1,721,224 research outputs found
FIGURE 6 in Description of Coeliccia lephuocdieui sp. nov. from the Central Highlands of Vietnam (Odonata: Zygoptera: Platycnemididae) with notes on its congeners
No full textFIGURE 6. Posterior pronotal lobe of prothorax of Coeliccia spp., all female. (6a, b) C. lephuocdieui sp. nov.; (6c, d) C. scutellum, Kon Ka Kinh National Park; (6e, f) C. yamasakii, Phu Quoc Islands.Published as part of Phan, Quoc Toan, Ngo, Quoc Phu & Bui, Anh Phong, 2020, Description of Coeliccia lephuocdieui sp. nov. from the Central Highlands of Vietnam (Odonata: Zygoptera: Platycnemididae) with notes on its congeners, pp. 69-80 in Zootaxa 4786 (1) on page 75, DOI: 10.11646/zootaxa.4786.1.5, http://zenodo.org/record/386498
The mod 2 cohomology rings of congruence subgroups in the Bianchi groups
Get PDFInternational audienceWe provide new tools for the calculation of the torsion in the cohomology of congruence subgroups in the Bianchi groups : An algorithm for finding particularly useful fundamental domains, and an analysis of the equivariant spectral sequence combined with torsion subcomplex reduction.__________With an appendix by Bui Anh Tuan and Sebastian Schönnenbec
EnseSmells : Deep ensemble and programming language models for automated code smells detection
Get PDFA smell in software source code denotes an indication of suboptimal design and implementation decisions, potentially hindering the code understanding and, in turn, raising the likelihood of being prone to changes and faults. Identifying these code issues at an early stage in the software development process can mitigate these problems and enhance the overall quality of the software. Current research primarily focuses on the utilization of deep learning-based models to investigate the contextual information concealed within source code instructions to detect code smells, with limited attention given to the importance of structural and design-related features. This paper proposes a novel approach to code smell detection, constructing a deep learning architecture that places importance on the fusion of structural features and statistical semantics derived from pre-trained models for programming languages. We further provide a thorough analysis of how different source code embedding models affect the detection performance with respect to different code smell types. Using four widely-used code smells from well-designed datasets, our empirical study shows that incorporating design-related features significantly improves detection accuracy, outperforming state-of-the-art methods on the MLCQ dataset with improvements ranging from 5.98% to 28.26%, depending on the type of code smell
Recognition of breast cancer from heterogeneous ultrasound images: A multi-level deep learning approach
Get PDFBreast ultrasound is a medical imaging technique that employs sound waves to produce breast images, and it has been primarily used to diagnose breast cancer and other related issues. With various machine learning algorithms being applied, many applications have shown promising results and demonstrated outstanding efficiency in giving doctors early accurate diagnoses. By investigating existing state-of-the-art approaches to breast lesion detection, given ConvNeXt-Small architecture as an example, we observe that although they bring a satisfactory performance in classification, their ability to detect small lesions is limited. Therefore, there is still room for improving the performance of DL-based approaches. In this paper, we present a practical Deep Learning-based solution for breast lesion detection, using DetectoRS with Gaussian Receptive Field-based Label Assignment (RFLA) and SegFormer-B4 for recognizing and segmenting small breast lesions, including malignant tumors. Our proposed solution involves three distinct models: ConvNeXt-Small for classification, Swin-Base combined with DetectoRS and RFLA for object detection, and SegFormer-B4 for segmentation. Each model is tailored specifically to address its respective task in breast cancer detection and analysis. The proposed approach has been evaluated on diverse ultrasound datasets. Our deep learning model achieves an Average Precision of 0.270 for small objects (AP_S), and records the highest mean Intersection over Union at 81.55%. The results show that the proposed model outperforms various well-established baselines. We suppose that our method can be integrated into computer-aided diagnosis systems to assist physicians in their clinical activities
Impact of trade liberalization on industrial pollution : empirical evidence from Vietnam
Get PDFThis study assesses the impact of trade liberalization on the environment in Vietnam. In particular it looks at the link between the amount of pollution produced by the country’s manufacturing industries and the degree to which this is affected by trade liberalization policies. The study was carried out by Pham Thai Hung, Bui Anh Tuan and Nguyen The Chinh, from Vietnam’s National Economics University. It finds that trade liberalization in the country exacerbates industrial pollution at both the firm and industry level. This trade-off is worrying as Vietnam has recently become a WTO member and further trade liberalization commitments are now in the pipeline. In light of their findings, the researchers recommend that the environmental impact of any future trade reforms should be carefully considered and that steps should be taken to mitigate any potential negative effects such reforms might have. They suggest that polluting industries should be given priority in any clean-up programme. They highlight key steps which can be taken to help reduce pollution, including the strict enforcement of environmental regulations support to promoting information technology application and technology advancement in the manufacturing sector
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
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