This study presents a multi-index performance system that is systematically used to assess the binder synergy and fly ash reactivity of eco-sustainable cementitious composite (ESCC) using the Strength Activity Index (SAI) as a reference in line with...
The rapid expansion of the express delivery sector, driven by the growth of e-commerce, has increased the importance of effective complaint management as an integral component of service quality and consumer protection. Although operational service p...
Distributed generation (DG) sources play a special role in the operation of active energy networks. The microgrid (MG) is known as a suitable substrate for the development and installation of DGs. However, the future of energy distribution networks w...
Seismic performance assessment of water distribution systems (WDSs) based on hydraulic simulation is essential for resilience evaluation of WDSs under earthquake disasters. The assessment is mainly to determine how the water supply will be affected d...
This study presents a multi-index performance approach that moves beyond the conventional reliance on compressive strength, offering a more holistic evaluation of nano-silica-enhanced binders in resource-efficient alkali-activated composites. Based o...
Thruster configuration dictates the hydrodynamic stability of underwater welding vehicles, yet standard design protocols rarely penalize undesired forces and moments that compromise precision. This study proposes a multi-index performance evaluation...
Typical seismic sway braces (SSBs) are composed of several bolted steel components. As the connecting bolts become loose, the stiffness and bearing capacity of SSBs decline from which their seismic performance degrades significantly. Based on the vib...
To overcome the inability of single life-based indices to represent the nonlinear degradation of asphalt-mixture bearing capacity, this study proposes a multi-index framework for splitting-fatigue damage characterization and residual-life estimation....
This study proposes an Index-Based Neural Network (IBNN) framework for the static analysis of truss structures, employing a Lagrangian dual optimization technique grounded in the force method. A truss is a discrete structural system composed of linea...
This research offers a fresh understanding of desertification in Turkmenistan by utilizing satellite remote sensing data and machine learning techniques. With 80% of its area covered by desert, Turkmenistan has particular difficulties as a result of...
Cassava is the sixth most important food crop globally, valued for its high starch accumulation in tuberous roots, which supports diverse applications in food processing and industrial production. Quality evaluation is vital for its utilization, yet...
Distributed coherent synthesis on dynamic platforms suffers from phase misalignment and significantly reduced synthesis efficiency due to navigation errors and communication delays. To address this challenge and dramatically enhance the synthesis eff...
Flavor profile and water dissolvability serve as core evaluation benchmarks for the quality of food and medicinal plant-derived instant granules. Currently, studies integrating flavor and dissolvability analysis to comprehensively characterize the ov...
To address the high dimensionality, redundancy, and noise interference present in wind turbine Supervisory Control and Data Acquisition (SCADA) data, as well as the limitations of conventional K-means algorithms—including excessive reliance on...
Reliable quantification of compound-drought risk under coupled climate change and land-use dynamics remains a critical challenge. This study employed the Ganjiang River Basin (80,948 km2) as a representative subtropical monsoon catchment, integrating...
Land degradation is a growing concern in arid and semi-arid regions, posing severe threats to ecosystem stability, agricultural productivity, and rural livelihoods due to the combined effects of natural processes and human activities. This study exam...
In order to address the challenges of limited accuracy in identifying non-meteorological clutter and the spatial overlap between meteorological and non-meteorological echoes in cloud radar observations under complex weather conditions, in this study,...
This study examines the comparative trade performance of India’s pharmaceutical industry vis-à-vis leading global pharmaceutical exporters, particularly the United States, Germany, and Switzerland, over the period 2005–2024, using...
Feed shortage and water scarcity critically constrain livestock production in semiarid regions, yet the interactive mechanism of growth by which planting density and mowing shape the trade-off between biomass yield and nutritional quality remain poor...
Water eutrophication poses a dual threat to ecological and human well-being. Gaining insight into the intricate dynamics of phytoplankton bloom phenology holds paramount importance in comprehending the complexities of aquatic ecosystems. Remote sensi...
Leaf nitrogen content (LNC) is an important physiological indicator for evaluating citrus nutritional status, photosynthetic capacity, and fertilization demand. However, conventional LNC determination mainly relies on field sampling and laboratory ch...
Through-going faults represent critical geological hazards that threaten the long-term operational safety of arch dams. Conventional studies predominantly rely on homogeneous material assumptions and static analysis, neglecting two essential characte...
In recent years, coal-fired power plants contribute the biggest part of power generation in China. Challenges of energy conservation and emission reduction of the coal-fired power plant encountering with a rapid growth due to the rising proportion of...
Accurate crop classification is essential for sustainable agriculture activities and food security studies. Recent advancements in remote sensing data acquisition and analysis techniques enable various solutions for cropland detection; however, relia...
As a highly heterogeneous and complex disease, the identification of cancer’s molecular subtypes is crucial for accurate diagnosis and personalized treatment. The integration of multi-omics data enables a comprehensive interpretation of the mol...
The growing pursuit of urban sustainability, liveability, and competitiveness has increased the need for comprehensive tools capable of assessing urban performance. However, existing city indices employ diverse conceptual frameworks, indicator sets,...
Without a well-defined energy management plan, achieving meaningful improvements in human lifestyle becomes challenging. Adequate energy resources are essential for development, but they are both limited and costly. In the literature, several solutio...
The stock market index future price forecasting is one of the imperative financial time series problems. Accurately estimated future closing prices can play important role in making trading decisions and investment plannings. This work proposes a new...
The concepts of resilience and sustainability appear multi-dimensional and correlated, depending on the context. Operational sustainability practices can enhance the resilience of a firm, and support its growth. This study aims at analyzing the impac...
To address the main challenges in thickness estimation of SiC epitaxial layers from infrared reflectance spectra, including refractive index dispersion, multi-beam interference, and spectral uncertainty, this study develops a physics-constrained inve...
This paper proposes a novel quantum image transmission framework to address the limitations of existing single-qubit time domain systems, which struggle with noise resilience and scalability. The framework integrates frequency domain processing with...
5 May 2020
A green manufacturing system is an important tool to realize green transformation of the manufacturing industry. The systematicness of green technology innovation as the key foundation of green manufacturing supports the entire huge green manufacturi...
The goal of this paper is to develop a quantitative resilience assessment framework for a supply chain system exposed to multiple risk factors. Most existing studies on supply chain resilience have primarily focused on assessing the system’s ab...
In a quest to solve the multi-objective optimal planning problem using a simple parameter-free metaheuristic algorithm, this paper establishes the recently proposed student psychology-based optimization (SPBO) algorithm as the most promising one, com...
A cascaded neural network framework is developed to solve the two-dimensional inverse scattering problem under transverse magnetic wave illumination. The framework employs a multi-stage deep learning architecture in which each sub-network iteratively...
Background/Objectives: Integrating multi-omics data for cancer prognosis remains a challenging problem in bioinformatics because molecular profiles are high-dimensional, heterogeneous, and structured by incomplete biological relationships. Pathway da...
The arrival of the era of big data for Earth observation (EO) indicates that traditional data management models have been unable to meet the needs of remote sensing data in big data environments. With the launch of the first remote sensing satellite,...
We propose a portfolio rebalance framework that integrates machine learning models into the mean-risk portfolios in multi-period settings with risk-aversion adjustment. In each period, the risk-aversion coefficient is adjusted automatically according...
The diversity of today’s malware and the conflicting criteria for predictive performance, computational efficiency, dependability, and interpretability have made the choice of a suitable malware detection model more complicated. Existing resear...
This study aims to evaluate the environmental performance of G7 countries using the Environmental Performance Index. To do this, we introduce a novel ranking multi-criteria method, Alternative Prioritization and Assessment System, for the first time...
The high-precision instance segmentation of tree saplings is a fundamental prerequisite for the high-throughput phenotypic analysis of individual seedlings in intelligent tree breeding and precision silviculture. However, sapling segmentation remains...
The significance of precise gold price forecasting is accentuated by its financial attributes, mirroring global economic conditions, market uncertainties, and investor risk aversion. However, predicting the gold price is challenging due to its inhere...
In response to the coexistence of multi-objective conflicts and environmental complexity in the renewal of contemporary urban industrial heritage, this study develops a simulation and decision-making methodology for architectural and environmental re...
Building atrium design is crucial to maintaining a sustainable built environment and providing thermal comfort to occupants. This study proposes a parametric framework to optimize the atrium’s geometry for environmental performance and thermal...
In modern aerospace systems, effective sensor optimisation is essential for ensuring reliable diagnostics, efficient resource allocation, and proactive maintenance. This paper presents Normalised Diagnostic Contribution Index (NDCI) integration into...
Proactive beam management is essential for high-mobility millimeter-wave communication systems, where transmission latency may cause beams selected from current observations to become mismatched with the optimal beams at future transmission times. Th...
Historic waterfront streets are not only an important component of urban public spaces but also highlight the distinctive features and historical contexts of the city. High-quality streetscape visual perception plays a crucial role in advancing the c...
Skin lesion segmentation is a primary step for skin lesion analysis, which can benefit the subsequent classification task. It is a challenging task since the boundaries of pigment regions may be fuzzy and the entire lesion may share a similar color....
Discontinuing ad creatives at an appropriate time is one of the most important ad operations that can have a significant impact on sales. Such operational support for ineffective ads has been less explored than that for effective ads. After pre-analy...
Achieving high fault-classification accuracy alone does not guarantee reliable autonomous operation under varying operating conditions, raising the need to assess prediction reliability and deployment readiness. This work proposes a resilience-orient...
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