Transform for Frequency-Varying Signal With Linear Group Delay

Reassigned method (RM) can provide a high energy-concentrated time–frequency representation (TFR) result for the frequency-varying signal with linear group delay by reassigning the TF coefficients among both the time and frequency directions, while the TFR result provided by RM cannot be reconstructed since the reassigned operators in RM are conducted on the absolute short-time Fourier transform (STFT) representation. Time-reassigned synchrosqueezing transform (TSST) is capable of depicting the changing dynamic of the weak frequency-varying signal with perfect signal reconstruction. However, the theoretical assumption in TSST makes it unsuitable to process strong frequency-varying signal. To make the RM result for the frequency-varying signal with linear group delay available for signal reconstruction, a frequency-domain energy-concentrated synchrosqueezing transform is proposed by taking the merits of the two time–frequency analysis (TFA) methods into an integrated whole. In the proposed method, the relationship between the reassigned operators in the RM and the inclination angle of the linear group delay of the frequency-varying signal is first analyzed, and then a new time-reassigned synchrosqueezing operator is formulated by adjusting a time length on the original time reassignment operator in RM on the basis of the estimated inclination angle. The validation results on both the simulated and real-world data highlight that the proposed method can provide a high energy-concentrated TFR result for the frequency-varying signal with linear group delay.

Sales Prediction and Product Recommendation Model Through User Behavior Analytics

The COVID-19 has brought us unprecedented difficulties and thousands of companies have closed down. The general public has responded to call of the government to stay at home. Offline retail stores have been severely affected. Therefore, in order to transform a traditional offline sales model to the B2C model and to improve the shopping experience, this study aims to utilize historical sales data for exploring, building sales prediction and recommendation models. A novel data science life-cycle and process model with Recency, Frequency, and Monetary (RFM) analysis method with the combination of various analytics algorithms are utilized in this study for sales prediction and product recommendation through user behavior analytics. RFM analysis method is utilized for segmenting customer levels in the company to identify the importance of each level. For the purchase prediction model, XGBoost and Random Forest machine learning algorithms are used to build prediction models and 5-fold Cross-Validation method is utilized to evaluate their. For the product recommendation model, the association rules theory and Apriori algorithm are used to complete basket analysis and recommend products according to the outcomes. Moreover, some suggestions are proposed for the marketing department according to the outcomes. Overall, the XGBoost model achieved better performance and better accuracy with F1-score around 0.789. The proposed recommendation model provides good recommendation results and sales combinations for improving sales and market responsiveness. Furthermore, it recommend specific products to new customers. This study offered a very practical and useful business transformation case that assists companies in similar situations to transform their business models.

Analysis of the efficacy of Chinese medicine in the treatment of covid-19 and the study of medication pattern

In order to explore the efficacy and medication pattern of Chinese medicine in the treatment of COVID-19, we conducted statistics on the medication use of Chinese medicine based on some clinical data of novel coronavirus pneumonia (COVID-19) and related literature, and used the statistical method of frequency analysis to screen out the drugs with high frequency of use in patients with different types of novel coronavirus pneumonia (COVID-19). We used the statistical method of frequency analysis to screen out the core drugs with high frequency of use in patients with different types of novel coronavirus pneumonia (COVID-19) and the related main drug symptoms; Several drugs with good conversion effect were screened out by mean comparison method in terms of conversion time of drugs, and drug analysis was also conducted by data mining and other methods, so as to derive several groups of core drug combinations of Chinese medicine in the treatment of novel coronavirus pneumonia (COVID-19), and to provide data support and research directions for the effectiveness of Chinese medicine intervention in the treatment of novel coronavirus pneumonia (COVID-19).

Bots in Public Arenas of Social Networks

In the study of social bots, one of the important trends is the transition from a technology-centered understanding of bots as a threat to information and computer security to a broader, socially-focused understanding of bots as a new tool of informational influence used by various social actors in online social networks. This transition is of value to modern sociology. As one such actor, the authors consider a group of civic activists who use bot-technology to construct and solve the problem of defrauded equity holders. The novelty of the article lies in the interpretation of this group’s activities in the context of the concept of public arenas. The botnet “Deceived equity holders of LenSpecStroy” was detected thanks to the author’s complex methodology that combined the method of frequency analysis of messages, profiling of bot accounts, including static and behavioral analysis of user profiles, statistical analysis of texts, analysis of the botnet’s structural organization, analysis of the content of its publications, and analysis of bursts of network publication activity. Analyzing these bursts of publication activity and the content of botnet publications showed how bot-technologies aided in implementing effective techniques aimed at constructing and maintaining the social problem of defrauded equity holders: expanding the capacity of the public arena, realizing (creating) dramaturgical novelty and emotional richness in discussing the problem, taking into account the organizational specifics of the public arena, directing interest in the problem towards other (related and equally important) public arenas (media, legislative and executive power, political parties).

Simulation experiments comparing nonstationary design-flood adjustments based on observed annual peak flows in the conterminous United States

While nonstationary flood frequency analysis (NSFFA) methods have proliferated, few studies have rigorously compared them for modeling changes in both the central tendency and variability of annual peak-flow series, also known as the annual maximum series (AMS), in hydrologically diverse areas. Through Monte Carlo experiments, we appraise five methods for updating estimates of 10- and 100-year floods at gauged sites using synthetic records based on sample moments and change trajectories of observed AMS in the conterminous United States (CONUS). We compare two methods that consider changes in both central tendency and variability - a Gamma generalized linear model estimated with weighted least squares and the Generalized Additive Model for Location, Scale, Shape (GAMLSS) - with a distribution-free approach (quantile regression), and baseline cases assuming stationarity or only changes in central tendency.‘Trend-space’ plots identify realistic AMS changes for which modeling trends in both central tendency and variability were warranted based on fractional root mean squared errors (fRMSE). They also reveal statistical properties of AMS under which NSFFA models perform especially well or poorly. For instance, quantile regression performed especially well (poorly) under strong negative (positive) skewness. Although the nonstationary LP3 distribution accommodates most AMS with trends well, the sensitivity of NSFFA model performance to different sample moments and trends suggests the need for more flexibility in prescribing design-flood adjustments in the CONUS. A follow-up comparison of regional NSFFA models pooling at-site AMS would further illuminate NSFFA guidance, especially for AMS with properties less conducive to NSFFA modeling, such as positive skewness and increasing variability.

Knowledge Management and Experience Transfer in Major Maintenance Activities: A Practitioner’s Perspective

Major overhauls, outages, shutdowns and turnarounds (MoOSTs) are significant maintenance interventions needed on a periodic basis to optimise the performance of physical industrial assets (PIAs). However, uncertainties in the forms of emergent and discovery work which sometimes cause delays and cost overruns are quite common partly because, MoOSTs are characterised by inherent challenges such as, but not limited to, short execution spans, volatility in ever-evolving schedules, task complexities as well as huge offline production and/or operation costs etc. Furthermore, in the literature, other complex elements which further constrains decision-makers in MoOSTs from satisfactorily achieving predetermined objectives have been identified, one of which is the lack of a formalised approach for capturing tacit knowledge from experienced practitioners. Consequently, because MoOSTs is an applied discipline, significant human endeavours are required in the planning and management, which makes it pertinent to examine and obtain the perspectives of experienced MoOSTs practitioners. Therefore, the aims of this study are two folds; firstly, to examine the extent of alignment between findings from literature as it relates to the challenges encountered during MoOSTs, as well as probe their underlying causes in practice. Secondly, to show how relevant the findings from this study would be in providing a baseline for establishing a proposal for capturing MoOSTs knowledge and the transfer of experience. The research approach adopted; thematic synthesis of themes which emerged from knowledge management challenges in MoOSTs identified via an earlier systematic literature review (SLR); and then, the identified challenges were validated through conducting interviews with practitioners. Demography analysis as well as specific MoOSTs related questions were administered via questionnaires, which were then analysed using frequency analysis method. Additionally, semi-structured interviews were conducted to investigate the perceptions of practitioners on pertinent MoOSTs issues. Both questionnaires and interview questions were formulated by findings obtained from the SLR, so as to examine whether the knowledge management challenges identified in the literature exist in practice, and if they do to what extent. In total, the selected responses of 49 practitioners, with origin across five industries were examined to determine the extent of alignment between literature and the practice-based perspectives. Based on the results, nine challenges were identified as critical themes, six of which were associated with managing knowledge. The study identified not only known constraints from literature but also their underlying causes based on the perspective of practitioners involved in multiple MoOSTs, which is crucial for developing sustainable mitigation. A unique contribution of this research is the mapping of demographic information such as industry, country, job class, years of experience, MoOSTs organization size, frequency for performing MoOSTs, etc., to responses obtained from participants, which has not been shown in literature prior to now. The importance of such rigorous efforts in the research design, is crucial for enabling the adoption of holistic approaches to eliminating the underlying causes of challenges encountered in MoOSTs, based on first hand reporting of people involved. In addition, the relevance of such first-hand analyses of responses obtained from this study; serve as baseline for the introduction of the proposal to adequately manage knowledge management issues in this discipline.

Short-time Fourier Transform Using Odd Symmetric Window Function

In this paper, a novel time–frequency (TF) analysis method, called the short-time Fourier transform using odd symmetric window function (OSTFT), is proposed using odd symmetric window function to replace the conventional even window function of STFT. Different from conventional STFT acquiring the amplitude maximum at time and frequency centers, OSTFT acquires the minimum amplitude of 0. Hence, OSTFT can obtain a TF representation (TFR) with high TF resolution by utilizing the leaked energy rather than restraining it. It is worth to mention that the proposed OSTFT can vitiate the effect of window size we choose on the TFR obtained. Furthermore, it also has a good performance on signals with complex instantaneous frequencies (IFs), even crossing IFs. Because we just replace the conventional window function of STFT, the time-consuming of the proposed OSTFT is at the same level as the conventional STFT. The effectiveness of proposed OSTFT has been validated on two complex multi-component simulated numerical signals and a signal collected from the brown bat.

Familial and Socio-Cultural Factors Contributing to the Rising Trend of Drug Addiction in Youth in Pakistan

Aim: To know about the major familial and socio-cultural factors contributing to the rising trend of drugs and substance use in youth in twin cities i.e. Rawalpindi and Islamabad. Methods: The study was conducted in July-September 2021 in Twin Cities i.e. Rawalpindi and Islamabad. Data was collected from 150 young drug addicts (between the age group of 15 to 40 years). Snow ball and purposive sampling techniques were used to collect the data. A pre devised interview schedule having close and open ended questions was used. Frequency analysis method was used to represent the basic demographic data whereas a 4-points Likert Scale was used to know the extent of factors contributing to the rising trend of drug addiction in youth. Results: Results showed that slightly more than one third of the respondents (34%) were quite young (21-25 years). Peer group/ bad company was found responsible factor to great extent (71%), To increase sexual pleasure was also found responsible (45.8%), Lack of knowledge about harms of drugs was found responsible to great extent (49.3%). Another factor i.e. curiosity to use / taste drugs was also found responsible to great extent (77.3%). Conclusion: Problem of drug addiction in youth in Pakistan is rising at a worrying trend. Numerous familial as well socio-cultural factors in the etiology of drug abuse and addiction have been found responsible. Keywords: Drug, Substance, Addiction, youth, familial, social-cultural, factors, Pakistan,

An Empirical Mode Decomposition approach for automated diagnosis of migraine

This study presents an Empirical Mode Decomposition (EMD) approach that aims to automatically detect migraine disease (MD) from electroencephalogram (EEG) recordings of migraine patient (MP) and healthy control (HC) subjects. First, the Multiscale Principal Component Analysis (MSPCA) method was applied to remove the noise on the raw EEG signals. Later, EEG signals were separated into intrinsic mode functions (IMF) components by EMD method. Statistical features were calculated and extracted from each IMF component. By applying the Kruskal Wallis (KW) test, the ability to distinguish these features in classification was tested. Classification performances are tested by classifying the features of each IMF component with a few leading ensemble algorithms. The highest classification accuracy of 92.47% was achieved by classifying the features of the IMF1 component with the Random Forest learning algorithm. At the last stage of the study, a comparative analysis with different time–frequency analysis methods is presented. As a result of the experimental comparison of our proposed method, it has been observed that it has a higher classification performance than other studies that detect EEG-based MD. With these aspects, our study reveals that it has the potential to be used as a computer aided diagnosis system that will support expert opinion in the detection of MD.

OPTIMIZATION OF OPERATIVE DELIVERY OF WOMEN IN LABOR WITH PLACENTA PREVIA

The aim – to evaluate the effectiveness of preventive ligation of uterine vessels during caesarean section in women with placenta previa.
 Material and Methods. The study was conducted on the basis of the Regional Perinatal Center and Maternity Hospital № 5 (Odessa) for 2000–2020 and performing the main stage of cesarean section after reducing perfusion in the placenta. Uterine ligation was performed after fetal removal. The volume of blood loss, the condition of the mother and fetus were monitored, and perinatal results were analyzed.
 Statistical processing was performed by methods of variance and frequency analysis using Statistica 13.0 software (TIBCO, USA).
 Results. The mean age of pregnant women was 33.4±1.2 years. The clinic of placenta previa during pregnancy was extremely scanty. As a rule, the diagnosis was made during ultrasound monitoring. In 16 (17.7 %) there was repeated bleeding from the genital tract without pain and increased uterine tone, with the development of anemia of moderate severity. Single bleeding was observed in 53 (58.9 %) women.
 Blood loss was 1380±112 ml in group I, 466±34 ml in group II (p<0.05). The frequency of anemia in the postoperative period was 38.0 % and 17.5 %, respectively (p<0.05). All newborns were discharged on the 5-7th day of the postpartum period in satisfactory condition. There were no cases of distress syndrome.
 Conclusions: 1. The method of control of blood loss during placenta previa by ligation of the uterine arteries is effective – blood loss was in group I 1380±112 ml, in group II – 466±34 ml (p<0,05). 2. The frequency of anemia in the postoperative period was 38.0 in group I and 17.5 % in group II (p<0.05).

The organizational culture of airlines as a risk factor for the professional health of pilots and flight safety in modern Russian Civil Aviation

Introduction. We present the study results of pilots of different age groups about the role of campaign policies in ensuring the safety of flights, health, and social well-being of pilots. The study aims to learn the ideas of civil aviation pilots of different age groups about the role of campaign policies in ensuring flight safety. Materials and methods. The researchers used the following methods as empirical research methods: focus group method, content analysis of pilots' statements, frequency analysis method, implemented in the SPSS-20 program. Results. According to the frequency analysis results, we identified adverse factors of the labor process that negatively affect flight safety. Of these, the most damaging factors of labor activity are: a violation of the elements and features of the organizational, legal and material, and economic management subsystems (organizational characteristics) - 97.5% of respondents; infringement of the work and rest regime of civil aviation pilots - 100% of respondents; stress in the workplace - 92.5% of respondents; poor-quality training - 77.5%; manipulation of wages - 77%. Conclusions. The analysis of the obtained results allows us to conclude that the management policy of the organization and personnel is a crucial factor determining flight safety, a high level of motivation to work, productivity, and health of pilots.