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The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions

In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause...

OTFS—A Mathematical Foundation for Communication and Radar Sensing in the Delay-Doppler Domain

Orthogonal time frequency space (OTFS) is a framework for communication and active sensing that processes signals in the delay-Doppler (DD) domain. This article explores three key features of the OTFS...

Gene expression based inference of cancer drug sensitivity

Inter and intra-tumoral heterogeneity are major stumbling blocks in the treatment of cancer and are responsible for imparting differential drug responses in cancer patients. Recently, the availability...

Theory-guided experimental design in battery materials research

A reliable energy storage ecosystem is imperative for a renewable energy future, and continued research is needed to develop promising rechargeable battery chemistries. To this end, better theoretical...

Passive Thermography Based Bearing Fault Diagnosis Using Transfer Learning With Varying Working Conditions

Bearing is one of the core components of any rotating machine, and its failure is widespread. This reason drives continuous monitoring and detecting bearing faults during machine operation to warn ope...

Optimisation and interpretation of machine and deep learning models for improved water quality management in Lake Loktak

Transfer learning–based ensemble support vector machine model for automated COVID-19 detection using lung computerized tomography scan data

Vibration and infrared thermography based multiple fault diagnosis of bearing using deep learning

The occurrence of multiple faults is a practical problem in the bearings of rotating machines, and early diagnosis of such issues in an intelligent manner is vital in the era of industry 4.0. The pres...

How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda

Data availability and accessibility have brought in unseen changes in the finance systems and new theoretical and computational challenges. For example, in contrast to classical stochastic control the...

Source Aware Deep Learning Framework for Hand Kinematic Reconstruction Using EEG Signal

The ability to reconstruct the kinematic parameters of hand movement using noninvasive electroencephalography (EEG) is essential for strength and endurance augmentation using exoskeleton/exosuit. For ...

Deep learning-based approach for identification of diseases of maize crop

In recent years, deep learning techniques have shown impressive performance in the field of identification of diseases of crops using digital images. In this work, a deep learning approach for identif...

Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach

Quantitative trading and investment decision making are intricate financial tasks that rely on accurate stock selection. Despite advances in deep learning that have made significant progress in the co...