Hasil untuk "Costs"

Emma Strubell, Ananya Ganesh, A. McCallum

Recent progress in hardware and methodology for training neural networks has ushered in a new generation of large networks trained on abundant data. These models have obtained notable gains in accuracy across many NLP tasks. However, these accuracy improvements depend on the availability of exceptionally large computational resources that necessitate similarly substantial energy consumption. As a result these models are costly to train and develop, both financially, due to the cost of hardware and electricity or cloud compute time, and environmentally, due to the carbon footprint required to fuel modern tensor processing hardware. In this paper we bring this issue to the attention of NLP researchers by quantifying the approximate financial and environmental costs of training a variety of recently successful neural network models for NLP. Based on these findings, we propose actionable recommendations to reduce costs and improve equity in NLP research and practice.

Z. Obermeyer, Brian W. Powers, C. Vogeli et al.

Racial bias in health algorithms The U.S. health care system uses commercial algorithms to guide health decisions. Obermeyer et al. find evidence of racial bias in one widely used algorithm, such that Black patients assigned the same level of risk by the algorithm are sicker than White patients (see the Perspective by Benjamin). The authors estimated that this racial bias reduces the number of Black patients identified for extra care by more than half. Bias occurs because the algorithm uses health costs as a proxy for health needs. Less money is spent on Black patients who have the same level of need, and the algorithm thus falsely concludes that Black patients are healthier than equally sick White patients. Reformulating the algorithm so that it no longer uses costs as a proxy for needs eliminates the racial bias in predicting who needs extra care. Science, this issue p. 447; see also p. 421 A health algorithm that uses health costs as a proxy for health needs leads to racial bias against Black patients. Health systems rely on commercial prediction algorithms to identify and help patients with complex health needs. We show that a widely used algorithm, typical of this industry-wide approach and affecting millions of patients, exhibits significant racial bias: At a given risk score, Black patients are considerably sicker than White patients, as evidenced by signs of uncontrolled illnesses. Remedying this disparity would increase the percentage of Black patients receiving additional help from 17.7 to 46.5%. The bias arises because the algorithm predicts health care costs rather than illness, but unequal access to care means that we spend less money caring for Black patients than for White patients. Thus, despite health care cost appearing to be an effective proxy for health by some measures of predictive accuracy, large racial biases arise. We suggest that the choice of convenient, seemingly effective proxies for ground truth can be an important source of algorithmic bias in many contexts.

S. Pushpakom, Francesco Iorio, P. Eyers et al.

Abdoul Razak Sawadogo, Alexandre Lagrange, Anaïs Bosetti et al.

Abstract Background Older adults, with complex needs and an elevated risk of complications, account for a high proportion of emergency visits in France. Mobile geriatric teams (MGTs) and the emergency geriatric medicine unit (EGMU) based in the emergency department (ED) have been developed to improve care. Although the EGMU reduces hospitalizations and readmissions, its cost-effectiveness remains uncertain. Methods This study assessed the incremental cost-effectiveness ratio (ICER) of the EGMU compared to the MGT unit. In all, 338 older patients were included: 102 managed by the MGT unit in January 2014 and 236 in the EGMU in January 2015, which replaced the MGT unit. The primary efficacy endpoint was the rate of readmission to the ED within 30 days (30DRA). We conducted the analysis from the payer’s perspective, incorporated a Monte Carlo simulation, and generated a cost-effectiveness acceptability curve. Result The average cost per patient was estimated to be €5738.16 in the EGMU, compared to €6701.35 in the MGT unit. The mean 30DRA was 0.09 for the EGMU and 0.13 for the MGT unit. The ICER was €24,079 per readmission avoided (RA). The probability that the EGMU would be cost-effective at a willingness-to-pay threshold of €33,622.84 per RA was 63.26%. Conclusion The EGMU appears to be more efficient than the MGT unit, reducing 30DRA and average costs, although further studies are needed to confirm these findings.

Jenna M Cole, Sergio A Balaguera-Reina, Melissa A Miller et al.

Invasive species impose major ecological and economic costs on ecosystems and countries where introduced. To effectively manage Argentine black and white tegus (Salvator merianae) within their invasive range, it is important that management actions are based on species' biology. We estimated tegu percentage fat and body condition in native (Cordoba, Argentina) and non-native (South Florida, United States) populations and identified biological, temporal, and environmental variables that influence tegu body condition in South Florida. Large adult tegus in Cordoba had larger fat reserves than tegus in South Florida. However, body condition values were highly similar between the native and non-native range throughout the year, showing a well-adapted tegu population to South Florida environmental conditions. Generalized additive mixed models (size estimate = 2.67) showed very strong (p-value < 0.001) to moderate (p-value <0.01) evidence of Julian day, minimum temperature, and percentage fat individually affecting tegu body condition in South Florida (deviance explained 37%). The direction and magnitude of univariate effects varied from positive linear relationship (minimum temperature) impacting body condition up to 18% to negative (Julian day) and positive (percentage fat) monomodal relationships impacting body condition up to 24% and 6%, respectively. Our results provide insights as to how adaptable tegus are physiologically to novel environments and their capability to maintain body condition that is similar to, or better than that of native individuals. These findings can inform management in Florida by identifying seasonal windows when tegus' activity and condition may make them more susceptible to targeted removal.

Eray Can Elumar, Cem Tekin, Osman Yagan

Recent advances in large language models (LLMs) have enabled automated dataset labeling with minimal human supervision. While majority voting across multiple LLMs can improve label reliability by mitigating individual model biases, it incurs high computational costs due to repeated querying. In this work, we propose a novel online framework, Cost-aware Majority Voting (CaMVo), for efficient and accurate LLM-based dataset annotation. CaMVo adaptively selects a subset of LLMs for each data instance based on contextual embeddings, balancing confidence and cost without requiring pre-training or ground-truth labels. Leveraging a LinUCB-based selection mechanism and a Bayesian estimator over confidence scores, CaMVo estimates a lower bound on labeling accuracy for each LLM and aggregates responses through weighted majority voting. Our empirical evaluation on the MMLU and IMDB Movie Review datasets demonstrates that CaMVo achieves comparable or superior accuracy to full majority voting while significantly reducing labeling costs. This establishes CaMVo as a practical and robust solution for cost-efficient annotation in dynamic labeling environments.

Thanasis Lianeas, Marios Mertzanidis, Aikaterini Nikolidaki

In Facility Location problems there are agents that should be connected to facilities and locations where facilities may be opened so that agents can connect to them. We depart from Uncapacitated Facility Location and by assuming that the connection costs of agents to facilities are congestion dependent, we define a novel problem, namely, Facility Location for Congesting (Selfish) Commuters. The connection costs of agents to facilities come as a result of how the agents commute to reach the facilities in an underlying network with cost functions on the edges. Inapproximability results follow from the related literature and thus approximate solutions is all we can hope for. For when the cost functions are nondecreasing we employ in a novel way an approximate version of Caratheodory's Theorem [5] to show how approximate solutions for different versions of the problem can be derived. For when the cost functions are nonincreasing we show how this problem generalizes the Cost-Distance problem [38] and provide an algorithm that for this more general case achieves the same approximation guarantees.

Chethan Bhateja, Joseph O'Brien, Afnaan Hashmi et al.

In machine learning, metric elicitation refers to the selection of performance metrics that best reflect an individual's implicit preferences for a given application. Currently, metric elicitation methods only consider metrics that depend on the accuracy values encoded within a given model's confusion matrix. However, focusing solely on confusion matrices does not account for other model feasibility considerations such as varied monetary costs or latencies. In our work, we build upon the multiclass metric elicitation framework of Hiranandani et al., extrapolating their proposed Diagonal Linear Performance Metric Elicitation (DLPME) algorithm to account for additional bounded costs and rewards. Our experimental results with synthetic data demonstrate our approach's ability to quickly converge to the true metric.

Sarah Schnyder, Josua Dubach, Lucas Dall’Olio et al.

Abstract Immersive virtual reality (IVR), as presented through headsets, is becoming increasingly relevant in education, especially in STEM fields, due to its potential to make complex concepts more accessible. Despite empirical evidence revealing the potential of IVR, its adoption in primary schools remains low. The objective of this paper is to examine the level of acceptance and intention to use IVR among different stakeholders in Swiss primary schools. To achieve this, we conducted online questionnaires with directors (n = 37), teachers (n = 70), and parents/caregivers (n = 202). The results indicated considerable variability in the responses, with a general resistance to integrating IVR being detected across all groups. Common reasons for this resistance included high costs, technical challenges, and uncertainty about IVR’s pedagogical value. However, we found that individuals who saw value in IVR were more likely to express the intention to integrate it into their schools. We discuss the importance of bridging the gap between IVR research and the reality of school implementation through targeted projects to encourage its integration into primary education.

Jim Kioko Katu, Tamás Tóth, László Varga

Feed accounts for up to 80% of poultry production costs, with high-quality grains such as soybean meal and corn traditionally serving as primary ingredients. However, increasing costs and competition for these grains have driven interest in low-grade and unconventional feed ingredients, including by-products like rapeseed meal and cottonseed meal. These alternatives are often constrained by high fiber content, anti-nutritional factors, and reduced nutrient bioavailability. Fermentation has emerged as a promising strategy to address these limitations, enhancing digestibility, palatability, and antioxidant properties while degrading harmful compounds such as tannins, trypsin inhibitors, and free gossypol. Solid- and liquid-state fermentation techniques utilize microbial inoculants, including lactobacilli and <i>Bacillus</i> species, to enzymatically break down complex macromolecules, thereby releasing essential nutrients. When combined with pretreatments like enzymatic hydrolysis, fermentation significantly improves the nutritional quality of feed ingredients while reducing costs without compromising poultry health or performance. This review examines the mechanisms, benefits, and challenges of fermentation techniques in poultry feed production, underscoring the importance of further research to optimize fermentation parameters, identify novel microbial strains, and ensure scalability and safety in industrial applications.

Jinhua Wang, Nengzhong Lei, Xiaolin Tang et al.

Taking the shield construction of Xiamen Metro Line 2 tunnel side-crossing the Tianzhushan overpass and under-crossing the Shen-Hai Expressway as the engineering background, FLAC3D 6.0 software was used to examine the deformation of adjacent structures based on shield construction parameters in upper-soft and lower-hard strata. The reliability of the numerical simulation results was verified by comparing measured and predicted deformations. The study results indicate that deformation of the pile will occur during the construction of the tunnel shield next to the pile foundation. The shape of the pile deformation curve in the horizontal direction is significantly influenced by the distance from the pile foundation to the adjacent tunnel’s centerline, as well as by soil bin pressure, grouting layer thickness, and stress release coefficient. During the tunnel shield construction beneath the expressway, increasing the soil bin pressure, the grouting layer thickness, and reducing the stress release coefficient can effectively minimize surface deformation and differential settlement on both sides of the deformation joints between the bridge and the roadbed. The practice shows that, by optimizing shield construction parameters in upper-soft and lower-hard strata, the deformation of nearby bridges and pavements can be kept within allowable limits. This is significant for reducing construction time and costs. The findings offer useful references for similar projects.

Zhiyi Ye, Xiang Yuan

Facing the critical challenge of partial maritime network disruptions caused by escalating natural disasters, geopolitical conflicts, and infrastructure failures, this research develops a novel methodology and optimization model for the rapid establishment of effective temporary shipping networks. The proposed model offers a cost-effective and operationally feasible network design by integrating shipping network resilience with emergency response capabilities. Specifically, the model introduces three innovative dimensions: (1) network discrepancy degree, which quantifies structural deviations from original configurations and minimizes cascading disruptions; (2) time-sensitive costs, addressing cargo delays, vessel demurrage, and supply chain penalties; and (3) carbon emission constraints, aligning with global decarbonization goals. A hub-and-spoke network variant is employed to dynamically reroute flows through resilient hubs during port failures. To solve this NP-hard problem, custom operators for meta-heuristic algorithms (SA, GA and PSO) are designed and enhanced through Bayesian hyperparameter optimization, ensuring algorithmic adaptability to real-time disruptions. A case study analyzing real Asia-Europe shipping scenarios demonstrates the model’s effectiveness: it reduces total costs by 37.36 % compared to traditional partial-adjustment models that neglect carbon emissions and network variability. Specifically, transportation costs decrease by 12.3 %, carbon emissions drop by 8.7 %, and congestion-induced penalties are minimized by 19.1 % through dynamic capacity allocation and multipath redundancy. The framework maintains 92.4 % operational efficiency during simulated port disruptions, outperforming benchmarks in both computational speed (42 % faster convergence) and solution quality (0.57 % error from the optimal). This study provides actionable strategies for shipping companies to enhance supply chain resilience while supporting industry compliance with evolving environmental regulations.

Jiasong CHEN, Xuefeng BAI, Guijiu WANG et al.

ObjectiveGiven that most salt rock strata in China consist of thin-layered salt formations, conventional single-well and single-cavity construction technologies are no longer adequate for the efficient construction of large-size salt cavities. In this context, the application of horizontal multi-step cavity-building technology for salt cavern gas storage can enhance the construction of salt cavities with expanded volumes in salt rock strata of limited thickness. MethodsThis study explored the influence of key parameters on the final shapes of cavities created through the horizontal multi-step cavity-building approach and analyzed both the cavity shape and the construction process from an engineering perspective, thus presenting recommended values for these key parameters. A physical simulation experimental setup was designed to examine cavity expansion patterns during horizontal multi-step cavity construction. Subsequent experiments incorporated various cavity-building parameters to generate horizontal cavities of different shapes. Finally, 3D scanning technology was employed to create complete 3D cavity models based on the cavities obtained from the experiments through mirroring operations. ResultsThe following results were derived from analyzing these 3D cavity models corresponding to various cavity-building parameters. For cavities with equal volumes, variations in water injection flow rates had a significant influence on their height, length, and maximum width. Tubing withdrawal distances had a major impact on the shape of the cavity roofs, while their effect on the overall size of the cavities was relatively minor. Additionally, the air cushion used during cavity construction to protect the roofs resulted in “flat top” shapes, which not only affected the stability of the cavities but also increased the economic costs for cavity construction. ConclusionWater injection rates ranging from 160 m3/h to 240 m3/h are considered rational for horizontal multi-step cavity building. It is recommended to use small tubing withdrawal distances. Additionally, continuous injection of dissolution inhibitors during construction for cavity roof protection is not advised. The research results offer valuable references and guidance for shape design and process parameter optimization of cavities using the horizontal multi-step construction approach for salt cavern gas storage.

Diptangshu Sen, Jingyan Wang, Juba Ziani

We study a two-sided online data ecosystem comprised of an online platform, users on the platform, and downstream learners or data buyers. The learners can buy user data on the platform (to run a statistic or machine learning task). Potential users decide whether to join by looking at the trade-off between i) their benefit from joining the platform and interacting with other users and ii) the privacy costs they incur from sharing their data. First, we introduce a novel modeling element for two-sided data platforms: the privacy costs of the users are endogenous and depend on how much of their data is purchased by the downstream learners. Then, we characterize marketplace equilibria in certain simple settings. In particular, we provide a full characterization in two variants of our model that correspond to different utility functions for the users: i) when each user gets a constant benefit for participating in the platform and ii) when each user's benefit is linearly increasing in the number of other users that participate. In both variants, equilibria in our setting are significantly different from equilibria when privacy costs are exogenous and fixed, highlighting the importance of taking endogeneity in the privacy costs into account. Finally, we provide simulations and semi-synthetic experiments to extend our results to more general assumptions. We experiment with different distributions of users' privacy costs and different functional forms of the users' utilities for joining the platform.

Samuel Howard, George Deligiannidis, Patrick Rebeschini et al.

Within the field of optimal transport (OT), the choice of ground cost is crucial to ensuring that the optimality of a transport map corresponds to usefulness in real-world applications. It is therefore desirable to use known information to tailor cost functions and hence learn OT maps which are adapted to the problem at hand. By considering a class of neural ground costs whose Monge maps have a known form, we construct a differentiable Monge map estimator which can be optimized to be consistent with known information about an OT map. In doing so, we simultaneously learn both an OT map estimator and a corresponding adapted cost function. Through suitable choices of loss function, our method provides a general approach for incorporating prior information about the Monge map itself when learning adapted OT maps and cost functions.

Mokhtar Aly, Emad A. Mohamed, Emad M. Ahmed

Modern electrical power grids are characterized by a significant increase in renewable energy generation, often complemented by energy storage systems. Integrating these storage devices helps to offset the challenges posed by the decreased system inertia resulting from high levels of renewable energy penetration. However, the limited capacity of these storage units, attributed to their high costs, necessitates incorporating controlled loads such as high voltage air conditioning (HVAC), compressors, chillers, or pumps to enhance frequency stability through demand response (DR). This paper proposes a novel control scheme containing a dual-hybrid fractional controller for load frequency control (LFC) and DR. The structure of this control scheme comprises two components, each utilizing fractional order tilt-integral-derivative alongside a fractional filter termed D-Hyd controller. One component handles the LFC through the area control error (ACE) signal, and the other handles the DR through the area frequency deviation. Moreover, a new application of the exponential distribution optimization (EDO) algorithm is developed to determine the parameters of the proposed controllers concurrently. The effectiveness of the proposed approach is evaluated through case studies involving two interconnected areas with photovoltaic and wind energy sources. Various test scenarios and comparisons with existing methods in the literature are presented to assess the performance of the proposed controller and optimization algorithm. Moreover, practical uncertainties are considered in the test scenarios to evaluate the stability and robustness of the proposed schemes. Compared to recent control methods in the literature, the proposed control scheme offers more flexibility and resiliency in preserving system stability.

R. Kaplan, R. Cooper

Jin Hyuk Choi, Jetlir Duraj, Kim Weston

We prove the existence of a continuous-time Radner equilibrium with multiple agents and transaction costs. The agents are incentivized to trade towards a targeted number of shares throughout the trading period and seek to maximize their expected wealth minus a penalty for deviating from their targets. Their wealth is further reduced by transaction costs that are proportional to the number of stock shares traded. The agents' targeted number of shares is publicly known, making the resulting equilibrium fully revealing. In equilibrium, each agent optimally chooses to trade for an initial time interval before stopping trade. Our equilibrium construction and analysis involves identifying the order in which the agents stop trade. The transaction cost level impacts the equilibrium stock price drift. We analyze the equilibrium outcomes and provide numerical examples.

Rebecca Balcom, Gumataw Kifle Abebe, Emmanuel K. Yiridoe et al.

IntroductionHow food is produced, processed, distributed, and consumed significantly impacts the sustainability of food supply chains. Short food supply chains (SFSCs) have been promoted as an alternative approach to offer sustainable solutions. However, empirical studies provide mixed evidence, and the findings greatly vary based on context. This study explores the social, economic, and environmental sustainability practices in Atlantic Canada's SFSCs from the perspective of farm businesses (producers).MethodsA semi-structured survey was conducted among 64 farmers/producers who participated in Atlantic Canadian SFSCs. Participants were asked what channel they used to sell their products and how far this location is in comparison to the production location if sold to an intermediary, how they believe they could better to improve the sustainability of their production methods, what barriers stood in their way of implementation, and how supply chain supporters could help achieve their sustainability goals.ResultsThe findings show that most farm businesses linked to SFCSs have applied ecologically sound production methods such as organic farming, IPM, or other sustainable practices, including regenerative agriculture and no-till farming. Over two-thirds of farm businesses applied sustainable practices such as pasture rotations, green fertilizers, low-carbon couriers, locally sourced inputs, and compostable or recyclable packaging materials. Farm businesses in the Atlantic Provinces highly value the social sustainability of SFSCs, followed by economic and environmental sustainability. Most farm businesses linked to SFSCs were robust to supply- and demand-side shocks, registered a low number of layoffs and fast recovery of operations, and increased their profits during COVID-19 compared to pre-COVID-19 levels. Yet, several barriers remain, the most important ones being high capital costs and longer payback periods. Other barriers include inconsistent inter-provincial trading restrictions, lack of qualified workers and shrinking agricultural land base.DiscussionSFSCs in Atlantic Canadian SFSCs have implemented several sustainable practices in their production and distribution systems. Most of the farm businesses linked to SFSCs are small, are focused on specific product groups, target small towns or rural areas, and rely on direct-on farm sales to individual customers, and thus can play a crucial role by complementing longer food supply chains. By taking SFSCs in Atlantic Provinces as a case, this study expands our understanding of recent efforts and challenges local producers face to adopt sustainable practices in their production and distribution systems.

Ephrem Abathun Ayalew, Ditaba David Mphuthi, Kholofelo Lorraine Matlhaba

Abstract Background One of the major challenges for healthcare professionals relates to awareness of patients’ preferences relative to how and when to break bad news and how much information should be disclosed in the eventuality of a serious medical diagnosis or prognosis. On occasions, a serious medical diagnosis or prognosis is withheld from the patient. There is a scarcity of evidence about cultural preferences regarding breaking bad news in the palliative care setting in Ethiopia. Therefore, it is necessary to understand the surrounding cultural issues to properly convey bad news. The purpose of the study was to explore Ethiopian patients’ cultural preferences for receiving bad news in a palliative care setting. Methods A qualitative research approach and nonprobability, purposive sampling method were applied. In-depth interviews were employed to collect data from eight patients who were diagnosed with cancer and cancer with HIV/AIDS during the time of data collection. Thematic analysis was applied to identify themes and subthemes. The data were transcribed verbatim and analysed using ATLAS.ti 22 computer software. Results The following three themes emerged and are reported in this study: (1) Perceptions about life-threatening illness: religious values and rituals are essential for establishing perspectives on life-threatening illnesses and preferences in receiving bad news. (2) Experiences with life-threatening illness: study participants’ experience with the method of breaking bad news was sad, and they were not provided with sufficient details about their medical condition. Making appropriate decisions, fulfilling the ordinance of religious faith, and avoiding unnecessary costs were outlined as benefits of receiving bad news. (3) Preferred ways of breaking bad news; the findings revealed that incremental, amiable and empathic methods for delivering bad news were preferred. It was suggested that the presence of family members is crucial when receiving bad news. Conclusion Patients choose to be told about their medical conditions in the presence of their family. However, the patient’s needs for receiving bad news were unmet. Patients should be involved in the treatment decision process. Delivery of bad news needs to tailor the preferred methods, cultural values, and religious beliefs. Delivering bad news according to the patients’ preferences helps to fulfil their wishes in palliative care.