1,720,961 research outputs found
Convolutional Neural Networks for Enhancing Detection of Dolphin Whistles in a Dense Acoustic Environment
Get PDFLatest developments in acoustic research suggest that using surveying methods based on artificial intelligence (AI) could improve the effectiveness of underwater monitoring. Passive acoustic monitoring (PAM) has proven to be a cost-effective approach for gathering information about the acoustic behavior of dolphins and plays a crucial role in studying their vocalizations, particularly whistles. This study investigates the efficiency of a binary convolutional neural network (CNN) in detecting dolphin whistles amidst high-density vocalizations in an aquatic environment. Specifically, this analysis intends to determine whether a properly trained CNN can recognize a single whistle even in challenging condition, including situations where multiple dolphins vocalize simultaneously, resulting in overlapping whistles that may have different shapes and durations. To this aim, experimental trials were conducted at Oltremare marine park, Riccione, Italy, where underwater recordings of seven-dolphin vocalizations were collected over 22 consecutive hours. The CNN was trained on labeled whistle spectrograms. The model, comprising three convolutional layers followed by max pooling layers and rectified linear unit (ReLU) activation functions, was evaluated using a 10-fold cross-validation approach. Confusion matrix and performance metrics indicate that the proposed approach achieves results comparable to those reported in the literature, despite the more challenging working conditions. The study supports the potential of AI models in enhancing passive acoustic monitoring techniques
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Effect of Extension Piece Design on Catch Patterns in a Mediterranean Bottom Trawl Fishery
Get PDFThe catch composition of bottom trawls is commonly refined and improved through changes in codend design. Measures like reducing the number of meshes in codend circumference or turning diamond netting by 90 degrees are well known to improve the size selectivity of fish species with rounded cross-sectional shape. Based on this we speculated whether the same measures, if applied in other parts of a bottom trawl, would provide similar benefits as in the codend. Therefore, experiments were carried out by deploying these changes to the trawl extension piece in a Mediterranean bottom trawl fishery. However, for European hake and monkfish, results showed no indication of improved selectivity or catch pattern compared to the standard extension piece in the trawl. Contrary, for red mullet, one of the most important species in this fishery, reducing the number of meshes in the circumference of the extension piece jeopardized the size selection obtained in the trawl with a standard extension piece. The lesson learnt from this study was that the design changes that work for the codend do not necessarily work for other parts of the trawl. In fact, they can even have negative effects
Cost-Effective Architectures For Underwater Sound-Recording Systems
No full textDolphin presence is typically monitored through Passive Acoustic Monitoring (PAM), deploying underwater devices. Commercial systems incur substantial costs, leading researchers to try to devise cost-effective sound recorders. While cost-efficient, enhancing recorder performance is crucial. The current study is designed to introduce and validate costeffective underwater sound-recording architectures. The test against a commercial system revealed minimal impact on recording performance. These systems, with a few-euro cost, proved highly economical compared to commercial options. The current technology provides a viable, budget-friendly solution for global continuous dolphin monitoring, offering valuable prospects for future studies and applications in marine environments
High-Accuracy Detection of Bottlenose Dolphin Whistle Using AI
No full textThe persistent interaction between dolphins and commercial fishing operations has led to ecological and socio-economic challenges, primarily through bycatch and depredation. Traditional mitigation strategies have shown limited success, needing innovative solutions. Intelligent robotic systems capable of identifying and consequently responding to dolphin vocalizations seem to be a promising approach to mitigate dolphin interactions with fishing operations. The core of this intelligent system should be an advanced algorithm or an artificial intelligence architecture capable of identifying dolphin vocalizations and distinguishing them from other underwater sounds. Thus, this study proposes a novel approach to detect dolphin whistles using a convolutional neural network (CNN) paired with advanced spectrogram processing techniques. The method utilizes audio recordings of common bottlenose dolphins (Tursiops truncatus) from Oltremare marine park in Italy. Whistle detection was enhanced by applying edge-detection filters to spectrograms, which highlights characteristic of dolphin whistles while filtering out noise. The processed spectrograms served as inputs to a CNN with a three-layer architecture optimized for binary classification of dolphin whistles. The model achieved very promising results, with accuracy, precision, recall, and F1-scores around 99% across a 10-fold cross-validation. The findings demonstrate the method robustness, offering potential applications in conservation efforts and real-time monitoring. Future research will focus on adapting the approach to field conditions where real-time processing and non-ideal whistle recording pose additional challenges
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