Search

The purpose of this research was to compare the geotouristic potential of the Sub-Tatra Region, expressed in the values of expert assessment of geosites, against the preferences of tourists coming to the area. Tourist preferences were evaluated by a survey in which tourists assessed the attractiveness of the types of geosites that can be admired in the area. The expert valorizations showed high and very high indices for most of the analyzed geosites. The highest of these assessment values show particularly high geotourism values for three geosites: the travertine hill with Spiš castle, the limestone hill with Orava castle and the travertine dome in Gánovce. A comparison of these results against average tourist preferences shows a moderate correlation (r = 0.4). Geosites of low and medium value according to expert assessments are rarely selected as the destination for equipment-intensive tourism. The sites with the highest combined valorization coefficients, i.e., hills with castle ruins, are of moderate interest to the surveyed group of respondents. The largest difference is in the assessment of the cave, waterfall and viewpoint geosites, where there is a great interest among tourist respondents, but the expert assessment index is low or moderate. [ABSTRACT FROM AUTHOR]

Air pollution causes more damage to health and economy than previously understood, contributing to approximately one in six deaths globally. However, pollution reduction policies remain controversial even when proven effective and cost negative, partially because of misunderstanding and growing mistrust in science. We used an expert assessment to bridge these research–policy divides in the State of Utah, USA, combining quantitative estimates from 23 local researchers and specialists on the human health and economic costs of air pollution. Experts estimated that air pollution in Utah causes 2480 to 8000 premature deaths annually (90% confidence interval) and decreases the median life expectancy by 1.1 to 3.6 years. Economic costs of air pollution in Utah totaled $0.75 to $3.3 billion annually, up to 1.7% of the state's gross domestic product. Though these results were generally in line with available estimates from downscaled national studies, they were met with surprise in the state legislature, where there had been an almost complete absence of quantitative health and economic cost estimates. We discuss the legislative and personal responses of Utah policy makers to these results and present a framework for increasing the assimilation of data into decision making via regional expert assessment. In conclusion, combining quantitative assessments from local experts is a responsive and cost-effective tool to increase trust and information uptake during time-sensitive policy windows. [ABSTRACT FROM AUTHOR]

The present article deals with two key drivers of social acceptance of wind energy: procedural justice and distributional justice. It is based on a comparative expert assessment carried out in the frame of the Horizon 2020 project WinWind covering six European countries. The focus of the paper is on procedural and financial participation of citizens and local stakeholders in wind energy projects. The first part covers institutional arrangements for public engagement in two areas of the decision-making process—wind turbine zoning/siting in spatial plans and authorization procedures. Here, three levels of public involvement—information, consultation and participation—were analyzed. The second part examines active and financial participation of citizens and local stakeholders. Here, we distinguish between two different modes of governance: institutionalized forms of public governance and voluntary forms of corporate governance. The outcomes suggest that concrete paths to the social acceptance of wind energy are fostered via appropriate institutional spaces for public engagement. Furthermore, missing opportunities for active and passive financial participation can have strong negative consequences for community acceptance [ABSTRACT FROM AUTHOR]

Simple Summary: Human aspects of birds are becoming increasingly popular because birds fulfil an important function for human well-being. Recent studies used ecological indicators, like species richness or diversity, but specific species traits are usually not studied. Here, we studied two new variables, visibility duration and obstruction, which are relevant to human–bird encounters. Visibility measures, if and for how long a bird is visible. Obstruction measures to what extent the bird is concealed by vegetation. We collected behavioral data using focal animal sampling. This was combined with an assessment where experts scored the visibility of the different species on a scale from 1 to 5. We present data for 68 bird species, how visible and obstructed they are, and we assume that this may have an influence on the perception of the species by humans. The most important factor of visibility duration was species identity. Concerning obstruction, 34% of the variance was explained by species identity. A cluster analysis on the species level led to a three-cluster solution. The mean expert assessment significantly correlated positively with visibility duration (r = 0.803) and negatively with obstruction (r = −0.422). The behavioral trait of visibility may be an important aspect in the analysis of human–bird encounters but also for ecological bird studies. Human dimensions of birds are becoming increasingly popular. One aspect is charismatic species and their impact on nature conservation, and the other is the positive impact of birds on human well-being. Studies exploring these relationships are mostly based on species richness, but specific species traits are usually not studied. Here, we propose two new variables, visibility duration, and obstruction, being relevant to human–bird encounters. Visibility measures if and for how long a bird is visible. Obstruction measures to what extent the bird is concealed by vegetation. We collected behavioral data using focal animal sampling (3 min with blocks of 15 s, one-zero sampling). Additionally, species identity, sex, flocking (yes/no) and observation distance were collected. This was combined with an assessment where three experts scored the visibility of the different species on a scale from 1 to 5. The most significant predictor of visibility duration was species identity with an explained variance of 44%. Concerning obstruction, 34% of the variance was explained by species identity. Sex and flocking were not significant. A cluster analysis on the species level led to a three-cluster solution. The mean expert assessment correlated positively with visibility duration (r = 0.803) and negatively with obstruction (r = −0.422). The behavioral trait of visibility may be an important aspect in the analysis of human–bird encounters but also ecological bird studies. [ABSTRACT FROM AUTHOR]

There are many surgical operations performed daily in operation rooms worldwide. Adequate anesthesia is needed during an operation. Besides hypnosis, adequate analgesia is critical to prevent autonomic reactions. Clinical experience and vital signs are usually used to adjust the dosage of analgesics. Analgesia nociception index (ANI), which ranges from 0 to 100, is derived from heart rate variability (HRV) via electrocardiogram (ECG) signals, for pain evaluation in a non-invasive manner. It represents parasympathetic activity. In this study, we compared the performance of multilayer perceptron (MLP) and long short-term memory (LSTM) algorithms in predicting expert assessment of pain score (EAPS) based on patient′s HRV during surgery. The objective of this study was to analyze how deep learning models differed from the medical doctors′ predictions of EAPS. As the input and output features of the deep learning models, the opposites of ANI and EAPS were used. This study included 80 patients who underwent operations at National Taiwan University Hospital. Using MLP and LSTM, a holdout method was first applied to 60 training patients, 10 validation patients, and 10 testing patients. As compared to the LSTM model, which had a testing mean absolute error (MAE) of 2.633 ± 0.542, the MLP model had a testing MAE of 2.490 ± 0.522, with a more appropriate shape of its prediction curves. The model based on MLP was selected as the best. Using MLP, a seven-fold cross validation method was then applied. The first fold had the lowest testing MAE of 2.460 ± 0.634, while the overall MAE for the seven-fold cross validation method was 2.848 ± 0.308. In conclusion, HRV analysis using MLP algorithm had a good correlation with EAPS; therefore, it can play role as a continuous monitor to predict intraoperative pain levels, to assist physicians in adjusting analgesic agent dosage. Further studies may consider obtaining more input features, such as photoplethysmography (PPG) and other kinds of continuous variable, to improve the prediction performance. [ABSTRACT FROM AUTHOR]

The prediction of rock bursts is of paramount importance in ensuring the safety of coal mine production. In order to enhance the precision of rock burst prediction, this paper utilizes a working face of the Gengcun Coal Mine as a case study. The paper employs a three-year microseismic monitoring data set from the working face and employs a sensitivity analysis to identify three monitoring indicators with a higher correlation with rock bursts: daily total energy, daily maximum energy, and daily frequency. Three subsets are created from the 10-day monitoring data: daily frequency, daily maximum energy, and daily total energy. The impact risk score of the next day is assessed as the sample label by the expert assessment system. Sample input and sample label define the data set. The long short-term memory (LSTM) neural network is employed to extract the features of time series. The Bayesian optimization algorithm is introduced to optimize the model, and the Bayesian optimization–long short-term memory (BO-LSTM) combination model is established. The prediction effect of the BO-LSTM model is compared with that of the gated recurrent unit (GRU) and the convolutional neural network (1DCNN). The results demonstrate that the BO-LSTM combined model has a practical application value because the four evaluation indexes of the model are mean absolute error (MAE), mean absolute percentage error (MAPE), variance accounted for (VAF), and mean squared error (MSE) of 0.026272, 0.226405, 0.870296, and 0.001102, respectively. These values are better than those of the other two single models. The rock explosion prediction model can make use of the research findings as a guide. [ABSTRACT FROM AUTHOR]

The optimal development of tourism clusters (quite active and effective, but not allowing overtourism) requires the development of methods for calculating their level of development and potential, taking into account the most important influencing factors. Consideration of the share of factors' influence on the development of tourism clusters does not adequately take into account the infrastructure and urban planning components. This article, based on a literature analysis and expert assessment, identifies the main factors influencing the development of tourism clusters and shows the leading role of infrastructure factors and the provision of a cluster with high-quality hotel stock. Formulas are given for calculating factor indicators and determining the integral level of development of the cluster, as well as its development potential, including infrastructural. An example of calculations of the development potential of a cluster and management decisions made in the field of construction is given using the example of an emerging tourism cluster, "Kirzhach". The results of the factor analysis and calculation of the cluster development potential will allow informed management decisions to be made not only for the investment and construction of hotel real estate and other tourism infrastructure, but also for cluster development priorities and areas of government regulation and support. [ABSTRACT FROM AUTHOR]

Background: Parents of pediatric patients with type I diabetes require competence in hypoglycemia management and skills in glucagon administration to deal with potentially life-threatening severe hypoglycemia. We aimed to compare parents' subjective self-ratings to an objective expert assessment of competences and skills in dealing with severe hypoglycemia. Methods: We interviewed 140 participants to assess their subjective self-ratings. The objective expert assessments used a standardized clinical case scenario of severe hypoglycemia and a practical demonstration of glucagon administration. Results: The participants self-rated their competence in hypoglycemia management as good (5) or very good (6), and their skills in administering glucagon as acceptable (3) [Scale: very poor (1) to very good (6)]. In the standardized clinical case scenario, 1.4% (2/140) of participants named all relevant steps of severe hypoglycemia management. In the practical demonstration of glucagon administration, 92.9% (130/140) of participants committed at least one drug handling error; 52.1% (73/140) committed at least one drug handling error rated with high clinical risk. Conclusions: We found discrepancies regarding participants' subjective self-ratings compared to their performance in the respective objective expert assessments. These discrepancies indicate a lack of error awareness and the need for intervention studies to improve competence in hypoglycemia management and glucagon administration. [ABSTRACT FROM AUTHOR]

This study aims to enhance the effectiveness of the preparation process and the performance of wheelchair users in international billiard competitions through modified equipment. The research methods include analysis and synthesis of the scientific and methodological literature, sociological research methods (questionnaires), expert assessment methods, pedagogical research methods (observation, testing, experimentation), and methods of mathematical statistics. The results of our study are significant: Implementing our developed training program for billiards players with musculoskeletal disorders, utilizing the modified equipment (special mechanical bridge and straps for cue fixation during shots) we created in a pedagogical experiment, demonstrated a probable improvement of 36% in the technical and tactical preparedness of the athletes compared to previous years. This led to a 33% increase in players from the Ukrainian team's competition performance at the national and European Pool Championships (wheelchair division). In conclusion, implementing our developed training program, accompanied by specialized auxiliary equipment, demonstrated promising results in a pedagogical experiment. These findings underscore the potential of the modified equipment and tailored training programs to optimize sports training for individuals with musculoskeletal impairments in adaptive billiards, contributing to the continued humanization of the sport and offering an effective preparation process for the athletes. [ABSTRACT FROM AUTHOR]

The purpose of the article was to investigate the potential of rural green tourism in Ukraine and to determine the main directions of its innovative development, taking into account global, national, and regional trends. SLR (Systematic Literature Review), methods of expert assessment, selective observation, and graphic method were used to achieve the set goal. The article analyzes the current state of rural green tourism in Ukraine; the tourism and recreation potential of rural areas of Ukraine was assessed; promising types of innovations that are currently relevant for implementation in the practice of providing services in the field of rural green tourism in Ukraine are defined and grouped; and the impact of global, national, and regional trends on the current stage of activity and further development of rural green tourism in Ukraine is determined. It is determined that in modern economic conditions, rural tourism serves as a stabilizing factor that will contribute not only to maintaining the normal living standards of rural residents, but also to the development of the region's economy, service infrastructure, household services, and the social sphere. Thus, rural green tourism is the main tool for stimulating the economic and socio-cultural development of rural areas. The results of the assessment of the tourist and recreational potential of rural green tourism of Ukraine showed that the recreational and tourist attractiveness of rural areas is mainly determined by natural and ecological conditions, cultural and historical conditions, and the tourist infrastructure of the region. Financial economic, socio-demographic, and administrative management conditions negatively affect the recreational and tourist attractiveness of rural areas, resulting in the low ability of the rural population to implement innovations. It has been established that in order for the tourist business to be able to quickly adapt to the normal state, it is necessary to introduce innovative types of tourism that will make it possible to attract a larger number of people to the tourist business and establish additional income due to the introduction of innovative offers, new tours, visits to special places, and the entire range of services of the best quality, which will contribute to the accelerated implementation of online forms and digital tools in the provision of tourist services, etc. It has been proven that the introduction of innovations plays an important role in ensuring the sustainable and balanced development of rural tourism in Ukraine, contributing to the creation of new opportunities and improving the quality of tourist services. [ABSTRACT FROM AUTHOR]

Road crashes, although random events, frequently occur on roads. However, certain characteristic infrastructural locations require detailed analysis regarding the frequency of road crashes. This study examines the dynamics of road crashes at characteristic infrastructural locations in Serbia from 2018 to 2022, focusing on bridges, tunnels, railroad crossings, and road work zones. Using data on road crashes from official reports, the analysis includes trends in crash rates, fatalities, injuries, and material damage during the above-mentioned time frame. In addition to the data analysis, 22 experts from the fields of traffic engineering ranked the mentioned characteristic infrastructural locations in terms of road safety. The same questions were asked to six different artificial intelligence software programs. The findings reveal significant variations in crash rates across different infrastructures, with bridges and road work zones having the highest number of crashes. Expert assessment is in line with the analysis of the results, while artificial intelligence gives a completely opposite assessment. [ABSTRACT FROM AUTHOR]

This research develops a method for synthesizing linguistic models of fuzzy systems with fuzzy input and output parameters that are described by linguistic variables. Based on the proposed method, linguistic models of the Title 1000 catalytic cracking unit for heavy residues at the Shymkent oil refinery are developed, describing the dependence of the volume and quality of gasoline on the input and operating parameters of the facility, which are fuzzy. It is substantiated that the use of a fuzzy approach, which allows the use of the experience, knowledge, and intuition (intelligence) of the decision maker and subject matter experts, is the most suitable effective method for synthesizing models of complex, fuzzily described objects and processes for comparison with other methods. The main idea of the proposed work is to solve the problems of shortage and fuzziness of initial information when developing models and optimizing the operating modes of a catalytic cracking unit through the use of knowledge, experience, and intuition of experts in this field. To solve the problems of the shortage of initial quantitative information and the fuzziness of available information when developing mathematical models, it is proposed to systematically use statistical methods, expert assessment methods, and a heuristic method based on fuzzy logic. The scientific novelty of the research lies in the development of a method for synthesizing linguistic models in a fuzzy environment and an algorithm for its implementation, which makes it possible to describe the dependence of the fuzzy values of the object's output parameters on its fuzzy input and operating parameters. The proposed approach allows the formalization and synthesis of models of fuzzily described objects when other methods of model development are not applicable or do not give the expected results. The results of the work were simulated in the MATLAB Fuzzy Logic Toolbox. [ABSTRACT FROM AUTHOR]

The construction industry is naturally complex and constantly changing, with various factors impacting project results. Among the different methods developed to navigate this complexity, partnering is believed to increase project value and performance. Therefore, this research aimed at analyzing and formulating elements as well as indicators at each phase of a partnership-based project life cycle, serving as tools and techniques for measuring the depth of partnering in construction projects. The methodology used included both qualitative and quantitative methods (mixed method). In the qualitative method, the literature from relevant journals, books, and previous research was reviewed. This process was followed by an expert assessment through a Focus Group Discussion (FGD) to define elements and indicators for measuring the depth of partnering in construction projects. Meanwhile, the quantitative method comprised analyzing secondary project data to compare projects with in-depth partnering in order to deliver better value. The result of this research was the development of Key Performance Indicators (KPIs) to measure maturity partnering in partnership-based projects. Typically, the tools were adjusted to different phases of the project life cycle, starting from project initiation, comprising all stakeholders. Consequently, the outcome of this research could be used by organizations in the construction industry to develop partnering in partnership projects in Indonesia. [ABSTRACT FROM AUTHOR]

Safety assessment of modern critical instrumentation and control systems is a complicated process considerably dependent on expert techniques, single/multiple faults consideration scope, other assumptions, invoked limitations, and support tools used during the assessment process. Ignoring these assumptions, as well as the significance of expert and tool influence, could lead to such effects as functional safety underestimation or overestimation in such a manner that functional safety assessment correctness and accuracy are affected. This paper introduces XMECA (x modes, effects, and criticality analysis, where x could be from different known techniques and domains—failures in functional safety, vulnerabilities and intrusions regarding cybersecurity, etc.) as a key technique of safety assessment. To verify the results obtained as XMECA deliverables, expert and uncertainty modes, effects, and criticality analysis (EUMECA) is performed, in particular focusing on decisions and judgments made by experts. Scenarios for processing verbal and quantitative information of XMECA tables from experts are offered. A case study of a possible functional safety assessment approach that considers the above-mentioned techniques and a supporting tool is provided. To assess the trustworthiness of safety analysis and estimation using XMECA, a set of the metrics is suggested. Features of adapting the suggested method for security assessment considering intrusions, vulnerabilities, and effects analysis (IMECA technique) are discussed. [ABSTRACT FROM AUTHOR]

This paper presents a model for determining the availability of continuous systems at open pits using the neuro-fuzzy system. The concept of availability is divided into partial indicators (synthetic indicators and sub-indicators). The presented model in relation to already existing models for determining availability uses a combination of the advantages of artificial neural networks and fuzzy logic. The case study addressed the I ECC (bucket wheel excavator–conveyors–crushing plant) system of the open pit Drmno, Kostolac. In this paper, in addition to the ANFIS model for determining the availability of continuous systems, a simulation model was developed. The obtained results of the ANFIS model were verified with the help of a simulation model that uses certain assumptions about the distribution of failures. This paper was created as a result of several years of field and theoretical research into the availability of continuous systems in open pits, and completes a cycle that consists of several published articles on the subject of modeling the behavior of these systems in real time using a time picture of the state, expert assessment, simulation and AI models, while respecting the multidisciplinarity of the problem (mining technological, mechanical, and information technological aspects). The developed ANFIS model is a key instrument for improving operational efficiency and resource management in the mining sector. Its ability to accurately predict the availability of the ECC system brings not only operational benefits through reduced downtime and optimized maintenance, but also a potential reduction in overall costs at coal open pits. Such an innovative model marks a significant step forward in the mining industry, especially when it comes to continuous systems in coal open pits. [ABSTRACT FROM AUTHOR]

The transportation of bulk or liquid cargo is crucial for ensuring the delivery of such cargo to areas lacking well-established infrastructure or favorable natural conditions. These areas may lack sufficient rail or air transport accessibility, or may not have suitable embankments along rivers, lakes or seas with appropriate loading and unloading facilities. Regarding distinctive characteristics, we would like to emphasize the following: (1) Efficient freight accessibility without the need for more infrastructure that is tailored to the existing natural circumstances; (2) An efficient and cost-effective mode of transportation for the movement of small quantities of goods; (3) The cargo philosophy is designed to meet customer expectations by providing a convenient and personalised service that is focused on delivering goods directly to their door. This research employed theoretical methodologies to characterize the primary force exerted by vehicles in the transportation of bulk and liquid commodities (the relationship between centrifugal force and speed and the relationship between the center of gravity and speed). Furthermore, by using expert assessment, the significance indicators pertaining to the individual criteria impacting the transportation of bulk and liquid cargoes were ascertained, along with the identification of their interrelationships (comparison of the different forces in the transportation process of bulk and liquid cargoes, comparison of the criteria of centrifugal force in the transportation process of bulk and liquid cargoes, comparison of the dangerous factors in the transportation process of bulk and liquid cargoes, comparison of the critical level of tank filling in the transportation process of bulk and liquid cargoes, and comparison of the factors that can affect the dynamics of a vehicle in the transportation process of bulk and liquid cargoes). [ABSTRACT FROM AUTHOR]

There is a need to explore and comprehend the performance of sustainable leadership in enterprises' circular economy-driven innovative activities. Firstly, there is a pressing necessity for businesses to remain agile and responsive to change, utilizing innovation not just as a buzzword but as a strategic tool for adaptation and growth. Secondly, the ethical dimension demands that innovation be pursued responsibly, considering its effects on communities, environments, and future generations. Lastly, the economic imperative underscores that sustainable innovation management can lead to efficiencies, cost savings, and new avenues for revenue generation. An improved comprehensive approach to evaluating the effectiveness of managing enterprises' innovative activities is proposed. This approach is based on the evaluation of 14 partial indicators, each reflecting a specific vector orientation. This assessment allows for the combination of indicators that essentially reflect the personal characteristics of the manager and the combination of formative and resultant factors of the management's influence on the state and results of innovative activity (the above-proposed factor approach). Consequently, it provides an opportunity to obtain a multifaceted, comprehensive, and most complete assessment of the sustainable management of innovative activity based on valid vector orientation within the scope of the subject and the object of research. Based on the proposed improved assessment, indicators of the effectiveness of managing innovative activities were calculated for the seven researched innovatively active industrial enterprises. Thus, the following were calculated: (1) the personal component (Pp) of the evaluation of the effectiveness of leadership in innovative activities using the expert assessment toolkit, (2) the managerial component (Plm), and (3) the innovatively sustainable component (Pis) of the evaluation of the effectiveness of sustainable management of innovative activities based on the internal reporting of the enterprise. This balances the partial subjectivity of the expert method with real data from specific enterprises. Consequently, based on the values of the three assessment components, a comprehensive integral indicator of the effectiveness of managing the innovative activity of the enterprise (Pef) was calculated. The proposed methodology's validation proved its effectiveness and efficiency. The authors forecast the degree of influence of external and internal factors, taking into account the results of a comprehensive, integrated assessment of the effectiveness of sustainable management (Pef) on the economic development and indicators of the enterprise's circular economy-driven innovative activities. This enables a significant strengthening of the resultant factors of managing innovative activities and predicting specific final results of all innovative activities. [ABSTRACT FROM AUTHOR]

This study aimed to improve the control system of the biological stage of wastewater treatment using the quality control information system to support the concept of environmental efficiency management. In this case, the object of the study was the treatment facilities of Sumy city (Ukraine). For automatic control of wastewater quality, pH, oxidation reduction potential (ORP), electrical conductivity, and temperature indicators were taken, as well as hydrobiological analysis of activated sludge and mathematical modelling. The pH of wastewater at the input system has systematically unacceptable values (above 8.5 were recorded). Unacceptable concentrations of sulphur-containing toxicants arrive at the entrance of treatment facilities (0.22–1.3 mg/L). The response of activated sludge biocenosis to increasing concentrations of hydrogen sulphide in wastewater was analysed. Furthermore, a mathematical model of monoculture population growth, with two factors that affect population growth (nutrient concentration and monoculture production concentration), was implemented for the initial assessment of possible negative effects on wastewater treatment. The differential equation of the population dynamics of the i-th species of microorganisms in activated sludge was described. The applied system of automated monitoring of wastewater parameters with expert assessment of activated sludge and a unified mathematical model of approaches allows for a complex system of decision-making support to be realised. However, this requires the construction of mathematical models that would take into account the cause–effect relations that operate under conditions of incomplete technological information and the potential presence of emergencies due to natural disasters and military activities. [ABSTRACT FROM AUTHOR]

Blood vessel visualization technology allows nursing staff to transition from traditional palpation or touch to locate the subcutaneous blood vessels to visualized localization by providing a clear visual aid for performing various medical procedures accurately and efficiently involving blood vessels; this can further improve the first-attempt puncture success rate for nursing staff and reduce the pain of patients. We propose a novel technique for hyperspectral visualization of blood vessels in human skin. An experiment with six participants with different skin types, race, and nationality backgrounds is described. A mere separation of spectral layers for different skin types is shown to be insufficient. The use of three-wavelength indices in imaging has shown a significant improvement in the quality of results compared to using only two-wavelength indices. This improvement can be attributed to an increase in the contrast ratio, which can be as high as 25%. We propose and implement a technique for finding new index formulae based on an exhaustive search and a binary blood-vessel image obtained through an expert assessment. As a result of the search, a novel index formula was deduced, allowing high-contrast blood vessel images to be generated for any skin type. [ABSTRACT FROM AUTHOR]

Comprehensive next-generation sequencing (NGS) panels for cancer diagnostics create a bottleneck for interpretation. QIAGEN Clinical Insights Interpret One (QCI) is a clinical decision support software that supports molecular pathologists in the classification of oncology-related variants. This study compares variant assessments by QCI to assessments utilizing current laboratory methods. Eight laboratories were recruited by the external quality assessment organization GenQA. The laboratories submitted VCFs from sequencing studies performed on both hematological disorders and solid tumors for analysis by QCI and an independent laboratory. Results were compared and conflicts were resolved using a panel of experts. In total, 14/149 variants (9%) reported as Tier 1 or Tier 2 by either QCI or the submitting laboratory were found to be discordant after expert panel review. In contrast, 41/149 variants (28%) reflected discrepancy among human reviewers. The expert panel was unable to reach resolution on eight variants. QCI demonstrates high concordance in the classification of actionable mutations with independent laboratory methods and expert assessment. The rate of disagreement among laboratories and the expert panel was greater than the disagreement between QCI and expert assessment. Disagreement among experts highlights the subjectivity of classifying variants. The study demonstrates that QCI interpretation supports streamlining and standardization of NGS variant interpretation. [ABSTRACT FROM AUTHOR]

All students should have equal opportunities to pursue education. When the COVID-19 pandemic began, almost all teaching activities had to be switched from the traditional face-to-face format to digital platforms. Although it is now the post-pandemic period, many online teaching and learning practices have been maintained. It is, therefore, crucial to ensure that teachers are doing their best to make online teaching inclusive, and an instrument assessing their practices is essential. This study aims to develop this instrument and validate it. Referring to relevant works and universal design for learning (UDL) guidelines, we developed an instrument that consists of five domains: affective, behavioural, cognitive, competence and awareness. Through expert assessment of face, content and construct validity, a pilot study, and data analysis of 505 respondents teaching in different educational levels from primary schools to higher institutions in Malaysia, using exploratory factor analysis (EFA) and correlational testing, the findings show that the instrument has high validity and reliability in assessing teachers' practices in delivering inclusive online education. While the instrument has implications for policymakers and researchers, it needs further validation in the context of different countries. Necessary amendments might be required to make it more context specific. [ABSTRACT FROM AUTHOR]

At the present time, an effective methodological toolkit has not been developed to manage economic processes in modern conditions in order to ensure the sustainable economic development of enterprises. On the basis of mathematical modeling, it has been proposed that such a tool could be created to provide a quantitative assessment of the main parameters in the creation of innovative products and activities of enterprises. Additionally, on the basis of this tool, decision makers could regulate these processes by introducing additional resources and buying risks. For this purpose, it is necessary to modernize the means of production, which requires a reassessment of the technical level of enterprises. It is possible to achieve these parameters through a certain technical policy of production modernization. In this aspect, the technical policy of enterprises should consider the fact that, depending on the complexity of innovative products put for development and production, the time lag between the start of production of such products and the moment when they enter the market with competitive advantage changes. This competitive advantage is determined by the design methods at a given cost. At the same time, the service models of enterprises are used as one of the most important tools to achieve the profitability of the enterprise, leading to its sustainable economic development. As a result of the proposed toolkit, a strategy for managing the processes of the sustainable economic development of enterprises could be developed based on the creation of an intelligent system using artificial intelligence and the use of large databases that create information support for decision makers to regulate these processes. This set of tools makes it possible to achieve the organization of sustainable economic development. To assess the technical, economic, and technological level of the enterprise, a complex integral indicator was obtained on the basis of mathematical modeling. It was proposed to confirm the obtained integral assessment by comparing the obtained calculated data with an expert assessment. The method of expert evaluation is used in the article. Expert assessments were obtained in science-intensive organizations in which the authors held managerial positions and were engaged in scientific projects. The obtained inputs were formulated based on the analysis of the reporting documentation provided by the organizations. The conducted research indicates the importance of the proposed practical recommendations and materials for solving the tasks set in this study. [ABSTRACT FROM AUTHOR]

Tourism is one of the most effective and attractive tools for achieving many goals including educational. Learning and gaining knowledge by traveling have been present in human history for centuries. Education does so well in tourism because it is accompanied by human curiosity about the world. Tourism can teach natural, social, and historical sciences. It is an important tool for learning about the past that influences the present and the future, especially if it is a difficult past such as the memory of the Holocaust. Tourism can help to draw conclusions about the past as long as it contributes to the acquisition of specific knowledge. Considering this role of tourism, it is worth asking when tourism starts? Many authors see the beginning of tourism at the stage of gathering information. The main assumption of this publication can be summarized as the consideration that the quality of an educational tourist product depends on the availability of information, its quality, and the manner in which it is provided. Today, the most important information distribution channel is digital media, including both websites and social media. Well-provided information accelerates the development of a resource, destination, or region; at the same time, information provided incorrectly or a lack of information in the virtual space may be an inhibitor of the development of educational tourism. The aim of the article is to assess the manner of communicating information related to the Holocaust of World War II, which took place in Nazi German-occupied Poland. The study was conducted with the use of qualitative methods—expert assessment and assessment of the information transfer effectiveness based on the scoring method. The research material included existing websites presenting the resources and methods of operation of museums dedicated to the Holocaust located in Poland. During evaluation, particular attention was paid to the scope of information, methods of its transmission, its internationalization, and timeliness of activities, especially in the field of promoting elements of the offer related to education and shaping attitudes. The aim of the research was to organize the official Internet resources, classify them, and discuss the functioning of information on the Holocaust in the virtual space, so as to use the potential of information in the most effective way to create a product for educational tourism. [ABSTRACT FROM AUTHOR]

The regulation of the anthropogenic load on waterbodies is carried out based on water quality standards that are determined using the threshold values of hydrochemical indicators. These applied standards should be defined both geographically and differentially, taking into account the regional specifics of the formation of surface water compositions. However, there is currently no unified approach to defining these regional standards. It is, therefore. appropriate to develop regional water quality standards utilizing modern technologies for the mathematical purpose of methods analysis using both experimental data sources and information system technologies. As suggested by the use of sets of chemical analysis and neural network cluster analysis, both methods of analysis and an expert assessment could identify surface water types as well as define the official regional threshold values of hydrochemical system indicators, to improve the adequacy of assessments and ensure the mathematical justification of developed standards. The process for testing the proposed approach was carried out, using the surface water resource objects in the territory of the Republic of Tatarstan as our example, in addition to using the results of long-term systematic measurements of informative hydrochemical indicators. In the first stage, typing was performed on surface waters using the neural network clustering method. Clustering was performed based on sets of determined hydrochemical parameters in Kohonen's self-organizing neural network. To assess the uniformity of data, groups in each of the selected clusters were represented by specialists in this subject area's region. To determine the regional threshold values of hydrochemical indicators, statistical data for the corresponding clusters were calculated, and the ranges of these values were used. The results of testing this proposed approach allowed us to recommend it for identifying surface water types, as well as to define the threshold values of hydrochemical indicators in the territory of any region with different surface water compositions. [ABSTRACT FROM AUTHOR]

Stroke survivors often suffer from movement impairments that significantly affect their daily activities. The advancements in sensor technology and IoT have provided opportunities to automate the assessment and rehabilitation process for stroke survivors. This paper aims to provide a smart post-stroke severity assessment using AI-driven models. With the absence of labelled data and expert assessment, there is a research gap in providing virtual assessment, especially for unlabeled data. Inspired by the advances in consensus learning, in this paper, we propose a consensus clustering algorithm, PSA-NMF, that combines various clusterings into one united clustering, i.e., cluster consensus, to produce more stable and robust results compared to individual clustering. This paper is the first to investigate severity level using unsupervised learning and trunk displacement features in the frequency domain for post-stroke smart assessment. Two different methods of data collection from the U-limb datasets—the camera-based method (Vicon) and wearable sensor-based technology (Xsens)—were used. The trunk displacement method labelled each cluster based on the compensatory movements that stroke survivors employed for their daily activities. The proposed method uses the position and acceleration data in the frequency domain. Experimental results have demonstrated that the proposed clustering method that uses the post-stroke assessment approach increased the evaluation metrics such as accuracy and F-score. These findings can lead to a more effective and automated stroke rehabilitation process that is suitable for clinical settings, thus improving the quality of life for stroke survivors. [ABSTRACT FROM AUTHOR]

Lift-jacking accidents are one of the five common accidents in the lift field, characterised as a high hazard. In addition, it is difficult to obtain absolute probabilities of risk factors for lift accidents which are ambiguous and uncertain. In order to solve related problems and perform a comprehensive risk assessment of lift-jacking accidents, a risk assessment methodology integrated with FFTA (Fuzzy Fault Tree Analysis) and FMEA (Failure Mode and Effects Analysis) has been proposed. First, qualitative analysis of the fault tree was applied to identify risk factors of TE (Top Event). Then, a hybrid approach for the fuzzy set theory and weight analysis was investigated to quantify the probability of every BE (Bottom Event), and quantitative analysis was conducted. Finally, an analytical model was constructed by linking FFTA and FMEA through indicator conversion, which leads to overall risk evaluation. An application on a real project example shows that (1) the FFTA-FMEA model can aggregate expert assessment opinions and effectively eliminate ambiguity and uncertainty of risk factors of lift-jacking accidents. (2) The FFTA-FMEA model can quantify the risk of lift-jacking accidents and identify medium to high-risk factors in a multi-angle, deeper, and precise level. The method offers a theoretical framework for the development of preventive measures and safety management strategies for lift-jacking accidents. The practical application in reliability engineering demonstrates its convenience and efficiency, indicating its significant value in this field. [ABSTRACT FROM AUTHOR]

When transporting different types of cargo, the factors affecting the cargo must be assessed to ensure a safe and fast transportation process. However, the specificity of the cargo means that the standard assessment methods do not reflect the existing conditions or are standard at the theoretical and/or recommendation level. Therefore, in the event of a traffic accident, when a vehicle or cargo is damaged or other traffic participants are put at rink, assessment of the situation is difficult and requires an expert assessment. Then, the most optimal means of accomplishing this is to simulate transportation parameters with a specific vehicle and cargo. The transportation of wooden logs is a very specific method of transportation where, in addition to the weight of the load itself, it is necessary to assess how the load affects the dynamics of the vehicle. Therefore, determining the priority of the forces that act on the vehicle carrying wooden logs becomes very important in order to model the transport parameters of this cargo. This article uses an analytical survey, an expert survey and its analysis, and methods to determine correlations. Given the fact that the main forces acting on the load most often manifest during a turn, this study assessed road turns and the respective speed on them as the main parameters. Other parameters, such as road roughness and roundabouts, were not assessed, because they would be an object of long-distance research. The study results revealed that the main forces affecting a vehicle transporting logs manifest in the following priority order: inertial forces, gravity forces, frictional forces and, finally, centrifugal forces. [ABSTRACT FROM AUTHOR]

The labor market has been significantly impacted by the rapidly evolving global landscape, characterized by increased competition, globalization, demographic shifts, and digitization, leading to a demand for new skills and professions. The rapid pace of technological advancements, economic transformations, and changes in workplace practices necessitate that employees continuously adapt to new skill requirements. A quick assessment of these changes enables the identification of skill profiles and the activities of economic fields. This paper aims to utilize natural language processing technologies and data clustering methods to analyze the skill needs of Lithuanian employees, perform a cluster analysis of these skills, and create automated job profiles. The hypothesis that applying natural language processing and clustering in job profile analyzes can allow the real-time assessment of job skill demand changes was investigated. Over five hundred thousand job postings were analyzed to build job/position profiles for further decision-making. In the first stage, data were extracted from the job requirements of entire job advertisement texts. The regex procedure was found to have demonstrated the best results. Data vectorization for initial feature extraction was performed using BERT structure transformers (sentence transformers). Five dimensionality reduction methods were compared, with the UMAP technique producing the best results. The HDBSCAN method proved to be the most effective for clustering, though RCBMIDE also demonstrated a robust performance. Finally, job profile descriptions were generated using generative artificial intelligence based on the compiled job profile skills. Upon expert assessment of the created job profiles and their descriptions, it was concluded that the automated job advertisement analysis algorithm had shown successful results and could therefore be applied in practice. [ABSTRACT FROM AUTHOR]

The functioning of Ukrainian national gas sector is directly dependent on the processes of fuel and energy resources consumption and trends in domestic and foreign markets. Nowadays, the majority of approaches and methods are formed with the obligatory use of expert assessment methods, which, in its turn, predetermines relatively subjective judgments and results. In the process of conducting a comprehensive analysis of financial and economic indicators and those reflecting the results of economic activity of gas distribution network operators functioning in the western region of Ukraine, the following approaches have been used in our study with the involvement of: Altman's two-factor model; Altman's five-factor model; Lis's bankruptcy prediction model; Richard Taffler's model; Beaver's coefficient; Tereshchenko's model and Matviychuk's model; however, the existing models for diagnosing bankruptcy of enterprises are characterized by ambiguity; as for example, if Lis's model indicates a low bankruptcy level, then other models prove the opposite situation; domestic diagnostic models need to be improved, as they were developed in the early 2000s and disregard current trends in functioning of enterprises. Since the existing models for diagnosing the bankruptcy of enterprises are characterized by ambiguity, the authors proposed and approbate their own approach to determining the level of competitiveness of gas distribution network operators. A feature of the proposed methodology is taking into account modern trends in the functioning of enterprises, taking into account the peculiarities of the activities of gas distribution network operators, and the market stage. A tangible advantage of this approach is the ability to identify the presence or likelihood of critical events at an early stage. [ABSTRACT FROM AUTHOR]

Due to the unavoidable operational risks and insufficient risk management capabilities of beginner pilots in flight training, the challenge of risk control in aviation schools has become increasingly prominent. To ensure the safety of flight training in aviation schools and to reduce costs and increase revenue, the essential prerequisite for improving efficiency is risk management. Therefore, it is necessary to explore risk identification and assessment methods. This paper adopts the holographic modeling (HHM) method and risk filtering, rating and management (RFRM) theory. First, the HHM idea is used to construct a risk identification framework (HHM-PAVE) for flight training. Second, based on the dual criteria, multiple criteria and cloud model (CM) in the RFRM approach, an improved risk assessment matrix-cloud model (IPC-CM) is proposed and combined with the N-K model and Bayes' theorem to propose a coupled risk scenario hazard measurement model (CR-HM) based on the HHM-RFRM approach in risk assessment. In the assessment process, the impact of risk factors on system stability as well as the uncertainty problem and coupling–risk quantification problem in expert assessment are considered to obtain scientific and objective quantitative assessment results. Finally, the risk identification and assessment experiments were conducted using HHM-RFRM on the flight training. The results show that the method can more accurately identify critical risk factors in a flight training system and provide a new perspective for risk prevention and control. [ABSTRACT FROM AUTHOR]

The railway sector is the largest branch of the economy in Kazakhstan. Nevertheless, environmental safety issues and the reduction and prevention of harmful impacts are not given sufficient attention. There is very little research on the impact of the railway sector of Kazakhstan on the natural environment, which hinders the further development of the railway sector and thus necessitates the addressal of environment issues. This study aimed to show possible environmentally hazardous sections of the country's railway infrastructure. The criteria chosen for the analysis were soil cover, water resources, rainfall, protected natural areas, and population. A map of environmentally sensitive areas was created to determine which areas require priority protection from the environmental hazards posed by the country's railway infrastructure. The map was developed in a GIS environment using the weighted overlay, expert assessment, and snowball methods. Additionally, a model for the Kazakhstan segment of the International Northern Railway Corridor was constructed in this article to identify integral indices that assess the susceptibility of the territory to environmental hazards. The data and results presented in the article can be used to solve current and future environmental issues concerning the country's railway communications and can be implemented in many practical applications. [ABSTRACT FROM AUTHOR]

Sustainable consumption and production strive for the rational management of natural resources, which implies a transition to the production of fewer goods with the greatest consumer value. Consequently, the consumer value assessment is a key task in the product and service design. However, a large number of applied practices for assessing consumer value is a challenge for researchers. Multiple heterogeneous solutions without a common classification and structure do not allow comparing methods with each other. Thus, there is a demand for some universal algorithm for assessing consumer value, which would be a model for the development of individual industry practices. Therefore, the present research aims to develop a universal algorithm for assessing consumer value, which is a unified sample. The work analyzes the current expertise in assessing consumer value. The paper provides a comparison of mathematical tools for aggregate indicators in order to develop a general formula for assessing consumer value. As a result, an algorithm for assessing consumer value has been developed, which includes the following stages: market segmentation by consumer groups, taking into account their personal characteristics and needs; product hierarchical division into groups according to indicators valuable to the consumer; selection of a scale for evaluating indicators; hierarchical convolution, calculation of the consumer value of selected indicators and their aggregation into a final assessment in accordance with coefficients obtained as a result of the initial data analysis. As part of the algorithm verification, an example of the implementation of the algorithm steps based on expert assessment of the tourist product characteristics is proposed. At the next stage of the study, a register of mathematical tools will be specified to ensure the implementation of the algorithm steps, and practical testing on real data on several products from different industries. [ABSTRACT FROM AUTHOR]

A Collaborative Networked Organization (CNO) is a set of entities that operate in heterogeneous contexts and aim to collaborate to take advantage of a business opportunity or solve a problem. Big data allows CNOs to be more competitive by improving their strategy, management and business processes. To support the development of big data ecosystems in CNOs, several frameworks have been reported in the literature. However, these frameworks limit their application to a specific CNO manifestation and cannot conduct intelligent processing of big data to support decision making at the CNO. This paper makes two main contributions: (1) the proposal of a metaframework to analyze existing and future frameworks for the development of big data ecosystems in CNOs and (2) to show the Collaborative Networked Organizations–big data (CNO-BD) framework, which includes guidelines, tools, techniques, conceptual solutions and good practices for the building of a big data ecosystem in different kinds of Collaborative Networked Organizations, overcoming the weaknesses of previous issues. The CNO-BD framework consists of seven dimensions: levels, approaches, data fusion, interoperability, data sources, big data assurance and programmable modules. The framework was validated through expert assessment and a case study. [ABSTRACT FROM AUTHOR]

Increasing interest in plant-based proteins is particularly relevant in the food service sector. For specific groups, e.g., older adults, it may be challenging to ensure the consumption of protein of sufficient quality. One way of doing this could be through the fortification of a staple food such as bread. This study examined wheat buns, in which 0%, 20%, 35% and 50% of the flour was replaced with three different milled texturized vegetable proteins (TVP) of different plant protein combinations. Sensory and baking qualities were evaluated through sensory profiling and measurements of rising ability, baking loss, protein content and colour. An expert assessment and a robustness test were conducted to evaluate potential use in the food service sector. By substituting 35% of the wheat flour with milled TVP, it was possible to increase the protein content of the buns by 83% (up to 25% of DM) and still maintain an acceptable quality. The different TVPs showed that pea and faba bean or pea, faba bean and quinoa were more suitable in bread fortification than pea, faba bean and hemp. The study demonstrates the potential for producing quality bread for people who need a high protein intake in all their meals. [ABSTRACT FROM AUTHOR]

The water environment treatment public-private partnership (PPP) project has a long cooperation period, large investment scale, high technical requirements, and more complex risks, which are very important to identifying and preventing risks. This paper establishes a risk evaluation model for water environmental treatment PPP projects based on the intuitionistic fuzzy Multi-Objective Optimization on the basis of a Ratio Analysis plus the full Multiplicative form (MULTIMOORA) improved Failure Mode and Effects Analysis (FMEA) method. Firstly, the risk indicators system of the water environmental treatment PPP project was constructed through the literature frequency statistics method and semi-structured interviews. Subsequently, the intuitionistic fuzzy FMEA method was used to assess the risk factors in terms of three aspects—occurrence(O), severity(S), and non-detectability(D)—and gather expert information, and the expert assessment method and deviation maximization model method were applied to assign the risk factors. Finally, Intuitionistic fuzzy Multi-Objective Optimization on the basis of a Ratio Analysis plus the full Multiplicative form (IF-MULTIMOORA) was applied to determine the risk indicator ranking and was combined with the water environmental treatment PPP project in Pingyu for example verification. The results show that the top five risk levels of PPP projects in Pingyu water environmental treatment are financing risk (changing financing conditions/high costs), market changes, government intervention and credit problems, imperfect legal and regulatory systems, and inflation. The risk assessment model proposed in this paper enables: (1) the evaluation of risk indicators from three perspectives, which is more accurate and comprehensive; (2) the introduction of intuitionistic fuzzy risk factor language variables to reasonably represent expert views; (3) the use of IF-MULTIMOORA for risk ranking to avoid the problem that RNP is the same and difficult to rank. This paper has important practical significance in promoting risk prevention and achieving the sustainable development of water environment treatment PPP projects. [ABSTRACT FROM AUTHOR]

Geopolymer is an inorganic material formed through the chemical reaction of an aluminosilicate precursor and an alkaline or acidic activating solution. It is seen as a green new alternative binder to ordinary Portland cement (OPC) for sustainable infrastructure development. The strength of the unary or blended geopolymer product is dependent on the composition and properties of the polymeric gel influenced by the ratios of Al2O3/SiO2, CaO/SiO2, CaO/(SiO2 + Al2O3), Na2SiO3/NaOH, SiO2/Na2O, and liquid/binder (L/B). Essential scientific inquiry has been progressively addressed by utilizing expert assessment and research metrics. The network visualization of bibliometric co-occurrence and co-citations is of particular significance. The present study aims to highlight the trends and progress of the most influential publication sources, keywords, authors, articles, and countries in geopolymer research in the last 10 years. Bibliometric data were retrieved through Scopus and visualized in VOSviewer to create bibliometric networks. The yearly distribution and growth trends (April 2011–2022) of geopolymer, geopolymer mortar, and geopolymer concrete before (after) applying inclusion criteria were from 754 to 9887 (5186), 47 to 1374 (866), and 145 to 3721 (2253), respectively, attributed to the discoveries in more precursor materials such as laterite and the growing interest in fire and heat-resistant structures, water and wastewater treatment, cement and concrete, and brick manufacturing. The top three journals in terms of prestige for geopolymer publications were the Journal of Hazardous Materials with an impact factor equal to 14.224 and h-index equal to 307, Cement and Concrete Research with an impact factor equal to 11.958 and h-index equal to 239, and the Journal of Cleaner Production with an impact factor equal to 11.072 and h-index equal to 232. The top three journals in terms of average citation per document were Cement and Concrete Research (135.75), Materials and Design (75), and Cement and Concrete Composites (68.35). Keywords such as "geopolymers", "inorganic polymer", "geopolymer", "compressive strength", "fly ash", and "geopolymer concrete" had the highest occurrences in publications. John Provis—University of Sheffield, Prinya Chindaprasirt—Khon Kaen University, and Jay Sanjayan—Swinburne University of Technology had the highest total citations of 6377, 5626, and 4311, respectively. The highest number of publications were from China, India, Australia, the United States of America, and Malaysia. The bibliometric findings from this study can act as a tool for academicians and policymakers to exchange research expertise, collaborate on novel geopolymer research, and create innovative joint ventures. [ABSTRACT FROM AUTHOR]

A holistic Good Agents Means Processes Order Sustainability (GAMPOS) framework for an adequate understanding of agri-food governance and assessing its quality is suggested, incorporating the interdisciplinary new institutional economics methodology. Agri-food governance is defined as a complex system with five components: (1) agri-food and related agents, (2) means (rules, forms, and mechanisms) that govern agents' behavior, activities, and relationships, (3) processes and activities related to making managerial decisions, (4) specific social order resulting from the governing process, and (5) outcomes of the functioning of the system in terms of the realization of sustainable development goals. To assess the quality of agri-food governance, a multidimensional hierarchical system with good governance 11 principles, 21 criteria, and 36 indicators and reference values is presented. A comprehensive assessment of agrarian governance in Bulgaria, based on statistical and expert data, showed that its overall quality is at a moderate EU level. In terms of sustainability, the quality of governance is at a good level, while for process, means, and order, it is at a satisfactory level. The quality of agrarian governance is highest in terms of equity and solidarity and the good functioning public sector. The quality of agrarian governance is lowest in terms of stakeholder involvement and the good working private sector. In the future, in the latter two areas, combined actions of public, private, and collective agents are needed to improve the country's agri-food governance. [ABSTRACT FROM AUTHOR]

This article discusses the need to transform real estate valuation methods. It is associated with the problems of obtaining unreliable results affecting the subsequent adoption of management decisions. As an important element of land plots assessment, the authors define the Negative Infrastructural Externalities arising from the presence of infrastructure and other regime-forming facilities. These externalities represent the loss of title holders due to the encumbrances arising from the use of land plots. The world community (and the authors as part of it) sees one of the transformation methods in the automation of the evaluation process. Therefore, the purpose of this study is to develop a mechanism of automating the Negative Infrastructural Externalities assessment process in the conditions of a non-existent and weak market activity of land relations. Modern trends dictate the saving of hardware, labor and money resources; in this connection, the methods of Negative Infrastructural Externalities assessment are implemented on the basis of the "thin client" technology. The research is based on the following methods: the analytical method is used to perform a critical analysis of the problem area and to substantiate the research topic's relevance; methods of object-oriented programming and methods of modular programming (Cowan's axiom of modularity) are used as tools for developing the web application logic, as well as the interaction of its individual elements; the attribute-driven design approach is used in the creation of software architectures. The result of the study is the developed and substantiated architecture of a web application for assessing negative infrastructural external factors in determining the land value, the implemented modular structure of the specified web application and the developed conceptual model of the database. The practical implementation of the listed proposals is made by means of the Python programming language. The advantage of the created automated system is the possibility of multi-disciplinary use of the expert assessment approach when changing the settings. [ABSTRACT FROM AUTHOR]

This article substantiates the structure of the crop insurance system and describes the participants of the insurance system and their activities. The positive impact of crop insurance development on all participants of the system has also been clarified. The aim of the article is to present a methodology for assessing substantiated directs of activity for public authorities in order to make more active crop insurance system performance. The application of the proposed methodology can help to activate crop insurance processes and to expand farmers' activities and achieve better commercial results of insurance companies. It has been proven that it is beneficial for the public authorities to reinsure farmers' crops and to refuse to pay direct payments to farmers for the losses incurred. The criteria selected for the assessment of the development directions are relevant to all participants of the insurance system. The research was carried out in a region of Lithuania in which the composition of agricultural business entities corresponds to the situation in the whole agricultural sector of the country. The identification of the insurance system participants and their functions, as well as the use of an expert assessment method with the application of quantitative data processing, showed directions for the activation of crop insurance activities. [ABSTRACT FROM AUTHOR]

By classifying BIM data, the intention is to enable different construction actors to find the data they need using software and machines. The importance of classification is growing as building projects become more international, generating more data that rely on automated processes, which help in making better decisions and operating devices. Different classification systems have been developed around the world. Each national construction information classification system (NCICS) aims to classify information on the built environment and thus meet national needs and ensure compliance with the principles of regional and international building information systems. The research purpose of this paper is to present a comparative assessment of two construction information classification systems, CCI and Uniclass 2015. The following methods were used: the expert assessment of NCICS alternatives; the assessment of NCICS alternatives; and a strengths, weaknesses, opportunities, and threats (SWOT) analysis of NCICS alternatives. We concluded that in the initial phase of NCICS development, CCI ontologies should be adopted as a base consisting of construction entities, spaces, and elements, with the gradual addition of complexes of buildings and infrastructure, along with roles and phases of the building life cycle (BLC). An explanatory NCICS development note should be drawn outlining the principles of classification and identification; the ontological structure; development and updating possibilities; methods of integrating existing national and international classification systems; and methods of integrating data of construction products, time, cost, or other individual characteristics. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer is able to damage the surface of the eye, especially in countries like Australia with high exposure to ultraviolet radiation from the sun. Such cancer (ocular surface squamous neoplasia or OSSN) is similar in appearance to a common and benign eye disease called pterygium. Currently, eye biopsy is the gold standard diagnostic method for OSSN, which is traumatic for the patient, carries risks, and has been potentially unnecessary in patients diagnosed with pterygium only. This research introduces an imaging-based method for OSSN screening, which will reduce pressure on health resources—and hopefully eliminate the need for eye biopsy in cases of suspected OSSN. In this study, differentiation of pterygium vs. ocular surface squamous neoplasia based on multispectral autofluorescence imaging technique was investigated. Fifty (N = 50) patients with histopathological diagnosis of pterygium (PTG) and/or ocular surface squamous neoplasia (OSSN) were recruited. Fixed unstained biopsy specimens were imaged by multispectral microscopy. Tissue autofluorescence images were obtained with a custom-built fluorescent microscope with 59 spectral channels, each with specific excitation and emission wavelength ranges, suitable for the most abundant tissue fluorophores such as elastin, flavins, porphyrin, and lipofuscin. Images were analyzed using a new classification framework called fused-classification, designed to minimize interpatient variability, as an established support vector machine learning method. Normal, PTG, and OSSN regions were automatically detected and delineated, with accuracy evaluated against expert assessment by a specialist in OSSN pathology. Signals from spectral channels yielding signals from elastin, flavins, porphyrin, and lipofuscin were significantly different between regions classified as normal, PTG, and OSSN (p < 0.01). Differential diagnosis of PTG/OSSN and normal tissue had accuracy, sensitivity, and specificity of 88 ± 6%, 84 ± 10% and 91 ± 6%, respectively. Our automated diagnostic method generated maps of the reasonably well circumscribed normal/PTG and OSSN interface. PTG and OSSN margins identified by our automated analysis were in close agreement with the margins found in the H&E sections. Such a map can be rapidly generated on a real time basis and potentially used for intraoperative assessment. [ABSTRACT FROM AUTHOR]

In southeast Europe, silvicultural measures for improving forest protective effects against rockfall are often based on unsystematic observation and experience. We compared formalised expert assessment of forest protective effects and silvicultural decision-making with an approach supported by modelling (Rockyfor3D, Rockfor.NET, shadow angle method). The case study was conducted in Fagus sylvatica dominated Alpine forests above the regional road leading to the Ljubelj pass, in Slovenia. We analysed rock sources, silent witnesses, forest structure and regeneration. Expert assessment indicated acceptable protection effects of the forest and their decline in the future. Modelling revealed several road sections endangered by rockfalls. It also indicated subtle differences between silvicultural alternatives: current forest, current forest with cable crane lines, selection forest and non-forested slope. This outcome may be due to short transition zones, small rock sizes, low rock source heights and low resolution of the digital elevation model. Modelling requires more initial input than formalised expert assessment but gives spatially explicit results that enable comparison of silvicultural alternatives, coordination of silviculture and forest operations, and delineation of protection forests. Modelling also supported prioritising of silvicultural measures, where the necessity of silvicultural measures increases with increasing rockfall susceptibility and decreasing long-term stability of stands. [ABSTRACT FROM AUTHOR]

The problem of the analysis of datasets formed by the results of group expert assessment of objects by a certain set of features is considered. Such datasets may contain mismatched, including conflicting values of object evaluations by the analyzed features. In addition, the values of the assessments for the features can be not only point, but also interval due to the incompleteness and inaccuracy of the experts' knowledge. Taking into account all the results of group expert assessment of objects for a certain set of features, estimated pointwise, can be carried out using the multiset toolkit. To process interval values of assessments, it is proposed to use a linguistic approach which involves the use of a linguistic scale in order to describe various strategies for evaluating objects: conservative, neutral and risky, and implement various decision-making strategies in the problems of clustering, classification, and ordering of objects. The linguistic approach to working with objects assessed by a group of experts with setting interval values of assessments has been successfully applied to the analysis of the dataset presented by competitive projects. A herewith, for the dataset under consideration, using various assessment strategies, solutions of clustering, classification, and ordering problems were obtained with the study of the influence of the chosen assessment strategy on the results of solving the corresponding problem. [ABSTRACT FROM AUTHOR]

Driver assistance systems (ADAS), and especially those containing driving automation, change the role of drivers to supervisors who need to safeguard the system’s operation. Despite the aim to increase safety, the new tasks (supervision and intervention) may jeopardize safety. Consequently, safety officers address the need for specific training on ADAS. However, these tasks are not assessed in driver licensing today. Therefore, we developed a framework to assess inpractice driving proficiency when drivers utilize ADAS. This study evaluated whether the proposed framework is able to identify meaningful differences in driving proficiency between driving with and without assistance. We applied the framework to perform a qualitative assessment of driving proficiency with 12 novice drivers in a field experiment, comparable to a license test. The assistance system concerned Adaptive Cruise Control (ACC). The test showed that driving with ACC has a negative influence on self-initiated manoeuvres (especially lane changes) and sometimes led to improved adaptations to manoeuvres initiated by other road users (like merging in traffic). These results are in line with previous research and demonstrate the framework’s successfulness to assess novice drivers’ proficiency to utilize ADAS in road-traffic. Therewith, the proposed framework provides important means for driving instructors and examiners to address the safe operation of ADAS. [ABSTRACT FROM AUTHOR]

The purpose of the research presented in the article is to identify the impact of the processes associated with the broadly understood maintenance of old residential buildings with a traditional construction on the size and intensity of the wear of their elements. The goal was achieved by analyzing the symptoms of the technical wear process, which involved the understanding of the mechanism of the occurrence of the phenomenon of damage, and the identification of the size and intensity of the damage to the elements of the evaluated buildings. The consequence of systematizing the most important processes that influence the loss of functional properties of residential buildings was the creation of the authors' own qualitative model and its transformation into a quantitative model. This, in turn, enabled a multi-criteria quantitative analysis of the cause and effect phenomena—"damage-technical wear"—of the most important elements of downtown tenement buildings to be carried out in fuzzy conditions, i.e., uncertainty concerning the occurrence of damage and the wear process. The following key question was answered in the subjective expert assessment of the technical condition of an evaluated residential building: what is the probability of the wear of an element, which may be more or less correlated with its average maintenance conditions, or more simply, what is the probability that the element is more or less (approximately) worn? It has been proven that the conditional probability of the technical wear of an element in relation to its damage increases with the deterioration of the maintenance conditions of the building, and this increase is very regular, even in the case of different building elements. This probability is characterized by a low standard deviation and a narrow range of the dispersion of results in the case of various elements with regards to each of the considered building maintenance conditions. [ABSTRACT FROM AUTHOR]

The cost and determination of construction projects are key issues for both customer and contractor when entering into a construction contract. For customers, calculation and evaluation of the cost of construction projects is complicated by the problem of underpricing, which may lead to the failure of contractors submitting a bid for a project, and, in addition, overpricing may lead to an overestimation of the average market value of specific groups of works. Therefore, the aim of the study is to compare the quality assurance of different contractors' contracts using a multi-functional decision-making process and to develop a set of quality assessment criteria. The Analytic Hierarchy Process (AHP) was used to determine the significance of the criteria and afterwards to evaluate the construction contracts. Two groups of experts were involved in this research: specialists for the customer group, and specialists for the contractor group that comprised professionals in their respective fields, with many years of experience in managing and implementing construction projects. Based on the results of this study, conclusions and recommendations are presented regarding possibilities of ensuring quality of construction contracts and minimizing disputes between customer and contractor. [ABSTRACT FROM AUTHOR]

This study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company's financial security using only economic indicators--as suggested in the existing literature--would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting calculated at any particular point in time, provide only a superficial understanding--and may even distort the overall picture. It has also been suggested that expert assessment is the most objective method, although it has disadvantages related to individual cognitive limitations. These limitations are not particular to artificial intelligence, which could assess an enterprise's financial security in a less biased way. However, by only imitating human behavior, it is not able to perceive and evaluate with intuition the dynamics of the company's development and holistically assess the financial condition--despite the possibility of learning and forecasting--because artificial intelligence is not able to think and predict, which, in an enterprise, is the most important skill of a manager. Therefore, the risk of developing artificial intelligence to assess a firm's financial security lies in a biased assessment of the enterprise's activities in general--and its financial security in particular. [ABSTRACT FROM AUTHOR]

Modern prosthetics largely relies upon visual data processing and implementation technologies such as 3D scanning, mathematical modeling, computer-aided design (CAD) tools, and 3D-printing during all stages from design to fabrication. Despite the intensive advancement of these technologies, once the prosthetic socket model is obtained by 3D scanning, its appropriate orientation and positioning remain largely the responsibility of an expert requiring substantial manual effort. In this paper, an automated orientation algorithm based on the adjustment of the 3D-model virtual anatomical axis of the tibia along with the vertical axis of the rectangular coordinates in three-dimensional space is proposed. The suggested algorithm is implemented, tested for performance and experimentally validated by explicit comparisons against an expert assessment. [ABSTRACT FROM AUTHOR]

Recognizing and classifying localized lesions on apple fruit surfaces during automated sorting is critical for improving product quality and increasing the sustainability of fruit production. This study is aimed at developing sustainable methods for fruit sorting by applying hyperspectral analysis and machine learning to improve product quality and reduce losses. The employed hyperspectral technologies and machine learning algorithms enable the rapid and accurate detection of defects on the surface of fruits, enhancing product quality and reducing the number of rejects, thereby contributing to the sustainability of agriculture. This study seeks to advance commercial fruit quality control by comparing hyperspectral image classification algorithms to detect apple lesions caused by pathogens, including sunburn, scab, and rot, on three apple varieties: Honeycrisp, Gala, and Jonagold. The lesions were confirmed independently using expert judgment, real-time PCR, and 3D fluorimetry, providing a high accuracy of ground truth data and allowing conclusions to be drawn on ways to improve the sustainability and safety of the agrocenosis in which the fruits are grown. Hyperspectral imaging combined with mathematical analysis revealed that Venturia inaequalis is the main pathogen responsible for scab, while Botrytis cinerea and Penicillium expansum are the main causes of rot. This comparative study is important because it provides a detailed analysis of the performance of both supervised and unsupervised classification methods for hyperspectral imagery, which is essential for the development of reliable automated grading systems. Support Vector Machines (SVM) proved to be the most accurate, with the highest average adjusted Rand Index (ARI) scores for sunscald (0.789), scab (0.818), and rot (0.854), making it the preferred approach for classifying apple lesions during grading. K-Means performed well for scab (0.786) and rot (0.84) classes, but showed limitations with lower metrics for other lesion types. A design and technological scheme of an optical system for identifying micro- and macro-damage to fruit tissues is proposed, and the dependence of the percentage of apple damage on the rotation frequency of the sorting line rollers is obtained. The optimal values for the rotation frequency of the rollers, at which the damage to apples is less than 5%, are up to 6 Hz. The results of this study confirm the high potential of hyperspectral data for the non-invasive recognition and classification of apple diseases in automated sorting systems with an accuracy comparable to that of human experts. These results provide valuable insights into the optimization of machine learning algorithms for agricultural applications, contributing to the development of more efficient and accurate fruit quality control systems, improved production sustainability, and the long-term storage of fruits. [ABSTRACT FROM AUTHOR]

The evaluation of quality in education has gained greater relevance, especially after the COVID-19 pandemic, which enhanced virtual learning and further highlighted the need for inclusive, equitable, and quality education in line with SDG 4. It has become indispensable to have evaluation models and tools supported by empirical validation to ensure their applicability and reliability in diverse educational contexts. This study addresses this need by validating a self-assessment guide designed to evaluate the quality of virtual education from an accessibility perspective. The validation process involved three phases: a preliminary phase with 4 experts to identify areas for improvement in the structure, clarity, and relevance of the content; an extended phase with 20 experts to evaluate reliability and validity; and a pilot study implemented in four higher-education institutions to verify the guide's applicability in real environments. Reliability and validity were assessed using standard psychometric techniques, confirming high internal consistency and content validity, although some areas required clarity adjustments. The findings indicate that this guide can serve as a robust tool for institutions aiming to advance accessible and high-quality virtual education, directly supporting SDG 4's commitment to inclusive education. [ABSTRACT FROM AUTHOR]