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As AI systems demonstrate increasingly strong predictive performance, their adoption has grown in numerous domains. However, in high-stakes domains such as criminal justice and healthcare, full automation is often not desirable due to…
Digital Twins (DTs) are becoming increasingly vital for future industrial applications, enhancing monitoring, control, and optimization of physical assets. This enhancement is made possible by integrating various Digital Models (DMs) within…
Drug-Drug Interactions (DDIs) Extraction refers to the efforts to generate hand-made or automatic tools to extract embedded information from text and literature in the biomedical domain. Because of restrictions in hand-made efforts and…
Responsible design of AI systems is a shared goal across HCI and AI communities. Responsible AI (RAI) tools have been developed to support practitioners to identify, assess, and mitigate ethical issues during AI development. These tools…
Digital pathology has revolutionized the field by enabling the digitization of tissue samples into whole slide images (WSIs). However, the high resolution and large size of WSIs present significant challenges when it comes to applying Deep…
Reliable and validated assessments of introductory physics have been instrumental in driving curricular and pedagogical reforms that lead to improved student learning. As part of an effort to systematically improve our sophomore-level…
This study investigates the dose-response effects of making music on youth development. Identification is based on the conditional independence assumption and estimation is implemented using a recent double machine learning estimator. The…
Multi-interest candidate matching plays a pivotal role in personalized recommender systems, as it captures diverse user interests from their historical behaviors. Most existing methods utilize attention mechanisms to generate interest…
We study how musicians use artificial intelligence (AI) across formats like singles, albums, performances, installations, voices, ballets, operas, or soundtracks. We collect 337 music artworks and categorize them based on AI usage: AI…
Multi-modal music generation, using multiple modalities like text, images, and video alongside musical scores and audio as guidance, is an emerging research area with broad applications. This paper reviews this field, categorizing music…
Mathematical models are crucial for optimizing and controlling chemical processes, yet they often face significant limitations in terms of computational time, algorithm complexity, and development costs. Hybrid models, which combine…
Broad application of human-machine interaction (HMI) demands advanced and human-centered control designs for the machine's automation. Human natural motor action shows stochastic behavior, which has so far not been respected in HMI control…
Noise is always presents in digital images during image acquisition, coding, transmission, and processing steps. Noise is very difficult to remove it from the digital images without the prior knowledge of noise model. That is why, review of…
The mechanical properties of human soft tissue are crucial for impact biomechanics, rehabilitation engineering and surgical simulation. Validation of these constitutive models using human data remains challenging and often requires the use…
Brain computer interface applications can be used to overcome learning problems, especially student anxiety, lack of focus, and lack of attention. This paper introduces a system based on brain computer interface (BCI) to be used in…
Both in academic and industry-based research, online evaluation methods are seen as the golden standard for interactive applications like recommendation systems. Naturally, the reason for this is that we can directly measure utility metrics…
A quantitative theory of operation of a novel device, namely Direct String Magnetic Gradiometer (DSMG), is presented. The paper provides a detailed analysis of DSMG basic functions and measured quantities, represented in terms of physical…
In recent years, machine learning, and in particular generative adversarial neural networks (GANs) and attention-based neural networks (transformers), have been successfully used to compose and generate music, both melodies and polyphonic…
Quantification of stylistic differences between musical artists is of academic interest to the music community, and is also useful for other applications such as music information retrieval and recommendation systems. Information about…
In the past, several works have investigated ways for combining quantitative and qualitative methods in research assessment exercises. In this work, we aim at introducing a methodology to explore whether citation-based metrics, calculated…