Optimal Resource Management Research Articles

A304 EXPLORING HEPATITIS C TREATMENT COST TRENDS OVER A DECADE: A CROSS-SECTIONAL ANALYSIS WITHIN MEDICARE PART D (2012-2021)

Abstract Background Chronic hepatitis C virus (HCV) infection negatively impacts quality and quantity of life. With the onset of direct-acting antivirals (DAAs), cure rates of HCV have increased to over 95%. Despite these advancements, chronic HCV infection continues to pose a substantial health and financial burden and without drug coverage, treatment of HCV with these DAAs is unaffordable. In the United States, Medicare Part D is a voluntary drug coverage plan predominantly for individuals covered by Medicare (typically over 65 years old) which can facilitate access to these DAAs. Aims This study aims to analyze the shifts in HCV treatment and spending in the USA from 2012 to 2021 for Medicare Part D and assess the impact of generic drugs on overall expenditure. Methods A retrospective cross-sectional study was conducted using publicly available Centers for Medicare and Medicaid Services (CMS) Medicare D drug spending data from 2012 to 2021. The total expenditure and utilization of HCV drugs was calculated, and average spending per beneficiary was utilized to estimate potential cost savings if generic DAAs were employed. Results The study revealed a decline in HCV claims and beneficiaries over 65 since 2015 with a peak of 134,752 beneficiaries decreasing to 35,735 in 2021. Accordingly, spending was the highest in 2015 (8.8 billion USD) and subsequently trended downwards to 1.5 billion in 2021. Over the ten-year period, the USA spent a total of 33.1 billion USD on HCV treatment. Harvoni accounted for 53% of the spending, followed by Sovaldi (17%) and Epclusa (14%). Generic drug utilization slowly increased with the introduction of generics in 2019 with 6.4% of beneficiaries treated with generic DAAs in 2019, rising to 15.3% in 2020 and 14.8% in 2021. If all prescriptions of Harvoni and Epclusa were substituted by ledipasvir/sofosbuvir and sofosbuvir/velpatasvir, respectively, there is a potential $2.7 billion cost reduction. This translates to a potential 47.3% reduction in HCV treatment expenditures from 2019 to 2021. Conclusions The decreasing number of beneficiaries for HCV treatment among people over the age of 65 suggests a decreasing HCV prevalence in this age group. This reflects the success of DAA treatment and low reinfection rates. However, the underutilization of generic DAAs despite their lower cost highlights a missed opportunity for substantial savings. This study emphasizes the importance of policy negotiations to ensure optimal resource management, advocating for a shift towards generic drug usage to alleviate the financial burden associated with HCV treatment. Trends in total spending on DAAs for HCV and number of beneficiaries within Medicare Part D from 2012 to 2021. Annual percent changes in expenditure are shown within the data bars. Funding Agencies None

Optimizing Resource Management for Shared Microservices: A Scalable System Design

A common approach to improving resource utilization in data centers is to adaptively provision resources based on the actual workload. One fundamental challenge of doing this in microservice management frameworks, however, is that different components of a service can exhibit significant differences in their impact on end-to-end performance. To make resource management more challenging, a single microservice can be shared by multiple online services that have diverse workload patterns and SLA requirements. We present an efficient resource management system, namely Erms, for guaranteeing SLAs with high probability in shared microservice environments. Erms profiles microservice latency as a piece-wise linear function of the workload, resource usage, and interference. Based on this profiling, Erms builds resource scaling models to optimally determine latency targets for microservices with complex dependencies. Erms also designs new scheduling policies at shared microservices to further enhance resource efficiency. Experiments across microservice benchmarks as well as trace-driven simulations demonstrate that Erms can reduce SLA violation probability by 5× and more importantly, lead to a reduction in resource usage by 1.6×, compared to state-of-the-art approaches.

Application and existing problems of artificial intelligence technology in the agricultural field

In recent years, the application of artificial intelligence technology in the field of agriculture has been rapidly developed. This paper summarizes the application of artificial intelligence in agriculture and divides it into two main directions: monitoring system and expert system. This paper analyzes the soil monitoring, pest monitoring, and plant growth detection of the monitoring system, the simple decision chain of the expert system, and the complex expert system combined with artificial intelligence technology. Utilizing sensor networks, image processing, and machine learning techniques, artificial intelligence enables real-time monitoring of soil parameters, automatic identification of pest and disease, analysis of plant growth status, and provision of tailored management recommendations. By employing rule-based expert systems, artificial intelligence assists farmers in making informed decisions. These applications have significantly advanced resource management optimization, pest control, precise growth monitoring, and intelligent decision-making in agriculture. At the end of the article, this paper summarizes the full text and looks forward to the future trend.

Queuing Model with Customer Class Movement across Server Groups for Analyzing Virtual Machine Migration in Cloud Computing

The advancement of cloud computing technologies has positioned virtual machine (VM) migration as a critical area of research, essential for optimizing resource management, bolstering fault tolerance, and ensuring uninterrupted service delivery. This paper offers an exhaustive analysis of VM migration processes within cloud infrastructures, examining various migration types, server load assessment methods, VM selection strategies, ideal migration timing, and target server determination criteria. We introduce a queuing theory-based model to scrutinize VM migration dynamics between servers in a cloud environment. By reinterpreting resource-centric migration mechanisms into a task-processing paradigm, we accommodate the stochastic nature of resource demands, characterized by random task arrivals and variable processing times. The model is specifically tailored to scenarios with two servers and three VMs. Through numerical examples, we elucidate several performance metrics: task blocking probability, average tasks processed by VMs, and average tasks managed by servers. Additionally, we examine the influence of task arrival rates and average task duration on these performance measures.

Design of federated learning-based resource management algorithm in fog computing for zero-touch network

The concept of zero-touch networking involves creating networks that are fully autonomous and require minimal human intervention. This approach is increasingly relevant due to the rapid growth of current cloud architectures, which are beginning to reach their limits due to continuous expansion demands from users and within the network core itself. In response, Fog computing, acting as a smart, localized data center closer to network nodes, emerges as a practical solution to the challenges of expansion and upgrading in existing architectures. Fog computing complements cloud technology. However, the realization of zero-touch networks is still in its early stages, and numerous challenges hinder its implementation. One significant challenge is the NP-hard problem related to resource management. This paper introduces an optimal resource management algorithm based on Federated Learning. The effectiveness of this algorithm is evaluated using the iFogSim simulator within the existing cloud-fog architecture. The results demonstrate that the proposed architecture outperforms the current infrastructure in several key aspects of resource management, including system latency, number of resources processed, energy consumption, and bandwidth utilization.

Research on Vehicle Task Management Based on TBMADDPG

<p>Recently, the traditional cloud computing network of vehicle networking has some problems to be solved: 1) the security trust between the vehicle and the subgrade unit; 2) The vehicle may be attacked by potentially malicious edge servers during task unloading. In this paper, in order to solve the above problems, aiming at the security problem of the edge computing network in the vehicle task unloading and resource allocation problems of multi-vehicle and multi-roadbed units in the urban intersection scene, the vehicle task unloading and resource management optimization algorithm and trust model based on the vehicle edge computing network are constructed, and the approximate optimal simulation is carried out for the urban intersection scene. Simulation results show that the proposed algorithm can effectively improve the overall efficiency of the system.</p> <p> </p>

Modeling of effective management of logistics supply of an industrial enterprise

Introduction. The economy and industry, which show a tendency to grow even in wartime, will require improved logistics and improved infrastructure. The implementation of such measures is based on scientifically based solutions in the effective management of high-tech (HT) production within the logistics management of integrated supply chains. The purpose of the paper is to determine an effective approach to inventory management at a high-tech industrial enterprise within the framework of developing a scientifically based inventory management strategy using the analysis of existing models. Results. The paper presents an analysis of the main models of operational inventory management of a high-tech enterprise: a single-product statistical model with deterministic demand, a model in the case of accounting for unsatisfied requirements, a model of inventory management based on random demand, a model in the case of loss of unsatisfied requirements, a model of a production system with periodic checks in case of random demand. It is emphasized that inventory management consists in establishing the moments and volumes of the order for their occupancy and distribution along the chains of the supply subsystem within the framework of strategic management. There is an orientation towards cost minimization. The whole inventory management process is imagined as a component of the supply-production-marketing system, which is managed on the basis of a complex logistics approach.Accounting for the features of each subsystem - supply, production, sales, as well as optimal management of resources, is based on cost minimization and leads to high-quality satisfaction of demand for ready-made innovative products with sufficient economic effect. Conclusion. Inventory management consists in establishing the moments and volumes of the order for their filling and distribution among the links of the supply subsystem. The listed inventory management models are intended for practical use, others are of interest because they allow you to understand the essence and identify the main properties of the inventory management system. Accounting for the specifics of each subsystem (supply, production, sales), as well as competent management of their resources, flows (financial, material, information), based on cost minimization, ultimately leads to the main goal of the IT of an industrial enterprise - high-quality satisfaction of demand for finished products with maximum economic effect.

Smart value chain tool advancing sustainability in the FoodBev manufacturing industry

The world is evolving towards sustainability and optimum resource management, with a rapid evolution towards a circular economy (CE). The focus on sustainability in the food and beverage (FoodBev) sector is a priority due to the close association and dependency on natural resources. The evolution of digitalization has accelerated sustainable development of the FoodBev sector and helped preserve sectorial natural resources dependencies. Digital skills are a key component of sustainable development, as skills are used to identify and implement sustainable solutions. Digitalization and the CE in the FoodBev sector are considered critical solutions for food waste and food loss, and potential drivers of sustainability. This study seeks to deploy a smart value chain tool for food waste and food loss management, and a digital mechanism for the sustainability of the FoodBev sector. The research team designs, develops, and demonstrates a python-enabled digital toolset, configured to construct a specific global search for sustainable alternates for waste and other streams of the FoodBev industry. The toolset adopts a combination of Artificial Intelligence techniques including data analytics and Natural Language Processing. The results provide for rapid technological alternatives identification for the sector. The paper provides technological alternatives for 18 FoodBev value streams.

Pathology of the cardiovascular system in people returning to sports after COVID-19

Aim: to summarize the data published in our country and abroad on the diagnosis of cardiac complications after COVID‑19 and to compare it with our own experience of examining such athletes.Materials and methods: open data sources such as eLibrary, Scopus, PubMed etc. were used as a scientific base to achieve the set goal, a meta-analysis of 42 domestic and foreign literature sources was carried out upon the results of post‑COVID changes in athletes. Besides that, the indicators of 11467 athletes, aged from 16 to 45 years, were studied who have been playing for the Moscow national team and who passed in‑depth medical examination on the basis of Sports Medicine Clinic in Moscow Scientific and Practical Center of Medical Rehabilitation, Restorative and Sports Medicine.Results: the prevalence of myocarditis in mild COVID‑19 in athletes does not exceed 1 %, arrhythmia does not exceed 9 %. Classical cardiovascular screening is sufficient for their detection in most cases. If hospitalization is necessary, the risks increase for myocarditis up to 7.2 %, for myocardial infarction up to 4,7 %, for other cardiac complications up to 3–14 % and require advanced diagnostics. For optimal resource management in the healthcare system, a working algorithm for examining athletes returning to trainings after a previous COVID‑19 is proposed.Conclusion: in most cases a classical cardiovascular screening is enough for symptomatic individuals returning to sports trainings after the COVID‑19. However, additional examinations, including loading tests and MRT, are required to find out possible latent ongoing pathology as well to evaluate prospects for the athlete.

Operating System and Server Integration for Business Effectiveness

Management Information Systems (MIS) have a crucial role in supporting the effectiveness of a company or agency. A strong MIS ensures optimal internal planning and control, involving people, documents, technology and procedures. The importance of MIS demands synergistic integration between the operating system and servers to manage hardware resources and store information efficiently. This research aims to explore the factors that influence SIM in the context of operating system and server integration. The focus is on understanding the impact of this integration on business effectiveness, particularly in terms of planning, control and data storage. Research reveals that the integration of operating systems and servers positively contributes to increasing SIM effectiveness. Harmonious cooperation between the operating system and servers encourages optimization of hardware resource management and information storage, supporting more efficient internal planning and control. These findings provide a new view regarding the importance of operating system and server integration in optimizing SIM. The implementation of this integration is expected to improve business performance through more accurate planning, tight control and efficient data storage. The novelty of this research lies in the integrative approach to operating systems and servers in the context of SIM. A deeper understanding of these relationships can provide practical guidance for companies to improve the effectiveness of their information systems.

Evaluation of the Success of E-Log Book Implementation for Handline Fishing Gear at Bitung Fishing Port

Ensure optimal and sustainable management of fishery resources and the preservation of fishery resources, accurate fisheries data is essential. One way to achieve this, is by using fishing log books. Improvements have been made by developing an electronic-based fishing log book (e-log book) that is Android-based, paperless, and capable of offline mode. However, an evaluation of the use of e-log books in the perspective of captains (users), has not been conducted. This research aims at assessing user satisfaction propensity and evaluating the extent of the success of the implementation of the e-log book for handline fishing gear at Bitung Fishing Port (PPS) using the DeLone and McLean model. The sampling method employed is purposive sampling, with 115 respondents consisting of handline captains who use e-log books. The research was carried out for 3 (three) months in January – March 2023.The data analysis was conducted using propensity test and PLS-SEM. The propensity test results indicate that the implementation of e-log books at Bitung Fishing Port is in the high category at 77.39%. The PLS-SEM analysis results indicate that out of the four proposed hypotheses, not all were supported and accepted. The quality of the system and service influences user satisfaction, and user satisfaction also affects net benefits. However, the quality of information does not impact user satisfaction. The conclusion drawn from this study depicts that, the satisfaction of handline fishing gear captains regarding the implementation of e-log books at Bitung Fishing Port is at a "high" level. Meanwhile, the e-log book application implementation still faces some challenges or aspects that need improvement to achieve the expected level of success.

Optimal service resource management strategy for IoT-based health information system considering value co-creation of users

PurposeThis paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.Design/methodology/approachAn adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.FindingsThe results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.Practical implicationsThe findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.Originality/valueThis study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.

A Time Series-Based Approach to Elastic Kubernetes Scaling

With the increasing popularity of cloud-native architectures and containerized applications, Kubernetes has become a critical platform for managing these applications. However, Kubernetes still faces challenges when it comes to resource management. Specifically, the platform cannot achieve timely scaling of the resources of applications when their workloads fluctuate, leading to insufficient resource allocation and potential service disruptions. To address this challenge, this study proposes a predictive auto-scaling Kubernetes Operator based on time series forecasting algorithms, aiming to dynamically adjust the number of running instances in the cluster to optimize resource management. In this study, the Holt–Winter forecasting method and the Gated Recurrent Unit (GRU) neural network, two robust time series forecasting algorithms, are employed and dynamically managed. To evaluate the effectiveness, we collected workload metrics from a deployed RESTful HTTP application, implemented predictive auto-scaling, and assessed the differences in service quality before and after the implementation. The experimental results demonstrate that the predictive auto-scaling component can accurately predict the future trend of the metrics and intelligently scale resources based on the prediction results, with a Mean Squared Error (MSE) of 0.00166. Compared to the deployment using a single algorithm, the cold start time is reduced by 1 h and 41 min, and the fluctuation in service quality is reduced by 83.3%. This process effectively enhances the quality of service and offers a novel solution for resource management in Kubernetes clusters.

Digital Product Passport: A Pathway to Circularity and Sustainability in Modern Manufacturing

The primary aim of this study is to explore and understand the potential benefits and applications of the Digital Product Passport (DPP) system within the modern manufacturing industry. To achieve this, we developed a unique methodology, model, and a template for creating a DPP, identifying the key characteristics essential for effective implementation. Our approach involved an analysis of the literature and the formulation of a unified DPP framework, tailored to enhance supply chain transparency and support sustainable manufacturing practices. The empirical findings from our research demonstrate the DPP’s impact on supply chain transparency, providing crucial product lifecycle information that bolsters decision-making and facilitates optimal resource management. Additionally, our study suggests that the DPP model, when applied to sectors such as electronics manufacturing, promises transformative results. This research underpins the pivotal role of DPPs in the future of manufacturing, highlighting their potential to catalyze a shift towards greater transparency and sustainability. Actionable guidelines are provided for manufacturers considering the adoption of this innovative system.

Research on the Optimization of Enterprise Resource Economic Benefits and Management Costs in Cloud Computing Environment

Abstract Based on cloud computing technology, this paper constructs a benefit-optimal enterprise resource scheduling model and an enterprise cost management prediction model to maximize the economic benefits of enterprise resources and optimize the management costs, respectively. Combining the improved greedy algorithm and the benefit function, a cloud resource scheduling algorithm based on benefit optimization is proposed, defining the benefit function about time and cost, and taking the highest user satisfaction as the optimal resource scheduling objective. A mathematical model for management cost prediction is constructed by using the fireworks algorithm to optimize the number of trees and the number of leaf nodes in the random forest, and the Informatica software is used to manage and integrate the enterprise source data. The performance of the company’s operating conditions after optimizing resource management and cost savings is explored as a case study of Company S. In 2023, the total asset turnover ratio of Company S increased to 21.45 from 0.48 in 2022, and the overall asset operating efficiency improved. Working capital rose to 262,852,200 yuan. The current ratio, quick ratio, and cash ratio improved, while the gearing ratio, equity ratio, and equity multiplier showed a downward trend. The net operating margin achieved the maximum profitability in the last three years, net total assets margin, and net equity margin, with an increase of 25.42%, 20.65%, and 31.49%, respectively.

The method of optimal resource management of a distributed dynamic system based on the algorithm of zeroing neural networks

The method of optimal resource management of a distributed dynamic system based on the algorithm of zeroing neural networks offers a new approach to effective resource management in distributed dynamic systems using advanced machine learning technologies. Research questions concern determining optimal resource management strategies in a distributed dynamic system, as well as evaluating the effectiveness of the proposed method in various scenarios. The research methods include mathematical formalization of the problem, development of an algorithm for zeroing neural networks and conducting numerical experiments based on computer modeling. The results of the study demonstrate the high efficiency of the proposed method of optimal resource management in a distributed dynamic system. The conclusions emphasize the importance of using the algorithm of zeroing neural networks in the context of optimal resource management in distributed systems and the possibility of its application to solve practical problems in various fields, such as energy, production, transport and others.

РОЛЬ УМНЫХ ГОРОДОВ В РАЗВИТИИ ЦИФРОВОЙ ЭКОНОМИКИ И ИННОВАЦИОННЫХ ЭКОСИСТЕМ

The article examines the impact of smart cities on the development of the digital economy and the creation of innovative ecosystems. The main task of the work is to analyze the technologies of smart cities – the Internet of Things, big data and artificial intelligence – and their impact on improving urban ecosystems, improving the standard of living of citizens and optimizing resource management. The methods used include a review of the literature and an analysis of practical examples of the introduction of digital technologies in urban management. An important aspect of the research is the study of financial models such as peer-to-peer financing and public-private partnerships. The main findings confirm that smart cities stimulate innovation processes and create conditions for the integration of technologies into urban systems. The peculiarity of the study lies in an integrated approach that covers the technological, social and economic aspects of the digital transformation of cities.

Sustainable Food Agriculture Utilizing Industry 4.0: A Short Note on the Impacts on Human Resources

This brief essay explores the correlation between Industry 4.0 (I4.0) and the agricultural sectors and the benefits they offer. Agriculture 4.0, the use of I4.0 technology in agriculture, has the potential to bring about a profound transformation in the agricultural sector by fostering sustainability. The advantages encompass catering to the increasing food requirements resulting from the rising human populace, attaining sustainable economic savings over time, improving food safety, and optimizing human resources. Integrating I4.0 into agriculture would improve productivity by reducing unnecessary workforce and addressing occupational health risks. Hence, implementing I4.0 technologies has considerable promise in promoting sustainable food production by leveraging data-driven decision-making, optimizing resource management, and improving efficiency in agricultural practices. In the age of I4.0, human resources (HR) 4.0 is crucial in utilizing digital technology to manage human resources efficiently and achieve organizational success, particularly in the agriculture industry.

ВЛИЯНИЕ ЦИФРОВИЗАЦИИ НА ЭФФЕКТИВНОСТЬ ПРОИЗВОДСТВА В АГРОПРОМЫШЛЕННОМ КОМПЛЕКСЕ

In the article, the authors analyze the impact of the introduction of digital technologies on the productivity and efficiency of agricultural organizations. The main purpose of the study is to assess the impact of digitalization on production processes, identify advantages and obstacles. The study examines modern digital technologies such as precision farming, the Internet of Things, big data analysis and automation. The main conclusions of the article are that digitalization in the agro-industrial complex helps to increase productivity, optimize resource management, improve product quality and reduce cost. However, the process of introducing digital technologies is accompanied by problems such as high initial investments, the need to develop infrastructure and increase digital literacy of farmers. The peculiarity of the work is a comprehensive analysis of the impact of digitalization on the agro-industrial complex and the development of methodological approaches to assessing the effectiveness of the introduction of digital technologies.

ДОСЛІДЖЕННЯ РОЛІ ЦИФРОВОЇ ЕКОНОМІКИ В ДОСЯГНЕННІ ЦІЛЕЙ СТАЛОГО РОЗВИТКУ ТА ЗБЕРЕЖЕННЯ ПРИРОДНИХ РЕСУРСІВ

The current stage of economic development is characterized by the integration of a wide range of digital technologies, services, goods and services into the economic system. One of the aspects of studying digitalization is the analysis of its impact on sustainable development. The article examines the relationship between the digital economy and sustainable development, as well as strategies and opportunities that can contribute to achieving the goals of sustainable development. The digital economy, thanks to its innovations and technologies, can make a significant contribution to sustainable development, but this requires the development and implementation of appropriate strategies: bridging the gap, Increasing efficiency, optimizing resource management, separating economic growth from environmental impact, expanding "green" opportunities practices, fighting illegal activities, Inclusive growth and increasing resilience, bridging the digital divide, empowering local communities, increasing resilience to climate change, encouraging sustainable innovation, promoting global cooperation. The impact of digital technologies on the economy and sustainable development is considered. The question of how to ensure a balance between economic development and preservation of the environment and social values in the conditions of digital transformation is being investigated. The growing relationship between digitalization and sustainable development processes has been revealed. The presence of environmental risks of digitalization is considered. An analysis of the impact of end-to-end digital technologies on the process of achieving 17 sustainable development goals, which are provided for by the Sustainable Development Agenda for the period up to 2030, adopted by the UN, has been carried out. It is substantiated that these goals provide the most comprehensive approach to assessing the achievement of sustainable development of the world economy. The classification of the impact of digitalization on the sustainable development of the economy is provided, which consists in the formalization of the possibilities and limitations of digitalization in the paradigm of achieving sustainable development. The Legatum Prosperity Index was studied in order to assess the dynamics of sustainable development and digitalization of Ukraine over the past 5 years (2019–2023).