Service Requirements Research Articles

Secrecy-Constrained UAV-Mounted RIS-Assisted ISAC Networks: Position Optimization and Power Beamforming

This paper investigates secrecy solutions for integrated sensing and communication (ISAC) systems, leveraging the combination of a reflecting intelligent surface (RIS) and an unmanned aerial vehicle (UAV) to introduce new degrees of freedom for enhanced system performance. Specifically, we propose a secure ISAC system supported by a UAV-mounted RIS, where an ISAC base station (BS) facilitates secure multi-user communication while simultaneously detecting potentially malicious radar targets. Our goal is to improve parameter estimation performance, measured by the Cramér–Rao bound (CRB), by jointly optimizing the UAV position, transmit beamforming, and RIS beamforming, subject to constraints including the UAV flight area, communication users’ quality of service (QoS) requirements, secure transmission demands, power budget, and RIS reflecting coefficient limits. To address this non-convex, multivariate, and coupled problem, we decompose it into three subproblems, which are solved iteratively using particle swarm optimization (PSO), semi-definite relaxation (SDR), majorization–minimization (MM), and alternating direction method of multipliers (ADMM) algorithms. Our numerical results validate the effectiveness of the proposed scheme and demonstrate the potential of employing UAV-mounted RIS in ISAC systems to enhance radar sensing capabilities.

User requirements for research data management services in Myanmar university libraries: A case study of the University of Yangon Library

University libraries in Myanmar are developing research data management services (RDMS) to support and boost the country's research and development. This paper reports on a research study that aims to identify and understand user requirements for RDMS. The University of Yangon Library (UYL) was selected as the research case, and 40 faculty members, research students, and library workers were approached and interviewed. The analysis of interview data adopted a thematic approach and used two analytic tools: coding for tagging and interpreting data; and concept map for visualising and demonstrating the progress of analysis. The analysis discerned 12 RDMS requirements in four theoretical themes: research data management planning, research data collection, research data processing and analysis, and research data preservation and sharing. Moreover, the analysis indicated that, to support the development of RDMS, libraries should enact three different roles, namely, participative role, educational and consultative role, and facilitative role. Also, practical implications were drawn from the analysis and suggested a three-stage action plan for RDMS development at the case library. Although this study focuses on libraries in Myanmar universities, the findings provide useful insights and implications for university libraries in other countries.

Performance of Cunninghamia lanceolata / Uncaria composite particleboard

Particleboards were prepared with thinning wood of Cunninghamia lanceolata (Chinese fir) and wood shavings of waste Uncaria sinensis branches by using melamine-urea-formaldehyde resin as the adhesive. Influences of particle mass ratio of C. lanceolata to Uncaria, adhesive loading, and target density on internal bonding strength (IB), modulus of rupture (MOR), modulus of elasticity (MOE), thickness swelling rate of water absorption (TS), and water absorption (WA) of the composite particleboard were investigated. Results showed that: (1) IB, MOR, MOE, 2h-TS, and 2h-WA of pure C. lanceolata particleboard met service requirements of type-P2 furniture particleboard of GB/T 4897-2015. (2) With the increase of Uncaria particles, IB of composite particleboard decreased gradually, while MOR, MOE, TS, and WA first increased and then decreased. The best comprehensive performances were achieved when the mass ratio of C. lanceolata to Uncaria was 75:25, manifested by 1.5 MPa of IB, 21.3 MPa of MOR, 2140 MPa of MOE, 2.4% of 2h-TS and 12.3% of 2h-WA. These performances basically meet the service requirements on type-P3 of the standard. (3) It can make C. lanceolata fir/Uncaria particleboard meet requirements on type-P4 heavy-load particleboard of the standard by increasing target density and adhesive loading appropriately. (4) The C. lanceolata/Uncaria composite particleboard showed higher thermostability and fire resistance.

Infrastructure-as-Code for 5G RAN, Core and SBI Deployment: A comprehensive review

The advent of 5G technology marks a significant transformation in the telecommunications landscape, promising to deliver ultra-fast data speeds, minimal latency, and widespread connectivity that supports many new services and applications, including IoT, augmented reality, and autonomous systems. However, achieving the full potential of 5G networks involves overcoming substantial infrastructure challenges. Deploying and managing 5G's intricate architecture, encompassing the Radio Access Network (RAN), Core network, and Service-Based Interfaces (SBI)—requires a shift from traditional, labor-intensive methods to more advanced, automated processes. Infrastructure-as-Code (IaC) has emerged as a game-changing methodology that addresses these needs by codifying infrastructure setup and management into programmable scripts. This comprehensive review delves into how IaC facilitates the efficient deployment and management of 5G components, enhancing agility, consistency, and scalability. By automating resource provisioning, configuration, and updates, IaC empowers network operators to rapidly deploy infrastructure that meets the demanding requirements of 5G services. The paper discusses how IaC enables seamless integration and scaling of network functions, improves operational efficiency through reduced human error, and supports consistent infrastructure management across distributed environments. Key tools such as Terraform, Ansible, and Kubernetes are explored, showcasing their applications in orchestrating various layers of the 5G network, from RAN deployment to core network orchestration and SBI configurations. Despite its advantages, adopting IaC in 5G deployment comes with its challenges. These include managing the complexities inherent in multi-vendor environments, ensuring robust security for automated provisioning scripts, and maintaining compliance with regional regulatory standards. The paper explores these obstacles in-depth, offering insights into best practices and potential solutions to navigate these hurdles. This review highlights emerging trends and research opportunities, such as the potential for zero-touch automation, which leverages IaC for autonomous network operations with minimal human intervention. It also discusses the role of artificial intelligence (AI) and machine learning (ML) in predictive resource management and automated fault detection, proposing a future where AI-enhanced IaC can revolutionize the deployment and operation of 5G networks. By examining these elements, the review aims to provide a holistic view of the current state and future trajectory of IaC in 5G RAN, Core, and SBI deployment, setting the stage for ongoing innovation and development in the field.

Vehicular Ad-Hoc Networks for Intelligent Transportation System: A Brief Review of Protocols, Challenges, and Future Research

Vehicular Ad Hoc Networks (VANET) play an essential role in the advancement of intelligent transportation systems, facilitating real-time communication between vehicles (V2V), infrastructure (V2I), and surrounding environments (V2X). This systematic review analyzes a range of VANET routing protocols, highlighting the strengths and weaknesses of topology-based, position-based, cluster-based, and hybrid methods. Additionally, this review explores core challenges in VANET, including high mobility, data security, Quality of Service (QoS) requirements, and connectivity issues in dynamic and high-density traffic environments. The paper also provides insights into simulation tools and performance metrics employed in VANET research alongside practical applications in modern transportation systems, such as autonomous driving, traffic management, and safety-related communication. Furthermore, this review emphasizes the need for ongoing research to address the identified challenges and optimize VANET performance. Integrating emerging technologies, including 5G, artificial intelligence (AI), and edge computing, offers promising avenues for enhancing system efficiency and sustainability. This review establishes a comprehensive foundation for further advancements in VANET by highlighting key findings and research gaps. Ultimately, the effective implementation of VANET has the potential to significantly improve transportation safety, efficiency, and sustainability, contributing to the realization of smart city initiatives and innovative mobility solutions. This work aims to guide future research directions, ensuring that VANET continues to evolve in alignment with the demands of modern transportation systems and the broader context of intelligent mobility.

Принципы государственной службы в решениях Конституционного Суда Российской Федерации

Today, we can safely say that the state civil service is one of the most important institutions that ensures the implementation of public administration within the system of administrative and legal regulation. In modern realities, the requirements for the state civil service are constantly supplemented and improved. The essence of the state civil service is revealed through its principles. Despite the fact that a single approach to defining the principles of public service has not been adopted for the entire long history of the existence of the institution of public service, nevertheless, their key importance for the implementation of the institution of public service, as a rule, does not raise objections and even more so doubts. In this paper, we have considered several examples of scientific understanding of the principles of public service, and concluded that there is both scientific and normative content of the principles of public service. For many years, the entire system of public administration has been subject to reform. Despite the fact that the basic Federal Law "On the State Civil Service of the Russian Federation" has been in force for exactly 20 years, it is regularly amended. In recent years, a large number of by-laws have been adopted regulating the procedure for organizing and passing the state civil service. The state civil service primarily contributes to ensuring the foundations of the constitutional system and compliance with the Constitution of the Russian Federation, as well as the practical implementation of federal legislation and laws of the subjects of the Russian Federation. Constitutional and legal regulation determines the further development of legal regulation of all spheres of our life. It is the constitutional and legal foundations of the state service that allow us to understand the main directions of legal support for the state service. In this work, we came to the conclusion that we have been paying unreasonably little scientific attention to studying the implementation of the principles of state service in judicial practice. In this regard, it is important to analyze the legal positions of the Constitutional Court of the Russian Federation on issues of implementing the principles of state service.

Exploring the prospects of services-led development for the Philippines

The growing importance of the services sector has prompted an examination of possible pathways to maximize its impact, particularly on the quality of economic growth. Some emphasize promoting job creation and exports in the sector, in addition to ensuring that the services requirements of the rest of the economy are met. Others argue that the potential for services-led development depends on being able to replicate the features of industrialization by leveraging trade, technology, training, and targeting. There are also proponents of more active strategies on the demand side of labor markets. This paper discusses the interrelated issues the country must address in pursuing economic transformation through services. Priority actions include boosting productivity, expanding services outside the National Capital Region, implementing structural reform, strengthening exports of digital services, accelerating digitalization, and increasing innovation. For the Philippines, harnessing services to achieve broad-based and inclusive growth should be the essence of services-led development.

Clinical pharmacy interventions in an Austrian hospital: a report highlights the need for the implementation of clinical pharmacy services

BackgroundClinical pharmacy services face challenges in Austria due to limited implementation and acceptance, outdated legislation and a lack of guidelines and training, despite the evidence from global studies of the...

A Modified Multiaxial Fatigue Model and Its Application for the Fatigue Life Prediction of Aircraft Hydraulic Pipes.

The fatigue failure of a structure may occur under a multiaxial vibration environment; it is necessary to establish a better multiaxial fatigue life prediction model to predict the fatigue life of the structure. This study proposes a new model (MWYT) by introducing the maximum absolute shear stress into the WYT model. The feasibility of the MWYT model is verified by using the multiaxial fatigue experimental data of 304 stainless steel, Q235B steel, 7075-T651 aluminum alloy and S355J0 steel. Further, finite element vibration simulations are performed on a typical parallel hydraulic pipe structure, and the vibration simulation results of the pipe structure are verified through the vibration experiment. Finally, the MWYT model is used to predict the fatigue lives of the pipe structure under random excitation and pulsation excitation, respectively, and the fatigue life of the pipe structure under the combined loading from random excitation and pulsation excitation is predicted based on Miner's rule. By comparing with the design life of the aircraft, the predicted life of the pipe structure meets the service requirements for it.

Effective Strategic Management of Kyrgyzstan Universities Through Monitoring and Quality Assurance Systems

In the context of globalization and changing requirements for formal services, the Kyrgyz Republic is faced with the need for a progressive university management system. This article analyzes the role of the monitoring system and quality assurance in increasing the competitiveness of universities, which ensures sustainable development and adaptation to the international standard. It is shown that the use of tools allows you to track the weaknesses of the educational process, make strategic decisions, and improve academic reputation. Special attention is paid to using the experience of universities in Kyrgyzstan and countries such as Uzbekistan and Kazakhstan, which helps to identify approaches for implementing effective strategies in the post-Soviet educational space.

Reliability Assessment of Cracked Reinforced Concrete Slab and Verification using a Full-Scale in-Situ Load Test

This paper presents a case study focused on the deterministic and probabilistic structural assessments of a cracked reinforced concrete (RC) slab and evaluation using in-situ load testing. The case study explores the practical application of in-situ load testing as a diagnostic tool for evaluating the condition of the slab and determining its ultimate load-carrying capacity in the presence of cracks, and service loads are used to verify its serviceability. Through comprehensive analysis and interpretation of test results, this study aims to provide valuable insights into the structural performance of cracked reinforced concrete slabs and inform effective repair and rehabilitation strategies. The building under examination is a G+4 reinforced concrete structure constructed using ready mix concrete transported to the construction site. Upon inspecting the slab, which had a total thickness of 170 mm, numerous deeply mapped cracks were evident, visible from the slab's surface and extending through its entire depth. Structural analysis indicated that the design included sufficient reinforcement and that the loads acting upon the slab were not expected to induce the cracking. Factors such as poor construction practices, potential issues with the cement used, and excessive evaporation may have contributed to the occurrence of these cracks, necessitating repairs. A full-scale in-situ load test was performed following ACI 318-08 testing procedures and results show that the slab under investigation is reasonably safe against serviceability and strength requirements with “no evidence” of failure.

Energy-Efficient Cooperative Transmission in Ultra-Dense Millimeter-Wave Network: Multi-Agent Q-Learning Approach.

In beyond fifth-generation networks, millimeter wave (mmWave) is considered a promising technology that can offer high data rates. However, due to inter-cell interference at cell boundaries, it is difficult to achieve a high signal-to-interference-plus-noise ratio (SINR) among users in an ultra-dense mmWave network environment (UDmN). In this paper, we solve this problem with the cooperative transmission technique to provide high SINR to users. Using coordinated multi-point transmission (CoMP) with the joint transmission (JT) strategy as a cooperation diversity technique can provide users with higher data rates through multiple desired signals. Nonetheless, cooperative transmissions between multiple base stations (BSs) lead to increased energy consumption. Therefore, we propose a multi-agent Q-learning-based power control scheme in UDmN. To satisfy the quality of service (QoS) requirements of users and decrease the energy consumption of networks, we define a reward function while considering the outage and energy efficiency of each BS. The results show that our scheme can achieve optimal transmission power and significantly improved network energy efficiency compared with conventional algorithms such as no transmit power control and random control. Additionally, we validate that leveraging channel state information to determine the participation of each BS in power control contributes to enhanced overall performance.

MAARS: Multiagent Actor-Critic Approach for Resource Allocation and Network Slicing in Multiaccess Edge Computing.

This paper presents a novel algorithm to address resource allocation and network-slicing challenges in multiaccess edge computing (MEC) networks. Network slicing divides a physical network into virtual slices, each tailored to efficiently allocate resources and meet diverse service requirements. To maximize the completion rate of user-computing tasks within these slices, the problem is decomposed into two subproblems: efficient core-to-edge slicing (ECS) and autonomous resource slicing (ARS). ECS facilitates collaborative resource distribution through cooperation among edge servers, while ARS dynamically manages resources based on real-time network conditions. The proposed solution, a multiagent actor-critic resource scheduling (MAARS) algorithm, employs a reinforcement learning framework. Specifically, MAARS utilizes a multiagent deep deterministic policy gradient (MADDPG) for efficient resource distribution in ECS and a soft actor-critic (SAC) technique for robust real-time resource management in ARS. Simulation results demonstrate that MAARS outperforms benchmark algorithms, including heuristic-based, DQN-based, and A2C-based methods, in terms of task completion rates, resource utilization, and convergence speed. Thus, this study offers a scalable and efficient framework for resource optimization and network slicing in MEC networks, providing practical benefits for real-world deployments and setting a new performance benchmark in dynamic environments.

A Mobility Handover Decision Method Based on Multi-Topology

With the emergence of new applications in mobile networks, users demand higher network stability and lower data transmission delays. When the network address of a mobile user changes, the data transmission path in the wired network may need to be switched to maintain service continuity. Traditional mobility support methods typically rely on a single switching path for all mobile data flows. However, if this path cannot meet the requirements of all the flows, it may lead to network congestion or a decline in user experience. To overcome this limitation, this paper proposes a mobility handover decision method based on multi-topology. It enables the dynamic allocation of mobile data flows across different switching paths within multiple logical topologies. The method models a multi-topology selection problem aimed at minimizing average packet transmission delay and packet loss rate, while considering network conditions and the Quality of Service (QoS) requirements for each flow. By solving the dual problem of the original optimization, a near-optimal solution is achieved. The proposed scheme and algorithm were implemented and tested using the Mininet network simulator. Results show that the proposed approach achieves low average packet transmission delay, low average packet loss rate, and high throughput, compared to traditional single-path switching methods and existing multipath routing methods.

Application of Task Allocation Algorithms in Multi-UAV Intelligent Transportation Systems: A Critical Review

Unmanned aerial vehicles (UAVs), commonly known as drones, are being seen as the most promising type of autonomous vehicles in the context of intelligent transportation system (ITS) technology. A key enabling factor for the current development of ITS technology based on autonomous vehicles is the task allocation architecture. This approach allows tasks to be efficiently assigned to robots of a multi-agent system, taking into account both the robots’ capabilities and service requirements. Consequently, this study provides an overview of the application of drones in ITSs, focusing on the applications of task allocation algorithms for UAV networks. Currently, there are different types of algorithms that are employed for task allocation in drone-based intelligent transportation systems, including market-based approaches, game-theory-based algorithms, optimization-based algorithms, machine learning techniques, and other hybrid methodologies. This paper offers a comprehensive literature review of how such approaches are being utilized to optimize the allocation of tasks in UAV-based ITSs. The main characteristics, constraints, and limitations are detailed to highlight their advantages, current achievements, and applicability to different types of UAV-based ITSs. Current research trends in this field as well as gaps in the literature are also thoughtfully discussed.

Expanding options to recruit, grow, and retain the public health workforce.

The public health workforce continues to atrophy due to mass and early retirement, under-funding, slow hiring processes, lack of advancement opportunities, and shifting policies. Organizational research into workforce sustainability is crucial for ensuring a robust, diverse staff capable of delivering essential public health services. We examined career ladders, a potential solution to workforce challenges, through interviews with 10 health departments (HDs) across seven states. Interview participants were recruited from HDs using or planning career ladders held administrative positions, and had a role in the hiring process. Many health department positions have traditionally included steps within certain job classifications that promote pay adjustments with increasing years of service. Career ladder approaches, however, specifically focus on providing opportunities for health continuing education, leadership development, or movement into formal leadership roles. Findings indicate that HDs have begun utilizing career ladders for professional development and critical role maintenance. Career ladders have been applied mostly for retention with limited impact on recruitment and increasing staff diversity. Challenges include civil service requirements, funding limitations, and complex recruitment that might exclude diverse candidates. This study emphasizes the importance of transparent development, engaging front-line staff, offering advancement pathways, and providing insights to enhance workforce recruitment and retention.

Can TDABC (Time-Driven Activity-Based Costing) help the NOVO hospital's medical biology laboratory to value the appropriate prescription? - Role of the biologist in reducing healthcare costs

The relevant and correct prescribing of medical biology is a major public health issue. Correct prescribing is a legal obligation under article L6211-8 of the French Public Health Code and is an integral part of the biologist's daily work, already specified in the 2012 (section 4.7) and 2022 (section 5.3.3) versions of the NF EN ISO 15189 standard. COFRAC document SH REF 02 v08 specifies the requirements for consultancy services. The adaptation of the prescriptions is a revision of the contract with the prescriber, which makes it possible to optimize patient care and ensure the satisfaction of the laboratory users. Although essential, accurate prescribing is time consuming. "Chronophage" is the term that has been used for almost a decade. At present, the work of biologists in this area is not valued. In fact, there is no evaluation system to highlight this regulation control activity. To date, no work has been published to estimate this time, this chronophagy, and to evaluate its impact. Cost measurement using Time-Driven Activity-Based Costing (TDABC), a variant of Activity-Based Costing (ABC), is based on a process approach. The main contribution of TDABC is that it uses a single cost driver: time. Serum immunofixation is a test used to confirm and monitor plasma cell dyscrasias, the archetype of which is multiple myeloma. The learned societies and the IMWG provide explicit diagnostic criteria, but the guidelines do not address the frequency of follow-up. In particular, the frequency of repeat and follow-up serum immunofixation remains unaddressed from an evidence-based medicine perspective. This work has made it possible to highlight the savings made between 1st January and 31th August 2023 thanks to the involvement of the biologist and to highlight his essential role in the process of controlling the overall expenditure (reagents, human resources, time and money) in the specialized biochemistry sector (bench: proteins) and to strengthen the role of the biologist within the institution. The various players in the healthcare sector - prescribing physicians, biologists, hospital administrators and, last but not least, patients - all have an essential role to play in maximizing value for patients and in the healthcare economy.

Research on the Construction of Internal Control Systems in Public Hospitals Under the New Situation

With the continuous reform of China’s medical system, people’s health needs are also rising, so people have higher requirements for public medical services. At present, the economic business activities and asset management of public hospitals are becoming increasingly complicated, and the pressure of operation management is increasing. It has promoted the hospital to optimize the allocation of resource allocation and improve the operating efficiency. The management model has changed from extensive to refined, promoting the sustainable development of public hospitals. This article first starts with the development status and significance of the construction of the internal control system of the public hospital, and then sorts out the internal control of existing problems in the public hospital. The article proposes the content and efforts of the construction of an internal control system for existing problems. In the process, ideas for improvement were proposed. It is hoped that through the improvement of the management level of the hospital’s internal control system, in a changing market environment, it will better meet the needs of patients and contribute to the healthy and sustainable development of medical institutions.

Cloud‐Edge Collaboration‐Based Multi‐Cluster System for Space‐Ground Integrated Network

ABSTRACTAs global informationization deepens, the importance of Space‐Ground Integrated Network (SGIN) as a new network architecture becomes increasingly prominent. SGIN combines the advantages of ground and space networks, enabling global information interconnection and sharing through various communication means such as satellites, drones, and ground stations. However, due to its complex network environment and diverse communication requirements, traditional network architectures struggle to meet its demands for efficiency, stability, and scalability. To address these challenges, we focus on the research, design, and implementation of a cloud‐edge collaboration‐based multi‐cluster system for SGIN. The goal is to construct an efficient, stable, and scalable network system capable of providing seamless global coverage and efficient communication within SGIN. We design a multi‐cluster system architecture based on container technology, leveraging cloud and edge computing techniques for dynamic resource allocation and efficient utilization. This architecture aims to meet the diverse network service requirements of ground terminals, enhancing responsiveness, efficiency, resilience, and reliability of network services. Additionally, we introduce a multipath data transmission mechanism to support the transfer of large‐scale data, such as remote sensing images. A simulation platform tailored for SGIN is developed, demonstrating the feasibility of the multi‐cluster system and the effectiveness of multipath data transmission.

Optimizing 5G network slicing with DRL: Balancing eMBB, URLLC, and mMTC with OMA, NOMA, and RSMA

The advent of 5th Generation (5G) networks has introduced the strategy of network slicing as a paradigm shift, enabling the provision of services with distinct Quality of Service (QoS) requirements. The 5th Generation New Radio (5G NR) standard complies with the use cases Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), which demand a dynamic adaptation of network slicing to meet the diverse traffic needs. This dynamic adaptation presents both a critical challenge and a significant opportunity to improve 5G network efficiency. This paper proposes a Deep Reinforcement Learning (DRL) agent that performs dynamic resource allocation in 5G wireless network slicing according to traffic requirements of the 5G use cases within two scenarios: eMBB with URLLC and eMBB with mMTC. The DRL agent evaluates the performance of different decoding schemes such as Orthogonal Multiple Access (OMA), Non-Orthogonal Multiple Access (NOMA), and Rate Splitting Multiple Access (RSMA) and applies the best decoding scheme in these scenarios under different network conditions. The DRL agent has been tested to maximize the sum rate in scenario eMBB with URLLC and to maximize the number of successfully decoded devices in scenario eMBB with mMTC, both with different combinations of number of devices, power gains and number of allocated frequencies. The results show that the DRL agent dynamically chooses the best decoding scheme and presents an efficiency in maximizing the sum rate and the decoded devices between 84% and 100% for both scenarios evaluated.