Adaptive Management Techniques Research Articles

Dynamic Power Allocation for Downlink NOMA

Dynamic Power Allocation for Downlink Non-Orthogonal Multiple Access (NOMA) is a critical research area in wireless communication systems. This study focuses on implementing and evaluating dynamic power allocation strategies in the context of downlink NOMA. We compare the performance of dynamic power allocation with fixed power allocation schemes to assess their impact on system throughput, interference management, and overall efficiency. Through extensive simulations and analysis in this paper using MATLAB, we demonstrate a comparison between dynamic power allocation and fixed power allocation, and the advantages of dynamic power allocation in adapting to changing channel conditions and user requirements, leading to improved system performance. Our results show the data rate and outage probability which provides valuable insights into the benefits of dynamic power allocation in downlink NOMA systems and highlight the importance of adaptive power management techniques in enhancing wireless communication networks.

Fault Prediction and Awareness for Power Distribution in Grid Connected RES Using Hybrid Machine Learning

This study addresses defects in electrical power systems, focusing on short circuits that can disrupt normal operation. The method emphasis is on hybrid microgrid systems connected to the grid, crucial for efficient power management. The novel method proposes an adaptive electricity management technique for fault scenarios in grid-tied conversions, minimizing sensor requirements. Power flow involves the hybrid energy storage system (HESS), renewable energy sources (RES), the electrical grid, and loads through a parallel hybrid RES arrangement. Semiconductor switch failures are common vulnerabilities, impacting grid functionality. The novel electricity management technique considers converter failures, renewable energy availability, and HESS state of charge restrictions. Power quality goals such as harmonic reduction, reactive power support, and a power factor of one are addressed. The proposed method was evaluated using MATLAB–based Simulink, showcasing its performance. The approach employs an Adaptive Power Management Strategy (APMS) in a hybrid renewable energy system, integrating wind and solar sources with battery and supercapacitor storage. A Hybrid Machine Learning-based Active Power Management System (HML-APMS) optimizes energy production, storage, and distribution for stability, reliability, and efficiency in the power utility system. The study underscores the significance of technology integration in achieving sustainable, reliable, and cost-effective power solutions.

Improving Abiotic Stress Mitigation via Predictive Modeling of Water Quality Parameters in Recirculated Aquaculture Systems

A sustainable aquaculture solution can be provided by Recirculated Aquaculture Systems or RAS, nevertheless, Abiotic stress factors can negatively impact aquatic organisms' growth and well-being. This study’s purpose is to demonstrate how Random Forests machine learning method helps to develop a predicting model that can aid in forecasting and in the mitigation of abiotic stressors in Recirculating Aquaculture Systems by regulating water quality influences.
 The study used the historical data on water quality, such as temperature, dissolved oxygen, pH, ammonia, and TDS levels in constructing a Random Forest-based predictive model. Based from the results reveal, the developed prediction model using random forests machine learning method was 90% accurate in making prediction and improved abiotic stress in RAS.
 Understanding the complex relations between water quality indicators and abiotic stress variables in RAS is crucial for identifying major abiotic stress drivers and developing effective models for forecasting water quality parameters, which results in real-time insights and actionable information for making proactive decisions and employing adaptive management techniques.
 Furthermore, RAS improves aquaculture productivity while reducing environmental impacts, which results in increased productivity, resource utilization, and system performance. This study makes a vital contribution to the aquaculture sector by proposing a data-driven method to improve the control of water quality parameters in RAS and, eventually, raise the sustainability and effectiveness of Recirculating Aquaculture Systems

Novel Adaptive Energy Management Technique for Multiport Fast EV Chargers

Novel Adaptive Energy Management Technique for Multiport Fast EV Chargers

Exploring Adaptive Management Techniques in Coastal Resource Conservation

This study explores the adaptive management techniques employed in coastal resource conservation, aiming to understand how different stakeholders integrate dynamic management practices to address these challenges effectively. This qualitative study involved semi-structured interviews with 27 stakeholders, including local community leaders, conservation experts, policymakers, and representatives from non-governmental organizations (NGOs). The participants were selected through purposive sampling to cover a broad range of experiences and insights. The interviews focused on their perspectives and practices in adaptive management, with the data collection process continuing until theoretical saturation was achieved. The analysis was conducted using thematic analysis to identify recurring themes related to adaptive management strategies. Four main themes emerged from the analysis: Adaptive Strategies, Challenges and Barriers, Conservation Outcomes, and Stakeholder Perceptions. These themes were detailed further into sub-categories, such as Risk Assessment, Resource Allocation, Stakeholder Engagement, Regulatory Constraints, Financial Limitations, Community Resistance, Biodiversity Enhancement, Pollution Control, Ecosystem Resilience, Sustainable Practices Adoption, Perceived Effectiveness, Suggestions for Improvement, and Future Prospects. Each category was supported by specific concepts derived from the interview data, illustrating the complexities and multifaceted nature of adaptive management in coastal conservation. The study underscores the importance of a flexible, inclusive, and integrated approach to adaptive management in coastal conservation. Effective management strategies should incorporate stakeholder engagement, economic considerations, and local knowledge to enhance the sustainability and efficacy of conservation efforts. The findings highlight the need for adaptive governance frameworks that can respond to the socio-economic and environmental dynamics of coastal ecosystems.

A Case for Adaptive Management of Rangelands’ Wicked Problems

Sagebrush-steppe restoration has long been seen as a wicked problem—each case has multifaceted problems with no universal solutions—and thus managers have had to adopt adaptive management techniques to meet ever-changing landscape demands. In this study, we characterize the efficacy of an adaptive management plan in a severely degraded sagebrush-steppe winter range habitat for mule deer for 8 yr by monitoring the plant community. During this time, managers have actively managed juniper encroachment through felling and responded to a 2014 wildfire by applying herbicide and seeding for native and forage vegetation. We found that the adaptive management practices reduced annual invasive grasses by about half post fire and nearly doubled preferred herbaceous plants’ cover and biomass. However, these successes were only recorded in plots that received repeated treatments, whereas in plots that only received a single treatment post fire, invasive annual grasses returned to prefire cover. Despite these successes in recovering desired herbaceous composition, shrub regeneration was nearly nonexistent during the study period despite repeated attempts to seed.

Comparative effect of conventional and adaptive management approaches on watershed health

Watershed management initiatives are designed to conserve essential soil, water, and vegetation resources while ensuring production and agricultural sustainability. As a result, assessing watershed management projects is a must for future executive planning and natural resource management. However, there has yet to be a quantitative performance evaluation of alternative watershed management techniques on the watershed's overall health. The current study used the pressure-state response (PSR) conceptual framework to assess watershed health in the current scenario and identify the related functional criteria and indicators at the sub-watershed level. Field surveys and reviews of available information were used to identify and characterize current watershed concerns and challenges. The PSR framework was used to assess the impact of conventional watershed management measures and a problem-oriented adaptive management strategy on watershed health in the Mikhsaz Watershed in northern Iran. The influence of changes in the contribution of the study criteria to the health and corresponding scenarios on modifying the watershed health was evaluated. A health index score of 0.68 revealed a healthy class in the current circumstances. The health index was somewhat enhanced after adding the typical or conventional measurements in the research area (i.e., 0.69). Adaptive management techniques in response to the identified issues improved the watershed's health index by 7.2% (i.e., 0.74) in a more efficient, technically acceptable, and ecologically benign manner. As a result, the adaptive management measure increased economic productivity by 61% compared to the conventional measures. The study's findings call for a global revival in watershed management policy, focusing on developing nations.

Synthesis of plant-soil feedback effects on eastern North American tree species: implications for climate-adaptive forestry

Climate change represents an existential threat to many forest ecosystems because tree populations are often adapted to local climate means and variability. If tree populations cannot migrate or adapt, they risk becoming increasingly maladapted with climate change. This emerging mismatch underscores the need for climate adaptive management techniques, such as assisted migration of tree species, to help mitigate climate change impacts on forest ecosystems. Although biotic and abiotic factors are known to constrain tree establishment success, the extent to which they may determine the success of assisted migration plantings is poorly understood. Thus, defining the extent to which trees affect—and in turn are affected by local soil environments and microbial communities (i.e., plant-soil feedbacks; hereafter PSFs) remains important for guiding effective climate-adaptive forest management. Our objectives were to synthesize the current state of knowledge about the direction and magnitude of PSF effects on temperate tree species of eastern North America, and to identify key hypotheses important for guiding future research. To accomplish these goals, we conducted a meta-analysis of 26 peer-reviewed publications that addressed our criteria. Our compiled database included 61 tree species and was composed primarily of short-term greenhouse experiments that studied PSF effects by manipulating the soil biota in three ways: (1) soil was previously inoculated by a conspecific or heterospecific tree species (i.e., home vs. away), (2) soil was live or sterilized, or (3) soil was untreated or treated with fungicide. We found that PSF had significant effects on tree growth, with the direction and magnitude of PSF strongly dependent on tree mycorrhizal guild. Arbuscular mycorrhizal tree species grown in live or home soils grew 13–33% less than those in sterile or away soils, while ectomycorrhizal tree species grew 11–44% more in live or home than sterile or away soils. PSF effects were associated with several plant functional traits, including specific leaf area, tissue nitrogen, and specific root length. We provide suggestions on incorporating PSFs into assisted migration trials and outline key knowledge gaps for future research. Our synthesis of context-dependent effects of PSFs on tree performance will help inform management decisions involving assisted migration.

Navigating Organizational Change: A Comparative Study of Adaptive Management Techniques and Their Effects on Employee Retention and Productivity

Navigating Organizational Change: A Comparative Study of Adaptive Management Techniques and Their Effects on Employee Retention and Productivity

Adaptive Clock Management of HLS-generated Circuits on FPGAs

In this article, we present Syncopation , a performance-boosting fine-grained timing analysis and adaptive clock management technique for High-Level Synthesis-generated circuits implemented on Field-Programmable Gate Arrays. The key idea is to use the HLS scheduling information along with the placement and routing results to determine the worst-case timing path for individual clock cycles. By adjusting the clock period on a cycle-by-cycle basis, we can increase performance of an HLS-generated circuit. Our experiments show that Syncopation improves performance by 3.2% (geomean) across all benchmarks (up to 47%). In addition, by employing targeted synthesis techniques along with Syncopation, we can achieve 10.3% performance improvement (geomean) across all benchmarks (up to 50%). Syncopation instrumentation is implemented entirely in soft logic without requiring alterations to the HLS-synthesis toolchain or changes to the FPGA, and has been validated on real hardware.

A Comparative Study of Fasciola Parasite Infection Rates in Local and Imported Sheep in Jeddah, Saudi Arabia

Fasciola hepatica and Fasciola gigantica are two trematodes (liver flukes) that cause water- and food-borne disease Fasciolosis. Many animals are involved in the life cycle of the Fasciola spp., such as sheep, cattle, and camels, and humans are the definitive host. This work investigated the prevalence of Fasciola among imported and local slaughtered sheep and the relation between infection rate and seasons of the year. A total of 720,290 local and imported sheep (251,701 and 468,489, respectively) were slaughtered in a Jeddah slaughterhouse (Western region of Saudi Arabia) over the periods of 2017-2018, 2018-2019, and 2019-2020. In the three years of inspection, the infection rate at slaughter was higher among imported than local sheep. In 2017-2018, both local and imported sheep had the highest level of infection in the spring and the lowest in the winter. However, in 2018-2019, the highest rate of infection for both was documented in the summer and the lowest in the winter. Lastly, in 2019-2020, the highest rate of infection for local sheep was observed in the summer of 2020 and the lowest rate of infection was observed in the spring of 2020. Among imported sheep, the highest rate of infection was in the summer and the lowest was in winter for both 2019 and 2020. To control this disease, there is the need to apply for successful integrated programs and practice adaptive management techniques.

Hybrid spectrum management using integrated fuzzy and femtocells in cognitive domain

In Today’s pandemic situation, ‘Spectrum accessing and smart usage’ is the sacred Mantra uttered by every individual citizen in the world. Work from home for techies, online classes for students, games for kids, webinar for teaching fraternity etc., are going almost on indoor coverage without any limit in pace because of the smart spectrum coverage by the network service providers. This paper provides an add-on facility to the existing wireless infrastructure to provide a better user experience in this highly regrettable routine. In this paper, a cognitive domain unused spectrum holes are efficiently handled by (i) adaptive spectrum management technique; (ii) Fuzzy Inference System based spectrum administration and (iii) Hybrid Cognitive Femtocell approaches based on the user demand and their applications. The proposed integrated cognitive femtocell and Fuzzy-based approach reduces the indoor coverage problems and enhances the throughput of the macrocell users by allowing adaptive spectrum management based on the demand, thereby eliminating spectrum underlay and overlay problems during critical conditions. In cognitive femtocell networks, the access points are prepared and installed with Cognitive Radio which can determine spectrum dynamically by macrocells and nearby Femto Access Points. It adjusts its radiating parameters to evade the macrocells’ interferences and the neighbouring femtocells, thereby maximising the spectrum band’s overall utility.

Concurrent Application Bias Scheduling for Energy Efficiency of Heterogeneous Multi-Core Platforms

Minimizing energy consumption of concurrent applications on heterogeneous multi-core platforms is challenging given the diversity in energy-performance profiles of both the applications and hardware. Adaptive learning techniques made the exhaustive Pareto-optimal space exploration practically feasible to identify an energy efficient configuration. Existing approaches consider a single application's characteristic for optimizing energy consumption. However, an optimal configuration for a given application in isolation may not be optimal when other applications are run concurrently. Approaches that consider concurrent application scenarios overlook the weight of total energy consumption per application, restricting them from prioritizing among applications. We address this limitation by considering the mutual effect of concurrent applications on system wide energy consumption to adapt resource configuration at run-time. We characterize each application's power-performance profile as a weighted bias through off-line profiling. We infer this model combined with an on-line predictive strategy to make resource allocation decisions for minimizing energy consumption while honoring performance requirements. The proposed strategy is implemented as a user-space process and evaluated on a heterogeneous hardware platform of Odroid XU3 over the Rodinia benchmark suite. Experimental results show up to 61 percent of energy saving compared to the standard baseline of Linux governors and up to 27 percent of energy gain compared to state-of-the-art adaptive learning-based resource management techniques.

Under New Management

Scherer, M.E.G.; Nicolodi, J.L.; Costa, M.F.; Corriani, N.R.; Gonçalves, R.K.; Cristiano, S.C.; Ramos, B.; Camargo, J.M.; Souza, V.A.; Fischer, L.O.; Sardinha, G.; Mattos, M.P.S., and Pfuetzenreuter, A., 2020. Under new management. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 945–952. Coconut Creek (Florida), ISSN 0749-0208.Beaches are of public access in most countries. This condition generates many societal benefits, which can be a challenge for managers. In Brazil, beaches are public spaces, with free access to all who wish to enjoy environmental services. Until recently, very limited choice of management autonomy was given to the local beach managers, which contrasted with the returned amount of responsibilities in keeping this public asset. Therefore, a new management option was put to local administrators by Federal Law 13.240/2015. The municipality can now take part in an agreement with the Federal Heritage Secretary, the national institution ultimately in charge of beach management. This agreement grants more power to local managers of urban beaches. In order to fulfil this agreement, they must observe and develop a set of measures that contribute to safer, equal and more sustainable use of the space. In a period of nearly three years, 61 Brazilian costal municipalities (out of 295 candidates) have been granted the agreement. In order to monitor and evaluate its compliance, a set of indicators were developed and are being applied. The evolution of these indicators scores is the most important tool to monitor the effectiveness of the agreement at diverse spatial and temporal scales, since the start of the decision process. Monitoring is then being carried out through on line and in situ data generation and treatment. The success of this co-management tool will depend on the application of well-established adaptive management techniques, as well as effective communication among stakeholders. Signing the agreement is not compulsory, but the majority of municipal managers are expected to do so, in face of potential outcomes. Due to the extent of the Brazilian coastline, and number of stakeholders potentially involved, this is believed to be one of the largest coastal management proposals in the world.

Multicast and Broadcast Enablers for High-Performing Cellular V2X Systems

This paper focuses on capabilities enabled by 5G connectivity in the cooperative, connected and autonomous cars, and elaborates on two technical enablers. One of the technical enablers consists of a beamformed broadcast/multicast technology that builds on adaptive and robust beam management techniques at the air interface. The other proposed technical component aims to improve the end-to-end architectural design of 5G networks to enable efficient broadcast and multicast transmissions for vehicle-to-anything services. Finally, the key results of multicast and broadcast technical components are described and ongoing and future areas of work and research are detailed.

Improving the Performance and Energy Efficiency of GPGPU Computing through Integrated Adaptive Cache Management

Hardware caches are widely employed in GPGPUs to achieve higher performance and energy efficiency. Incorporating hardware caches in GPGPUs, however, does not immediately guarantee enhanced performance and energy efficiency due to high cache contention and thrashing. To address the inefficiency of GPGPU caches, various adaptive techniques (e.g., warp limiting) have been proposed. However, relatively little work has been done in the context of creating an architectural framework that tightly integrates adaptive cache management techniques and investigating their effectiveness and interaction. To bridge this gap, we propose IACM, integrated adaptive cache management for high-performance and energy-efficient GPGPU computing. IACM integrates the state-of-the-art adaptive cache management techniques (i.e., cache indexing, bypassing, and warp limiting) in a unified architectural framework. Our quantitative evaluation demonstrates that IACM significantly improves the performance and energy efficiency of various GPGPU workloads over the baseline architecture (i.e., 98.1 and 61.9 percent on average, respectively), achieves considerably higher performance than the state-of-the-art technique (i.e., 361.4 percent at maximum and 7.7 percent on average), and delivers significant performance and energy-efficiency gains over the baseline GPGPU architecture enhanced with advanced architectural technologies.

Utilizing a multi-index decision analysis method to overall assess forage yield and quality of C3 grasses in the western Canadian prairies

Seasonal dynamic of forage quality and yield has a major impact on livestock production. A sound evaluation on quality and quantity of forage is useful for cost-effective utilization of forage. However, forage quality and yield can vary with forage species, harvest seasons and yearly climate conditions. To improve forage use efficiency, a field experiment (2008–2010) was conducted in Swift Current, Saskatchewan, Canada. Dry matter yield and quality indicators (fiber, protein, digestibility and minerals) were measured for nine cool-season grasses harvested in June, August and October. The interrelationships and attributes among quality indicators were determined by principal component analysis (PCA) and the weights of quality indicators were calculated by entropy weight (EW) method. To synthesize different attribute indicators into a comprehensive index that reflects quality ranking of different forage species, an integrated multi-index decision analysis method, i.e., PCA-based TOPSIS with EW, was used in this paper. The evaluation process and results showed that the interrelation patterns and positive or negative attributes for quality indicators were consistent with years and harvest seasons, whereas the rankings of most grasses in yield and comprehensive quality varied with years and harvest seasons. According to the yearly and seasonal rankings of forage quality and yield, flexible production tactics and adaptive management techniques should be considered within the western Canadian prairie region. For instance, Northern wheatgrass (Agropyron dasystachyum) can be recommended to be mixed with high quality forages due to its high yield in any harvest season. Meadow bromegrass (Bromus Riparius) can be recommended to be mixed with high yield forages due to its high quality in summer and fall. These findings will provide valuable information for forage breeders, and livestock and forage managers to maximize grass utilization efficiency while balancing yield and quality.

Adaptive Management Techniques for Optimized Burn-in of Safety-Critical SoC

The cost of Burn-In is a major concern for the testing of Automotive Systems-on-Chip (SoC). This paper highlights problematic aspects of a Burn-In flow and describes a two-layered adaptive technique that permits to optimize the stress application and strongly reduce BI test time. At the SoC level, the described methodology adaptively copes with FLASH erase time uncertainties; at the Automatic Test Equipment (ATE) level, the strategy relies on power monitors and tester intelligence. The paper reports experimental results on a SoC manufactured by STMicroelectronics; figures show an optimized usage of stress resources and demonstrates a reduction of 25% in the BI test time when using the proposed adaptive techniques.

Adaptive Thermal Management Technique to Improve the Efficiency of SSPA for Geo-Synchronous Satellite

This paper presents a novel adaptive thermal management technique to improve the efficiency of solid-state power amplifier (SSPA) for geo-synchronous satellites. The thermal management for space segment is very important as it determines the reliability of the satellite. The microwave power amplifiers (MPAs), either traveling wave tube amplifiers (TWTAs) or SSPAs, are the maximum power consuming and heat dissipative elements in the satellite and their power efficiency determines weight, volume, cost, and reliability of the satellite. So, it is necessary to improve the efficiency of the SSPA. A novel technique is presented, which improves the efficiency of the SSPA and hence, saving of costly DC power generation on-board and reduction of the heat dissipation.

Did enhanced afforestation cause high severity peat burn in the Fort McMurray Horse River wildfire?

Climate change mediated drying of boreal peatlands is expected to enhance peatland afforestation and wildfire vulnerability. The water table depth–afforestation feedback represents a positive feedback that can enhance peat drying and consolidation and thereby increase peat burn severity; exacerbating the challenges and costs of wildfire suppression efforts and potentially shifting the peatland to a persistent source of atmospheric carbon. To address this wildfire management challenge, we examined burn severity across a gradient of drying in a black spruce dominated peatland that was partially drained in 1975−1980 and burned in the 2016 Fort McMurray Horse River wildfire. We found that post-drainage black spruce annual ring width increased substantially with intense drainage. Average (±SD) basal diameter was 2.6 ± 1.2 cm, 3.2 ± 2.0 cm and 7.9 ± 4.7 cm in undrained (UD), moderately drained (MD) and heavily drained (HD) treatments, respectively. Depth of burn was significantly different between treatments (p < 0.001) and averaged (±SD) 2.5 ± 3.5 cm, 6.4 ± 5.0 cm and 36.9 ± 29.6 cm for the UD, MD and HD treatments, respectively. The high burn severity in the HD treatment included 38% of the treatment that experienced combustion of the entire peat profile, and we estimate that overall 51% of the HD pre-burn peat carbon stock was lost. We argue that the HD treatment surpassed an ecohydrological tipping point to high severity peat burn that may be identified using black spruce stand characteristics in boreal plains bogs. While further studies are needed, we believe that quantifying this threshold will aid in developing effective adaptive management techniques and protecting boreal peatland carbon stocks.