6,019 research outputs found
Multi-Label Bird Species Classification Using Sequential Aggregation Strategy from Audio Recordings
Birds are excellent bioindicators, playing a vital role in maintaining the delicate balance of ecosystems. Identifying species from bird vocalization is arduous but has high research gain. The paper focuses on the detection of multiple bird vocalizations from recordings. The proposed work uses a deep convolutional neural network (DCNN) and a recurrent neural network (RNN) architecture to learn the bird's vocalization from mel-spectrogram and mel-frequency cepstral coefficient (MFCC), respectively. We adopted a sequential aggregation strategy to make a decision on an audio file. We normalized the aggregated sigmoid probabilities and considered the nodes with the highest scores to be the target species. We evaluated the proposed methods on the Xeno-canto bird sound database, which comprises ten species. We compared the performance of our approach to that of transfer learning and Vanilla-DNN methods. Notably, the proposed DCNN and VGG-16 models achieved average F1 metrics of 0.75 and 0.65, respectively, outperforming the acoustic cue-based Vanilla-DNN approach
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Cycling Through the Pandemic : Tactical Urbanism and the Implementation of Pop-Up Bike Lanes in the Time of COVID-19
Provides an international overview on how tactical urbanism was implemented to give more space to cycling
Demonstrates the conceptual framework surrounding tactical urbanism and how it plays out theoretically
Proposes new methodological insights to understand the effects of tactical urbanism intervention
UMSL Bulletin 2022-2023
The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp
VNHSGE: VietNamese High School Graduation Examination Dataset for Large Language Models
The VNHSGE (VietNamese High School Graduation Examination) dataset, developed
exclusively for evaluating large language models (LLMs), is introduced in this
article. The dataset, which covers nine subjects, was generated from the
Vietnamese National High School Graduation Examination and comparable tests.
300 literary essays have been included, and there are over 19,000
multiple-choice questions on a range of topics. The dataset assesses LLMs in
multitasking situations such as question answering, text generation, reading
comprehension, visual question answering, and more by including both textual
data and accompanying images. Using ChatGPT and BingChat, we evaluated LLMs on
the VNHSGE dataset and contrasted their performance with that of Vietnamese
students to see how well they performed. The results show that ChatGPT and
BingChat both perform at a human level in a number of areas, including
literature, English, history, geography, and civics education. They still have
space to grow, though, especially in the areas of mathematics, physics,
chemistry, and biology. The VNHSGE dataset seeks to provide an adequate
benchmark for assessing the abilities of LLMs with its wide-ranging coverage
and variety of activities. We intend to promote future developments in the
creation of LLMs by making this dataset available to the scientific community,
especially in resolving LLMs' limits in disciplines involving mathematics and
the natural sciences.Comment: 74 pages, 44 figure
PubMed and Beyond: Recent Advances and Best Practices in Biomedical Literature Search
Biomedical research yields a wealth of information, much of which is only
accessible through the literature. Consequently, literature search is an
essential tool for building on prior knowledge in clinical and biomedical
research. Although recent improvements in artificial intelligence have expanded
functionality beyond keyword-based search, these advances may be unfamiliar to
clinicians and researchers. In response, we present a survey of literature
search tools tailored to both general and specific information needs in
biomedicine, with the objective of helping readers efficiently fulfill their
information needs. We first examine the widely used PubMed search engine,
discussing recent improvements and continued challenges. We then describe
literature search tools catering to five specific information needs: 1.
Identifying high-quality clinical research for evidence-based medicine. 2.
Retrieving gene-related information for precision medicine and genomics. 3.
Searching by meaning, including natural language questions. 4. Locating related
articles with literature recommendation. 5. Mining literature to discover
associations between concepts such as diseases and genetic variants.
Additionally, we cover practical considerations and best practices for choosing
and using these tools. Finally, we provide a perspective on the future of
literature search engines, considering recent breakthroughs in large language
models such as ChatGPT. In summary, our survey provides a comprehensive view of
biomedical literature search functionalities with 36 publicly available tools.Comment: 27 pages, 6 figures, 36 tool
Composed Image Retrieval using Contrastive Learning and Task-oriented CLIP-based Features
Given a query composed of a reference image and a relative caption, the
Composed Image Retrieval goal is to retrieve images visually similar to the
reference one that integrates the modifications expressed by the caption. Given
that recent research has demonstrated the efficacy of large-scale vision and
language pre-trained (VLP) models in various tasks, we rely on features from
the OpenAI CLIP model to tackle the considered task. We initially perform a
task-oriented fine-tuning of both CLIP encoders using the element-wise sum of
visual and textual features. Then, in the second stage, we train a Combiner
network that learns to combine the image-text features integrating the bimodal
information and providing combined features used to perform the retrieval. We
use contrastive learning in both stages of training. Starting from the bare
CLIP features as a baseline, experimental results show that the task-oriented
fine-tuning and the carefully crafted Combiner network are highly effective and
outperform more complex state-of-the-art approaches on FashionIQ and CIRR, two
popular and challenging datasets for composed image retrieval. Code and
pre-trained models are available at https://github.com/ABaldrati/CLIP4CirComment: Accepted in ACM Transactions on Multimedia Computing Communications
and Applications (TOMM
“MUSICA FATTA SPIRITUALE”: AQUILINO COPPINI, CLAUDIO MONTEVERDI, AND MADRIGAL CONTRAFACTS IN EARLY SEVENTEENTH-CENTURY MILAN
Between 1607 and 1609, the Milanese professor of rhetoric, Aquilino Coppini (d. 1629), published three volumes of spiritual contrafacts, mostly of madrigals by Claudio Monteverdi (1567–1643). Musicologists have already noted some of the ingenuities of Coppini’s close readings of Monteverdi’s music, but have treated them as an interesting yet inconsequential footnote. My dissertation offers a necessary reappraisal of Coppini’s approach to contrafacts both by contextualizing his project within post-Tridentine spiritualities in Milan under its new archbishop, Cardinal Federico Borromeo, and by reading his texts and their musical consequences far more carefully than has hitherto been the case. Informed by archival research and interdisciplinary approaches to music, literature, art, and religious studies, my close reading of these works demonstrates new intertextualities that connect a network of Humanists linked by a highly elaborate form of Milanese syncretism joining the sacred and the secular. Coppini’s contrafacts place Monteverdi’s music within a Milanese constellation of texts (musical, artistic, and literary) that sought to confront the rapidly changing world of the early seventeenth century. I argue that they provide a first-hand account of how Monteverdi’s madrigals were heard by reading them through the lens of Coppini’s rhetorical and poetic practices based on his own syncretic sense of religious affectivity. He catered both to secular audiences and to those in religious institutions, not least convents. It also becomes clear that Coppini must reconstruct texts that Monteverdi first deconstructed, which requires attention to musical rhetoric and not just oratory, prompting new analytical readings of the original madrigals themselves. My approach challenges the typical narratives of “Counter Reformation” contrafacts as didactic instruments of power to create a more nuanced view of works that served not just Coppini’s personal and professional needs, but also broader communities seeking new ways to perform their spiritual lives.Doctor of Philosoph
Body perception and brain plasticity in blind and sighted individuals
Lack of vision is associated with large-scale brain plasticity. Vision, touch, proprioception,
interoception, and other sensory modalities are thought to play a vital role in developing
and maintaining bodily awareness. How do blind people perceive their bodies, and what
kind of compensatory neuroplasticity processes are involved?
This thesis comprises a series of experiments focused on a profoundly understudied
topic – the perception of one’s body following blindness.
Study I shows that blind individuals are significantly better at perceiving their heartbeats
than sighted individuals. The results indicate that blind individuals experience signals from
inner organs differently than sighted individuals, which has implications for further
research on emotional processing and bodily awareness. Study II provides a broader
insight into tactile perception following blindness by studying discriminative and affective
touch plasticity in blind and sighted groups. A key novel finding is changed pleasantness
sensation due to affective touch, that is, slow, gentle, caress-like stroking of the skin,
especially on the palm, in blind participants compared to sighted participants. The results
have implications for understanding social and physical interactions in blind individuals.
Study III re-examines a classic paradigm to study multisensory bodily awareness, the
somatic rubber hand illusion, in a large sample of blind participants with a well-matched
sighted control group. The results present strong evidence that blind individuals are
“immune” to this illusion which suggests that they rely more on unisensory processing
rather than multimodal integration of sensory signals, compared to sighted individuals.
Study IV investigates the effect of short-term visual deprivation by a two-hour
blindfolding procedure on the bodily senses of cardiac interoception, thermosensation,
and discriminative touch in sighted participants. The results show no effect on these
senses, which suggests that the changes observed in blind individuals on these sensory
functions relate to their long-term lack of visual experience and associated brain
plasticity changes. Finally, Study V uses structural magnetic resonance imaging to analyze
cortical thickness in a group of blind individuals and a matched sighted control group and
relate the cortical thickness measure to the behaviorally registered changes in cardiac
interoceptive accuracy. The key finding is that blind individuals with thicker occipital
cortices are better at sensing their heartbeats; this finding advances our understanding
of the limits of cross-modal plasticity following blindness and suggests that the visual
cortex supports the awareness of inner bodily sensations in blind individuals.
Overall, this thesis is the first systematic characterization of differences and similarities
between blind and sighted individuals in body perception and functioning of the bodily
senses, opening a line of research with important links to mental health
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