The main factor determining the conduct of this study is the progress of urbanization and the steady growth of the urban population, which contribute to the intensification of multidimensional challenges related to climate, the environment, transport...
The main priority at wastewater treatment plants (WWTPs) is the attainment of a high quality of treated effluent ensuring the highly effective removal of pollutants and protecting the environment and public health. However, WWTPs are made of energy-i...
While hardware selection is widely recognized as a key factor in machine learning performance, systematic and reproducible evaluation across heterogeneous and accessible platforms remains limited, particularly when jointly considering execution time,...
Migrating to Post-Quantum Cryptography (PQC) is critical for securing resource-constrained Internet of Things (IoT) devices against the “harvest-now, decrypt-later” threat. While ML-KEM (CRYSTALS-Kyber) has been standardized under FIPS 20...
Distinguishingstructured nonlinear temporal behaviour from stochastic variability remains a fundamental challenge in the analysis of noisy and nonstationary time series, particularly when conventional nonlinear methods are sensitive to noise and fini...
Many studies have developed methods for assessing attractiveness, but the question is which one should be used to evaluate geopark designated areas? Therefore, the aim of this study is to find suitable criteria for assessing the attractiveness of a n...
Quantum machine learning is commonly benchmarked by matching a quantum head’s parameter count to that of a classical baseline. We show that this control is insufficient. We compare a 32-parameter parameterized quantum circuit (PQC) head against...
Publicly accessible, elaborated grid datasets, i.e., benchmark grids, are well suited to publish and compare methods or study results. Similarly, developing innovative tools and algorithms in the fields of grid planning and grid operation is based on...
Applied engineering studies that use evolutionary multi-objective optimisation (MOO) rarely report confidence bounds on the Pareto-optimal solutions they recommend. This paper presents a four-stage sensitivity-analysis protocol that supplies them: cr...
This paper proposes a methodological architecture to integrate Q-learning into economic modelling systematically. It addresses a common gap: the lack of a shared framework linking economic foundations to Reinforcement Learning components. Rather than...
Sustainable forest management depends on reliable compartment-level growing stock volume (GSV) estimates, which inform the prescribed cut. At the University Forest of Pertouli (Greece), four management-plan inventories (1989–2028) span a method...
For a long time, data has been treated as a general problem because it just represents fractions of an event without any relevant purpose. However, the last decade has been just about information and how to get it. Seeking meaning in data and trying...
Reported gains from multimodal fusion, feature-attribution explanations, and model-confidence scores are only as trustworthy as the evaluation protocol and preprocessing pipeline behind them, yet these are rarely audited together. We develop a benchm...
The stability of miRNAs in biological fluids and their association with pathological conditions position them as promising biomarkers for non-invasive cancer diagnostics, including those for non-small cell lung cancer (NSCLC). However, variability in...
Cross-sectional energy benchmarking in the building domain has become crucial for policymakers, energy managers and property owners as they can compare an immovable property performance against its closest peers. For this, Key Performance Indicators...
Deep vision multimodal learning aims at combining deep visual representation learning with other modalities, such as text, sound, and data collected from other sensors. With the fast development of deep learning, vision multimodal learning has gained...
Lung cancer is one of the deadliest form of cancer in Europe, characterized by a lack of obvious symptoms until the terminal stages of the illness. Electronic noses are a rising screening technology to detect early-stage lung cancer directly in the h...
This article presents a comparative accessibility study between a real city and its redraft as a Garden City. The benchmarking methodology involves defining and evaluating a location-based accessibility indicator in a GIS environment for the city of...
Energy management in the hotel industry remains a cornerstone in mitigating climate change. To successfully deploy energy management practices, correct energy KPIs are needed. Moreover, the development of a uniform taxonomy on how to classify hotel i...
A significant loss of microbial biodiversity on the skin has been linked to an increased prevalence of skin problems in the western world. The primary objective of this study was to obtain a benchmark value for the microbial diversity found on health...
Sustainable and reliable operation of water distribution systems requires timely detection of bursts and effective control of real water losses. The digitalisation of water utilities and the increasing deployment of smart monitoring infrastructures a...
For load forecasting, numerous machine learning (ML) approaches have been published. Besides fully connected feedforward neural networks (FFNNs), also called multilayer perceptron, more advanced ML approaches like deep, recurrent or convolutional neu...
The 2019 European Open Data Directive identifies geospatial data as data that could have a major impact on human activities (high-value data, HVD) and advocates its provision as open data (OD), i.e., without barriers to access and re-use. Although Cr...
Despite their enormous potential, the use of indoor localization systems (ILS) remains seldom. One reason is the lack of market transparency and stakeholders’ trust in the systems’ performance as a consequence of insufficient use of test and evaluati...
Publicly available grid datasets with electric steady-state equivalent circuit models are crucial for the development and comparison of a variety of power system simulation tools and algorithms. Such algorithms are essential to analyze and improve th...
Legged robot locomotion remains a critical challenge in robotics, demanding control strategies that are not only dynamically stable and robust but also capable of adapting to complex and changing environments. deep reinforcement learning (DRL) has re...
This study benchmarks three ROS 2 Navigation2 local controllers—Dynamic Window Approach Based (DWB), Regulated Pure Pursuit (RPP), and Model Predictive Path Integral (MPPI)—under three complementary operational stressors in simulation: (i...
This study examines how strongly demand-load prediction and adaptive load control in photovoltaic heating systems rely on computationally intensive artificial neural network (ANN) models. To streamline the computational workflow and reduce runtime re...
Retrieval-Augmented Generation (RAG) over vulnerability databases is widely expected to improve LLM-based vulnerability detection. We report a pre-specified evaluation in which it does not, and derive from it an evaluation protocol. On a near-balance...
Extracting transferable design knowledge from Discrete Element Method (DEM) simulations remains challenging in granular material handling. We develop an explainable surrogate framework for two solar-panel-recycling subsystems: a silo discharge system...
Selecting a data-management subsystem is a consequential decision in data-intensive applications, including AI pipelines that rely on low-latency storage. Such decisions are often informed by lightweight, application-specific benchmarks whose measure...
Distributed ledgers must migrate from elliptic-curve signatures to post-quantum alternatives, and the open question is no longer which primitives are available but which ledger resource they exhaust first. This paper identifies the binding constraint...
By applying the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to the polyethylene-reflected plutonium (PERP) benchmark, this work presents results for the first- and second-order sensitivities of this benchmark’s leakage resp...
The automotive family design is known as one of the most complex engineering design problems with multiple groups of stakeholders involved from different domains of interest and contradictory attributes. Taking into account all stakeholders’ pr...
To address the challenge of limited evaluations of expensive high-complexity functions in surrogate modeling, this paper proposes a methodological framework that integrates multi-fidelity Gaussian process (MFGP) regression, sequential active sampling...
This paper presents a benchmarking survey on query expansion techniques for social media information retrieval, with a focus on comparing the performance of methods using semantic web technologies. The study evaluated query expansion techniques such...
This work applies the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to compute the 1st-order and unmixed 2nd-order sensitivities of a polyethylene-reflected plutonium (PERP) benchmark’s leakage response with respect to the be...
This work continues the presentation commenced in Part I of the second-order sensitivity analysis of nuclear data of a polyethylene-reflected plutonium (PERP) benchmark using the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM). This...
Responses defined at critical points are particularly important for reactor safety analyses and licensing (e.g., the maximum fuel and/or clad temperature). The novel mathematical framework of the first-order comprehensive adjoint sensitivity analysis...
In the recent era, the need for modern smart grid system leads to the selection of optimized analysis and planning for power generation and management. Renewable sources like wind energy play a vital role to support the modern smart grid system. Howe...
This work applies the Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) to compute the mixed 2nd-order sensitivities of a polyethylene-reflected plutonium (PERP) benchmark’s leakage response with respect to the benchmark’s...
The Second-Order Adjoint Sensitivity Analysis Methodology (2nd-ASAM) is applied to compute the first-order and second-order sensitivities of the leakage response of a polyethylene-reflected plutonium (PERP) experimental system with respect to the fol...
The subcritical polyethylene-reflected plutonium (PERP) metal fundamental physics benchmark, which is included in the Nuclear Energy Agency (NEA) International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook, has been selected to se...
Even though Industrial Kitchens (IKs) are among the highest energy intensity spaces, very little work has been done to forecast their consumption. This work explores the possibility of increasing the accuracy of the consumption forecast in an IK by f...
The assessment of bridge functionality during earthquakes is fundamental in the evaluation of emergency response and socio-economic recovery procedures. In this regard, resilience may be considered a key parameter for decision-making procedures such...
The advent of quantum computing threatens the long-term security of classical public-key cryptosystems: RSA and standard elliptic-curve cryptography are vulnerable to Shor’s algorithm, making quantum-resistant alternatives a priority for modern...
Despite the improvements in tool development for DNA methylation analysis, there is a lack of a consensus on computational and statistical models used for differentially methylated cytosine (DMC) identification. This variability complicates the inter...
The increased focus on energy efficiency, both at the national and international levels, has fostered the diffusion and development of specific energy consumption benchmarks for most relevant economic sectors. In this context, energy-intensive facili...
This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of fre...
Geogenic concentrations are defined as those concentrations that represent the natural background without any anthropogenic influence. The paper describes a statistical method for determining geogenic metal concentrations in rivers based on the conce...
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