Management Processing Research Articles

The state of postgraduate support for young teachers in the regions of the Russian Federation

Introduction. The article presents the findings of a study on the state of postgraduate support for young teachers in various regions of the Russian Federation. This research has identified the difficulties, challenges, crises, and barriers that these individuals face when entering the profession.Aim. The present research aims to examine the current state of postgraduate support and retention of young teachers in the Russian Federation, as assessed by the teachers themselves, heads of educational organisations, and instructors from higher education, secondary vocational, and additional vocational education institutions.Methodology and research methods. The methodological foundation of this study is grounded in anthropological, acmeological, systemic, and reflexive-activity approaches. The research is based on an analysis of information regarding the organisation of postgraduate support for young teachers in various types of educational institutions, which was obtained through a survey. A total of 1,103 respondents from 10 regions of the Russian Federation participated in the empirical study.Results. As a fundamental principle in establishing a support system, most respondents emphasise the importance of adhering to priority tasks within the field of education. This reflects their understanding of the significance of the issue at hand, as well as principles related to targeting, individualisation, and the orientation of support aimed at addressing the challenges faced by young teachers. Most respondents advocate for evaluating the effectiveness of initiatives aimed at young teachers based on criteria such as their satisfaction with professional development outcomes and a reduction in the turnover rate of young teachers within the first few years of their careers. Furthermore, both teachers and administrators are generally well-informed about the resources available to support young educators and largely agree on their potential effectiveness. They also recognise that the support of young teachers is a manageable process, involving the active participation of many teachers and administrators. Additionally, young teachers themselves play an active role in organising this support.Scientific novelty. The scientific novelty of this study lies in the generalisation of existing trends and issues, the identification of priority tasks, principles, directions, and methods for establishing a system of postgraduate support and retention for young teachers in the profession. Practical significance. The results obtained can be utilised to design a support system for young teachers, including those in postgraduate programmes, while considering the unique characteristics of various types of educational organisations.

Implementation and optimisation of the cdugksFoam solver on the Sunway TaihuLight supercomputer

In this study, the cdugksFoam solver was successfully implemented on the Sunway TaihuLight system using the MPI + Athread programming model. To utilise the heterogeneous SW26010 many-core processor fully, we implemented three levels of parallelisation: MPI process-level hybrid parallelisation in physical space and velocity space, thread-level parallelisation to further partition physical space, and single-instruction multiple-data (SIMD) vectorisation. To address the performance bottleneck caused by the low memory bandwidth of the SW26010 processor, a series of optimisation methods, including kernel fusion, transcendental function optimisation, and soft cache, were designed and implemented to reduce discrete memory access and improve the computational efficiency of CPEs. The accuracy of the optimised program was validated through simulations of the 3D lid-driven cavity flow and rarefied supersonic flow past a sphere. Based on the experimental results from multiple grid scales, the overall performance achieved an acceleration of over 5 times compared to running on the management processing elements. In both strong and weak scalability tests, a parallel efficiency exceeding 90% was achieved.

Empowerment of the “Sinar Bahagia” Cocoa Farmers Group in Bebidas Village, Wanasaba District, East Lombok Regency Through Diversification of Cocoa Bean Processing

Bebidas Village is one of the villages in Wanasaba District, East Lombok Regency, which has relatively potential to be developed into a cocoa production center. There are two main obstacles faced by farmers, namely the lack of knowledge, attitudes, and skills of cocoa farmers towards cocoa farming management and cocoa bean processing technology into various commercial products and the absence of a standard procedure to produce quality dry cocoa beans. This community service activity aims to assist in processing cocoa plant products into various cocoa products with economic value to increase the income of cocoa farmers in Bebidas Village, Wanasaba District, East Lombok Regency. This activity can increase the productivity of cocoa plants and increase the types of processed cocoa plant products with commercial value.

Detection of production relevant deviations in paint sprays

AbstractSpray painting is still a poorly manageable process due to the complex interaction of physical, chemical and environmental influences like turbulent air flows, strong electrostatic fields, complex viscosity of paints and paint booth conditions. Consequently, many important properties of the painted film, like thickness, color, surface structure and the efficiency of the process are not controllable in an adequate manner, despite the enormous economic ramifications of poor quality control in high volume applications, such as in the automotive industry. This study shows how novel, online spray monitoring can instantaneously generate characterizing quantities from the spray to detect harmful deviations in the process. In this study, several minute changes have been experimentally imposed on a paint system, such as changed paint viscosity or pigmentation, deviations in air flow and paint flow rates, and defective or used and worn equipment parts. It will be shown that all these deviations lead to features which allow a clear distinction from the intact and reference cases. Additionally, it is shown that most of the deviations, if not detected, would have led to quality issues of the paint coating.

Applications of AI in Financial Fraud Detection

Artificial intelligence (AI) has emerged as a pivotal tool in combating financial fraud, offering advanced techniques to detect and mitigate fraudulent activities in real time. By leveraging machine learning algorithms, neural networks, and pattern recognition technologies, AI systems can identify anomalies, assess transaction risks, and predict potential threats with unparalleled accuracy. This research examines the various applications of AI in financial fraud detection, including its role in transactional analysis, user authentication, and predictive modeling. Key areas of focus include the integration of supervised and unsupervised learning methods, the use of natural language processing (NLP) for fraud analysis, and real-time data processing for dynamic threat management. The study also explores the challenges of implementing AI, such as data privacy concerns, algorithmic biases, and the need for regulatory compliance. By analyzing case studies and successful implementations, this research highlights best practices for leveraging AI in financial institutions to ensure robust fraud prevention. The findings underscore AI's transformative potential to enhance security, improve operational efficiency, and build trust in financial ecosystems.

تأثير استخدام الذكاء الاصطناعي في المتاجر الإلكترونية على المستهلكين

The study examines the impact of using artificial intelligence in e-stores on consumer behavior. The study highlights the importance of artificial intelligence in improving the online shopping experience, by providing personalized recommendations and analyzing purchasing patterns to better meet consumer needs. Artificial intelligence techniques such as natural language processing, deep learning, and augmented reality are used to provide a distinctive experience that contributes to increasing customer loyalty and raising conversion rates. The study indicates that artificial intelligence can automate many tasks, such as inventory management and order processing, which contributes to reducing costs and improving operational efficiency. Artificial intelligence also plays an important role in enhancing e-commerce security, as it can detect fraud and protect personal data. The study included the impact of AI-supported shopping practices on customers’ functional, financial, social, and emotional values. The results of previous studies reviewed indicate the positive impact of artificial intelligence on the efficiency of marketing methods, and raising the competitive advantage of e-stores by improving the mental image and increasing profitability.

SLR ABOUT THE COSTS OF PRIVATE BLOCKCHAIN TECHNOLOGY FOR BUSINESSES

Since the appearance of Bitcoin (2009), blockchain technology has been used in many fields. Companies use it for financial services, goods tracking, data authentication and secure storage, among other things, in order to make their operations more transparent and efficient. This technology has revolutionized the data management and transaction processing, but the associated costs are also significant and relevant to understand. The costs of blockchains vary and depend on the type of blockchain and how it is used. In this article, we examine the costs of using blockchain technology based on international literature, studies and reports with systematic literature review. In the results the range of possibilities offered by technology is presented, as well as the technology related cost types, and expenditures what companies have to deal with.

An IoT Based Smart Dustbin System

All human being are throws waste in dustbin or some other different places. The waste are plastics, degradable and non-degradable. All people are trying to put the waste in dustbin or garbage bin only. In cities, there are many public places where we see that dustbin or garbage bin are placed but there are overflowing. This create unhygienic condition in the surrounding. And it also create some serious diseases. At a same time, an odor extends throughout the city, and degrading the environment. Recycling bin is really a waste management processing, but they are limited space in a garbage bin, it does not require extra waste. Waste disposal is an efficient method of eliminating garbage disposed in commercial settings such as businesses, classrooms, colleges, shopping centers, and other public areas. We have to design the project, where the dustbin is fulled or not and the waste level of the trash bin is measured. The NodeMCU and the ultrasonic sensor is a hardware component for measuring the garbage bin. The software component is an IFTTT Webhook, and it is used to receiving a notification.The main concept of this project is when more than 70 percent of the garbage bin is filled, the IFTTT Webhook sends the notification and we receive the email.

The Subscription Management System

Subscription-based membership systems have become increasingly popular for digital services like Spotify, Prime Video, and YouTube. This project explores the development of a subscription management system using JavaFX, focusing on creating an intuitive user interface and efficient backend integration. The system supports functionalities such as user registration, subscription management, and payment processing, offering a seamless experience for both administrators and users. This study addresses key aspects such as GUI design, security challenges, performance optimization, and integration of RESTful APIs for backend communication. The implementation aims to provide a scalable, secure, and user-friendly solution for managing various subscription models. Additionally, this research compares different subscription models to optimize user engagement and retention. Advanced features like automated billing, personalized recommendations, and analytical insights are integrated to enhance the overall user experience. The study also highlights best practices for integrating third-party payment gateways and managing user data securely. The results demonstrate the system’s ability to handle a large user base effectively while maintaining high performance and security standards. Future work will explore the integration of machine learning techniques to predict user preferences and improve personalization further

Harnessing Big Data for Machine Learning (Strategies, Approaches, and Challenges)

This paper explores the dynamic relationship between big data and machine learning, highlighting the key strategies, methodologies, and challenges associated with their integration. The convergence of these technologies presents transformative opportunities across industries, but it also introduces complexities in terms of data management, infrastructure, and real-time processing. This study examines the role of big data in fueling machine learning models, discusses critical success factors, and identifies best practices for implementing machine learning at scale.

The study of management processes of regional projects to determining algorithms of prototyping: A review

In the context of modern competition, project management approach can ensure higher speed and quality of achieving strategic objectives set for health care industry at minimal cost and risk. Due to the need to implement regional projects with higher speed and quality, the problems of algorithmization of project management processes becomes relevant. The complex multi-level system of project implementation in health care industry, instability of external environment and variety of needs of stakeholders requires finding algorithm to implement management processes. The purpose of the study was to find prototype model for managing processes of medical organization project, built on formalized data of functional components of project and algorithms obtained during stage-by-stage modeling of the system. In the process of development of operation of the system its elements and presentation of data were iteratively refined and in accordance with data algorithms were synchronously refined too. To build prototype model of management processes in regional medical organization for subsequent digitization it is necessary to formalize variables, to determine in accordance with size of the range of values that variable can take for subsequent effective algorithmization of management processes. The stages of project management processes were correlated with classification characteristics of models to establish stages of their construction and modeling of working model of prototype project. To establish optimal prototype of project management processes its immediate integration with project environment of medical organization is required using machine learning methods. The study results confirmed necessity to proceed search for project management tools increasing efficiency of operational activities of medical organizations implementing regional projects in health care industry.

Slice admission control in 5G wireless communication with multi-dimensional state space and distributed action space: A sequential twin actor-critic approach

Network slicing represents a paradigm shift in the way resources are allocated for different 5G network functions through network function virtualization. This innovation aims to facilitate logical resource allocation, accommodating the anticipated surge in network resource requirements. This will harness automatic processing, scheduling, and orchestration for efficient management. To overcome the challenge of managing network resources under heavy demand, slice providers need to leverage both artificial intelligence and slice admission control strategies. While 5G network resources can be allocated to maintain a slice, the logical allocation and real-time network evaluation must be continuously examined and adjusted if network resilience is to be maintained. The complex task of leveraging slice admission control to maintain 5G network resilience has not been fully investigated. To tackle this problem, we propose a machine learning approach for slice admission control and resource allocation optimization so as to maintain network resilience. Machine learning algorithms offer a powerful tool for making robust and autonomous decisions, which are crucial for effective slice admission control. By intelligently allocating resources based on real-time demand and network conditions, these algorithms can help ensure long-term network resilience and achieve key objectives. While various machine learning algorithms hold promise for 5G resource management and admission control, reinforcement learning (RL) has emerged as a particularly exciting solution. Its ability to mimic human learning processes makes it a versatile solution, well-suited to tackle the complex challenges of network control. To fill this gap, we propose a new technique known as sequential twin actor critic (STAC). Simulations show that the STAC improves network resilience through enhanced admission probability and overall utility.

Strengthening urban deer management with structured decision making

Urban deer management (UDM) decision‐makers face social, ecological, regulatory, and economic pressures when creating an agreeable deer management plan for stakeholders. Historically, decision making techniques (e.g. consensus‐based analyses) have not effectively balanced UDM elements leading to short‐lived management progress. Structured decision making (SDM) is a formal, values‐based approach to identifying an optimal management solution. Although SDM has been applied to other wildlife management decisions, it has not been applied in UDM. We provide the first case‐study of SDM‐based UDM and streamline the process for wildlife managers. We focused on one suburban and one semi‐rural community near Atlanta, Georgia, USA. We established a problem statement to capture what decision‐makers must address in UDM programs and reviewed the primary literature and UDM plans from five states to establish four fundamental objectives. We then utilized a support–effectiveness analysis to identify acceptable UDM alternatives and gathered expert insights to calculate the consequences of alternatives on objectives. Finally, we asked each community's decision‐makers to weigh objectives against each other. Using this framework, education was the most optimal UDM technique to implement in the suburban community, and sharpshooting was the most optimal UDM technique to implement in the semi‐rural community. This paper positions SDM as a transparent, defensible, inclusive, and adaptive approach to UDM. Furthermore, our SDM framework provides managers with the means and justification to create an optimal plan of action for communities in need of UDM.

Concept of a medical and public health cancer genomics platform

Abstract Background This study aims to produce the concept of an open-access medical and public health cancer genomics platform aimed at aggregating and sharing documentation of ongoing initiatives and data resulting from the CAN.HEAL project, available for EU researchers, healthcare professionals, policy makers, citizens and patients. Methods The context (reference sector, stakeholders and research evidences), feasibility (privacy management and data processing), and platform’s end users were analysed; the CAN.HEAL project deliverables were listed and clustered; aspects related to the definition of the overall platform architecture and modules integration were studied. Results The project deliverables were catalogued into 8 categories which could be the platform’s cloud interface main labels: results from events, policy papers, newsletters, mapping results and reports, datasets, recommendations and guidelines, use cases, courses and training activities. To define the overall system architecture, the following key activities should be implemented: content management system choice, hosting configuration and setup of the development domain, content management system installation, development of HTML web pages, data entry, data visualisation and graphic layout, and test and debug. To the modules integration purposes the following items should be addressed: creation of a server analytics account; social network integration; activation of additional system for sending newsletters. Conclusions Cloud-based data platform allows to securely manage, integrate, analyse and share large datasets. Establishing an infrastructure to help researchers access, store and analyse large amounts of biological data is of paramount importance both to enable advances in research and support health policy making processes. The CAN.HEAL platform could help aligning clinical and population-based interventions for integrating the genome of Europe biobanking initiative into public health genomics for cancer. Key messages • Connecting healthcare data can support the challenge of accessing the relevant information needed for the policy and decision making processes to effectively promote population health and wellbeing. • The set-up of a medical and public health cancer genomics platform promotes the effective translation of genome-based knowledge and technologies into public policy and health services.

Hero's journey as a framework to study a project manager

PurposeThe purpose of this study is to explore which insights the hero’s journey framework provides to the micro-level perspective of the process a project manager goes through in a project.Design/methodology/approachThe study design involves a longitudinal qualitative case study in which we follow a project manager over the course of two projects. In Canada, the project manager undertook the world’s first hotel rooftop honeybee garden project. Later, he implemented a rooftop honeybee garden at the Waldorf Astoria New York. The stages and archetypes within the hero’s journey framework are used as an analytical grid for analysis.FindingsOur research reveals how the hero’s journey framework can be utilized as a lens to understand the process of a project from the viewpoint of the project manager. The research shows that projects can have comprehensive stages and transform the project managers themselves.Research limitations/implicationsThe research investigates small-scale projects that are peripheral to the core business of the case organizations. A limitation is that the findings may not be applicable for bigger, more complex and core business projects. Another limitation is that the research relies on secondary data only. Two managerial implications: For a project manager to start out on a hero’s journey, triggers that make the project manager respond to “a calling” need to be present. The project manager must be able to deal with different archetypes, whether helpful or harmful, along the process.Originality/valueThe research extends existing knowledge on a project manager’s decisions, obstacles, opportunities, thoughts, emotions and actions through the project process by showing how the hero’s journey framework can be used as a supplement to the well-known metaphor of a project as a temporary organization. Further on, the research demonstrates how an analytical framework can enhance the understanding of the process of a project manager from a micro-level perspective. In addition, the research deals with corporate social responsibility (CSR) related projects that are of high relevance in the contemporary society.

Use of management games within the education process of future managers at universities in Slovakia and Czech Republic

Use of management games within the education process of future managers at universities in Slovakia and Czech Republic

Edge Computing and Cloud Computing for Internet of Things: A Review

The rapid expansion of the Internet of Things ecosystem has created an urgent need for efficient data processing and analysis technologies. This review aims to systematically examine and compare edge computing, cloud computing, and hybrid architectures, focusing on their applications within IoT environments. The methodology involved a comprehensive search and analysis of peer-reviewed journals, conference proceedings, and industry reports, highlighting recent advancements in computing technologies for IoT. Key findings reveal that edge computing excels in reducing latency and enhancing data privacy through localized processing, while cloud computing offers superior scalability and flexibility. Hybrid approaches, such as fog and mist computing, present a promising solution by combining the strengths of both edge and cloud systems. These hybrid models optimize bandwidth use and support low-latency, privacy-sensitive applications in IoT ecosystems. Hybrid architectures are identified as particularly effective for scenarios requiring efficient bandwidth management and low-latency processing. These models represent a significant step forward in addressing the limitations of both edge and cloud computing for IoT, offering a balanced approach to data analysis and resource management.

Characterization of Robusta Coffee Powder with Addition of Palm Sugar and Vanilla Powder to Improve The Quality of Robusta Coffee (Coffea canephora Pierre)

Bondowoso Robusta Coffee is a type of Robusta coffee that has a distinctive taste and high quality. The distinctive taste and high quality are obtained from the results of harvest management and post-harvest processing in accordance with Standard Operating Procedures (SOP). This research will be carried out by testing the characteristics of Robusta ground coffee with a mixture of palm sugar and vanilla flavoring to improve the quality of Robusta ground coffee. This was done by knowing the physicochemical and organoleptic properties of the mixed Robusta ground coffee. The aim of this research is to determine the interaction between roasting level and the composition of palm sugar and vanilla powder on the physiochemical and organoleptic properties of 3 in 1 Robusta Coffee. This research uses an experimental plan arranged factorially with the basic pattern of a Completely Randomized Design (CRD) with 4 replications. This design has two factors, the first factor is the roasting level and the second is the mixture composition. The results of this research show (1) The interaction of Roasting Level and Mixture (palm sugar and vanilla powder) has no significant effect on all observed variables such as water content, Brix content, pH value, and powder bulk density. (2) The effect of the main level of roasting has a very significant effect on the observed variables of rainfall density and an insignificant effect on the variables of air content, Brix content and pH value. (3) The effect of the main mixture has a very significant effect on the observed variables of air content, Brix content and powder bulk density and has no significant effect on the variable pH value.

Visualizing environmental change as inevitable, manageable, and deconstructive

ABSTRACT Working from a visual cultural approach that interrogates issues of visibility and visuality, this article theorizes how coastal residents represent their own observations and experiences of environmental change through photography and storytelling. We present results from an exploratory photovoice study in Maine, where participants framed change as an inevitable, manageable, or deconstructive process of social-ecological interaction. These results point to multiple, often contradictory ways participants understand and construct their environment and reveal the impact of their views on the perceived availability, desirability, and feasibility of community responses to change. In turn, the article presents critical implications for communication and dialogue about community development, resource management, and coastal adaptation.

Synthesis of agro-industrial wastes/sodium alginate/bovine gelatin-based polysaccharide hydrogel beads: Characterization and application as controlled-release microencapsulated fertilizers

Synthesis of novel agro-industrial wastes/sodium alginate/bovine gelatin-based polysaccharide hydrogel beads, micromeritic/morphometric characteristics of the prepared formulations, greenhouse trials using controlled-release microencapsulated fertilizers, and acute fish toxicity testing were conducted simultaneously for the first time within the scope of an integrated research. In the present analysis, for the first time, 16 different morphometric features, and 32 disinct plant growth traits of the prepared composite beads were explored in detail within the framework of a comprehensive digital image analysis. The hydrogel beads composed of 19 different agro-industrial wastes/materials were successfully synthesized using the ionotropic external gelation technique and CaCl2 as cross-linker. According to micromeritic characteristics, the ionotropically cross-linked beads exhibited 77.86 ± 3.55 % yield percentage and 2.679 ± 0.397 mm average particle size. The dried microbeads showed a good swelling ratio (270.02 ± 80.53 %) and had acceptable flow properties according to Hausner's ratio (1.136 ± 0.028), Carr's index (11.94 ± 2.17 %), and angle of repose (25.03° ± 5.33°) values. The settling process of the prepared microbeads was observed in the intermediate flow regime, as indicated by the average particle Reynolds numbers (169.17 ± 82.81). Experimental findings and non-parametric statistical tests reveal that dried fertilizer matrices demonstrated noteworthy performance on the cultivation of red hot chili pepper plant (Capsicum annuum var. fasciculatum) according to the results of greenhouse trials. Surface morphologies of the best-performing fertilizer matrices were also characterized by Scanning Electron Microscopy. Moreover, the static fish bioassay experiment confirmed that no abnormalities and acute toxic reactions occurred in shortfin molly fish (Poecilia sphenops) fed with dried leaves of red hot chili pepper plants grown with formulated fertilizers. This study showcased a pioneering investigation into the synthesis of microcapsules using synthesized hydrogel beads along with digital image processing for bio-waste management and sustainable agro-application.