Results 71 to 80 of about 9,795 (189)

Sentiment Analysis Using LSTM Algorithm Regarding Grab Application Services in Indonesia

Journal of Applied Informatics and Computing
This study aims to analyze the sentiment of user reviews for the Grab Indonesia application using Long Short-Term Memory (LSTM) algorithms. Two variants of LSTM, namely Stacked LSTM and Bi-Directional LSTM, were compared to determine the most effective ...
Akbar Rikzy Gunawan, Rifda Faticha Alfa Aziza   +1 more
doaj   +1 more source

Observation‐Driven Correction of Numerical Weather Prediction for Marine Winds

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Accurate marine wind forecasts are essential for safe navigation, ship routing, and energy operations, yet they remain challenging because observations over the ocean are sparse, heterogeneous, and temporally variable. We present an observation‐informed correction approach for global numerical weather prediction (NWP) of marine winds.
Matteo Peduto, Qidong Yang, Jonathan Giezendanner, Devis Tuia, Sherrie Wang   +4 more
wiley   +1 more source

SA-Bi-LSTM: Self Attention With Bi-Directional LSTM-Based Intelligent Model for Accurate Fake News Detection to Ensured Information Integrity on Social Media Platforms

IEEE Access
Detecting fake news is increasingly crucial in the digital age as social platforms and online news outlets amplify the spread of misinformation. This study proposes a novel approach for fake news detection using a Bi-LSTM neural network with an attention
Wang Jian, Jian Ping Li, Muhammad Atif Akbar, Amin Ul Haq, Shakir Khan, Reemiah Muneer Alotaibi, Saad Abdullah Alajlan   +6 more
doaj   +1 more source

Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities

Bipolar Disorders, Volume 28, Issue 5, August 2026.
ABSTRACT Background Clinicians aspire to predict the emergence of Bipolar Disorder (BD) in a timely manner. To accomplish this, markers reflecting mental states that can be gathered non‐invasively and at large scale are needed. Here, we systematically evaluate evidence relating speech‐based markers to mood states in BD.
Farida Zaher, Jessica Ahrens, Delphine Raucher‐Chéné, Alban Voppel, Lena Palaniyappan   +4 more
wiley   +1 more source

RetinoDeep: Leveraging Deep Learning Models for Advanced Retinopathy Diagnostics

Sensors
Diabetic retinopathy (DR), a leading cause of vision loss worldwide, poses a critical challenge to healthcare systems due to its silent progression and the reliance on labor-intensive, subjective manual screening by ophthalmologists, especially amid a ...
Sachin Kansal, Bajrangi Kumar Mishra, Saniya Sethi, Kanika Vinayak, Priya Kansal, Jyotindra Narayan   +5 more
doaj   +1 more source

Detecting Opioid Misuse on Social Media via Named Entity Recognition (NER) With Deep Learning

Expert Systems, Volume 43, Issue 8, August 2026.
ABSTRACT The opioid overdose epidemic constitutes a critical public health crisis, necessitating advanced surveillance tools to enable timely intervention. Social media platforms provide a real‐time source of information on drug‐related behaviours. However, extracting structured knowledge from their informal, slang‐heavy and fragmented text presents ...
Muhammad Ahmad, Rita Orji, Fida Ullah, Ildar Batyrshin, Grigori Sidorov   +4 more
wiley   +1 more source

A Review of Breath Sensing for Disease Monitoring and Diagnosis: Breathomics, Artificial Intelligence, and Nanomaterials for the Future of Medicine

Advanced Sensor Research, Volume 5, Issue 7, July 2026.
Breathomics is established as a non‐invasive diagnostic strategy by combining volatile organic compound biomarkers, nanomaterial‐based sensor arrays, and AI‐driven classification. Key diseases, sensing materials, and analytical challenges are critically compared, revealing how portable, data‐enabled breath platforms are moving toward clinically useful ...
Anesu Nyabadza, Mayur Makhesana, Suman Chatterjee, Dermot Brabazon   +3 more
wiley   +1 more source

Intelligent Control Strategy of a Battery Energy Storage for a Climate‐Controlled Greenhouse with a High Proportion of Local Renewable Energy

IEEJ Transactions on Electrical and Electronic Engineering, Volume 21, Issue 7, Page 1020-1027, July 2026.
Greenhouse cultivation offers the advantage of controlled growth conditions, leading to enhanced crop productivity and quality. However, maintaining these optimal conditions requires substantial energy, resulting in increased greenhouse gas emissions and operational costs. Integrating local renewable energy sources, particularly photovoltaic (PV) solar
Akihiro Funaki, Jorge Solis
wiley   +1 more source

Relation extraction based on CNN and Bi-LSTM

网络与信息安全学报, 2018
Relation extraction aims to identify the entities in the Web text and extract the implicit relationships between entities in the text.Studies have shown that deep neural networks are feasible for relation extraction tasks and are superior to traditional methods.Most of the current relation extraction methods apply convolutional neural network (CNN) and
Xiaobin ZHANG, Fucai CHEN, Ruiyang HUANG
openaire   +3 more sources

Text Extraction with Optimal Bi-LSTM

Computers, Materials & Continua, 2023
Bahera H. Nayef, Siti Norul Huda Sheikh Abdullah, Rossilawati Sulaiman, Ashwaq Mukred Saeed   +3 more
openaire   +1 more source