This paper studies how hidden, stochastic continuation of informed participation shapes price discovery in a two-period Kyle-type market. Hidden participation separates two analytical questions that coincide in the standard Gaussian-linear model. Con...
Boron Neutron Capture Therapy (BNCT) is an emerging radiation treatment for cancer, and its challenges are being explored. Systems capable of capturing real-time observations of this treatment’s effectiveness, particularly BNCT-SPECT methods th...
25 August 2022
Colorectal cancer is among the leading causes of cancer worldwide. Processed meat was known to be positively associated with a higher risk of gastrointestinal cancer. This study focused on the long-time trends of colorectal cancer mortality attributa...
Although a large number of mortality projection models have been proposed in the literature, relatively little attention has been paid to a formal assessment of the effect of model uncertainty. In this paper, we construct a Bayesian framework for emb...
An organization’s strategic objectives are accomplished through portfolios. However, the materialization of portfolio risks may affect a portfolio’s sustainable success and the achievement of those objectives. Moreover, project interdepen...
One common problem in the construction industry is project cost overrun. Cost overrun can have significant impacts on financial profitability, project completion, project quality, and stakeholder satisfaction. The average percentage of construction p...
Based on the Copula theory, a multiple correlation analysis model for the operation safety risks of long-distance water diversion projects was established. Combined with Bayesian network reasoning, a polynomial regression analysis, and other techniqu...
Complex construction projects are characterized by a large scale, high dynamics, many unknown risks, high complexity, etc., which often result in serious consequences, such as schedule delays, cost overruns, and uncontrolled objectives. Organizationa...
In China, high-speed rail projects have brought huge social and economic benefits to the affected regions after they are completed. However, the potential externalities of such projects cause competition for the station during the project planning ph...
The problem with evaluating investment projects is that there are many factors that determine the degree of their successful conclusion. Consequently, there has been an active debate for years as to which critical success factors (CSFs) contribute mo...
Public-Private Partnerships (PPPs) are essential for accelerating sustainable development as they combine public goals with private sector efficiency, leading to improved service delivery and less financial burden on governments. It is a project deli...
The study investigates the hierarchical uncertainty of multi-ensemble hydroclimate projections for the Southern Hills-Gulf region, USA, considering emission pathways and a global climate model (GCM) as two main sources of uncertainty. Forty projectio...
The schedule is a critical factor in the development of prefabricated buildings. This paper establishes the schedule risk influencing factors for prefabricated building projects across five dimensions—design, production, transportation, install...
10 December 2019
In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risk...
Megaproject Social Responsibility (MSR) is widely acknowledged as contributing to project performance. However, the effect of Megaproject Social Responsibility Behavior (MSRB) implemented by organizations participating in construction on project perf...
Coastal zones in arid regions are particularly vulnerable to climate change because of their limited sediment supply and high sensitivity to marine and aeolian forces. This study provides probabilistic projections of coastal evolution for a 130 km se...
Inter-basin water transfer projects (IBWTPs) play a crucial role in addressing the uneven spatial and temporal distribution of water resources and ensuring water security in the receiving areas. However, these projects are subject to various risk fac...
The wave of digital transformation has driven profound changes in construction mode. As the core driving force for the sustainable development of digital construction, organizational capabilities have gradually attracted widespread attention from bot...
This study investigated the strength and limitations of two widely used multi-model averaging frameworks—Bayesian model averaging (BMA) and reliability ensemble averaging (REA), in post-processing runoff projections derived from coupled hydrological...
Long-term energy system planning depends on projections of future wind turbine characteristics, yet existing approaches rely on either costly expert elicitation or deterministic trend extrapolation without formal uncertainty quantification. We presen...
Aiming at the state estimation problem of nonlinear systems (NLSs), the traditional typical nonlinear filtering methods (e.g., Particle Filter, PF) have large errors in system state, resulting in low accuracy and high computational speed. To perfect...
This study assesses the informational usefulness of several uncertainty metrics in predicting the monetary policy and actual economic activity of Tunisia. We use a Bayesian time-varying vector autoregressive (VAR) model to identify uncertainty shocks...
Understanding the demographic mechanisms underlying the decline of endangered tree species is essential for developing effective conservation strategies. This study aimed to quantify the population trajectory and its demographic drivers in the Korean...
The aging population in China highlights the significance of elderly long-term care (LTC) services. The number of people aged 65 and above increased from 96 million in 2003 to 150 million in 2016, some of whom were disabled due to chronic diseases or...
Water project and watershed management is currently being reengineered under digital twin schemes in China through pilot projects. An evaluation on pilot reengineering is important for its further implementation and improvement. This paper investigat...
The construction of buildings invariably involves time and costs, and disruptions impact ongoing construction projects. Crisis situations in management strategies, structural confusion, and financial miscalculations often arise due to misguided decis...
The “trillion-dollar era” of megaprojects has increased the demand for the scope of mega infrastructure. To address the requirement for high-quality “investment, construction, and operation” integration, the EPC and PPP models...
Urban flooding, intensified by climate change, poses significant threats to sustainable development, necessitating accurate precipitation projections for effective risk management. This study utilized Bayesian Model Averaging (BMA) to optimize CMIP6...
This study adapts the United Nations’ methodology for national probabilistic population projections to subnational contexts. The Bayesian approach used by the UN addresses data collection complexities effectively. By applying hierarchical model...
“Not In My Back Yard” (NIMBY) conflicts have emerged as a significant challenge in the siting and construction of power grid projects. Traditional risk management methods are often inadequate for addressing the complex interactions betwee...
This paper proposes a parallel monitoring method for plant-wide processes by integrating mutual information and Bayesian inference into a global-local preserving projections (GLPP)-based multi-block framework. Unlike traditional multivariate statisti...
Statistical models for hydrologic simulation are a common choice among researchers particularly when catchment information is limited. In this study, we adopt a new statistical approach, namely Bayesian regression with multivariate linear spline (BML...
Construction projects are high-risk environments characterized by workforce mobility, fragmented operations, schedule pressure, and multilayer subcontracting. This study examines how team safety climate and workgroup-shared perceived organizational s...
The implementation of railway infrastructure construction projects including sustainable development goals is a complex process characterized by a significant extension of individual investment stages. The need for additional works has a big impact o...
Background: Acute hepatitis E (AHE) poses escalating risks to older adults (≥65 years), compounded by immunosenescence and comorbidities. Using Global Burden of Disease (GBD) 2021 data, this study analyzes global AHE burden, trends, and projection...
This study presents a comprehensive review of risk assessment and scheduling techniques in highway construction, addressing the complex interplay between uncertainty, project planning, and decision-making. The research critically reviews key risk ass...
In Water Resources Planning and Management, decision makers, although unsure of future outcomes, must take the most reliable and assuring decisions. Deterministic and probabilistic prediction techniques, combined with optimization tools, have been wi...
Effective control of collusive behavior in the government bidding process is a prerequisite for promoting the high-quality development of social economy, consolidating the results of the anti-corruption struggle and the smooth operation of the projec...
Big data applications have tremendously increased due to technological developments. However, processing such a large amount of data is challenging for machine learning algorithms and computing resources. This study aims to analyze a large amount of...
The rise in global temperatures and increased extreme weather events, such as heatwaves, underscore the need for accurate regional projections of daily maximum temperature (Tmax) to inform effective adaptation strategies. This study develops the CNN-...
Reliable cost estimation during the preconstruction phase remains challenging because decisions must be made with limited project information, substantial uncertainty, and project-specific cost drivers. This study proposes and empirically evaluates a...
The successful implementation of project portfolios (PP) calls for effective risk management, in which selecting optimal risk response strategies help to reduce the impact of risk. Project portfolio risks (PPRs) exhibit causality and time dependency...
Logarithmic Scaling and Normalization (LSN) of power system measurements has recently shown potential for improving modal representations and visualizing inter-area dynamic behavior. However, the logarithmic base used in LSN is commonly selected empi...
Safety, progress, and investment risks are correlated during the construction period of large-scale water transfer projects. However, previous studies have only considered individual risk factors, overlooking the potential systemic risk posed to safe...
To address ecological threats such as land degradation in the karst regions, several ecological restoration projects have been implemented for improved vegetation coverage. Forests are the most important types of vegetation. However, the evaluation o...
Radar mainlobe jamming has attracted considerable attention in the field of electronic countermeasures. When the direction of arrival (DOA) of jamming is close to that of the target, the conventional antijamming methods are ineffective. Generally, ma...
Fire plays a critical role in both the formation and degradation of ecosystems; however, there are still significant uncertainties in the estimation of burned areas (BAs). This study systematically evaluated the performance of ten global climate mode...
Background/Objectives: Alopecia areata (AA) is a common autoimmune disorder with substantial psychosocial impact, but contemporary assessments of its epidemiology and future burden remain limited. We aimed to comprehensively characterize the epidemio...
With the increasing complexity and dimensionality of datasets in statistical research, traditional methods of identifying interactions are often more challenging to apply due to the limitations of model assumptions. Logic regression has emerged as an...
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