The purpose of the research is to provide a comprehensive analysis of employment dynamics and to identify the main factors influencing change in the context of modern economic development. Methodology. The methodological basis is a comparative analysis of employment and total population statistics, which are the main determinants that reveal the level of employment at different times. This made it possible to trace changes in trends before and during the deployment of large-scale military operations. The study is based on official statistical data and methods of dynamic analysis, generalisation and economic and statistical approaches, providing a comprehensive assessment of employment transformation. Results. The analysis showed that employment is the main element of the labour market and reflects the extent to which a society utilises its labour potential, determining the state of a country's socio-economic development. Employment not only provides the population with a means of obtaining labour income, but it is also an important factor in social stability, the reproduction of human capital, and regional development. The statistical analysis revealed a significant reduction in the employed population and a change in the trajectory of its dynamics in conditions of military upheaval. The main determinants of these changes were found to be demographic losses, large-scale external migration, a decrease in economic activity and structural imbalances in labour supply and demand. At the same time, adaptation processes in the labour market are evident, as demonstrated by the gradual stabilisation of individual employment indicators. Practical significance. The results obtained can be used to inform state employment policy and develop measures to support the labour market in the event of military challenges. They can also be used to forecast future trends in its development during the economic recovery period. Value / Originality. The novelty of this study lies in its comprehensive approach to assessing employment dynamics among the Ukrainian population. By combining analysis of the pre-war and wartime periods, it provides a deeper understanding of the nature of labour market transformations and their systemic consequences.
Economics as a science, Management. Industrial management
Financial fraudsters use Gen AI, digital channels, global networks, and synthetic identities making it complex to identify the fraudulent activities. Traditional rule-based systems relying on traditional methods do not identify frauds which use multi-step transaction routing with multiple institutions and across borders. Graph database using Labelled Property Graphs, represents customers, accounts, and transactions as interconnected nodes and edges. By ingesting live transaction data, they apply pattern-matching and community-detection to expose suspicious subgraphs. Money-laundering rings or collusive clusters—and let investigators trace multi-hop links to “hub” accounts with clear visual audit trails. Machine learning models trained on vast historical datasets, using supervised classifiers (e.g., gradient boosting) and unsupervised anomaly detectors. Features like transaction amounts, geolocation consistency, device fingerprints, and temporal sequences feed these models, while recurrent architectures capture evolving fraud tactics. Yet they often suffer from concept drift, require extensive labelled data, underperform on imbalanced cases, and behave as opaque black boxes, generating false positives and hampering trust. A hybrid framework combines relational graph insights with statistical scoring, boosting detection accuracy, reducing false alarms, and enhancing investigators’ confidence in fraud detection and prevention.
Abstract Remanufacturing has become a mainstream sustainable manufacturing paradigm for energy conservation and environmental protection. Disassembly and reprocessing operations are two main activities in remanufacturing. This work proposes multiobjective integrated scheduling of disassembly and reprocessing operations considering product structures and random processing time. First, a stochastic programming model is developed to minimize maximum completion time and total tardiness. Second, a reinforcement learning-based multiobjective evolutionary algorithm is devised considering problem-specific knowledge. Three search strategy combinations are formed: crossover and mutation, crossover and key product-based iterated local search, mutation and key product-based iterated local search. At each iteration, a Q-learning method is devised to intelligently choose a combination of premium strategies. A stochastic simulation is incorporated to evaluate the objective values of the searched solutions. Finally, the formulated model and method are compared with an exact solver, CPLEX, and three well-known metaheuristics from the literature on a set of test instances. The results confirm the excellent competitiveness of the developed model and algorithm for solving the considered problem.
Electronic computers. Computer science, Information technology
Роман Штонда, Світлана Паламарчук, Олена Бокій
et al.
У сучасних умовах інтенсивного розвитку інформаційно-комунікаційних технологій та стрімкого зростання кількості кіберзагроз, захист кінцевих пристроїв та інформаційно-комунікаційних систем організацій набуває критичного значення. У зв’язку з цим антивірусні програмні засоби залишаються ключовим інструментом у забезпеченні кіберзахисту від шкідливого програмного забезпечення та сценаріїв цілеспрямованих атак. Однак, для вибору оптимального антивірусного програмного засобу важливо мати об’єктивний і комплексний підхід до оцінки їхніх функціональних можливостей. Метою цієї статті є розробка Комплексної методики оцінювання функціональних можливостей антивірусного програмного забезпечення. Запропонована методика враховує широкий спектр тестів, що моделюють типові та нетипові вектори проникнення шкідливого програмного забезпечення: від заражених ZIP-архівів, фішингових листів, змін системних файлів (hosts, реєстру) до виявлення Beacon-активності, автозавантажуваних скриптів, обфускованих PowerShell-команд, макросів Office-документів тощо. У дослідженні оцінюються чотири популярні антивірусні програмні засоби: ESET Endpoint Security, Avast Business Antivirus, Zillya та Windows Defender. У межах експерименту дослідницька група провела оцінювання функцій кожного антивірусного програмного засобу за 21 критерієм. Оцінювання здійснювалось у балах (0–2) із відповідною вагою критичності (1 – критична, 0.8 – висока, 0.5 – середня). Методика дозволяє визначити загальний рівень функціональності та ефективність у відсотковому значенні. Це дозволяє об’єктивно підходити до вибору антивірусного програмного засобу залежно від характеру інформаційної інфраструктури та рівня ризику. Запропонований підхід є універсальним і придатним до адаптації під інші платформи та умови, а також може бути розширений для взаємодії з системами класу Endpoint Detection and Response (Extended Detection and Response). Результати дослідження підтверджують важливість комплексного підходу до кіберзахисту, з урахуванням особливостей сучасних кібератак.
<p>The research and development department (R&D) is a necessary and vital organ for all organizations that intend to be active in domestic and foreign markets, and it is of undeniable importance for domestic and international competition as one of the most important factors for achieving the goals of organizations and industries in economic progress and access to commercial markets. Hence, in the present study, the intelligent R&D management model was evaluated with an agility approach, and to this end, the data was collected from 270 participants using a questionnaire, including managers, professors, senior experts, and experts of petrochemical companies. Then, the fitted data, obtained from the structural equation model, was analyzed with the help of partial least squares method using PLS statistical software. The results of the path coefficients showed that there is a significant relationship between the research variables and the evaluation indices of the model fit. Also, it was found that the relevant model has a good fit. Therefore, it can be stated that intelligent research and development management with an agility approach has improved processes, innovation, optimized communication, and also has financial and competitive consequences for the organization.</p>
MOHAMMAD EHSANIFAR, Associate Professor Ph.D, FATEMEH DEKAMINI, Ph.D, MOEIN KHAZAEI, Ph.D
et al.
The current research was conducted with the topic of investigating the effect of cultural, economic and technological
factors on the risk management of construction companies in Iran. This research was applied in terms of purpose and
descriptive-survey in terms of method. The statistical population of this research is: senior managers and engineers of
grade 1 construction companies in Iran, of which 120 people were selected as a sample through sampling in available
was selected and a researcher-made questionnaire was distributed among them and they were asked to rate each item
according to its importance from one (lowest) to five (highest). To analyze the data, partial least squares technique was
used with the help of SmartPLS software, and the results showed that cultural and economic factors do not affect the
risk management of Iran construction companies, but technological factors have an effect on the risk management of
Iran construction companies.
Commercial geography. Economic geography, Economics as a science
This manuscript focuses on analyzing the growth dynamics of the Central Taiwan Science Park (CTSP) and Silicon Glen in Scotland with a specific emphasis on their approaches to energy, environmental conservation, and economic management. The objective is to provide insights into their sustainable development strategies. In terms of energy, CTSP addresses Taiwan’s energy security and green transformation challenges, while Silicon Glen concentrates on Scotland’s wind energy generation technologies. Both regions prioritize the advancement of renewable energy sources and smart grid technologies. In the realm of environmental conservation, both CTSP and Silicon Glen prioritize environmental protection and sustainability by implementing rigorous environmental monitoring measures. Regarding economic management, CTSP and Silicon Glen serve as vital technology industry hubs in Taiwan and Scotland, respectively, attracting a multitude of high-tech and startup enterprises. This growth is facilitated through various means, including policy support, access to research resources, and robust infrastructure. This manuscript presents a comparative analysis of these two industrial parks, focusing on their environmental and economic management strategies. It aims to elucidate the principles underpinning the sustainable development and economic growth of industrial parks, offering valuable insights to decision-makers and stakeholders involved in the planning of sustainable industrial parks.
Gianluca Veneziani, Diego L. García-González, Sonia Esposto
et al.
In virgin olive oil industries, the technological choices of the production plant affect the biochemical activities that take place in the olives being processed throughout the entire process, thereby affecting the quality of the final product. The lipoxygenase pool enzymes that operated their activity during the first phases of the process need the best conditions to work, especially concerning temperature and oxygen availability. In this study, a system was equipped to supply oxygen in the crusher at a controllable concentration in an industrial olive oil mill at pilot plant scale, and four oxygen concentrations and two cultivars, Coratina and Ogliarola, were tested. The best concentration for oxygen supply was 0.2 L/min at the working capacity of 0.64 Ton/h. Further, using this addition of oxygen, it was possible to increase the compound’s concentration, which is responsible for the green, fruity aroma. The effect on volatile compounds was also confirmed by the sensory analyses. However, at the same time, it was possible to maintain the concentration of phenols in a good quality olive oil while also preserving all the antioxidant properties of the product due to the presence of phenols. This study corroborates the importance of controlling oxygen supply in the first step of the process for process management and quality improvement in virgin olive oil production.
In this paper, we propose a method to estimate the mean square error (MSE) of the estimated channel for ATSC (Advanced Television Systems Committee) 3.0 systems. When combining the channel MSE and noise variance, we can better estimate the a priori LLR (log likelihood ratio) for the sum–product algorithm. The experimental results show that doing so yields better BER (bit error rate) performance in the 0 dB echo channel. The improvement in the 2-D channel estimation is about 0.2 dB. In the 1-D estimation case, the proposed approach is essential to decode codewords.
Matteo Gavazzoni, Nicola Ferro, Simona Perotto
et al.
We present a new algorithm to design lightweight cellular materials with required properties in a multi-physics context. In particular, we focus on a thermo-elastic setting by promoting the design of unit cells characterized both by an isotropic and an anisotropic behavior with respect to mechanical and thermal requirements. The proposed procedure generalizes the microSIMPATY algorithm to a thermo-elastic framework by preserving all the good properties of the reference design methodology. The resulting layouts exhibit non-standard topologies and are characterized by very sharp contours, thus limiting the post-processing before manufacturing. The new cellular materials are compared with the state-of-art in engineering practice in terms of thermo-elastic properties, thus highlighting the good performance of the new layouts which, in some cases, outperform the consolidated choices.
Dynamic Mode Decomposition (DMD) is a data-driven and model-free decomposition technique. It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data. Conceptually, DMD performs a low-dimensional spectral decomposition of the data into the following components: the modes, called DMD modes, encode the spatial contribution of the decomposition, whereas the DMD amplitudes specify their impact. Each associated eigenvalue, referred to as DMD eigenvalue, characterizes the frequency and growth rate of the DMD mode. In this paper, we demonstrate how the components of DMD can be utilized to obtain temporal and spatial information from time-dependent flow fields. We begin with the theoretical background of DMD and its application to unsteady flow. Next, we examine the conventional process with DMD mathematically and put it in relationship to the discrete Fourier transform. Our analysis shows that the current use of DMD components has several drawbacks. To resolve these problems we adjust the components and provide new and meaningful insights into the decomposition: we show that our improved components capture the spatio-temporal patterns of the flow better. Moreover, we remove redundancies in the decomposition and clarify the interplay between components, allowing users to understand the impact of components. These new representations, which respect the spatio-temporal character of DMD, enable two clustering methods that segment the flow into physically relevant sections and can therefore be used for the selection of DMD components. With a number of typical examples, we demonstrate that the combination of these techniques allows new insights with DMD for unsteady flow.
World-systems scholars are increasingly engaged in issues at the intersection of ecological and economic concerns since the proliferation of debates on the Anthropocene. Recently, the alternative concept of Capitalocene—age of Capital—has emerged to draw attention to the world-ecological disruption of capitalism founded on cheap nature appropriation at ever-emerging extraction zones. This paper extends these discussions to the oceanic frontier, as the latest trend in the abstraction of value from the environment. Based on original archival research conducted in the context of a larger ethnographic project on the politics of industrial desalination—creating potable water from the sea—the article analyzes how this practice emerged in two phases. First, the Cold War opened the ocean as a commodity frontier during the pax Americana. Then, when this technopolitical agenda stagnated, financialization techniques were deployed to appropriate seawater, utilizing a mode of financial engineering—desalination via financialization reinstates the cultural hegemony of the Capitalocene that privileges infrastructure for water supply management solutions. As such, the article highlights the co-production of nature with financial capitalism.
Investigating the behavior of religious households is among the important subjects in Islamic countries. As there are religious expenditures in consumption basket, recognizing factors affecting these expenditure is significantly important. By using income-expenditure data, and probit method, this paper is analyzing the case of Iran, in urban and rural regions during 2014. The variables include payment to charity funds, age, literacy level, household dimensions, employment, marriage situation, and home ownership. The results show that there is a positive and significant relationship between the above variables and the religious payments. The household dimension, however, does indicate a negative impact on religious payments. The literacy in rural areas and employment in urban areas do have much more impact relatively. Finally, this research is an implicit testing of Barro’s hypothesis (negative relationship between religious behavior at one hand and prosperity and literacy on the other).
Francisco Duarte, Pascal Béguin, Valérie Pueyo
et al.
This paper presents the main results of a Franco-Brazilian Research project entitled "Work, Innovation and Development". The aim is to conceptually consider work activity within sustainable development, and to contribute methodologically towards developing strategies for designing sustainable work systems. After a brief description of the factors and the dimensions that have contributed to the creation of ideas on sustainable development, we will put forward two main approaches for understanding work activity within the context of sustainability, these being: the durability of work activity and the development of work activities for sustainable development. Both approaches are presented and examples are given. This is followed by a discussion of the design of sustainable work systems that focuses particularly on the political and technical dimensions of project management.