To ensure sustainability, the Ecosystem Approach to Fisheries (EAF) requires the evaluation of the impacts of fisheries beyond the main targeted species, to include those on bycaught, endangered, threatened and protected populations and keystone spec...
Fisheries management in the Mediterranean Sea faces persistent challenges due to the prevalence of data-poor and data-limited stocks, small-scale multi-species fisheries, and limited long-term monitoring programs. Effective assessment methodologies a...
The silky shark, Carcharhinus falciformis is one of the most heavily exploited sharks, being the main by-catch species in both tuna longline and purse-seine fisheries in tropical waters worldwide. Despite this severe exploitation, little is known abo...
Hydrological methods are widely used for environmental-flow assessment in data-limited rivers, but different methods often produce divergent monthly thresholds, making method selection difficult under strong seasonal variability. This study develops...
The status of data-limited tuna fishery stocks in India has been tested using the latest and most advanced computerized methods, CMSY and BSM. Five tuna fish stocks from both the Eastern and Western Indian Ocean were assessed using both catch and cat...
This paper investigates the epistemic uncertainty associated with dependence modeling and its impact on structural reliability analysis when data for vine structure selection is limited. Conventionally, the vine copula model characterizing dependent...
The southern coast of Central Java Province is one of Indonesia’s largest eels (Anguilla spp.) fishing grounds. The annual eel catches in this region showed an increasing trend in 2011–2014 but then plummeted in 2019–2021. However,...
Network-level congestion assessment requires segment states to be aggregated across roads that differ in length, observed flow, capacity, and functional role. In data-limited settings, however, traffic agencies may only have road class, segment lengt...
Fisheries in the Curonian Lagoon (1584 km2 coastal lagoon in South-East Baltic) can be classified as artisanal, small-scale, multi-species, and multi-gear. Such types of fisheries are characterised as data-poor and require appropriate investigation m...
Accurate estimation of fish stock abundance and exploitability is critical for effective fishery management; however, fishery-dependent data are often affected by temporal and spatial heterogeneities due to the seasonal migration of fish, posing chal...
Aras Dam reservoir, a key inland fishery in northwest Iran, faces increasing socioecological threats that jeopardize sustainable resource use. To provide updated information on stock conditions under limited data availability, this study applied the...
The spiny lobster Palinurus elephas has been intensively harvested across its range and is generally considered overfished, with global landings declining sharply from an average of 820 t in 1960–79 to 385 t in 2000–19. Despite its econom...
Given the scarcity of information suitable for stock assessments, the growth and mortality of seven exploited marine fishes in Azorean waters were estimated based on length-frequency data. The studied species were Trachurus picturatus, Sparisoma cret...
The Philippines experiences intense rainfall but has limited ground-based monitoring infrastructure for flood prediction. Satellite rainfall products provide broad coverage but contain systematic biases that reduce operational usefulness. This study...
Model-based optimization is an important means by which to analyze the energy-saving potential of chiller plants. To obtain reliable energy-saving results, model calibration is essential, which strongly depends on operating data. However, sufficient...
This study proposes a remaining useful life (RUL) prediction method using limited degradation data with an unknown degradation model for hydraulic pumps with long service lives and no failure data in turbine control systems. The volumetric efficiency...
A general framework for structural fatigue life evaluation under fatigue cyclic loading using limited sensor data is proposed in this paper. First, limited sensor data are measured from various sensors which are preset on the complex structure. Then...
This paper presents a systematic and general method for Lamb wave-based crack size quantification using finite element simulations and Bayesian updating. The method consists of construction of a baseline quantification model using finite element simu...
In the early stage of product development, reliability evaluation is an indispensable step before launching a product onto the market. It is not realistic to evaluate the reliability of a new product by a host of reliability tests due to the limiting...
Reference crop evapotranspiration (ETo) is an important component of the hydrological cycle that is used for water resource planning, irrigation, and agricultural management, as well as in other hydrological processes. The aim of this study was to es...
In this study, we investigate the application of the direct sampling method (DSM) to identify small dielectric objects in a limited-aperture inverse scattering problem. Unlike previous studies, we consider the bistatic measurement configuration corre...
Currently, the tasks of intelligent data analysis in medicine are becoming increasingly common. Existing artificial intelligence tools provide high effectiveness in solving these tasks when analyzing sufficiently large datasets. However, when there i...
Dual-energy CT (DECT) with scans over limited-angular ranges (LARs) may allow reductions in scan time and radiation dose and avoidance of possible collision between the moving parts of a scanner and the imaged object. The beam-hardening (BH) and LAR...
Satellite precipitation products (SPPs) have advanced remarkably in recent decades. However, the bias correction of SPPs still performs unsatisfactorily in the case of a limited rain-gauge network. This study proposes a new real-time bias correction...
Vibration signals collected in real industrial environments are usually limited and unlabeled. In this case, fault diagnosis methods based on deep learning tend to perform poorly. Previous work mainly used the unlabeled data of the same diagnostic ob...
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...
In the field of transplantology, where medical decisions are heavily dependent on complex data analysis, the challenge of small data has become increasingly prominent. Transplantology, which focuses on the transplantation of organs and tissues, requi...
Under cyclic loading, almost immediately after its onset, a surface layer forms where hardening and softening processes occur. The interaction of plastic deformation traces with each other, and with other structural elements, leads to the formation o...
The increasing demand for sustainable development and energy efficiency underscores the importance of optimizing motors in driving the upgrade of energy structures. This paper studies a data-driven approach for the multi-objective optimization of mot...
Structural health monitoring (SHM) based on Lamb waves relies on sensors to acquire structural response signals. However, sensor data acquisition is severely constrained under complex damage conditions. Digital twins (DTs) can enhance damage monitori...
A methodology named the step response separation (SRS) method for deriving S-curves solely from the data for basin runoff and the associated instantaneous unit hydrograph (IUH) is presented. The SRS method extends the root selection (RS) method to ge...
In current practice, the deployment of artificial intelligence models for the optimization of construction processes is highly complex and limited, primarily due to the lack of data available for training models. Collecting real-world data is both ti...
Given its highly coupled multi-power sources with diverse dynamic response characteristics, the mode transition process of a power-split Hybrid Electric Vehicle (HEV) can easily lead to unanticipated passenger-felt jerks. Moreover, difficulties in pa...
The emitter is one of the most critical components in drip irrigation. The flow path geometry parameters have a significant effect on the emitter’s hydraulic performance and have a direct impact on the emitter’s irrigation uniformity and...
This paper examines the asymptotic behavior of the conditional hazard function using kernel-based methods, with particular emphasis on functional weakly dependent data. In particular, we establish the asymptotic normality of the proposed estimator wh...
The use of spherical radial basis functions (SRBFs) in regional gravity field modeling has become popular in recent years. However, to our knowledge, their potential for combining gravity data from multiple sources, particularly for data with differe...
On 17 October 2015, a large-scale subaerial landslide occurred in Taan Fiord, Alaska, which released about 50 Mm
The expected development of the future generation of wireless communications systems such as 6G aims to achieve an ultrareliable and low-latency communications (URLLCs) while maximizing the data rates. These requirements push research into developing...
Fuel burn during the actual route flown is an important indicator of aircraft operational efficiency. This study aims to assess and systematically evaluate the method for fuel consumed during flights using data from the automatic dependent surveillan...
The development of accurate and efficient image reconstruction algorithms is a central aspect of quantitative photoacoustic tomography (QPAT). In this paper, we address this issues for multi-source QPAT using the radiative transfer equation (RTE) as...
Appropriate data collection and using reliable and accurate procedures are the first steps in conducting an experiment that will provide trustworthy outcomes. It is key to perform an assertive statistical analysis and data visualization for a correct...
Background/Objectives: This study examined the impact of data pre-processing on indirectly derived reference intervals for intact parathyroid hormone (iPTH). Routine laboratory data from a single Norwegian site, measured on the Abbott Alinity i analy...
This study assessed hourly electricity consumption profiles in railway signal boxes located in Poland. The analyses carried out consisted of assessing the correlation among the hourly demand profile, weather indicators, and calendar indicators, e.g.,...
This work employs the Birnbaum–Saunders distribution to model the fatigue-life of metallic materials under cyclic loading and compares it with the normal distribution. Fatigue-limit models are fitted to three datasets of unnotched specimens of...
Chub mackerel (Scomber japonicus) is a major targeted species in the Northwest Pacific Ocean, fished by China, Japan, and Russia, and predominantly captured with purse seine fishing gear. A formal stock assessment of Chub mackerel in the region has y...
Despite its relevance, measuring the contributions of the bioeconomy to national economies remains an arduous task that faces limitations. Part of the difficulty is associated with the lack of a clear and widely accepted concept of the bioeconomy and...
Image classification in data-limited environments presents a significant challenge, as collecting and labeling large image datasets in real-world applications is often costly and time-consuming. This has led to increasing interest in developing model...
Modeling potential evapotranspiration (ET0) is an important issue for water resources planning and management projects involving droughts and flood hazards. Evapotranspiration, one of the main components of the hydrological cycle, is highly effective...
The three-step rule of distributed photovoltaic (DPVs) connecting to a distribution network in the planning of practical photovoltaic projects is modeled in this paper. On this basis, a method based on large sample historical generation-load data is...
Dolphin signals are effective carriers for underwater covert detection and communication. However, the environmental and cost constraints terribly limit the amount of data available in dolphin signal datasets are often limited. Meanwhile, due to the...
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