Adaptive Resource Research Articles

Real-Time Adaptive Partition and Resource Allocation for Multi-User End-Cloud Inference Collaboration in Mobile Environment

Real-Time Adaptive Partition and Resource Allocation for Multi-User End-Cloud Inference Collaboration in Mobile Environment

Parental warmth in mother-child dyads and children’s emotional adjustment during secondary-school transition: a longitudinal investigation on bidirectional relationships

AbstractThe transition from primary to secondary school affects children’s psychological functioning, necessitating resources for (post-)transition adaptation. Maternal warmth serves as a valuable resource, buffering against negative transition effects on emotional adjustment. Nevertheless, little is understood about the bidirectional effects of (divergent) mother-child reports on emotional adjustment during the transition to secondary school. Data from 2101 German children (48.8% female, Mage T1 = 8.57, SDage = 0.58) and their mothers (Mage T1 = 36.28, SDage = 4.49) from the pairfam panel, collected over seven annual waves from the children’s 3rd to 9th grades, were used. Random intercept cross-lagged panel models were employed to examine within-family cross-lagged effects. The findings suggest that early in the transition to secondary school, low levels of maternal warmth and heightened emotional problems in children tend to co-occur and mutually reinforce each other over time. However, discrepancies in perceptions between mothers and children appear to have positive normative consequences rather than enduring negative impacts on children, particularly before the transition to secondary school. The results are discussed considering the progressing school transition, with additional developmental changes, such as puberty, potentially leading to changes in perceived and actual maternal warmth and emotional problems in children.

Adaptive Dual-Layer Resource Allocation for Maximizing Spectral Efficiency in 5G Using Hybrid NOMA-RSMA Techniques

The unprecedented growth in data demands for 5G communication systems necessitates advanced techniques to maximize spectral efficiency while ensuring user fairness and low latency. This study proposes Adaptive Dual-Layer Resource Allocation (ADLRA), a novel hybrid technique combining Non-Orthogonal Multiple Access (NOMA) and Rate-Splitting Multiple Access (RSMA). The ADLRA framework introduces dynamic user pairing, hierarchical beamforming, and adaptive power and rate allocation strategies to optimize resource utilization. Key features include dynamic user pairing, leveraging machine learning algorithms for efficient group formation based on channel conditions, and hierarchical beamforming, which prioritizes high-priority users in the NOMA layer while effectively managing shared resources in the RSMA layer. Interference mitigation is achieved through spatial filtering and multi-user diversity techniques, ensuring minimal intra-cell and inter-cell interference. Simulation results demonstrate significant performance gains Spectral efficiency improved by 32%, compared to traditional NOMA. Latency reduced by 18%, ensuring seamless communication for ultra-reliable low-latency applications. Achieved a 94% fairness index, reflecting equitable resource allocation among users. Enhanced throughput, with an average gain of 28%, compared to RSMA-only systems. These results highlight the potential of ADLRA to meet the stringent requirements of next-generation 5G systems, offering a scalable and efficient solution for diverse communication scenarios. The proposed method sets a foundation for future hybrid access strategies in wireless communication networks.

International Climate Migrant Policy and Estimates of Climate Migration

International Climate Migrant Policy and Estimates of Climate Migration

Survey of the Importance of Using Basic Biomedical Science Lecture Guidebooks Containing Personality Types for Health Faculty Students

In higher education, especially in the health sector, a deep understanding of the course material is the key to academic success. In improving the quality of student learning, the use of teaching materials is essential to achieve competency targets. However, each student has a different personality so that their learning style type is different. Based on this, it is necessary to develop more adaptive learning resources that not only include scientific materials, but also pay attention to the different personality types of students. This study aims to explore the importance of using basic biomedical science lecture guidebooks that are tailored to the personality types of students at the Faculty of Health. This research method uses a descriptive survey approach with a purposive sampling technique. A survey was conducted on a number of students to assess the effectiveness and needs of guidebooks designed based on personality types. The survey results showed that most students felt helped by the existence of guides that were in accordance with their learning characteristics, which ultimately improved understanding and academic achievement. It can be concluded that personalized teaching materials according to student personality are useful and needed in the learning process.

Intersectionality shapes the access to various adaptive resources in climate-vulnerable contexts

Abstract Intersectional approaches are becoming essential to understanding the differential impacts of climate change and the heterogeneity of adaptive capacities. Varying factors of social and economic privileges and inequalities synergistically shape the local power structure, ultimately determining disproportionality and unequal access to adaptive resources. Using empirical data from coastal Bangladesh, which is part of the Ganges Delta, and one of the world’s -most climate-vulnerable regions, this study shows how religion, gender, and ethnicity intersect with patterns in (i) farm and non-farm incomes, (ii) land conflicts, (iii) the size of farms, and (iv) access to critical sources of weather information. The study highlights that multilayered identity, which is shaped by various structural determinants, including local power structure, can determine gendered dimensions of access to various adaptation resources. It also shows that if policymakers and development partners partially understand or do not understand the complex landscape of local vulnerability or unequal power structures including the adaptive capacity of the vulnerable populations, they would not be able to provide critical support in times of crisis. The concept of intersectionality is therefore critical in addressing adaptation and risk management challenges for regions like the Ganges Delta and other parts of the world, where people are struggling with similar social and environmental challenges.

Human Resource Planning Strategy to Improve the Quality of Online Library Management Information Systems (E-Libraries) of Higher Education in the Industrial Era 5.0

Library management information systems in universities are essential for managing e-libraries in universities. The world of education will face one of the challenges after 2030: the use of information technology or robotics in various sectors of human life, one of which is university libraries. This research was conducted using a literature approach by collecting data from various relevant theoretical sources about human resource management and higher education management information systems in the context of university library human resource planning strategies. This article delves into the practical application of library human resource planning strategies in universities. It discusses the formulation of university library human resource planning and the development of human resources in the era of Society 5.0. Furthermore, it explores the challenges and opportunities in implementing these strategies, such as change management, adaptive higher education management information system policies, and the development of librarians' professionalism in the era of society 5.0. This study uses a literature approach by collecting data from relevant theoretical sources about library human resource management and higher education management information systems in the educational context of university library human resource planning strategies. Data is analyzed through systematic literature synthesis to identify university library human resource planning strategies that can improve the quality of management e-library in the era of Society 5.0. In this era, adaptive and technology-oriented human resource management strategies are the key to improving the quality of university e-library management.

PASE: Pro-active Service Embedding in The Mobile Edge

Mobile edge computing offers ultra-low latency, high bandwidth, and high reliability. Thus, it can support a plethora of emerging services that can be placed in close proximity to the user. One of the fundamental problems in this context is maximizing the benefit from the placement of networked services, while meeting bandwidth and latency constraints. In this study, we propose an adaptive and predictive resource allocation strategy for virtual-network function placement comprising services at the mobile edge. Our study focuses on maximizing the service provider’s benefit under user mobility, i.e., uncertainty. This problem is NP-hard. Therefore, we propose a heuristic solution: we exploit local knowledge about the likely movements of users to speculatively allocate service functions. We allow the service functions to be allocated at different edge nodes, as long as latency and bandwidth constraints are met. We evaluate our proposal against a theoretically optimal algorithm as well as against recent previous work, using widely used simulation tools. Through an extensive simulation study, we demonstrate that under realistic scenarios, an adaptive and proactive strategy coupled with flexible placement can achieve close-to-optimal benefit.

Dynamics of life satisfaction of students of higher education during war

Introduction. Analysis of changes in mental health components as well as the development of organizational culture models of personal support in difficult life situations are serious challenges faced by psychologists. Aim: to empirically investigate the dynamics of life satisfaction of higher education students during war and establish its correlates. Methods. A comparative and correlational research strategy was used in the empirical study. The psychodiagnostic instruments included: Life Satisfaction Scale (SWLS), Posttraumatic Growth Scale (PTGI), Hospital Anxiety and Depression Scale (HADS). The comparison of quantitative data was done in percentage terms and the Pearson method was used to establish the relationship. Results. The dynamics of students' life satisfaction reflected the non-linear process of their personal adaptation to life in war conditions. A significant number of students assessed their life as unfavorable and needed better resources. There was a statistical relationship between students' life satisfaction and their feeling of support during their studies as well as students' psycho-emotional stability and ability for spiritual growth. Conclusions. The obtained results make it possible to develop war-sensitive psychological support strategies for students' adaptive resources.

Performance Optimization in Distributed SQL Environments : A Comprehensive Analysis of Presto Query Engine

This comprehensive article examines performance optimization techniques for Presto, a distributed SQL query engine widely adopted for large-scale data analytics. Through systematic analysis of both theoretical frameworks and empirical evidence, we present a multifaceted approach to enhancing query performance and resource utilization. The article encompasses critical aspects including memory management strategies, parallel processing optimization, and storage connector configurations across diverse deployment scenarios. Our investigation reveals that strategic implementation of query planning algorithms, coupled with fine-tuned JVM configurations, can yield performance improvements of up to 40% in complex analytical workloads. The article also introduces a novel framework for workload-specific optimization patterns, validated through extensive testing across various data scales and query complexities. Through detailed case studies of large-scale deployments, we demonstrate how combined optimization techniques can significantly reduce query latency while maintaining system stability. Furthermore, we present empirical evidence supporting the effectiveness of adaptive resource allocation strategies in mixed-workload environments. These findings contribute to the growing body of knowledge in distributed query processing optimization and provide practical guidelines for organizations seeking to enhance their Presto deployments.

Thriving, not just surviving: Using positive psychology to build psychological wellbeing in pre-tertiary students

The significance of psychological wellbeing for student success is under-investigated, particularly for pre-tertiary Enabling students (those traditionally under-represented in higher education). Positive Psychology Interventions (PPIs) have proven effective in enhancing wellbeing but are rarely integrated into university courses. This study explored a PPI, Be Positive, a 12-week program, designed to teach students strategies and techniques to help them re-frame their thinking about themselves and their academic pursuits. The program was evaluated with 37 Enabling students who completed weekly wellbeing questionnaires alongside self-reports about their study-related wellbeing. Results indicated fluctuating but generally positive levels of wellbeing throughout the program, with the highest levels recorded in the final weeks. A significant number of participants (79%) reported positive wellbeing by the program end, contrasting typical declines in student wellbeing during university terms. Thematic analysis of student reflections on how the program supported their wellbeing identified four key areas: affective balance, adaptive psychological resources, self-regulation, and positive implications for both academic and personal life. The findings suggest that PPIs like Be Positive can offer a proactive approach to mental health, equipping students with tools for resilience and emotional regulation, thereby enhancing wellbeing and potentially subsequent academic performance.

An interactive and adaptive learning resource for teaching first-year human anatomy

Anatomy is a particularly challenging unit in many first-year university courses, however adaptive learning resources provide an opportunity to engage students in practical-based units such as anatomy. Here, the impact on student engagement, student learning and exam preparedness of implementing 21 interactive online adaptive lessons was evaluated. A total of 276 first-year students, enrolled in allied health undergraduate degrees from 2016 to 2020, consented to participate in this mixed methods study. Our findings suggest a positive correlation between the number of lessons a student completed and a positive performance in each of the three assessment items in the unit (p<0.05). We also identify an increase in students perceived understanding of anatomy after completing the lesson (p<0.0001). Students worldwide appreciate individualised, flexible and engaging nature of learning technologies. Here, we evidence that students appreciated online adaptive lessons to learn anatomy and exhibited a high level of satisfaction.

Improving access to undergraduate research using digitized natural history collections course‐based research experiences

AbstractCourse‐based undergraduate research experiences (CUREs) can be a powerful tool in broadening participation in undergraduate research. In this paper, we review the benefits of and barriers to undergraduate research experiences and explore how CUREs can mitigate some of those issues. As a part of the NSF‐supported Biological Collections in Ecology and Evolution Network (BCEENET) activities, a series of network meetings produced a set of recommendations to increase the accessibility of CUREs for all students at all institution types. We use BCEENET CUREs that focus on digitized natural history collections data to illustrate how leveraging adaptable open educational resources that use freely available data and analysis tools can increase accessibility of undergraduate research. We also discuss how inclusive networks of educators and research collaborators can support broadening CURE implementation.

Block-level spatial integration of population density, social vulnerability, and heavy precipitation reveals intensified urban flooding risk

Under the context of global warming and rapid urbanization, cities worldwide confront the pressing problem of urban waterlogging, hindering progress towards Sustainable Development Goals. Effective planning and mitigation of urban flooding require a comprehensive understanding of the spatial and temporal patterns of rainfall and risk heterogeneity. However, evaluating urban water-logging risk is challenged by the need for city-scale hydrological simulation and generally lacks comprehensive metrics integrating fine-scale datasets. To address these gaps, we developed a simulation method for urban flood hazards by integrating hydrological models and Random Forest algorithms. We then took Shenzhen, a megacity in China, as a case study, and investigated the spatial patterns of urban flooding risk and its determinants at the block level based on the risk assessment framework represented by Hazards-Exposure-Vulnerability (H-E-V) dimensions. We found that socio-economic indicators exhibited spatial clustering, while hazard-related indicators displayed more dispersed patterns. High-risk areas exhibited a highly heterogeneous spatial pattern, predominantly influenced by vulnerability and exposure factors, as well as the spatial mismatch among the three dimensions. Our results emphasize the importance of integrating spatial heterogeneity of exposure and vulnerability into climate adaptation resource allocation, addressing both current and future demands for effective climate mitigation.

A Federated Reinforcement Learning Framework via a Committee Mechanism for Resource Management in 5G Networks.

This paper proposes a novel decentralized federated reinforcement learning (DFRL) framework that integrates deep reinforcement learning (DRL) with decentralized federated learning (DFL). The DFRL framework boosts efficient virtual instance scaling in Mobile Edge Computing (MEC) environments for 5G core network automation. It enables multiple MECs to collaboratively optimize resource allocation without centralized data sharing. In this framework, DRL agents in each MEC make local scaling decisions and exchange model parameters with other MECs, rather than sharing raw data. To enhance robustness against malicious server attacks, we employ a committee mechanism that monitors the DFL process and ensures reliable aggregation of local gradients. Extensive simulations were conducted to evaluate the proposed framework, demonstrating its ability to maintain cost-effective resource usage while significantly reducing blocking rates across diverse traffic conditions. Furthermore, the framework demonstrated strong resilience against adversarial MEC nodes, ensuring reliable operation and efficient resource management. These results validate the framework's effectiveness in adaptive and efficient resource management, particularly in dynamic and varied network scenarios.

Scaffolding-informed design of open educational resources in Chinese secondary school mathematics: insights from multi-cycle formative evaluation

In the post-pandemic world, open educational resources (OER) have the potential to ensure educational equity by providing all students with access to learning materials and by supporting teachers’ instructional practices through readily available, adaptable resources. However, the quality of OER continues to be a concern. Therefore, this study explored the use of (1) GeoGebra and scaffolding strategies to develop OER for secondary school mathematics teaching and (2) formative evaluation techniques to enhance the quality of the OER. A GeoGebra expert and a total of 40 frontline teachers participated in three review cycles of the OER development in the project. The feedback from each cycle informed the application of scaffolding strategies in the development of OER for the subsequent cycles. In Cycles 2 and 3, teachers rated the OER and provided feedback through surveys for further improvement. The results indicated that teacher ratings were significantly higher in Cycle 3 (n = 40, Mdn = 5) than in the previous cycle (n = 21, Mdn = 4) regarding the appropriateness of the OER for students with different learning preferences, z = − 2.87, p < 0.05. The results of the project-end satisfaction survey further revealed that all of the teacher participants were satisfied with the OER, which also enhanced their teaching practices. The results of the study offer a theoretical foundation that OER developers can ground upon to enhance their OER design. They also provide practical insights into the application of formative evaluation in the OER development that OER developers can adopt to create resources that are finely attuned to the needs of frontline teachers.

Habitat management decisions for conservation: a conceptual framework

The focus of this selection of papers is the linkage of habitat and population dynamics for the purpose of conservation. We thus provide a general framework for making conservation decisions, emphasizing how knowledge of habitat–population linkages fits into this framework. We begin by describing structured decision-making (SDM) as a general approach to making conservation decisions. SDM requires the development of the following elements: objectives, actions, model(s), monitoring, and decision algorithm. We then describe adaptive resource management (ARM), a specific type of SDM developed for recurrent decisions characterized by potentially resolvable uncertainty. Many different classes of actions can be used to influence animal population dynamics, and modification of habitat is one class of action that is frequently used. Habitat management requires models for predicting responses of the managed system to management actions, and these models are based on our knowledge of habitat–population linkages. Frequently, these models are decomposed into two submodels: one used to predict habitat changes expected to result from management actions and another used to predict population responses to habitat changes. This latter modeling focuses generally on the influence of habitat change on vital rates governing the dynamics of population state variables (variables such as population size or density that describe the status or health of a population). Specific recommendations depend on 1) the vital rates and state variable(s) being considered, 2) the relative spatial scales of animal movement and habitat measurement, and 3) the relative temporal scales of habitat change and vital rate estimation. Finally, we present an example of an ARM program for habitat management, highlighting the role of habitat-linked population modeling in this effort.

Pengaruh Artificial Intelligence dalam Pembuatan Laporan Keuangan

The presence of Artificial Intelligence (AI) has a significant impact on the preparation of financial reports, especially in terms of efficiency and accuracy. This article aims to examine the influence of AI on the process of preparing financial reports that were previously carried out conventionally and the challenges faced by companies in adopting it. This study uses a literature study method to identify trends and findings related to the use of AI in accounting. The results show that AI is able to improve operational efficiency, data analysis, and security, although there are challenges in its implementation, such as human resource adaptation and data security.

An efficient Protocol for Enhanced Flynet Communication in Presence of Partitioning

This paper presents an adaptive fault-tolerant resource allocation protocol tailored for FlyNet, a dynamic aerial network characterized by its mobility and three-dimensional operational space. Addressing the challenges of network partitioning and resource allocation in aerial networks, the proposed algorithm dynamically adjusts to the network's changing topology, ensuring consistent and efficient resource management. Through robust fault tolerance mechanisms, the protocol enhances FlyNet's reliability, maintaining seamless communication and optimal resource utilization even amid node mobility and disruptions. Simulation results demonstrate the algorithm's effectiveness in adapting to dynamic environments, maximizing resource utilization, and minimizing communication delays.

Does Strategy Formulation Process Matter on Human Resource Strategy Outcome?

This article explores the way in which human resource strategies come into being. Using modes of strategy formulation process three hypotheses are established. A cross-sectional research design was adopted. Data was collected using Structure questionnaires while multiple regression analysis was performed to test for a number of hypothesized relationships. Findings shows that rational and adaptive human resource strategy formulation processes explain significant variation in human resource strategy outcome while interactive human resource strategy has no significant relationship with human resource strategy outcome. The contribution of this study to knowledge is that HR strategy formulation process that involves inputs from multiple stake holders has a significant effect on strategy outcome of human resource strategies hence a source of competitive advantage. More importantly, this article found that there is a problem of inability to formulate human resource strategies in the public sector. Therefore the study recommends that State corporations should adopt interactive HR strategy formulation process to facilitate formulation and implementation of HR strategies in their organizations.