相关论文: Length, Weight, and Yield in Channel Catfish, Lake…
Estimates of age-specific natural (M) and fishing (F) mortalities among economically important stocks are required to determine sustainable yields and, ultimately, facilitate effective resource management. Here we used hazard functions to…
User behavior sequences in modern recommendation systems exhibit significant length heterogeneity, ranging from sparse short-term interactions to rich long-term histories. While longer sequences provide more context, we observe that…
This paper proposes a novel modelling and control framework for growth models that incorporate a size spectrum in conjunction with numerical computation and extensive field surveys. In fisheries management, the size spectrum, characterized…
Blue Mesa Reservoir is the largest body of water in Colorado and is located on the western slope of the Rocky Mountains at an elevation of 7520 feet. Blue Mesa Reservoir contains recreationally important populations of lake trout…
The effects of different levels of maltose on feed pellet water stability and nutrient leaching were studied. Five treatments, including control with three replicates with setup (0.0, 20, 25, 30 and 35%). Pellet leaching rates were used to…
The determination of rates of body growth is the first step in many aquatic population studies and fisheries stock assessments. ELEFAN (Electronic LEngth Frequency ANalysis) is a widely used method to fit a growth curve to length-frequency…
In this manuscript we investigate the long-term behavior of a single-species fishery, which is harvested by several fleets. The time evolution of this population is modeled by a discrete time stochastic age-structured model. We assume that…
This study presents a novel machine learning-based (ML) framework that utilizes the ConvLSTM-1D model to hindcast or forecast wave heights at coastal locations using a nonuniform array of wind observations. This approach was applied to Lake…
We present a vessel and target-specific positive mathematical programming model (PMP) for Hawaii's longline fishing fleet. Although common in agricultural economics, PMP modeling is rarely attempted in fisheries. To demonstrate the…
Recently, channel-independent methods have achieved state-of-the-art performance in multivariate time series (MTS) forecasting. Despite reducing overfitting risks, these methods miss potential opportunities in utilizing channel dependence…
We report here that channel power gain and Root-Mean-Square Delay Spread (RMS-DS) in Low/Medium Voltage power line channels are negatively correlated lognormal random variables. Further analysis of other wireline channels allows us to…
Fish stock assessment often involves manual fish counting by taxonomy specialists, which is both time-consuming and costly. We propose FishNet, an automated computer vision system for both taxonomic classification and fish size estimation…
Reproductive phenology, growth and mortality rates are key ecological parameters that determine population dynamics and are therefore of vital importance to stock assessment models for fisheries management. In many fish species, the…
Deep learning provides the opportunity to improve upon conflicting reports considering the relationship between the Amazon river's fish and dolphin abundance and reduced canopy cover as a result of deforestation. Current methods of fish and…
Based on different projection geometry, a fisheye image can be presented as a parameterized non-rectilinear image. Deep neural networks(DNN) is one of the solutions to extract parameters for fisheye image feature description. However, a…
The goal of electronic monitoring of longline fishing is to visually monitor the fish catching activities on fishing vessels based on cameras, either for regulatory compliance or catch counting. The previous hierarchical classification…
Deep super-resolution networks for precipitation downscaling achieve strong bulk skill yet systematically under-predict the heavy-tail events that drive flood risk. We demonstrate that the primary obstacle is the loss function, not the…
Understanding coastal geomorphic change is essential for advancing the United Nations Sustainable Development Goals (SDGs) through a multi-scale coastal management framework. In particular, characterization of coastal geomorphic change…
Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer learning…
This work presents a new approach, called MISFIT, for fitting generalized functional linear regression models with sparsely and irregularly sampled data. Current methods do not allow for consistent estimation unless one assumes that the…