Low bearing capacity soils may pose serious construction concerns such as reduced bearing capacity and excessive hydro-associated volume changes. Proper soil remediation techniques must be planned and implemented before commencing any construction on...
The construction sector has a very high share in solving the energy demand of the world and global warming problems. Therefore, it had to increase studies on building materials-based heat storage and thermal insulation. Foam concrete is one of them,...
The present study mainly investigates the synthesis of calcined marl-based geopolymeric cement under different synthesis conditions including NaOH concentration, sodium silicate (SS)/sodium hydroxide (SH) mass ratios, solid (S)/liquid (L) mass ratios...
Modern materials science is aimed towards abandoning Portland cement in the production of building materials. The scientific novelty of this study lies in its being the first time a comprehensive study of the structure formation of alkali-activated m...
This research explores the modification of marl by the incorporation of diopside (CaMgSi2O6) to develop a composite material with improved dielectric properties, while addressing environmental and economic challenges through the use of abundant natur...
The rapid integration of electric vehicles (EVs) and decentralized renewable energy sources is transforming urban power systems, while simultaneously increasing the complexity of real-time coordination across charging infrastructure, distributed ener...
UAV, mounted aerial base stations offer remarkable deployment flexibility for 6G Non Terrestrial Networks (NTNs), yet their hovering energy demands present a critical sustainability bottleneck, particularly as network topologies continuously evolve i...
The rapid growth of Internet of Things (IoT) and Industrial IoT applications has intensified the demand for low-latency and reliable computation support for deadline-constrained periodic real-time tasks. While unmanned aerial vehicles (UAVs) enabling...
Cyber wargaming serves as a core tool for simulating cyber confrontations and supporting operational decision verification. Existing multi-agent methods face issues such as the absence of cross-level mechanisms and poor adaptability to dynamic enviro...
The deployment of autonomous robots in construction remains constrained by the complexity and variability of real-world environments. Conventional programming and single-agent approaches lack the adaptability required for dynamic multi-robot operatin...
This study investigates the mechanical performance, freeze–thaw durability, and microstructural characteristics of marl soil treated with iron and steel cooling water sludge (CWS) and polypropylene fibers (PPFs). The CWS used in this study is a...
Identifying suitable local materials for civil engineering is a key challenge for geotechnical engineers. This study characterises the physico-mechanical properties of Taza marl-limestone (Morocco), focusing on the correlation between uniaxial compre...
This study proposes a Cooperative Traffic Controller System (CTS), an urban eco-network control system that leverages Multi-Agent Reinforcement Learning (MARL), to address urban road congestion and environmental pollution. The proposed system synergi...
This review summarizes the major research and scientific findings on the relevance of using calcined marl as supplementary cementitious material in developing eco-friendly cement for the next generation. Incorporation of calcined marl into cement can...
The optimal control of complex energy systems via Bellman’s principle of optimality quickly becomes difficult for high-dimensional, path-dependent dynamics because the state space grows exponentially with each time step. We propose a computatio...
The coupling of quantum computing with multi-agent reinforcement learning (MARL) provides an exciting direction to tackle intricate decision-making tasks in high-dimensional spaces. This work introduces a new quantum-inspired multi-agent reinforcemen...
Centralized UAV logistics controllers can achieve strong navigation performance in controlled settings, but they do not capture key deployment factors in crowdsourcing-enabled emergency logistics, where heterogeneous UAV owners participate with unrel...
This paper presents a cooperative highway platooning strategy that integrates Multi-Agent Reinforcement Learning (MARL) with Proximal Policy Optimization (PPO) to effectively manage the complex task of merging. In modern transportation systems, plato...
Cyber–Physical Systems (CPS), including smart grids and industrial control networks, must maintain secure and stable operations despite increasingly adaptive cyber threats. Existing moving target defense (MTD) approaches often rely on fixed rec...
The effects of compaction on soil shrinkage behavior need to be considered for engineering long-term durable mineral liners of landfill capping systems. For this purpose, a new three-dimensional laser scanning device was coupled with a mathematical-e...
This research investigates the seasonal ground heave/settlement of an area covered by an expansive soil of Cyprus called Nicosia marl, highlighting the degree of influence of the main causal factors. For this purpose, existing geotechnical data from...
To tackle frequent voltage violations in distribution networks with high photovoltaic penetration ratios, voltage regulation methods that dispatch the active and reactive powers of PV panels are widely studied. Because of the costly global communicat...
Multi-Agent Reinforcement Learning (MARL) faces key challenges in credit assignment and the curse of dimensionality as agent numbers grow. In cooperative settings, uniform treatment of agents often exacerbates these issues. We argue that an agent&rsq...
Modern Software-Defined Wide Area Networks (SD-WANs) require adaptive controller placement addressing multi-objective optimization where latency minimization, load balancing, and fault tolerance must be simultaneously optimized. Traditional static ap...
The intelligent warehouse is a modern logistics management system that uses technologies like the Internet of Things, robots, and artificial intelligence to realize automated management and optimize warehousing operations. The multi-robot system (MRS...
Although multi-agent reinforcement learning (MARL) has achieved significant success in various domains, its deployment in real-world scenarios remains challenging, particularly in communication-constrained environments involving multi-task coupling....
The paper presents new reactive materials, namely marl and travertine, and their thermal modifications and the Polonite® material, analyzing their phosphorus removal from water and wastewater by sorption. Based on the experimental data, an analys...
Controller placement in software-defined wide area networks (SD-WANs) is commonly optimized assuming continuously available controllers, leaving the control plane vulnerable to overload and abrupt reassignment after controller unavailability. This pa...
Biofilm-associated bacterial infections are the major reason for treatment failure in many diseases including burn trauma infections. Uncontrolled inflammation induced by bacteria leads to materiality, tissue damage, and chronic diseases. Specialized...
Multi-Agent Reinforcement Learning (MARL) presents a promising approach for addressing the complexity of Traffic Signal Control (TSC) in urban environments. However, existing platforms for MARL-based TSC research face challenges such as slow simulati...
Tight marl is a special type of unconventional oil and gas resource, and the study on its reservoir characteristics and controlling factors is of immense scientific significance. In this paper, 113 core samples of marl from Gouxi Area, Eastern Sichua...
The increasing complexity of urban traffic networks has highlighted the potential of Multi-Agent Reinforcement Learning (MARL) for Traffic Signal Control (TSC). However, most existing MARL methods assume homogeneous observation and action spaces amon...
Future network services must adapt to the highly dynamic uplink and downlink traffic. To fulfill this requirement, the 3rd Generation Partnership Project (3GPP) proposed dynamic time division duplex (D-TDD) technology in Long Term Evolution (LTE) Rel...
Cooperative multi-agent reinforcement learning (MARL) is hard when rewards are sparse. This is an evaluation study built around a negative result. We study CHARM (Cooperative Hindsight-Augmented Role-conditioned Memory), a four-part memory layer that...
The soil shrinkage behavior of mineral substrates needs to be considered for engineering long-term durable mineral liners of landfill capping systems. For this purpose, a novel three-dimensional laser scanning device was coupled with (a) a mathematic...
The limestone–marl cliffs along France’s northern coast, particularly from Arromanches-les-Bains to Longues-sur-Mer, are experiencing significant erosion. This study investigates cliff retreat mechanisms and classifies instability types t...
Byzantine-resilient multi-agent reinforcement learning (MARL) matters in networked cyber-physical systems, where corrupted sensor messages degrade formation accuracy and execution-time safety. This paper presents an evaluation and audit study: a mult...
Coniolo and Brusaschetto, are two small towns located in the Monferrato area of the Alessandria Province, northern Italy. These communities have similar histories related to development and subsequent abandonment of marl quarry activity that began mo...
Unmanned aerial vehicle (UAV) confrontation scenarios play a crucial role in the study of agent behavior selection and decision planning. Multi-agent reinforcement learning (MARL) algorithms serve as a universally effective method guiding agents towa...
The “yellow cobblestones” of Sofia are considered one of the city’s symbols. This high-quality clinker was developed in Budapest in the late 19th century by using a local marl. Since this paving was declared part of Sofia’s cu...
The simple and labor-intensive tasks of workers on the job site are rapidly becoming digital. In the work environment of logistics warehouses and manufacturing plants, moving goods to a designated place is a typical labor-intensive task for workers....
While the adoption of swarm robotics is accelerating in the dynamic and uncertain environment of the construction industry, conventional path-planning algorithms based on shortest physical distance induce severe bottlenecks and schedule delays during...
Coordinating multiple unmanned aerial vehicles (UAVs) for cooperative missions requires agents that perceive their environment, reason about objectives, and generate joint actions. Vision–language–action (VLA) models unify these capabilit...
Autonomous vehicles (AVs) are expected to operate safely and efficiently in complex urban environments characterized by dynamic and uncertain elements such as pedestrians, cyclists and adverse weather. Although current neural network-based decision-m...
Unmanned Aerial Vehicles (UAVs) have become increasingly important in various applications, including environmental monitoring, disaster response, and surveillance, due to their flexibility, efficiency, and ability to access hard-to-reach areas. Effe...
Microbial populations involved in forming the distinctive precipitates of S, Fe, Mn, and Ca in the San Diego River watershed reflect an interplay between the mineralogy of the rocks in the watershed, sparse rainfall, ground- and surface-water anoxia,...
Cube-shaped automated storage and retrieval systems (AS/RS) enhance storage density by organizing inventory in a three-dimensional grid. However, they face two operational bottlenecks: (1) digging—the temporary removal and restacking of upper b...
Nowadays, the global brick industry utilizes billions of cubic meters of clay soil annually, resulting in the massive consumption of non-renewable resources. This study explores the viability of utilizing red marl from phosphate mining waste rocks fo...
Weathered marl hillslopes fail repeatedly across peri-urban Morocco, yet engineers investigating them rarely know which soil or geometric property most deserves their limited testing budget. This study answers that question for the landslide-prone sl...
Energy efficiency remains a major challenge in IoT-enabled wireless sensor networks because sensor nodes operate with limited battery capacity and are often deployed in environments where battery replacement is impractical. Existing clustering and ro...
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