Academic Articles & Research Papers

DeepPROTACs is a deep learning-based targeted degradation predictor for PROTACs

The rational design of PROTACs is difficult due to their obscure structure-activity relationship. Here the authors present a deep neural network model - DeepPROTACs - for predicting the degradation capacity of a proposed PROTAC molecule....

A learning‐based energy management strategy for hybrid energy storage systems with compressed air and solid oxide fuel cells

Abstract The intermittency and volatility of renewable energy have been major challenges in modern power systems. This paper proposes a self‐adaptive energy management strategy based on deep reinforcement learning (DRL) to integrate renewab...

Deep Learning-Based Land Cover Extraction from Very-High-Resolution Satellite Imagery for Assisting Large-Scale Topographic Map Production

The demand for large-scale topographic maps in Indonesia has significantly increased due to the implementation of several government initiatives that necessitate the utilization of spatial data in development planning. Currently, the nation...

MWG-UNet: Hybrid Deep Learning Framework for Lung Fields and Heart Segmentation in Chest X-ray Images

Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression abili...

Association between intrinsic capacity transitions and the risk of diabetes in middle-aged and older adults.

Generalization in Deep Learning

This chapter provides theoretical insights into why and how deep learning can generalize well, despite its large capacity, complexity, possible algorithmic instability, non-robustness, and sharp minima, responding to an open question in the...

The Microbiome Composition of a Man's Penis Predicts Incident Bacterial Vaginosis in His Female Sex Partner With High Accuracy

Background: We determined the predictive accuracy of penile bacteria for incident BV in female sex partners. In this prospective cohort, we enrolled Kenyan men aged 18–35 and their female sex partners aged 16 and older. We assessed BV at ba...

A machine learning and clustering-based approach for county-level COVID-19 analysis.

COVID-19 is a global pandemic threatening the lives and livelihood of millions of people across the world. Due to its novelty and quick spread, scientists have had difficulty in creating accurate forecasts for this disease. In part, this is...

Rapid Estimation of Static Capacity Based on Machine Learning: A Time-Efficient Approach

With the global surge in electric vehicle (EV) deployment, driven by enhanced environmental regulations and efforts to reduce transportation-related greenhouse gas emissions, managing the life cycle of Li-ion batteries becomes more critical...

DaDianNao: A Machine-Learning Supercomputer

Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...

Enabling High-Degree-of-Freedom Thermal Engineering Calculations via Lightweight Machine Learning

U-tube steam generators (UTSGs) are crucial in nuclear power plants, serving as the interface between the primary and secondary coolant loops. UTSGs ensure efficient heat exchange, operational stability, and safety, directly impacting the p...

Machine learning for ecosystem services

Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...

Analysis of applying machine learning methods in rock classification problems on core samples

Relevance. Core studies in the oil and gas industry allow us to obtain some filtration and capacity characteristics of rocks, as well as to give an idea of the composition and structure of the subsoil. This information is extremely importan...

Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery

Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...

Precision water quality indices forecasting through an optimized hybrid SMW-LSSVM-R model enhanced by SATLDE and uncertainty analysis

Precise forecasting of water quality indices (WQI) is essential for safeguarding ecosystems, human health, and sustainable water resource management. This study presents an innovative approach for evaluating river Water Quality Indices usin...

Source apportionment and stochastic evaluation of soil contamination and human health risks of potentially toxic elements in Nangodi, northern Ghana

Abstract Artisanal and Small-Scale Mining (ASM) is a critical driver of soil contamination in West Africa, yet quantifying the relative contributions of natural and anthropogenic sources remains a major challenge. This study presents an int...

Investment portfolio optimization with supervised learning and attention mechanism

Portfolio optimization is a process that involves distribution of capital with the purpose of maximizing returns and at the same time minimizing risks. The current paper discusses the use of Transformer networks in supervised learning for p...

Epidemiology and Ecology of Toscana Virus Infection and Its Global Risk Distribution

Toscana virus (TOSV), a member of the Phlebovirus genus transmitted by sandflies, is acknowledged for its capacity to cause neurological infections and is widely distributed across Mediterranean countries. The potential geographic distribut...

AN IMPROVED GRU BASED ON RECURRENT ATTENTION UNIT AND SELF- ATTENTION TECHNIQUE FOR TEXT SENTIMENT ANALYSIS

In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...

PosturAll: A Posture Assessment Software for Children

From an early age, people are exposed to risk factors that can lead to musculoskeletal disorders like low back pain, neck pain and scoliosis. Medical screenings at an early age might minimize their incidence. The study intends to improve a ...