Resource Management Approach Research Articles

Using 5G Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System

ABSTRACTThe introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing resource usage, managing mobility, ensuring cost‐efficiency, managing interference, and maximizing spectral efficiency. The fast advancement of artificial intelligence (AI) in several domains yields improved performance in contrast to traditional methods. Hence, including AI in 5G standards would enhance performance by catering to diverse end‐user applications. Initially, we provide an overview of concepts such as Industry 4.0, the 5G standard, and recent developments in the sphere of wireless communications in the future. The goal is to use 5G technology to look at current research problems. We present a new architecture for Industry 4.0 and 5G‐compliant smart healthcare systems. We develop and run the proposed model to investigate the current 5G methods using the Network Simulator (NS2). The results of the simulation show that 5G resource management and interference management approaches already in use face challenges including performance trade‐offs.

A multi-objective indirect neural adaptive processes control design for minimization of energy consumption: An experimental validation on a transesterification reactor

Nowadays, energy management environment is a very important issue that technologies have focused on in order to save costs and minimize energy waste. This objective can be achieved by means of an energy resource management approach through an appropriate optimization technique. However, energy savings can conflict with other objective functions, to solve the problem a multi-objective optimization that considers the minimization of the control energy can be adopted. In this paper, we propose to use a multi-objective indirect neural adaptive control concept for nonlinear systems with unknown dynamics. The control scheme consists of an adaptive instantaneous neural emulator and neural controller built on fully connected real-time recurrent learning networks (RTRL). The multi-objective particle swarm optimization (MOPSO) algorithm is used as a mechanism to find NE and NC adaptive learning rates that optimize the proposed objective functions: control energy minimization and closed-loop preservation. Comparative studies and experimental validation on a semi-batch reactor, used to generate cleaner biofuels, are performed to confirm the effectiveness of the proposed strategy.

CPH-Fmnet: An Optimized Deep Learning Model for Multi-View Stereo and Parameter Extraction in Complex Forest Scenes

The three-dimensional reconstruction of forests is crucial in remote sensing technology, ecological monitoring, and forestry management, as it yields precise forest structure and tree parameters, providing essential data support for forest resource management, evaluation, and sustainable development. Nevertheless, forest 3D reconstruction now encounters obstacles including higher equipment costs, reduced data collection efficiency, and complex data processing. This work introduces a unique deep learning model, CPH-Fmnet, designed to enhance the accuracy and efficiency of 3D reconstruction in intricate forest environments. CPH-Fmnet enhances the FPN Encoder-Decoder Architecture by meticulously incorporating the Channel Attention Mechanism (CA), Path Aggregation Module (PA), and High-Level Feature Selection Module (HFS), alongside the integration of the pre-trained Vision Transformer (ViT), thereby significantly improving the model’s global feature extraction and local detail reconstruction abilities. We selected three representative sample plots in Haidian District, Beijing, China, as the study area and took forest stand sequence photos with an iPhone for the research. Comparative experiments with the conventional SfM + MVS and MVSFormer models, along with comprehensive parameter extraction and ablation studies, substantiated the enhanced efficacy of the proposed CPH-Fmnet model in addressing difficult circumstances such as intricate occlusions, poorly textured areas, and variations in lighting. The test results show that the model does better on a number of evaluation criteria. It has an RMSE of 1.353, an MAE of only 5.1%, an r value of 1.190, and a forest reconstruction rate of 100%, all of which are better than current methods. Furthermore, the model produced a more compact and precise 3D point cloud while accurately determining the properties of the forest trees. The findings indicate that CPH-Fmnet offers an innovative approach for forest resource management and ecological monitoring, characterized by cheap cost, high accuracy, and high efficiency.

Spatio-temporal characteristics of rainfall and drought conditions are using the different drought indices with geospatial approaches in Karnataka state

Karnataka state drought conditions are assessed via drought indices. Over the past several decades, several indices of drought (DI) have been developed and presented, although some of them are region-specific and have problems regarding their applicability to other climatic circumstances. Additionally, choosing the best DI time step to illustrate the drought condition is difficult because of the DIs' various time steps. The study compares the Standardized Precipitation Index (SPI), Statistical Z-Score, China Z-Index (CZI), Rainfall Anomaly Index (RAI), and Rainfall Departure (RD) to determine which one is most appropriate for the districts of the Karnataka state that are prone to both dry and rainy conditions. This study has pointed out that the best drought indices are SPI and RD, and the least accountable drought indice is China Z index. Droughts were most common in 22 districts in 2009, which represent around 70.97% of the state's landmass. In comparison with the rest of the districts, the Ramanagara district noticed the worst drought conditions in 2003, with rainfall reaching 92.47 mm and SPI -3.68, RAI-6.04, MCZI -2.39, and Z score −2.62. Overall, the results of the study will aid in the organization and improvement of drought, flood, agriculture, and water resource management approaches in the state.

Human resources for health: a framework synthesis to put health workers at the centre of healthcare

BackgroundHuman resources are a key determinant for the quality of healthcare and health outcomes. Several human resource management approaches or practices have been proposed and implemented to better understand and...

Impacts of commercial and subsistence fishing on marine and cultural ecosystem services important to the wellbeing of an Indigenous community in Hawai'i

Marine ecosystems provide essential services to coastal residents, particularly for indigenous fishing communities that have strong ties to the environment and obtain multiple benefits from their use and management of ocean spaces. However, understanding of how these are impacted by fisheries, external pressures, and ocean management, remains limited due to a focus on economic valuation and aggregated metrics. This study explores the importance of select marine ecosystem services to the wellbeing of an indigenous community in West Hawaiˈi and the observed impacts on these ecosystem services by commercial and subsistence fishing. We used a mixed-methods approach that combined a workshop with an online survey of community perceptions regarding community important marine resources and cultural values. We find that both fish and non-fish species are important to all four well-being categories, including food security, culture, mental wellbeing, and income, though the least importance was given to the economic value. This study also found that commercial fishing is perceived to have a higher negative impact on marine resources and cultural values than subsistence fishing, but a generally lower impact on non-fish than fish species. The lack of community input into legislation development and a lack of enforcement capacity were perceived to aggravate these further, whereas the integration of place-based knowledge, values and rules of the environment was seen as beneficial to both marine and cultural ecosystem services. Overall, this study shows that non-economic and disaggregated valuation approaches are critical for revealing the variable ecosystem services that marine environments provide to local communities and the importance of more inclusive resource management approaches to manage impacts on these services.

Analysis of the issue of capital / resources management for higher institutions in the light of the problem of high enrolment and low retention rates: A case study of private higher institutions in the UK

Higher education institutions, particularly private higher education institutions in the UK, are facing significant challenges related to capital and resource management, exacerbated by high enrolment rates coupled with low student retention rates. The effective management of financial and physical resources is crucial for sustaining institutional operations and achieving educational objectives. High enrolment places pressure on existing resources, while low retention impacts long-term financial stability and resource allocation. Understanding these issues is essential for developing strategies to balance enrolment and retention while optimizing resource use. This study aims to analyze how private higher institutions in the UK manage their capital and resources in the context of high enrolment and low retention rates. It explores the impact of these challenges on resource management practices and identifies strategies that institutions use to address these issues. The research provides insights into the effectiveness of current resource management approaches and their implications for institutional sustainability and student success. The research employs a mixed-methods approach, combining quantitative and qualitative data. A comprehensive review of institutional financial reports and resource allocation documents provides quantitative data on capital management. Qualitative data is gathered through interviews with key stakeholders, including administrative staff and financial officers from selected private higher institutions. The study also includes surveys of students to understand their experiences and perceptions related to enrolment and retention. Data analysis involves statistical techniques to assess the relationship between resource management practices and enrolment/retention rates, as well as thematic analysis to identify key issues and strategies from qualitative data. The study reveals that private higher institutions in the UK face considerable challenges in managing their capital and resources effectively due to high enrolment and low retention rates. Key findings include that institutions with higher enrolment rates experience increased pressure on financial and physical resources, leading to difficulties in maintaining service quality and infrastructure. Resource allocation strategies focusing on short-term enrolment gains may negatively impact long-term retention efforts. Effective resource management practices, such as targeted financial planning and enhanced support services, are associated with better retention outcomes. Institutions adopting innovative resource management approaches, including technology integration and strategic partnerships, show improved ability to balance enrolment and retention challenges. The findings highlight the need for private higher institutions in the UK to develop more robust capital and resource management strategies to address the dual challenges of high enrolment and low retention rates. Institutions should consider adopting comprehensive financial planning, investing in retention-focused initiatives, and leveraging technology to optimize resource use. Policy recommendations include enhancing funding models to better support resource allocation and encouraging collaboration between institutions to share best practices. By addressing these issues, institutions can improve their financial sustainability and enhance the overall student experience, leading to better educational outcomes and institutional success.

The synergy of debt management, big data technology and corporate decision-making: A catalyst for enhanced financial performance through operational efficiency and sustainable business strategies

This research explores the impact of debt management and big data technology utilization in management decision-making on corporate financial performance with a focus on operational efficiency and sustainable business strategy effectiveness as intervening variables. It aims to delve into how a firm's debt management strategies and its incorporation of big data into decision-making processes influence its financial outcomes. This study scrutinizes the company's approach to managing its debt structure and levels while the use of big data technology in decision-making reflects the integration of advanced technology in strategic planning by examining debt management. The study further investigates how operational efficiency and the effectiveness of sustainable business strategies act as intermediaries in this relationship indicating the role of a firm's internal processes and corporate strategy in driving financial success. Moreover, the research considers mediating variables such as industry type and market competition level which could affect the relationship between the independent and dependent variables. This study aims to test these relationships providing insights into the influence of debt management and big data technology on financial performance using statistical data analysis. Expected outcomes include a deeper understanding of the strategic implications of these factors for achieving sustainable and improved financial performance in a complex business landscape. Emphasizing the importance of efficient debt management and the strategic application of big data technology, the study highlights the necessity for firms to adopt wise financial resource management and innovative decision-making approaches to navigate the challenges of the modern business environment effectively.

Main Characteristics of the Geological Structure of the Evaporite Formation of the Amu Darya Syneclise

The geological structure of the evaporite formation in the Amu Darya syneclise is a complex system that provides valuable insights into the region's geological history and economic potential. The study aims to analyse the main characteristics of the geological structure of the evaporite formation in the Amu Darya syneclise to expand knowledge of the geological and environmental history of the region and to identify the potential of these deposits for various applications. The methods used for this study included geological mapping, mineralogical analysis, stratigraphic analysis and geochemical research. The study identifies three distinct water-bearing horizons within the evaporite complex: Sharaplinsky, Yolotan, and Sakar. These horizons exhibit varying characteristics in terms of composition, water content, and distribution across the basin. Geomorphological manifestations, such as salt lakes and salt marshes, play a crucial role in understanding the ecological and geological history of the region. The evaporite formation holds substantial economic importance, hosting valuable resources including salts, oil, and gas. This geological structure supports regional industrial development, job creation, and overall economic growth. The study also highlights the need for further research into the geology and geomorphology of the Amu Darya syneclise to better understand the formation and dynamics of evaporite deposits and their role in the region’s current environmental and economic sectors. The study emphasizes the need for efficient technologies and methods for resource extraction and management to ensure sustainable development and minimize environmental impact. The research provides crucial data for optimizing mineral extraction strategies and developing effective natural resource management approaches. It underscores the importance of understanding the geological structure for sustainable ecological and economic development in the region. The practical significance of this study is a basis for developing more effective natural resource management strategies based on an understanding of the geological processes of evaporite sedimentation in the Amu Darya syneclise, which is key to the sustainable development of the region’s ecological and economic systems.

Modelling the availability of water, energy, and food resources in transboundary river basins to achieve Sustainable Development Goals 2, 6, and 7

The Water-Energy-Food Nexus (WEFN) has gained international attention as an approach for managing water more holistically, building on the progress made by the Integrated Water Resources Management (IWRM) approach. However, modelling the availability of water, energy, and food and their interconnections is complex, with major barriers that include the availability of both data and modelling platforms capable of assessing the interconnected systems of the WEFN. There have been attempts to model resource availability in each sector generally, but few attempts to consider the WEFN in complex transboundary basins, especially considering Sustainable Development Goals (SDGs). Here, a water, energy, and food availability model was developed using a combination of remotely sensed, national government reported, and global datasets. The model explores the complex interactions between the physical availability and production of water, energy, and food for several subbasins representing different states. Results showed the potential impacts of socioeconomic development, population changes and transboundary cooperation on resources. Transboundary cooperation in the case study Ma Basin in Southeast Asia, under existing resources and operations could improve monthly food security and reduce coal power operations using excess hydropower in the basin during the dry season. These findings show that transboundary cooperation improves access to energy and food, whilst potentially reducing demands for water. Furthermore, the research has highlighted ways in which transboundary cooperation can further assist in attaining SDGs 12 and 13 on responsible production and climate action, respectively. The modelling framework is easily transferable and can support similar analysis in other basins, contributing to global attainment of several SDGs.

Building Green Human Resource Behavior with Integrity: An Islamic Human Resource Management (HRM) Approach

This research aims to explore how the application of Islamic Human Resource Management (HRM) principles can shape human resource behavior that embodies integrity and aligns with Islamic teaching values, while also integrating green HRM practices to promote environmental sustainability. Using a qualitative approach and in-depth literature study, this research analyzes the concept of Islamic HRM, the core values it encompasses, and human resource management practices that are consistent with Islamic principles. Additionally, this study examines the role of green HRM in fostering environmentally responsible behaviors among employees, highlighting the synergies between Islamic HRM and sustainability. The research results show that the application of Islamic HRM can cultivate human resource behavior characterized by integrity, trust, fairness, responsibility, and environmental stewardship. This research also provides examples of best practices from organizations that have successfully implemented both Islamic HRM and green HRM principles in managing their human resources. The findings of this research offer valuable insights for human resource practitioners, organizational leaders, and academics in designing strategies to develop human resource behavior that not only aligns with the values of Islamic teachings but also supports sustainable business practices.

Models for estimating the diameter at breast height as a function of the diameter of the stump Pinus taeda L.

The study addressed the use of models to estimate dendrometric variables in a commercial plantation of Pinus taeda L. Allometric relationships were applied to estimate diameter at breast height (DBH) based on stump diameter (SD), providing a mathematical approach to relate these two variables. Additionally, a "conventional" measurement exclusively of DBH was conducted to compare the values obtained with traditional approach to the results of the proposed modeling. The study also explored hypsometric relationships to estimate tree height as a function of DBH, enabling an efficient and economical assessment of tree characteristics in the forest stand. Furthermore, a forest census was conducted in the area, allowing a comprehensive comparison between the methods used and the actual data from the forest stand, reinforcing the importance of these approaches for effective forest resource management. The results showed that the models were effective in estimating volume, basal area, and the number of trees per hectare, with consistent results compared to the forest census. Therefore, the study concludes that stump inventory methods are effective in estimating dendrometric data in Pinus taeda L. plantations, even after forest cutting events, thereby supporting forestry experts in conducting precise assessments in areas with completed timber harvesting and in making informed decisions. This contributes to the effective and sustainable management of forest resources and the enforcement of laws in cases of environmental or economic damage.

Managing Transboundary Water Resources At the Edge of Human Interface: A Case of Kagera River Basin, Tanzania

Globally, water concerns stemming from human factors are evident, and the Kagera River Basin exemplifies this challenge. This study investigated the influence of human elements on transboundary water resource management in the Kagera River Basin. Utilizing focus group discussions, household surveys, key informant interviews, and field observations, the study analysed land use changes via remote sensing; and processed quantitative data using SPSS 20 and ArcGIS 10.4. Results highlighted economic, political, and social factors as key factors influencing transboundary water resource management. The institutional analysis identified major players to include the Ministry of Water, Lake Victoria Basin Water Board, NELSAP, Ministry of Agriculture, village governments, and CONCERN/OXFAM. Non-climatic factors such as water infrastructure management, socio-economic factors, conflicting water uses, agricultural practices causing soil erosion, and land use/cover changes were identified as central to transboundary water resource challenges. Agricultural expansion and land use shifts in the basin in 1986, 2000 and 2021 were pinpointed as contributors to water resource challenges, impacting availability, access, and quality. Anthropogenic-driven land use changes emerged as significant contributors to pollution, habitat loss, and alterations in water quality. While human factors substantially influence water resources, their impact is exacerbated by anthropogenic activities. Thus, fostering collaborative planning and stewardship initiatives at the local level is crucial for sustaining transboundary water resources. This involves engaging community members and leaders in developing resilience plans and initiating international cooperation, and innovative participatory approaches for effective transboundary water resources management.

Modeling Potential Habitats of Macrophytes in Small Lakes: A GIS and Remote Sensing-Based Approach

Macrophytes, which are foundational to freshwater ecosystems, face significant threats due to habitat degradation globally. Habitat suitability models are vital tools used to investigate the relationship between macrophytes and their environment. This study addresses a critical gap by developing a Geographic information system-based HSM tailored for small lakes, which are often overlooked in ecological studies. We included various abiotic predictors to model the potential macrophyte habitat for several small lakes in southern Bavaria (Germany). Key factors such as the distance to groundwater inflow, depth, availability of photosynthetically active radiation (PAR), and littoral slope were identified as significant predictors of macrophyte occurrence. Notably, the HSM integrates remote sensing-based data to derive PAR availability at the growing depths of the macrophytes using Sentinel-2 MSI data. Integration of an MSI-based time series of PAR availability enabled the introduction of a temporal component allowing monitoring and predicting changes in macrophyte habitats over time. The modeled habitat suitability score correlates highly (R = 0.908) with macrophyte occurrence. We see great promise in using habitat modeling for macrophytes as a tool for water management; in particular, the use of Sentinel-2 MSI data for habitat suitability modeling holds promise for advancing water management. By demonstrating the efficacy of GIS- and remote sensing-based HSM, we pave the way for future applications of this innovative approach in ecological conservation and resource management.

Decentralized micro water-energy co-optimization for small communities

The water-energy nexus encompasses the interdependencies between water and energy resources identifying the existing links between the production and distribution of these resources. Therefore, understanding the water-energy nexus is crucial for developing sustainable and integrated resource management approaches. This paper proposes a decentralized co-optimization model for a micro water-energy nexus system (MWEN), aiming to optimize the combined supply of both resources to end consumers. The approach respects the separate ownership and management of the water and energy sectors while bridging the gap between their optimized operations. An enhanced version of the alternating direction method of multipliers (ADMM) is proposed, the objective-based ADMM (OB-ADMM), which is able to robustly optimize each system independently towards a common objective, only sharing information about the power consumption of water management, providing privacy for each resource provider.

Implementing IWRM approaches with climate-change adaptation on riverside slum upgrading, Indonesia

ABSTRACT Characterized by limited access to basic services, slums are particularly vulnerable to the impacts of climate change. The Integrated Water Resources Management (IWRM) approach plays a vital role in addressing these challenges by improving urban resilience. This paper discusses the implementation of the IWRM approach with a climate-change adaptation (CCA) outlook on riverside slum upgrading in Indonesia using the qualitative methodology and a case-study approach. These implementations are analyzed in two layers, at the river-basin and the kampung level. The study found that a multilayered continuation of policy is required to plan the whole-basin water resources management, while the practices at the kampung level require scaling down and contextualization for specific locations. The involvement of multisector stakeholders collaborating with communities at different levels and secured land-tenure status are crucial for success. Different strategies linking water resources management in urban riverside slums with prioritization in addressing hazard control above other pillars of IWRM are a prerequisite for a safe settlement. The paper also highlights the need for more effective implementation, the importance of bridging the gaps between policy orientation and management, and implementations at all levels to ensure success.

Interdependent water and power infrastructure model (IWPIM): A modeling approach for water and energy resource management in rural communities

The importance of the dependencies between water and power systems is more acutely perceived when challenges emerge. As both energy and water supply are limited, efficient use is a must for any sustainable future, especially in rural areas. Although important, a modeling tool that can analyze water-energy systems interdependencies in rural systems, at the architectural level highlighting the physical interconnections and synergies of these systems, is still lacking. We present a multi-agent system model that captures the features of both systems, at the same levels of fidelity and resolution, with coordinated operations and contingency components represented. Unlike other models, ours captures architectural features of both systems and technical constraints of the systems’ components, which is critical to capture physical intricacies of the interplay between systems components and shed light on the impacts of disruptions of either system on the other. This model, which includes multiple infrastructure components, shows the importance of a holistic understanding of the systems, for cooperation across systems physical boundaries and enhanced benefits at larger scales. This study looks to investigate water-power resource management in an irrigation system via the analysis of physical links and highlight strengths and vulnerabilities. The effects of water shortage, water re-allocation and load shedding are analyzed through scenarios designed to illustrate the utility of such a model. Results highlights the importance of inter-reservoir relationships for alleviating effects of disruption and unforeseen rise in energy demand. Water storage is also critical, helping to mitigate the impacts of water scarcity, and by extension, to keep the energy system unaffected. It can be a viable part of the solution to compensate for the negative impact of shortage for both resources.

Cross-Border Water Management in Transboundary River conflicts in Palestine

Purpose: The aim of the study was to analyze cross-border water management in transboundary river conflicts in Palestine. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Research on cross-border water management in transboundary river conflicts stresses cooperation, trust-building, and integrated approaches for sustainable solutions. Equitable resource allocation, effective communication among riparian states, and international legal frameworks play vital roles in resolving disputes. Adaptive governance mechanisms are crucial for addressing changing hydrological conditions and political dynamics. Collaborative efforts are essential for managing transboundary river conflicts effectively. Unique Contribution to Theory, Practice and Policy: Hydro-hegemony theory, institutional collective action (ICA) theory & environmental peacebuilding theory may be used to anchor future studies on cross-border water management in transboundary river conflicts in Palestine. Implementing integrated water resources management (IWRM) approaches that involve stakeholders from all riparian countries can enhance practical efforts to address transboundary river conflicts. Developing robust legal and institutional frameworks at both national and international levels is crucial for resolving transboundary river conflicts and promoting cooperation.

INTEGRASI PERILAKU DAN KOMPETENSI KEPEMIMPINAN TRANSFORMASIONAL DALAM MENUNJANG KINERJA ORGANISASI ( Studi organisasi Kantor “x”)

Abstract. This case study explores the influence of transformational leadership style in facilitating innovation and synergy in an institution. Through the analysis of conceptual relationship diagrams among various operational elements within the organization, this study demonstrates how transformational leadership impacts decision-making processes, innovation, and competency enhancement. In this context, leadership acts not only as a decision maker but also as a motivator inspiring active participation and commitment from team members. The emphasis on consultation and coordination in decision-making illustrates the implementation of democratic practices supporting a collaborative and inclusive work environment. Furthermore, the study identifies innovation as a central pillar driving the institution to adapt to changes and meet the dynamic market needs. Initiatives such as the implementation of modern technology and new approaches in human resource management are illustrated as key components in the organization’s innovative strategy. The findings of this case study underscore that transformational leadership is effective in triggering organizational growth and sustainability by integrating innovation and collaboration. The implications of these findings provide important insights for other institutional leaders in designing leadership strategies that not only direct the organization to achieve its targets but also ensure ongoing adaptation and growth in a continually changing environment. This study offers valuable contributions to the literature on organizational leadership, particularly in the context of institutions operating in the era of globalization and digital transformation.

Analysis of Approaches for Diverse and Inclusive Human Resource Management

Analysis of Approaches for Diverse and Inclusive Human Resource Management