Trade-off Research Articles

선삭 절삭력 예측을 위한 지식 기반 툴 개발

In this study, a knowledge-based tool is developed to enhance the manufacturing efficiency of mechanical components, particularly those requiring the removal of large components, such as the struts of airplane landing gears. Using this tool, knowledge is extracted and implemented during the turning process. The cutting forces and material-removal quantities are calculated based on the obtained knowledge. User-friendly graphical user interfaces are provided for user interactions. They can be used to input various parameters, such as the workpiece, cutting tool, and machining conditions, including the cutting material, rotational speed, and cut depth. The tool outputs essential parameters, such as the cutting forces, torque, power consumption, and material-removal rate, under different cutting conditions. More importantly, the tool enables users to conduct trade-off analyses, thus enabling the identification of near-optimal cutting conditions while accounting for factors such as tool life and production efficiency. This study contributes to the machining of high-strength materials by providing a useful tool for efficient industrial manufacturing.

An Engineered Assessment System to Manage Demand Reduction Initiatives

The Joint Warfighting Concept is a framework for how the United States will fight in the future security landscape. To successfully carry out these new concepts, the military services must find ways to lessen the logistics burden at the strategic, operational, and tactical levels. Only by reducing the demands on its current and planned sustainment systems can the United States continue to be a dominant force on the world stage. However, defense agencies such as the Logistics Functional Capability Board lack a quantitative, credible, repeatable process to effectively assess and manage demand reduction initiatives. This paper is based on work from a student/faculty team that created an assessment system for demand reduction initiatives. Discussion highlights the systems engineering techniques that were used in the effort, which includes but is not limited to stakeholder analysis, functional analysis, morphological analysis, and value modeling. The blended qualitative and quantitative methods focused on user and stakeholder needs to create a process system to evaluate technologically disparate, multicriteria systems. The team expects that the resultant assessments system’s applicability to a range of demand reduction initiatives would be of interest to organizations that must prioritize technology proposals, as well as perform trade-off analysis. Additionally, the approach to create the assessment system has the flexibility to adapt to changes in the stakeholders’ requirements from the reduction initiatives, as well as the ongoing evolution of the warfighting concepts.

Efficiency and longevity trade-off analysis and real-time dynamic health state estimation of solid oxide fuel cell system

Solid oxide fuel cell (SOFC) is a promising energy conversion technology due to its advantages of high efficiency, low emissions, and fuel adaptability. Addressing the balance between efficiency and longevity is crucial for their application on a large scale. Accurate estimation and prediction of the health state of SOFC systems is essential for the study of optimization between system efficiency and degradation. In this work, the influence law of degradation, the relationship between efficiency and longevity, and their joint optimization, alongside the state of health (SOH) estimation of the SOFC system have been deeply investigated, based on a rigorously validated model of a degraded SOFC system. First, the influential variables that predominantly influence system degradation are identified and analyzed via principal component analysis, including stack average temperature, stack temperature gradient, and fuel utilization. Then, the exploration of the trade-off relationship between system efficiency and longevity under all operating conditions is conducted, and the influence laws of influential variables on system degradation are revealed. In light of the lack of accuracy during load changes and the high time cost for existing SOH estimation methodologies, a novel improved SOH estimation strategy, considering both stack voltage and current-related states, is proposed for real-time estimation of system SOH under varying fuel compositions and dynamic power scenarios. The performance of the proposed method is demonstrated by comparing with existing methodologies. This comprehensive study lays the groundwork for the effective and sustainable health management of SOFC systems, ensuring their efficiency and longevity are maintained at an optimal balance.

Free-breathing, fat-corrected T1 mapping of the liver with stack-of-stars MRI, and joint estimation of T1, PDFF, , and .

Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat and inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath-hold. This work proposes a novel, volumetric (3D), free-breathing T1 mapping method to account for multiple confounding factors in a single acquisition. Free-breathing, confounder-corrected T1 mapping was achieved through the combination of non-Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace-constrained, locally low-rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast-enhanced imaging in healthy volunteers, also at 3.0 T. The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = -96.3 ms (95% CI [-82.1 to -110.5]), r2 = 0.981) compared to saturation recovery-based T1 maps. The proposed method produces whole-liver, confounder-corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, and in a single, free-breathing acquisition and has excellent agreement with reference measurements in phantoms.

A biological circuit to anticipate trend

Abstract Organisms gain by anticipating future changes in the environment. Those environmental changes often follow stochastic trends. The steeper the slope of the trend, the more likely the trend’s momentum carries the future trend in the same direction. This article presents a simple biological circuit that measures the momentum, providing a prediction about future trend. The circuit calculates the momentum by the difference between a short-term and a long-term exponential moving average. The time lengths of the two moving averages can be adjusted by changing the decay rates of state variables. Different time lengths for those averages trade off between errors caused by noise and errors caused by lags in predicting a change in the direction of the trend. Prior studies have emphasized circuits that make similar calculations about trends. However, those prior studies embedded their analyses in the details of particular applications, obscuring the simple generality and wide applicability of the approach. The model here contributes to the topic by clarifying the great simplicity and generality of anticipation for stochastic trends. This article also notes that, in financial analysis, the difference between moving averages is widely used to predict future trends in asset prices. The financial measure is called the moving average convergence–divergence indicator. Connecting the biological problem to financial analysis opens the way for future studies in biology to exploit the variety of highly developed trend models in finance.

The Nexus between Poverty and Elections in Africa: A Case Study of Somaliland and the Gambia

This article explores the states of democracy and the conduct of elections in Somaliland and the Gambia. The article examines the democratic and electoral institutions responsible for the conduct of elections in the two countries and assesses their level of effectiveness for a free and transparent election. The article uses multiple case studies as the research design to generate data on elections in Somaliland and the Gambia. Triangulation was also adopted as a method of obtaining multiple data to test their validity and relevance for this study. The study adopted content analysis as the technique for data analysis. The study found that the conduct of elections in both Somaliland and the Gambia has been influenced by vote buying which is the consequence of poverty. The study found that limited economic opportunities in both countries make citizen trade off their votes for favors during elections. The study recommends widening economic opportunities and strengthening the media and civil society organizations for civic education and capacity building of political parties and government officials.

The interplay of future solar energy, land cover change, and their projected impacts on natural lands and croplands in the US

Projections for deep decarbonization require large amounts of solar energy, which may compete with other land uses such as agriculture, urbanization, and conservation of natural lands. Existing capacity expansion models do not integrate land use land cover change (LULC) dynamics into projections. We explored the interaction between projected LULC, solar photovoltaic (PV) deployment, and solar impacts on natural lands and croplands by integrating projections of LULC with a model that can project future deployment of solar PV with high spatial resolution for the conterminous United States. We used scenarios of LULC projections from the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios from 2010 to 2050 and two electricity grid scenarios to model future PV deployment and compared those results against a baseline that held 2010 land cover constant through 2050. Though solar PV's overall technical potential was minimally impacted by LULC scenarios, deployed PV varied by −16.5 to 11.6 % in 2050 from the baseline scenario. Total land requirements for projected PV were similar to other studies, but measures of PV impacts on natural systems depended on the underlying land change dynamics occurring in a scenario. The solar PV deployed through 2050 resulted in 1.1 %–2.4 % of croplands and 0.3 %–0.7 % of natural lands being converted to PV. However, the deepest understanding of PV impacts and interactions with land cover emerged when the complete net gains and losses from all land cover change dynamics, including PV, were integrated. For example, one of the four LULC projections allows for high solar development and a net gain in natural lands, even though PV drives a larger percentage of natural land conversion. This paper shows that integrating land cover change dynamics with energy expansion models generates new insights into trade offs between decarbonization, impacts of renewables, and ongoing land cover change.

Inventory Management Optimization: Balancing Cost and Service Levels

Efficient management of inventory plays a role, in the success of businesses across sectors. Finding the equilibrium between keeping inventory costs low and meeting customer needs is a challenge that requires constant exploration and creativity. This study delves into the complexities of optimizing inventory management focusing on strategies that effectively handle the trade offs between minimizing expenses and fulfilling customer expectations. By delving into an analysis of existing literature this study consolidates approaches, models and best practices implemented by companies to enhance the efficiency of inventory management. It thoroughly examines aspects such as improving demand prediction accuracy reducing lead times optimizing safety stock levels and integrating supply chains. Additionally it explores how advanced technologies like intelligence data analytics and automation are transforming inventory management processes.Moreover this research delves into how industry landscapes, market dynamics and business goals influence inventory management tactics. Through real world examples and empirical data analysis it offers insights, on how organizations can tailor their strategies to meet needs while balancing the objectives of cost control and service level improvement. In the end this study adds to what we know about improving inventory management by providing advice and tips for companies to gain lasting edges in todays ever changing market. KEYWORDS: Research Paper, Blockchain, Management, Risk Evaluation, Empirical Analysis

Optimizing lunar regolith for vat polymerization and sintering: pre-processing & mineral composition impact

Lunar regolith is the most abundant resource on the lunar surface, which can be used for in-situ fabrication and repair technologies. Vat photopolymerization-based additive manufacturing is among the most promising techniques, capable of producing precise ceramic parts of complex shapes from the lunar regolith feedstock for the needs of future crewed exploration missions to the Moon. One of the under-studied aspects of additive manufacturing with lunar regolith is the pre-and post-treatment procedures, which would ensure optimal energy and material consumption and the best printing performance. The goal of the present article was to define the influence of the mineral composition of lunar regolith simulants and the parameters of their pre-processing on the properties of sintered regolith ceramics. It was found that the highland regolith could be sintered to higher relative density compared to the mare regolith. The optimal sintering temperature was determined to be 1150 °C for both types of lunar regolith. An optimal mineral and fractional composition for the regolith feedstock was determined based on the trade-off analysis between lunar regolith sinterability and its printability via vat photopolymerization-based additive manufacturing. Vat-polymerization was performed to produce complex-shaped ceramic parts, yielding 95 % of relative density and a mean ultimate flexural strength of 106 ± 5 MPa, confirming the proposed trade-off point.

Rationale, conceptual issues, and resultant protocol for a mixed methods Person Trade Off (PTO) and qualitative study to estimate and understand the relative value of gains in health for children and young people compared to adults.

Economic evaluation of healthcare typically assumes that an identical health gain to different patients has the same social value. There is some evidence that the public may give greater value to gains for children and young people, although this evidence is not always consistent. We present a mixed methods study protocol where we aim to explore public preferences regarding health gains to children and young people relative to adults, in an Australian setting. This study is a Person Trade Off (PTO) choice experiment that incorporates qualitative components. Within the PTO questions, respondents will be asked to choose between treating different groups of patients that may differ in terms of patient characteristics and group size. PTO questions will be included in an online survey to explore respondent views on the relative value of health gains to different age groups in terms of extending life and improving different aspects of quality of life. The survey will also contain attitudinal questions to help understand the impact of question style upon reported preferences. Additionally, the study will test the impact of forcing respondents to express a preference between two groups compared with allowing them to report that the two groups are equivalent. One-to-one 'think aloud', semi-structured interviews will be conducted to explore a sub-sample of respondents' motivations and views in more detail. Focus groups will be conducted with members of the public to discuss the study findings and explore their views on the role of public preferences in health care prioritisation based on patient age. Our planned study will provide valuable information to healthcare decision makers in Australia who may need to decide whether to pay more for health gains for children and young people compared with adults. Additionally, the methodological test of forcing respondent choice or allowing them to express equivalence will contribute towards developing best practice methods in PTO studies. The rationale for and advantages of the study approach and potential limitations are discussed in the protocol.

Economic shocks and skill acquisition: Evidence from a national online learning platform at the onset of COVID-19

We study how large shocks impact individuals’ skilling decisions using data from a large, government-sponsored, online learning platform in Saudi Arabia. The onset of the COVID-19 pandemic brought about a massive increase in online skilling, and demand shifted towards courses that offered skills, such as telework, likely to be immediately valuable during the pandemic. Consistent with a model where individuals trade off reskilling costs with their expectations of future labor market conditions and their duration of work, we find that shifts into telework courses were largest for older workers. In contrast, younger workers increased enrollments in courses related to new skills, such as general, occupation-specific, and computer-related skills. Using national administrative employment data, we provide descriptive evidence that these investments in skills in early 2020 helped users maintain employment over the course of the pandemic.

Evaluating alternatives to improve drinking water supply within a complex and uncertain human-environment system: case of the Port-au-Prince Metropolitan Region

ABSTRACT Improving decision making in urban water supply systems under a wide range of changing human-environmental scenarios represents a challenging issue, especially when there is a high level of uncertainty and the available information is limited or scarce. To address this concern, the present study applied a decision aiding process to evaluate long-term planning solutions for the Port-au Prince Metropolitan Region’s water supply in Haiti, which is recognized for having a low coverage of water services and great lack of monitoring data. The methodological framework assessed pre-specified alternatives to face uncertain future conditions, with the main emphasis of being aware of how these uncertainties can be framed in the water management practices. To discover the most robust management solutions, a tradeoff analysis and multi-objective optimization allowed to explore the performance of alternatives across many future states of the world and multiple criteria. The results highlighted that human factors associated with the increase of per-capita water use and population growth posed a greater risk on water supply coverage than climatic factors. In addition, the decision support can offer a comprehensive representation of potential supply/demand futures, and provides decision-makers with the opportunity to discuss a posteriori the most appropriate water supply solution under an extensive variety of information with severe uncertainty.

Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design

AbstractAccess to reliable, clean energy sources is a major concern for national security. Much research is focused on the “grand challenge” of producing energy via controlled fusion reactions in a laboratory setting. For fusion experiments, specifically inertial confinement fusion (ICF), to produce sufficient energy, the fusion reactions in the ICF fuel need to become self‐sustaining and burn deuterium‐tritium (DT) fuel efficiently. The recent record‐breaking NIF ignition shot was able to achieve this goal as well as produce more energy than used to drive the experiment. This achievement brings self‐sustaining fusion‐based power systems closer than ever before, capable of providing humans with access to secure, renewable energy. In order to further progress toward the actualization of such power systems, more ICF experiments need to be conducted at large laser facilities such as the United States's National Ignition Facility (NIF) or France's Laser Mega‐Joule. The high cost per shot and limited number of shots that are possible per year make it prohibitive to perform large numbers of experiments. As such, experimental design relies heavily on complex predictive physics simulations for high‐fidelity “preshot” analysis. These multidimensional, multi‐physics, high‐fidelity simulations have to account for a variety of input parameters as well as modeling the extreme conditions (pressures and densities) present at ignition. Such simulations (especially in 3D) can become computationally prohibitive to turn around for each ICF experiment. In this work, we explore using Bayesian optimization with Gaussian processes (GPs) to find optimal designs for ICF double shell targets, while keeping computational costs to manageable levels. These double shell targets have an inner shell that grades from beryllium on the outer surface to the higher Z material molybdenum, as opposed to the nominally used tungsten, on the inside in order to trade off between the high performance associated with high density inner shells and capsule stability. We describe our results for “capsule‐only” xRAGE simulations to study the physics between different capsule designs, inner shell materials, and potential for future experiments.

Coevolution of longevity and female germline maintenance.

An often-overlooked aspect of life-history optimization is the allocation of resources to protect the germline and secure safe transmission of genetic information. While failure to do so renders significant fitness consequences in future generations, germline maintenance comes with substantial costs. Thus, germline allocation should trade off with other life-history decisions and be optimized in accordance with an organism's reproductive schedule. Here, we tested this hypothesis by studying germline maintenance in lines of seed beetle, selected for early (E) or late (L) reproduction for 350 and 240 generations, respectively. Female animals provide maintenance and screening of male gametes in their reproductive tract and oocytes. Here, we reveal the ability of young and aged E- and L-females to provide this form of germline maintenance by mating them to males with ejaculates with artificially elevated levels of protein and DNA damage. We find that germline maintenance in E-females peaks at young age and then declines, while the opposite is true for L-females, in accordance with the age of reproduction in the respective regime. These findings identify the central role of allocation to secure germline integrity in life-history evolution and highlight how females can play a crucial role in mitigating the effects of male germline decisions on mutation rate and offspring quality.

On optimal three-impulse Earth–Moon transfers in a four-body model

Within the emerging age of lunar exploration, optimizing transfer trajectories is a fundamental measure toward achieving more economical and efficient lunar missions. This study addresses the possibility of reducing the fuel cost of two-impulse Earth–Moon transfers in a four-body model with the Earth, the Moon, and the Sun as primaries. Lawden’s primer vector theory is applied within this framework to derive a set of necessary conditions for a fuel-optimal trajectory. These conditions are used to identify which trajectories from an existing database could benefit from the insertion of an additional intermediate impulse. More than 10,000 three-impulse transfers are computed with a direct numerical optimization method. These solutions contribute to enriching the database of impulsive trajectories, useful to perform trade-off analyses. While the majority of trajectories exhibit only marginal improvements, a significant breakthrough emerges for transfers featuring an initial gravity assist at the Moon. Implementing a corrective maneuver after the lunar encounter yields substantial reductions in fuel costs.

Grid-Aware Tradeoff Analysis for Outage Mitigation Microgrids at Emerging Resilience Hubs

Grid-Aware Tradeoff Analysis for Outage Mitigation Microgrids at Emerging Resilience Hubs

Forests for Health Promotion: Future Developments of Salutogenic Properties in Managed Boreal Forests

Visits to forests can improve human health and well-being through various mechanisms. They can support the immune system, promote physical activity, and restore stress and attention fatigue. Questions remain about how perceived qualities in forests important to support such salutogenic, i.e., health-promoting, benefits can be represented in forest simulation tools to allow quantitative analyses, e.g., long-term projections or trade-off analyses with other forest functions, such as biodiversity conservation, wood production, etc. Questions also remain about how different forest management regimes might impact such perceived qualities in forests. Here, we defined three types of salutogenic forest characteristics (SFCs), referred to as Deep, Spacious, and Mixed forest characteristics, respectively. We did so by using the perceived sensory dimension (PSD) model, which describes and interrelates more fundamental perceived qualities of recreational outdoor environments that are important to support people’s health and well-being. We identified proxy variables for the selected PSD models in boreal forest stands and compared the effect of five different management regimes on both individual PSD models and the derived SFCs when projecting a forest landscape 100 years into the future. Our results suggest combinations of protection (set-aside) and variations of continuous cover forestry as the most promising strategies to achieve these salutogenic properties in the long-term future. Depending on the SFC in focus and the specific management regime used, between 20% and 50% of the landscape could support associated properties in the long term (100 years). This might impact how forests should be managed when salutogenic outcomes are considered alongside, e.g., wood production and other forest contributions.

The privacy calculus in the context of novel health technology for diagnosing and tracking infectious diseases: The role of disease severity and technology's evidence base for effectiveness in adoption and voluntary health data-sharing

In the past decades, accelerated by the recent COVID pandemic, the field of healthcare has faced technological advancements, such as wearables and mobile applications, that collect personal or health data. However, such tools are ineffective if they are not adopted by a large part of the population or if relevant health data, collected by the application, are not (voluntarily) shared. This study assessed the role of disease severity and evidence base for the effectiveness of the technology in the Privacy Calculus risk-benefit trade-off to contribute or hinder technology acceptance and data sharing. A large-scale 2 × 2 × 2 online vignette experiment (n = 822) was carried out, where participants were presented with a hypothetical scenario describing a novel health technology for diagnosing and tracking of infectious diseases. The results indicated that participants’ privacy concerns negatively affected their intention to use the technology and willingness to share data, and that a high severity of the disease weakened this relationship. None of the other expected effects on intentions to use, willingness to share data or privacy concerns, were significant. These findings highlight the role of privacy as a barrier to technology acceptance, and suggest disease severity plays a role in the Privacy Calculus risk-benefit trade off by weakening the negative effect of privacy concerns on adoption in contexts where disease severity is high.

DG-ViTh: A decision guidance system for repositories of virtual things

ABSTRACT Entrepreneurs encounter significant challenges in translating their ideas into tangible or digital products. Conventional idea-to-market processes often prove inflexible, siloed, and linear, leading to missed optimisation opportunities and substantial material, energy and labour waste. To address these challenges, this paper proposes DG-ViTh, a Decision Guidance System for search, optimisation and trade-off analysis of Virtual Things, which are parameterised specifications of products, services or anything of value. Virtual things are associated with analytic performance models that express customer-facing characteristics of a ‘thing’ in terms of virtual thing’s parameters. DG-ViTh allows virtual things’ parameters be optimally instantiated and then ordered by consumers from capability providers on demand. To develop DG-ViTh, this paper provides the design and formal mathematical semantics of a repository for general virtual things, core DG-ViTh functions, and a prototype implementation demonstrating optimisation capabilities for arbitrary pluggable virtual thing specifications. DG-ViTh versatility is demonstrated using the example virtual bike, illustrating its potential for a broad range of applications.

Spatiotemporal variations of ecosystem services in the Aral Sea basin under different CMIP6 projections

The Aral Sea, located in Central Asia, has undergone significant reduction in surface area owing to the combined impacts of climate change and human activities. This reduction has led to a regional ecological crisis and profound repercussions on ecosystem services. Investigating the spatiotemporal variations and synergistic trade-offs of ESs in the Aral Sea basin is crucial for fostering the integrated development of the region’s socioeconomic ecology. This study utilizes the Future Land-Use Simulation and InVEST models to analyze future land-use scenarios, integrating CMIP6 projections to assess the quality of four key ecosystem services: water production, soil conservation, carbon storage, and habitat quality over two timeframes: the historical period (1995–2020) and the projected future (2021–2100). Employing Spearman correlation, the study explores the trade-offs and synergies among these ecosystem services. Findings reveal that the primary forms of land-use change in the Aral Sea basin are the reduction in water area (− 49.59%) and the rapid expansion of urban areas (+ 504.65%). Temporally, habitat quality exhibits a declining trend, while carbon storage shows an increasing trend, and water production and soil retention fluctuate initially decreasing and then increasing. Spatially, water production and carbon storage demonstrate an increasing trend from the northwest to the southeast. Habitat quality exhibits a higher spatial pattern in the southeast and south, contrasting with lower spatial patterns in the north and west. Low-level soil conservation is predominantly distributed in the northwest, while medium to low-level soil conservation is prevalent in the east of the basin. The trade-off and synergy analysis indicates that between 1995 and 2020, a trade-off relationship existed between carbon storage and habitat quality and water production, whereas synergies were observed between soil conservation and carbon storage, water production and habitat quality, and soil conservation. The correlation between water production and soil conservation emerges as the strongest, whereas the correlation between carbon storage and habitat quality appears to be the weakest. The dynamic spatiotemporal changes, trade-offs, and collaborative relationships of ESs constitute major aspects of ecosystem service research, holding substantial implications for the effective management of the regional ecological environment.