Personnel Monitoring Research Articles

A critical appraisal of South African oncology pharmacy standards: A comparison with international best practice standards.

The demand for oncology pharmacy services is set to increase as the burden of cancer rises in sub-Saharan Africa. Oncology pharmacists may be exposed to antineoplastic drugs (ADs) and need comprehensive health and safety guidelines. The objective of the study was to assess the effectiveness of the local oncology pharmacy practice standards, by critically evaluating them against international best practice standards. We compared the Independent Clinical Oncology Network (ICON) administration of ADs standards resource document (ICON standards) and Good Pharmacy Practice (GPP) standards with the International Society of Oncology Pharmacy Practitioners (ISOPP) Standards for the safe handling of cytotoxics, and the Quality standard for the oncology pharmacy service (QuaPos), using 10 domains: transport of ADs, working arrangements, education and training, engineering controls, use of personal protective equipment, risk management, medical monitoring of personnel, cleaning procedures, accident management and documentation, labelling and checking procedures. The ICON standards align closely with international best practice standards, but the GPP standards focus only briefly on the compounding of ADs.The GPP standards are outdated and some of the stipulations are erroneous. Oncology pharmacists would do better to adhere to the more comprehensive ICON standards, although these standards also need to be updated in line with best practice. Revising and improving both these local standards in consultation with key role players in the oncology pharmacy industry will go a long way in protecting the health and safety of oncology pharmacists in South Africa.

ОСОБЛИВОСТІ ВПРОВАДЖЕННЯ МОНІТОРИНГУ ПЕРСОНАЛУ НА СУЧАСНИХ ПІДПРИЄМСТВАХ

Businesses related to various niches and industries use employee monitoring to protect themselves from potential risks of data leakage and other external threats. Employee monitoring is a new strategy in today's business that is central to improving productivity and operational efficiency. The application of scientific methods of monitoring and analyzing the activities of employees in real time allows organizations to achieve a high level of accountability, optimal allocation of resources and making informed management decisions. Such a monitoring system contributes to the rise and development of the enterprise, creating a more productive and motivated work environment. The article examines the peculiarities of the implementation of employee monitoring as an important tool for ensuring the efficient operation of the enterprise, maintaining labor discipline and rational use of resources. Separate forms of monitoring that are used in practice are considered. Attention is focused on the legal aspects of the monitoring process, compliance with the needs of both employers and employees, in particular, taking into account the rights and privacy of the latter. In the modern conditions of business operation and development, employers have an interest in the most efficient use of their staff's working time. Time control is one way to achieve this. Controlling working hours can be efficient and beneficial for a company, but it can also raise certain ethical and legal issues. It is important that this control is carried out in compliance with all relevant legal requirements and taking into account the rights and interests of employees. Therefore, the employer must develop and implement internal regulatory documents that regulate monitoring procedures, as well as ensure that employees are informed about their rights and obligations in this process. This will avoid conflicts and ensure the legal purity of monitoring, maintaining a balance between the needs of the enterprise and the rights of employees. The choice of personnel monitoring and tracking tools is not limited to technical aspects, but includes the creation of a culture of trust and openness in the relationship between the employer and employees.

ELECTRONIC ASSESSMENT ANXIETY SCALE: DEVELOPMENT, VALIDITY AND RELIABILITY

The widespread availability of internet access in daily life has resulted in a greater acceptance of online assessment methods. E-assessment platforms offer various features such as randomizing questions and answers, utilizing extensive question banks, setting time limits, and managing access during online exams. Electronic assessment enables real-time monitoring, customization, and scalability of feedback, benefiting students, academic staff, and administrative personnel. However, students encounter specific challenges in the electronic assessment environments. These challenges include limited control over test settings and the isolated nature of taking exams without peers. Furthermore, the technological proficiency of both instructors and students, along with resource constraints (computers, mobile devices, internet), can impede the effective utilization of these assessment tools. Technical issues like slow internet connection or disconnections can have significant consequences, especially in online exams, posing difficulties for corrections. The main goal of this study is to develop a Likert-type scale capable of measuring anxiety related to technical issues, social isolation, and the test interface experienced in e-assessment contexts. The study consists of two separate groups: the first group comprising 359 participants and the second group consisting of 356 participants. Both groups include undergraduate and pedagogical formation certificate program students from a university in the Eastern Anatolia Region of Turkiye. Construct validity was assessed through exploratory and confirmatory factor analyses. Item parameters were examined using item analysis based on classical test theory. As a result of the study, a two-factor scale structure comprising 21 items measuring social and technical anxiety was developed. These two dimensions account for 59.89% of the total variance. The Cronbach’s alpha coefficient for the entire scale was 0.93, the McDonald’s omega coefficient was 0.93, and the construct reliability was 0.99.

Algorithms for pollutants forecasting

The impact of pollution on human health is very well known and affects more and more economic and social activities. Since the authorities do not always have the necessary equipment and trained personnel for pollution monitoring, we observed the need to develop algorithms for approximating different polluting values. This paper is a review of the main algorithmic approaches to estimate pollutant values. Most of the proposed approaches are based on machine learning, neural networks and decision trees.

Research on standardization of power transformer monitoring and early warning based on multi-source data

To meet the growing demand for integrated monitoring of complex power grid equipment, it is necessary to improve the situational awareness model of power transformers. The model is expected to assist monitoring personnel in timely identifying transformers with deteriorating trends among massive and discrete monitoring information, and to make responses in advance. However, the current transformer state awareness technology generally has the problem of single data source and poor timeliness, and still requires monitoring personnel to make artificial analysis and prediction in combination with telemetry information, which cannot fully meet the requirements of power grid equipment monitoring. This paper is based on multi-source data fusion technology, through associating and mining transformer alarm information, equipment maintenance records and power transmission and transformation online monitoring data, to extract the dimension features of transformer operation situation assessment. By constructing a multi-layer perceptron model, a transformer state transition model based on the principle of Markov chain is established, which can predict possible defects 2 h in advance and achieve good results, and determine the transformer state early warning index, providing sufficient time for monitoring personnel to deploy transformer operation and maintenance work in advance. Finally, the effectiveness of the method proposed in this paper is proved by the case of transformer crisis state in a city substation, and the method proposed in this paper has important significance for transformer state early warning.

Monitoring of cardiovascular emergencies in the emergency department

In the emergency department, patients with potential or confirmed cardiovascular diseases constitute a significant portion of the overall patient population. Monitoring for cardiovascular surveillance of these patients, until and during the diagnostics and acute therapy often presents an interdisciplinary and interprofessional challenge. This is partly due to the limited number of monitoring spaces in emergency departments. Therefore, it is crucial to establish a differentiated indication for cardiovascular monitoring. Despite limited monitoring resources, ensuring high patient safety is paramount. The correct approach holds significant prognostic importance. For patients requiring extended monitoring, especially using invasive systems, close personnel monitoring is essential, in addition to appropriate staffing and medical equipment. The overarching goal for such patients is to ensure prompt transfer to a suitable destination unit. The provision of an intensive care bed for further care within one hour is aimed for according to the directive of the Federal Joint Committee on staged emergency care in hospitals. Often, at the beginning of the emergency department visit, a definitive diagnosis is not yet established - this is addressed accordingly with symptom-oriented considerations. The present review article focuses on the practical Implementation and modalities of monitoring, as well as its application in a selection of cardiovascular diagnoses in the emergency department.

WZMACNIANIE ŚRODKÓW BEZPIECZEŃSTWA DLA WOJSKOWYCH BAZ LOTNICZYCH - INTEGRACJA ZAAWANSOWANYCH TECHNOLOGII I STRATEGII OPERACYJNYCH

The security of military air bases is of paramount importance in light of increasing global tensions and rapid technological advancements. The goal of this article is to investigate the protection of these critical installations by identifying significant threats, optimizing security measures, and integrating advanced technologies. The research problems of the work are presented in the form of questions: How can military air bases be protected against emerging technological threats? What are the most effective security measures for mitigating both external and internal threats? How can advanced technologies be integrated into existing security protocols to enhance overall security? The research hypothesis underscores the necessity for robust, multi-layered security systems combining physical protection, advanced technological measures, and clear operational procedures. The research methods used in the work include, among others, a comprehensive review of literature and data analysis. The study examines past incidents and current best practices. The research highlights the potential of advanced technologies such as drone surveillance, biometric access controls, and artificial intelligence to significantly enhance security. However, their successful implementation requires proper integration, continuous updates, and thorough training for personnel. The study also emphasizes the importance of balancing stringent security measures with operational efficiency, ensuring that enhanced security protocols do not impede daily operations. Internal security measures are critical, as insider threats can be as dangerous as external attacks. Stringent background checks, continuous personnel monitoring, and fostering a culture of security awareness are essential to mitigate these risks. The study calls for international cooperation to share best practices and innovations in military air base security, recognizing that these challenges are global and collaborative efforts can lead to more robust solutions. Future research should focus on developing advanced cybersecurity defenses, exploring the human factors influencing security personnel performance, and fostering international cooperation to share best practices. Integrating traditional security measures with modern technologies and international collaboration can significantly enhance the protection of military air bases, ensuring their safety and operational readiness in an increasingly volatile world. By addressing both conventional and emerging threats, this research provides actionable insights for enhancing the security of military air bases globally, ensuring their safety and operational readiness amidst evolving threats and technological landscapes.

Monitoring of surgical staff x-ray exposure in the operating room with DosiBadge

Surgical procedures involving the use of x-rays in the operating room (OR) have increased in recent years, thereby increasing the exposure of OR staff to ionizing radiation. An individual dosimeter makes it possible to record the radiation exposure to which these personnel are exposed, but there is a lack of compliance in the wearing of these dosimeters for several practical reasons. This makes the dose results obtained unreliable. To try to improve the rate of dosimeter wearing in the OR, the Dosibadge project studied the association of the individual dosimeter with the hospital access badge, forming the Dosibadge. Through a study performed at the Tours University Hospital in eight different ORs for two consecutive periods of 3 months. The results show a significant increase in the systematic use of the dosimeter thanks to the Dosibadge, which improves the reliability of the doses obtained on the dosimeters and the monitoring of personnel. The increase is especially marked with clinicians. Following these results and the very positive feedback to this first single-centre study, we are then planning a second multicentre study to validate our proof of concept on different sites, with the three brands of individual dosimeters used in France i.e. dosimeters supplied by Dosilab; Landauer and IRSN.

Detection of ionizing radiation in operating room and hospital areas

The implementation of new medical techniques and technologies has increased occupational exposure to ionizing radiation and consequently the development of neoplasia and adverse effects on health personnel. Have real information on the absorbed dose by healthcare personnel exposed to ionizing radiation in an operating room. TLD 100 dosimeters were used to measure absorbed doses by brightness curves. 42 surgical interventions in different specialties were monitored, in each intervention a minimum of 4 dosimeters were used, with the objective of analyzing the dose based on the participation role of the individual within the operating room. A database was created with the 42 monitored surgeries, for each one a minimum of 4 analyzed data were obtained (one for each participant in the surgical procedure, that is, one for each dosimeter). The highest absorbed dose was for the specialty of traumatology, followed by otorhinolaryngology, neurosurgery and finally ophthalmology. It was possible to use an adequate monitoring system to measure the dose of absorbed ionizing radiation during different surgical procedures. Based on the results, constant dosimetry follow-up monitoring of trauma specialty personnel is recommended.

An optimization strategy for anchor point placement for underground coal mine area positioning

Coal mine underground positioning technology plays an important role in safe mining, personnel monitoring and dispatching, and post-disaster rescue. Recently, there has been an increasing interest in indoor localization due to the demand for location-based services. Diverse techniques have been described in the literature to improve indoor localization services, but their accuracy is significantly affected by the number and location of the anchors, which act as a reference point for localizing tags in a given space. This work describes APOTSA, a novel approach for discovering a high-quality placement of anchors to improve the accuracy of area-based indoor localization systems while requiring a shorter execution time than existing approaches. The proposed algorithm is based on Tabu search and optimizes the localization accuracy by minimizing the expected residence area, which indicates a geographical area containing the tag. APOTSA's effectiveness with respect to solution quality and time of execution is shown by evaluating different scenarios involving up to five anchors. Moreover, a simple yet effective discretization approach is introduced to speed up the calculations, and the trade-off between the running time and solution quality of our algorithm can be controlled by a parameter. Our results indicate that the expected residence area and the time of execution can be reduced by up to 9.5 % and 99 %compared to the state-of-the-art local search anchors placement (LSAP) algorithm, respectively.

A Lightweight Pine Wilt Disease Detection Method Based on Vision Transformer-Enhanced YOLO

Pine wilt disease (PWD) is a forest disease characterized by rapid spread and extremely high lethality, posing a serious threat to the ecological security of China’s forests and causing significant economic losses in forestry. Given the extensive forestry area, limited personnel for inspection and monitoring, and high costs, utilizing UAV-based remote sensing monitoring for diseased trees represents an effective approach for controlling the spread of PWD. However, due to the small target size and uneven scale of pine wilt disease, as well as the limitations of real-time detection by drones, traditional disease tree detection algorithms based on RGB remote sensing images do not achieve an optimal balance among accuracy, detection speed, and model complexity due to real-time detection limitations. Consequently, this paper proposes Light-ViTeYOLO, a lightweight pine wilt disease detection method based on Vision Transformer-enhanced YOLO (You Only Look Once). A novel lightweight multi-scale attention module is introduced to construct an EfficientViT feature extraction network for global receptive field and multi-scale learning. A novel neck network, CACSNet(Content-Aware Cross-Scale bidirectional fusion neck network), is designed to enhance the detection of diseased trees at single granularity, and the loss function is optimized to improve localization accuracy. The algorithm effectively reduces the number of parameters and giga floating-point operations per second (GFLOPs) of the detection model while enhancing overall detection performance. Experimental results demonstrate that compared with other baseline algorithms, Light-ViTeYOLO proposed in this paper has the least parameter and computational complexity among related algorithms, with 3.89 MFLOPs and 7.4 GFLOPs, respectively. The FPS rate is 57.9 (frames/s), which is better than the original YOLOv5. Meanwhile, its mAP@0.5:0.95 is the best among the baseline algorithms, and the recall and mAP@0.5 slightly decrease. Our Light-ViTeYOLO is the first lightweight method specifically designed for detecting pine wilt disease. It not only meets the requirements for real-time detection of pine wilt disease outbreaks but also provides strong technical support for automated forestry work.

СОВРЕМЕННыЕ ИНСТРУМЕНТы МОНИТОРИНГА СОСТОЯНИЯ ВОВЛЕЧЕННОСТИ ПЕРСОНАЛА

In this article, the authors consider modern methods of personnel monitoring regarding the possibility of their use in studying the state of employee engagement in the company. The authors evaluate the conditions of use of each of the monitoring tools, give recommendations on their use, noting the positive characteristics of each of the methods and their possibilities in studying the state of staff involvement. The article also provides brief recommendations on the use of each of the tools for monitoring staff engagement, offers recommendations on which topics a particular survey should address, which questions should be included in it, and highlights the features of the proposed monitoring tools. The article provides examples of modern monitoring tools that are available to advanced employers

FUNCTIONAL FEATURES AND TYPOLOGY OF SUBURBAN TERRITORIAL COMMUNITIES OF TERNOPOL

Peculiarities of the timing of suburban (in relation to the city of Ternopil) territorial communities are considered. Such parameters as the area of suburban territorial communities were analyzed; peculiarities of the number, density and location of the population of communities; financial condition and capacity of communities, according to their incomes, expenses, transfers, location of industry, features of transport infrastructure. Attention is drawn to the main environmental problems of suburban communities, possible ways to overcome them, the availability and peculiarities of the use of recreational resources and the spread of recreational infrastructure are motivated. The functional structure and spatial arrangement of the territories of the nature reserve fund were analyzed. The problems of the development of territorial communities at the present stage are becoming particularly urgent. Important aspects of development are ensuring coherence of economic, social and environmental vectors, taking into account the potential of local resources, as well as additional favorable factors, such as investments, logistics and infrastructure. Within territorial communities, an inventory of the resource base is carried out, investment passports are created, development strategies are developed, existing problems are analyzed and ways to solve them are substantiated. Solving these complex tasks requires a high level of professional training of management personnel and effective monitoring of development processes. The authors have published a series of articles devoted to the analysis of the potential of natural resources, problems of environmental development management, unbalanced land use and other aspects. The choice of suburban territorial communities of the city of Ternopil is due to their belonging to the former Ternopil district (according to the old administrative and territorial system) and their location around the regional center. What determines the specificity of the structure of agriculture, the location of the population, industry, transport infrastructure, environmental conditions, etc. The adoption of the state regional development strategy for 2021-2027 is the main legal document aimed at strategic planning of effective development, including territorial communities. The main methodological approaches are the strategy of sustainable development, the concept of balanced ecological-social-economic development and the principles of the system approach. The suburban territorial communities of Ternopil include: Biletska, Baikovetska, Velikobirkivska, Velikogaivska, Velikoberezovytska and Pidhorodnyanska territorial communities. Recreational resources in the studied communities are represented mainly by forest areas and a pond network, which is often equipped with the necessary infrastructure. Historical and architectural resources are represented by a network of ancient churches, cultivated springs, etc. Separately, we can recall the arched railway bridge in the village. Butsniv at the end of the 19th century. A much better developed tourist infrastructure is represented by recreation centers, numerous hotels, and catering establishments. The general ecological state of the main components of the natural environment shows an increase in the degree of environmental pollution. Areas of excessive pollution are observed around industrial centers, large industrial facilities, landfills, radiation-contaminated territories, where various types of pollution are deposited and along hydraulic networks, highways and railways, which affects the natural living conditions of the population. The conducted research showed that suburban territorial communities have an unsatisfactory land use structure. The population of the communities is prone to pendulum migrations, due to better employment opportunities and a greater number of various services in the regional center. Within the studied communities, it is necessary to optimize the structure of land use, increase the area under natural lands, carry out measures to replant and afforest unproductive and eroded agricultural lands. Plant forests to create a full-fledged integrated green zone of the city of Ternopil, which will perform important recreational and ecological stabilization functions. The conducted analysis demonstrates a significant inhibition of the ecological vector of sustainable development. We see a perspective in the development of geoecological projects, environmental measures in schools, organizations and institutions, communities. It is necessary to create new and expand existing nature reserves. In general, optimization measures aimed at improving the ecological condition of the territory and the quality of life of the population should be carried out. The results of the study can be useful to the administrations of suburban territorial communities for the implementation of optimization measures of various levels and directions. Key words: territorial community, financial capacity, infrastructure, ecological condition, nature reserve fund.

The data acquisition methodology to build the source information base for personnel monitoring (technological approach)

The All-Russia monitoring of the staffing needs in librarianship is an efficient way to get valuable current and prospective data through using the latest technological solutions and efficient interaction between public libraries affiliated with regional/municipal agencies of culture of the Russian Federation constituents.The authors discuss the technology and results of data acquisition, as well as the obtained staff monitoring database. For the first time, the tested method of data acquisition enabled the Russian State Library to monitor the staff needs in librarianship in the multitasking mode and to apply the cloud technology with the professional application designed for online operation on the national scope. The authors explore the differences between national and foreign software providers in rendering specific services to online users. The professional application enabled to conduct monitoring in the shortest term, to optimize expenses and to save resources in complex environment. Among methodological solutions, the Center of Educational Programs Monitoring of the Research Educationa Activities Department of the Russian State Library, have designed the standardized data collection forms for every level of libraries.The effectiveness of this methodology enabled to launch the system of data acquisition for the All-Russian monitoring of staff needs in the library sphere, to systematize data by the RF constituents and as a data set, and to build the source database for staff monitoring in librarianship.

Integration of Fire Detection and Personnel Accountability System

Fire incidents in public spaces pose significant risks to life and property. Traditional fire detection systems often suffer from delays and inaccuracies, necessitating the development of advanced solutions. This paper presents a comprehensive system for integrating fire detection and personnel accountability in surveillance scenarios. With the increasing concerns about safety in public spaces, the need for effective systems to detect fires and ensure personnel safety has become paramount. Traditional methods rely on manual intervention or basic sensors, often resulting in delayed or inaccurate alerts. To address these challenges, our system employs advanced image processing and machine learning to enhance safety measures. By analyzing surveillance camera feeds, it detects changes in pixel intensity, smoke patterns, and heat signatures to identify potential fire incidents. Machine learning models, such as convolutional neural networks (CNNs), are trained to accurately classify fire and non-fire regions in video frames. Additionally, the system tracks personnel presence and movement, ensuring accountability within the surveillance area. Modular and scalable, our system integrates seamlessly with existing infrastructure, providing reliable fire detection and personnel monitoring. Experimental results demonstrate its effectiveness, contributing to enhanced safety in public spaces and facilitating prompt emergency responses.

Wireless Sensor Placement Optimization for Bridge Health Monitoring: A Critical Review

In recent years, wireless sensors have progressively supplanted conventional limited sensors owing to their attributes of small size, low cost, and high accuracy. Consequently, there has been a growing interest in leveraging wireless sensor networks for bridge structural health monitoring applications. By employing wireless sensor nodes to gather data from various segments of the bridge, information is relayed to a signal-receiving base station. Subsequently, the health status of the bridge is inferred through specific data processing and analysis, aiding monitoring personnel in making informed decisions. Nonetheless, there are limitations in this research, particularly pertaining to power consumption and efficiency issues in data acquisition and transmission, as well as in determining the appropriate wireless sensor types and deployment locations for different bridge configurations. This study aims to comprehensively examine research on the utilization of wireless sensor networks in the realm of bridge structural health monitoring. Employing a systematic evaluation methodology, more than one hundred relevant papers were assessed, leading to the identification of prevalent sensing techniques, data methodologies, and modal evaluation protocols in current use within the field. The findings indicate a heightened focus among contemporary scholars on challenges arising during the data acquisition and transmission processes, along with the development of optimal deployment strategies for wireless sensor networks. In continuing, the corresponding technical challenges are provided to address these concerns.

Influence of systemic inflammatory indices on hospital stay and dialysis post-earthquake: A clinical study.

Natural disasters pose significant challenges to medical response due to the surge of patients and emergent injuries. Amid such scenarios, where personnel for patient monitoring might be scarce, effective biomarkers are crucial for guiding treatment plans and predicting patient prognosis. We aimed to evaluate the correlation between systemic inflammatory indices and morbidity in earth-quake-induced crush injuries. Additionally, we assessed the potential of these indices as prognostic markers for adverse outcomes. We studied 140 patients with earthquake-related crush injuries (ECR) admitted between February and March 2023 and compared them to 200 healthy controls (CG) chosen using a simple random method. Using the complete blood count data upon admission, we computed and statistically compared indices including NLR (neutrophil lymphocyte ratio), PLR (platelet lymphocyte ratio), MLR (monocyte lymphocyte ratio), SII (systemic immune-inflammatory index), SIRI (systemic inflammatory response index), and PIV (pan-immune inflammation value). Regression analyses determined the prediction of hospitalization duration and dialysis necessity. PLR and MLR upon admission significantly predicted the length of hospital stay. MLR and SIRI were significant predictors for dialysis requirement, with Exp(B) values of 0.306 (p = 0.024) and 1.261 (p = 0.038), respectively. Systemic inflammatory indices can serve as valuable prognostic tools in disaster scenarios. Utilizing these indices can enhance patient management, effectively allocate resources, and potentially save lives in the aftermath of earthquakes.

COVID-19 monitoring of school personnel through molecular salivary test and dried blood spot analysis.

When the coronavirus disease 2019 (COVID-19) pandemic broke out, most countries enforced school closures as a precautionary measure. Although COVID-19 is still present three years later, schools have been reopened. We aimed to test the association of molecular salivary testing (MST) and dried blood spot (DBS) analysis for community surveillance by investigating the immunological profile of a group of school staff during and following COVID-19 vaccination. We conducted the study in a school in Milan from April 2021, when school staff were administered the first dose of vaccine against SARS-CoV-2, until the school year ended in June 2022. Each participant provided samples for MST and DBS one month (T1, W1) after receiving their first dose of vaccine. Subsequently, they collected weekly MST samples for five weeks (W2-W6), plus a DBS sample in the last week (T2). Both samples were collected one (T3), four (T4), and seven months (T5) after the administration of the second vaccine dose in May 2021. A final DBS sample was collected one year (T6) after T3. Sixty participants provided 327 MSTs and 251 DBSs. None of the MST samples tested positive for SARS-CoV-2 RNA during the study period. A total of 201 DBS samples tested positive for the IgG semiquantitative analysis. Negative samples were found only at T1 (20.45%) and T2 (7.32%). We observed borderline results at T1 (4.55%), T2 (7.32%), and T4 (2.70%). The anti-SARS-CoV-2 average antibody ratio increased after the second dose between T2 and T3, and the trend peaked after the third dose between T4 and T6. We performed an immunoenzymatic assay of antibodies against nucleocapsid protein on samples collected at T1 from five participants who reported having been infected before the study and from four subjects with an abnormal increase in the antibody values at T4. Two samples tested positive in the first group and two in the second one. Our findings show that MST and DBS could be effective tools in the active surveillance of school personnel and that schools could be considered safe settings in view of SARS-CoV-2 infection. Vaccines might have contributed to case and/or symptom reduction.

Use of Statistical Tools and Artificial Intelligence for Hydrosedimentological Analysis in Experimental Units in Semiarid Brazil

Objective: To compare statistical and artificial intelligence tools to assist in the analysis and influence of hydrosedimentological variables on runoff generation and sediment yield in experimental units in the Brazilian semiarid region. Theoretical framework: The increasing frequency of extreme weather events in areas prone to natural disasters has led to economic, social, and loss of life due to the lack of urban planning, disorderly occupation in densely populated areas, intensive use of natural resources, and difficulty in maintaining and conserving natural ecosystems (CARMO & LIMA, 2020). Continuous monitoring of hydrosedimentological processes is necessary for natural resource planning and management. There is a need for expanding long-term environmental monitoring in Brazil, which is not simple and costly. In hard-to-reach areas, investment in tools and variable analysis for secure estimation of flow and erosion is necessary (AIRES, 2022). Method: Data obtained from the São João do Cariri Experimental Basin - SJCEB (13.6 km²) were used through conventional rain gauges and automatic data collection platforms from three micro-watersheds (0.16 – 1.63 ha) and two experimental plots (100 m²) located in the semiarid region of Paraíba, Northeast Brazil. For the analyses, 147 rain events that generated surface runoff in at least one of the five experimental units of the SJCEB were used, with data on area (m²), vegetation cover (0 no cover and 1 with vegetation cover over the entire area), average slope (%), daily precipitation (mm), period without rainfall (days), runoff depth (mm), and sediment yield (kg.ha⁻¹), from 2001 to 2008. The statistical and artificial intelligence tools used in the analyses were: simple linear regression, Pearson correlation, and Self-Organizing Maps (SOM). The models were implemented in the R programming language. Results and conclusion: In the statistical summary of the studied variables, precipitation ranged from 2.2 mm to 133.0 mm, with a mean of 21.1 mm. The period without rainfall ranged from 0 to 240 days, with an average of 16.2 days. Slope varied from 3.40% to 7.50%, with a mean of 5.7%. The average vegetation cover was 0.44, with a median of 0.60. The Pearson correlation analysis revealed that precipitation showed a positive and significant correlation with surface runoff and sediment yield variables, ranging from moderate to strong. Simple linear regression was unable to provide satisfactory answers to assist in the analysis of runoff and sediment yield, therefore considered inefficient for hydrosedimentological regionalization. The unsupervised SOM network, by presenting complex relationships among the studied variables, detected that sediment yield is particularly influenced by the interactions with precipitation, vegetation cover, and slope. Thus, it can be inferred that models based on unsupervised neural networks are attractive alternatives, as they were able to extract complex and nonlinear relationships among the analyzed variables. When there are complex cause-and-effect relationships between variables of hydrosedimentological processes, the use of nonlinear and multivariate models, such as artificial neural networks. Implications of the research: Manipulations in experimental areas have favored the measurement of flow and quantification of sediment yield. However, the high costs to maintain physical structures and the presence of specialized personnel for monitoring, processing, and dissemination of collected data are factors that may make it impractical to maintain and expand environmental monitoring networks in Brazil. In ungauged areas, the prediction of flow and erosion is necessary, and can be performed through mathematical, statistical, or artificial intelligence tools that facilitate the identification of priority areas for intervention. Manipulations in experimental areas have favored the measurement of runoff and sediment yield, but the high costs of maintaining the physical structures and the presence of specialized personnel to monitor, process and disseminate the collected data are factors that make maintenance and the expansion environmental monitoring networks in Brazil. In non-instrumented areas, forecasting and analysis of runoff and erosion becomes necessary, using mathematical, statistical or artificial intelligence tools that favor the identification of priority areas for intervention. Originality/value: Use of different statistical and artificial intelligence tools for hydrosedimentological regionalization in small experimental units in the Brazilian semiarid region, with emphasis on the application of unsupervised learning neural networks (SOM).

АВТОМАТИЗАЦІЯ ОБЛІКУ ТА МОНІТОРИНГУ ПОКАЗНИКІВ ЕФЕКТИВНОСТІ ВИКОРИСТАННЯ ПЕРСОНАЛУ НА ПІДПРИЄМСТВАХ

The article is devoted to the study of accounting and monitoring of indicators of the effectiveness of the use of personnel. It has been established that the rational use of personnel is the main reserve for increasing production volumes, both at the level of each individual enterprise and at the level of the state. Considering this, the issue of monitoring the effectiveness of personnel use is an important methodological task at the theoretical and practical levels. The article defines the problems of automating the monitoring of personnel efficiency indicators. The clarified advantages of monitoring, in particular, the collection and analysis of personnel performance indicators, helps the enterprise to focus not only on control, but also on how effectively the personnel are used and what steps can be taken to improve a certain situation. It has been proven that the implementation of a monitoring system helps to identify problems in time and respond to them before they lead to destabilization of the enterprise. The article describes programs for automation of personnel monitoring, presents the interface and functionality.