Hasil untuk "Industrial relations"

Marina Yu. Lachaeva

The author examines the ideological, target and practical aspects of the purpose of credit cooperation, as well as the activities of its organizers and participants in the fight against poverty and increasing national welfare in the 1870-1880s. This study is in the context of the involvement of Russian peasants in new economic relations during the reforms and in the post-reform period. In their text, the author reveals the role of V.N. Khitrovo, the official for special missions of the Ministry of Finance in the organization and activities of loanandsavings partnerships, when headed the St. Petersburg branch of the Committee on rural loan-and-savings and industrial partnerships under the Imperial Moscow Society of Agriculture across a significant period of time. The author analyzes the process of overcoming the class character of lending to villages, and the main areas of work in this direction by V.N. Khitrovo and his associates in the St. Petersburg branch of the Committee. The author provided information on the organizing role of the Committee during the period of V.N. Khitrovo’s secretarial duties in it from 1871 to 1890 and in the formation and strengthening of credit cooperation, a new phenomenon in the socioeconomic life of Russia.

Marcos Kalinowski, Lucas Romao, Ariane Rodrigues et al.

Lean R&D has been used at PUC-Rio to foster industry-academia collaboration in innovation projects across multiple sectors. This industrial experience paper describes recent experiences and evaluation results from applying Lean R&D in partnership with Petrobras in the oil and gas sector and Americanas in retail. The findings highlight Lean R&D's effectiveness in transforming ideas into meaningful business outcomes. Based on responses from 57 participants - including team members, managers, and sponsors - the assessment indicates that stakeholders find the structured phases of Lean R&D well-suited to innovation projects and endorse the approach. Although acknowledging that successful collaboration relies on various factors, this industrial experience positions Lean R&D as a promising framework for industry-academia projects focused on achieving rapid, impactful results for industry partners.

Muhammad Junaid Asif, Abdul Rehman, Asim Mehmood et al.

This research proposes an extensive technique for monitoring and controlling the industrial parameters using Internet of Things (IoT) technology based on wireless communication. We proposed a system based on NRF transceivers to establish a strong Wireless Sensor Network (WSN), enabling transfer of real-time data from multiple sensors to a central setup that is driven by ARDUINO microcontrollers. Different key parameters, crucial for industrial setup such as temperature, humidity, soil moisture and fire detection, are monitored and displayed on an LCD screen, enabling factory administration to oversee the industrial operations remotely over the internet. Our proposed system bypasses the need for physical presence for monitoring by addressing the shortcomings of conventional wired communication systems. Other than monitoring, there is an additional feature to remotely control these parameters by controlling the speed of DC motors through online commands. Given the rising incidence of industrial fires over the worldwide between 2020 and 2024 due to an array of hazards, this system with dual functionality boosts the overall operational efficiency and safety. This overall integration of IoT and Wireless Sensor Network (WSN) reduces the potential risks linked with physical monitoring, providing rapid responses in emergency scenarios, including the activation of firefighting equipment. The results show that innovations in wireless communication perform an integral part in industrial process automation and safety, paving the way to more intelligent and responsive operating environments. Overall, this study highlights the potential for change of IoT-enabled systems to revolutionize monitoring and control in a variety of industrial applications, resulting in increased productivity and safety.

Margit Julia Guerra Ayala, Enaidy Reynosa Navarro, Emma Lourdes Durand Gómez et al.

This study analyzed the relationship between enjoyment and oral English proficiency in Peruvian future teachers. It previously validated a measurement instrument of enjoyment setting for future teachers who are learners of English as a Foreign Language (EFL) and then delved into understanding the role of enjoyment as a predictor of oral proficiency. The sample comprised 119 students from a State Higher School of Education in Peru, randomly selected from various careers and grouped according to English language competency levels ranging from A1 to B1+ based on a subscale inspired by the Common European Framework of Reference (CEFR). Students’ oral proficiency was evaluated using a rubric covering five aspects, and enjoyment was assessed through a nine-question questionnaire. The results initially demonstrated a significant positive relationship (r = 0.900, p < 0.001) between enjoyment and oral proficiency in EFL. Secondly, a linear regression model determined that enjoyment was a highly significant predictor (β = 0.957, p < 0.001) of oral proficiency. These findings support the importance of enjoyment in developing oral proficiency as a reliable tool to predict oral proficiency in EFL in the context of EFL teacher education. This study highlighted a significant influence of enjoyment on oral proficiency in learning EFL to prospective teachers. Results analysis underscored the importance of enjoyment as a significant predictor of oral proficiency, suggesting that promoting enjoyment in the learning and teaching process can be an effective strategy to foster significant development of oral skills in English. These findings have significant implications for teacher education, emphasizing the need to integrate activities and psycho-pedagogical approaches that promote enjoyment in the English classroom. Furthermore, the proposed model was validated as a reliable tool to assess teachers’ enjoyment of learning EFL. Understanding and nurturing enjoyment in learning English can significantly enhance the oral English proficiency of future teachers and, ultimately, contribute to a more robust command of the EFL.

Onur Yavaş, Bilal Coşan

This research aims to analyse the variables that influence time-related underemployment in Türkiye. The sample was derived from the 2022 Household Labour Force Statistics microdataset from the Turkish Statistical Institute (TURKSTAT). First, descriptive statistics were used to analyse the distribution of time-related underemployment across the sub-sample groups. For the difference analysis, the Mann–Whitney U and Kruskal– Wallis-H tests were applied. Finally, binary logistic regression analysis was used to identify the determinants of time-related underemployment. All the independent variables, which were categorised as individual, social, and work-related, were found to result in statistically significant differences between the sub-sample groups. Furthermore, the findings indicate that gender, age, level of education, marital status, proximity, region of residence, Social Security Institution (SSI) registration, and workplace situation variables are significant predictors of time-related underemployment. In contrast, the analysis revealed that household size did not emerge as a significant predictor. When considered collectively, these independent variables account for 19.2% of the variance in time-related underemployment risk.

Ekaterina Chytilová, Jarmila Straková, Milan Talíř

The main aim of this article is to identify the evolution of the importance of supplier-customer relations in the period of crisis and the factors influencing the change of this importance. The research question was answered by testing a total of 6 hypotheses, which focused on comparing the degree of influence of factors such as firm size, industry, and profitability on the growth in the importance of supplier-customer relationships in the COVID-19 period. Boxplot and histogram were used to ensure the normality of data. The results suggest that the significance of supplier-customer relationships increased during the crisis period (COVID-19). The firm's profitability influences the growth in the importance of supplier-customer relationships before the pandemic, industry (the growth in importance is more pronounced in industrial firms) and overall sector (the growth in importance is stronger in the secondary sector than in the tertiary sector). In contrast, the association between firm size and the growth in the importance of supplier-customer relationships is not confirmed. Limitations of the study: the research results apply only to enterprises in the Czech Republic, and it is of a short-term focus (i.e., it cannot be said with certainty whether the increase in the importance of supplier-customer relationships is permanent or a short-term fluctuation). Thus, the results of the impact of individual factors may vary over longer time horizons.

Lucas Lacasa, Abel Pardo, Pablo Arbelo et al.

Methods of Machine and Deep Learning are gradually being integrated into industrial operations, albeit at different speeds for different types of industries. The aerospace and aeronautical industries have recently developed a roadmap for concepts of design assurance and integration of neural network-related technologies in the aeronautical sector. This paper aims to contribute to this paradigm of AI-based certification in the context of supervised learning, by outlining a complete validation pipeline that integrates deep learning, optimization and statistical methods. This pipeline is composed by a directed graphical model of ten steps. Each of these steps is addressed by a merging key concepts from different contributing disciplines (from machine learning or optimization to statistics) and adapting them to an industrial scenario, as well as by developing computationally efficient algorithmic solutions. We illustrate the application of this pipeline in a realistic supervised problem arising in aerostructural design: predicting the likelikood of different stress-related failure modes during different airflight maneuvers based on a (large) set of features characterising the aircraft internal loads and geometric parameters.

Christian W. Frey

Industrial production processes, especially in the pharmaceutical industry, are complex systems that require continuous monitoring to ensure efficiency, product quality, and safety. This paper presents a hybrid unsupervised learning strategy (HULS) for monitoring complex industrial processes. Addressing the limitations of traditional Self-Organizing Maps (SOMs), especially in scenarios with unbalanced data sets and highly correlated process variables, HULS combines existing unsupervised learning techniques to address these challenges. To evaluate the performance of the HULS concept, comparative experiments are performed based on a laboratory batch

Olaf Sassnick, Georg Schäfer, Thomas Rosenstatter et al.

Industrial Operational Technology (OT) systems are increasingly targeted by cyber-attacks due to their integration with Information Technology (IT) systems in the Industry 4.0 era. Besides intrusion detection systems, honeypots can effectively detect these attacks. However, creating realistic honeypots for brownfield systems is particularly challenging. This paper introduces a generative model-based honeypot designed to mimic industrial OPC UA communication. Utilizing a Long ShortTerm Memory (LSTM) network, the honeypot learns the characteristics of a highly dynamic mechatronic system from recorded state space trajectories. Our contributions are twofold: first, we present a proof-of concept for a honeypot based on generative machine-learning models, and second, we publish a dataset for a cyclic industrial process. The results demonstrate that a generative model-based honeypot can feasibly replicate a cyclic industrial process via OPC UA communication. In the short-term, the generative model indicates a stable and plausible trajectory generation, while deviations occur over extended periods. The proposed honeypot implementation operates efficiently on constrained hardware, requiring low computational resources. Future work will focus on improving model accuracy, interaction capabilities, and extending the dataset for broader applications.

Hang Duong, Brian Pearson, Steven Anderson et al.

Information on industrial hemp (<i>Cannabis sativa</i>) water use and water stress is sparse. We studied water stress impact in two essential-oil hemp cultivars (‘Wife’ and ‘Cherry’) prompted by anecdotal differences in growth and water use. In a greenhouse setting, we measured water relations, water use, growth, and essential oil (CBD-cannabidiol and THC-delta-9 tetrahydrocannabinol) concentrations. Water stress did not significantly affect THC and CBD concentrations, but both cultivars responded to water stress by reducing transpiration through notably different mechanisms. ‘Cherry’ had more anisohydric behavior, maintaining high stomatal conductance (Gs) and more negative leaf water potential until root zone water depletion triggered partial afternoon stomatal closure to moderate stress, resulting in lower flower and CBD yield. By contrast, water-stressed ‘Wife’ rapidly defoliated half its leaf area in balance with less applied water and so maintained high Gs and flower yield on par with well-watered plants, suggesting potential for deficit irrigation to conserve water and reduce post-harvest vegetation management. Differences in water use translated to provisionally suggested crop coefficients of 1 for ‘Cherry’ and 1.3–1.5 for ‘Wife’, but further research is needed. Because hemp is genetically diverse, and cultivar naming conventions are currently lax, further germplasm screening and research are needed to determine the extent to which either conservative ‘Cherry’ or the water-stress defoliation response of ‘Wife’ is found in the larger population of hemp cultivars.

T. S. Denisova, S. V. Kostelyanets

Nigeria and Ghana, some of the largest countries in Africa in terms of population and GDP, possess considerable scientific and technological potential, which, due to many objective and subjective reasons, has not been fully realized. Yet these West African states have enormous human and natural resources and occupy an important place in the system of international trade and economic relations, not only as major oil exporters, but also due to a fairly high (by African standards) level of industrial development. After the Russia-Africa summit, which was held in Sochi in October 2019, the process of expanding economic contacts with African countries has intensified, and Nigeria and Ghana are becoming important partners of the Russian Federation. In this connection, an adequate assessment of the scientific and technical level of West African labor force and specialists able to utilize foreign know-how and develop own technical solutions adapted to African realities is of particular relevance.The purpose of the present paper is to identify the degree of adaptation of the educational systems of Nigeria and Ghana to the needs of these countries in providing industry, the ICT sector, and scientific institutions with qualified personnel, as well as the level and nature of the application of modern technologies. To achieve this the authors employed the historical-systemic and comparative methods of analysis. In the paper it has been argued that the lack of funding and the lack of qualified personnel, i.e. the problems that the Nigerian and Ghanaian education systems have not yet dealt with, remain serious obstacles to the large-scale introduction of modern technologies. At the same time, autonomous specialized institutes that are not associated with educational institutions and which conduct research in specific sectors of the economy (e.g. fishing, energy, construction, banking, medicine) are better integrated with producers and thus generate most practical results.

Savvas Papaioannou, Andrew Markham, Niki Trigoni

To date, the majority of positioning systems have been designed to operate within environments that have long-term stable macro-structure with potential small-scale dynamics. These assumptions allow the existing positioning systems to produce and utilize stable maps. However, in highly dynamic industrial settings these assumptions are no longer valid and the task of tracking people is more challenging due to the rapid large-scale changes in structure. In this paper we propose a novel positioning system for tracking people in highly dynamic industrial environments, such as construction sites. The proposed system leverages the existing CCTV camera infrastructure found in many industrial settings along with radio and inertial sensors within each worker's mobile phone to accurately track multiple people. This multi-target multi-sensor tracking framework also allows our system to use cross-modality training in order to deal with the environment dynamics. In particular, we show how our system uses cross-modality training in order to automatically keep track environmental changes (i.e. new walls) by utilizing occlusion maps. In addition, we show how these maps can be used in conjunction with social forces to accurately predict human motion and increase the tracking accuracy. We have conducted extensive real-world experiments in a construction site showing significant accuracy improvement via cross-modality training and the use of social forces.

Oluwatosin Ogundare, Gustavo Quiros Araya, Ioannis Akrotirianakis et al.

This paper proposes a study of the resilience and efficiency of automatically generated industrial automation and control systems using Large Language Models (LLMs). The approach involves modeling the system using percolation theory to estimate its resilience and formulating the design problem as an optimization problem subject to constraints. Techniques from stochastic optimization and regret analysis are used to find a near-optimal solution with provable regret bounds. The study aims to provide insights into the effectiveness and reliability of automatically generated systems in industrial automation and control, and to identify potential areas for improvement in their design and implementation.

Olav Lamberts, Konrad Wolsing, Eric Wagner et al.

Industrial systems are increasingly threatened by cyberattacks with potentially disastrous consequences. To counter such attacks, industrial intrusion detection systems strive to timely uncover even the most sophisticated breaches. Due to its criticality for society, this fast-growing field attracts researchers from diverse backgrounds, resulting in 130 new detection approaches in 2021 alone. This huge momentum facilitates the exploration of diverse promising paths but likewise risks fragmenting the research landscape and burying promising progress. Consequently, it needs sound and comprehensible evaluations to mitigate this risk and catalyze efforts into sustainable scientific progress with real-world applicability. In this paper, we therefore systematically analyze the evaluation methodologies of this field to understand the current state of industrial intrusion detection research. Our analysis of 609 publications shows that the rapid growth of this research field has positive and negative consequences. While we observe an increased use of public datasets, publications still only evaluate 1.3 datasets on average, and frequently used benchmarking metrics are ambiguous. At the same time, the adoption of newly developed benchmarking metrics sees little advancement. Finally, our systematic analysis enables us to provide actionable recommendations for all actors involved and thus bring the entire research field forward.

Viktoriia Niziaieva, Margaryta Liganenko, Irina Muntyan et al.

Digital technologies are actively implemented in all areas of tourism. The article identifies the main areas of balancing interests in the field of tourism on the basis of optimization of digital marketing tools. Analytical research has shown that a set of sales channels in the Internet environment and a set of tools are formed, depending on the marketing strategy of the travel company. The main tactics and tools of digital marketing in tourism are highlighted. These are: the company's website, digital marketing channels - online channels for promoting and attracting customers: SEO, online advertising, email marketing, sales funnel, content marketing, teaser advertising, SMM, etc. The study proposes the application of portfolio investment theory to optimize investment in digital marketing tools to achieve a specific goal. The article uses a method of building a mathematical model that will optimally distribute financial investments in digital marketing. Thus balancing of interests in the field of tourism on the basis of digital marketing tools is offered on the basis of KPI indicators, according to the allocated purposes.

Yang Xingzhu, Yin Chengqiang

Driven by the rapid development of tourism, human settlement space in tourism destinations is facing an unprecedented multifunctional transformation. Multifunctional theory provides a new theory and paradigm for research on the sustainable development of human settlements and provides creative solutions for the construction and regulation of human settlements in tourism destinations under the typical regional environment of China. This study systematically analyzes and summarizes the concept evolution, evaluation system, changing characteristics, driving mechanism, and adaptive regulation of multifunctional human settlements in tourism destinations at home and abroad. The study reveals the evolution path of current research and offers future research directions and suggestions. The main conclusions are described as follows: 1) Regarding concept connotation and evaluation system, more research focuses on the diversified needs of high-quality human settlements. 2) Regarding spatial changing characteristics, more research presents a transformation from the overall description of macro region, focusing analysis on villages and towns in mesoscale, to the in-depth exploration of interior space for residences on a micro scale. 3) In exploring the driving mechanism, more studies combine natural factors and social factors to explore driving forces. The current research results show the characteristics of a "natural resource base determining the spatial function type" in the initial stage, to "industrial development leading the spatial function transformation" in the mid-term stage, and "the pursuit of natural comfort in human settlements" in the later stage. 4) In terms of adaptive regulation, most studies conclude to countermeasures that mainly realized through the coordination of stakeholders' social relations and the optimization of the combination and utilization development of physical space. Finally, this study establishes the evolution path map of the three stages of multi-functional human settlement in tourism destinations, and offers a focus for follow-up research, including evaluation systems combined with humanism, a more comprehensive coupling and trade-off driving mechanism within stakeholders on the multi-level spatial scale, and a multifunctional transition optimization strategy combining top-down and bottom-up approaches. Meanwhile, it is emphasized that the integration and innovation of interdisciplinary methods will become an important breakthrough.

Sara Mehrab Daniali, Sergey Evgenievich Barykin, Marzieh Zendehdel et al.

The current study aims to examine how students’ intentions to use 4.5G mobile phones are affected by the social-economic factors of performance expectancy, cost, effort expectancy, and social influence. This study is based on the perspectives of the unified theory of acceptance and use of technology (UTAUT). The central assumption of this study is that when students use 4.5G mobile services to source information at university, their academic performance is likely to improve. From eight private and public universities in Malaysia, 2117 students were enrolled in this study. We investigated the effects of gender and awareness as moderators on the relationships among the variables of interest. The findings showed that social influence and performance expectancy positively affected university students’ intentions to use 4.5G mobile phones. The researchers conducted a multigroup analysis to confirm the moderating effect of gender among the underlying relationships in the model. Structural equation modeling analysis indicated that, unlike awareness, gender did not moderate social influence, effort expectancy, performance expectancy, or the cost of students’ intentions to use 4.5G mobile phones. The implications of the proposed approach, considering the digital transformation concept, could be a topic for future research.

S. M. Mironova, D. V. Kozhemyakin, A. E. Ponomarchenko

The subject of the article is impact the gig economy to the legal regulation of labor, civil, tax relations.The purpose of the article is to identify the problems of legal regulation of relations between gig workers and digital platforms in the gig economy and suggest ways to improve it.The methodology includes systematic approach, comparative method, formal-logical method, formal-legal method, analysis, synthesis.The main results of the research. The transition from a “classic” industrial employment relationship between an employer and an employee to one based on the gig economy, using digital platforms to link the employee to their job, has created problems in classifying employment arrangements in labor law. In the current situation, the state needs to do a lot of work: (1) the sphere of the gig economy requires the compilation of clear terminology, as well as the analysis and identification of the functions of digital platforms and gig workers, then it requires amendments to labor legislation; (2) it is necessary to develop criteria for gig workers or independent contractors, one of the criteria can be proposed: the performance of work by a gig worker without the control of the hiring firm. The hiring firm's control should be limited to accepting or rejecting the results a gig worker achieves, not how they achieve them; (3) It is necessary to delimit the sphere of regulation of hired labor from the sphere of regulation of gig-employment, to withdraw gig-employment from the regulation of labor legislation.An analysis of the current legislation and law enforcement practice shows that the cornerstone of legal regulation in the field of the gig economy is the issue of legal registration of relations between digital platforms and their partners. Thus, with a rigid approach that identifies these relations with labor relations, the gig economy loses its specificity, digital platforms lose their competitive advantages in many ways, and in some cases, their ability to function. At the same time, the current relations in the field of employment of individuals on digital platforms allow us to speak about the presence of certain differences between such relations and labor relations, which are manifested mainly in greater freedom on the side of the "employee" and less control on the part of the employer – the digital platform, and also the unstable nature of this form of employment and its subsidiarity to more traditional forms. The specificity of the relationship between platforms and its counterparties also raises the question of the need to reform the provisions on civil liability, aimed at formulating special grounds for the responsibility of digital platforms, the distribution of this responsibility between them and their partners. Such provisions may be based on the existing norms on the liability of the employer for harm caused by his employee.Conclusions. The change of labor relations between employees and the employer to the relationship between the digital platform and gig workers predetermines the transformation of tax legal relations, in terms of the following aspects: what taxes should a gig worker pay, should there be any special tax regime; how the issue of paying insurance premiums should be resolved, whether they should be mandatory or voluntary; what role digital platforms will play in tax relations, whether they should act as tax agents or data providers; what requirements for gig workers, as taxpayers, should be imposed by tax legislation in terms of record keeping and reporting; how tax control should be exercised over gig workers and digital platforms.

Tim Schreiter, Lucas Morillo-Mendez, Ravi T. Chadalavada et al.

Robots are increasingly deployed in spaces shared with humans, including home settings and industrial environments. In these environments, the interaction between humans and robots (HRI) is crucial for safety, legibility, and efficiency. A key factor in HRI is trust, which modulates the acceptance of the system. Anthropomorphism has been shown to modulate trust development in a robot, but robots in industrial environments are not usually anthropomorphic. We designed a simple interaction in an industrial environment in which an anthropomorphic mock driver (ARMoD) robot simulates to drive an autonomous guided vehicle (AGV). The task consisted of a human crossing paths with the AGV, with or without the ARMoD mounted on the top, in a narrow corridor. The human and the system needed to negotiate trajectories when crossing paths, meaning that the human had to attend to the trajectory of the robot to avoid a collision with it. There was a significant increment in the reported trust scores in the condition where the ARMoD was present, showing that the presence of an anthropomorphic robot is enough to modulate the trust, even in limited interactions as the one we present here.

Chao Dong, Xiaoxiong Xiong, Qiulin Xue et al.

Network architecture design is very important for the optimization of industrial networks. The type of network architecture can be divided into small-scale network and large-scale network according to its scale. Graph theory is an efficient mathematical tool for network topology modeling. For small-scale networks, its structure often has regular topology. For large-scale networks, the existing research mainly focuses on the random characteristics of network nodes and edges. Recently, popular models include random networks, small-world networks and scale-free networks. Starting from the scale of network, this survey summarizes and analyzes the network modeling methods based on graph theory and the practical application in industrial scenarios. Furthermore, this survey proposes a novel network performance metric - system entropy. From the perspective of mathematical properties, the analysis of its non-negativity, monotonicity and concave-convexity is given. The advantage of system entropy is that it can cover the existing regular network, random network, small-world network and scale-free network, and has strong generality. The simulation results show that this metric can realize the comparison of various industrial networks under different models.