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Item type:Publication, 3D Shape Matching for Retrieval and Recognition(Springer, 2020-01-01)Nowadays, multimedia information such as images and videos are present in many aspects of our lives. Three-dimensional information is also becoming important in different applications, for instance, entertainment, medicine, security, art, just to name a few. It is therefore necessary to study how to properly process 3D information taking advantage of the properties that it provides. This chapter gives an overview of 3D shape matching and its applications in shape retrieval and recognition. In order to present the subject, we opted for describing in detail four approaches with good balance among maturity and novelty, namely, the PANORAMA descriptor, spin images, functional maps, and Heat Kernel Signatures for retrieval. We also aim at stressing the importance of this field in areas such as computer vision and computer graphics, as well as the importance of addressing the main challenges on this research field.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Podcasting collaborations and ontological relationships of being ‘here’ and ‘there’ in the Lower Marañón River in Peru(2021-11-12)This article is about podcasts and mobile phones not only as “daily technologies of life” but also as ways to convey personal stories and to do ethnographic research. However, we do not romanticize the use of digital technology for anthropological research. We use podcasts as a form to write our ethnographic work with our collaborators, and also as a way to keep in contact with our collaborators while in a global pandemic. For podcasts, we had to do several interviews and later edited them as both dialogues and individual stories. Interviews were mostly done by other digital devices such as WhatsApp, Facebook messenger, and telephone calls. The stories in our podcast series are mostly about an Amazonian indigenous community struggling to survive the global pandemic after several oil spills and other epidemics. Podcasts create a sort of intimacy and co-presence stimulating a multimodal, sensorial experience. However, power relations do not disappear, nor did they become invisible. Rather, power relations are accommodated in the new audio/digital scenario. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A contingency perspective for knowledge management solutions in different decision-making contexts(IGI Global, 2021-01-01)A contingency perspective of knowledge management, as one of the popular ways of promoting decision making capabilities, recognizes the need for a fit between knowledge management solutions (KMS) and decision-making contexts which they support. In order to determine the best fit, a field survey was carried out to investigate the impact of two different types of KMS (technical and social) on decision makers' behavior and performance in different decision contexts (simple and complex). According to the results, there is a partial support for the contingency view. As expected, social KMS appears as the best fit for complex contexts, based on subjects' superior performance from comparable adoption of both KMS. In contrast, the results suggest that both KMS were an equally good fit for simple contexts, based on similar levels of subjects' performance, but social KMS was preferred in terms of adoption. These findings contribute to much necessary empirical evidence for research and provide useful guidance for practice. However, their limitations necessitate further study. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Light-field imaging reconstruction using deep learning enabling intelligent autonomous transportation system(Institute of Electrical and Electronics Engineers Inc., 2021-05-27)Light-field (LF) cameras, also known as plenoptic cameras, permit the recording of the 4D LF distribution of target scenes. However, many times, surface errors of a microlens array (MLA) are responsible for degradation in the images captured by a plenoptic camera. Additionally, the limited pixel count of the sensor can cause missing parallax information. The aforementioned issues are crucial for creating accurate maps for Intelligent Autonomous Transport System (IATS), because they cause loss of LF information, and need to be addressed. To tackle this problem, a learning-based framework by directly simulating the LF distribution is proposed. A high-dimensional convolution layer with densely sampled LFs in 4D space and considering a soft activation function based on ReLU segmentation correction is used to generate a superresolution (SR) LF image, improving the convergence rate in the deep learning network. Experimental results show that our proposed LF image reconstruction framework outperforms the existing state-of-the-art approaches; specifically, it is effective for learning the LF distribution and generating high-quality LF images. Different image quality assessment methods are used to evaluate the performance of the proposed framework, such as PSNR, SSIM, IWSSIM, FSIM, GFM, MDFM, and HDR-VDP. Additionally, the computational efficiency was evaluated in terms of number of parameters and FLOPs, and experimental results demonstrated that our proposed framework reached the highest performance in most of the datasets used. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Light field image quality enhancement by a lightweight deformable deep learning framework for intelligent transportation systems(MDPI AG, 2021-05-02)Light field (LF) imaging has multi-view properties that help to create many applications that include auto-refocusing, depth estimation and 3D reconstruction of images, which are required particularly for intelligent transportation systems (ITSs). However, cameras can present a limited angular resolution, becoming a bottleneck in vision applications. Thus, there is a challenge to incorporate angular data due to disparities in the LF images. In recent years, different machine learning algorithms have been applied to both image processing and ITS research areas for different purposes. In this work, a Lightweight Deformable Deep Learning Framework is implemented, in which the problem of disparity into LF images is treated. To this end, an angular alignment module and a soft activation function into the Convolutional Neural Network (CNN) are implemented. For performance assessment, the proposed solution is compared with recent state-of-the-art methods using different LF datasets, each one with specific characteristics. Experimental results demonstrated that the proposed solution achieved a better performance than the other methods. The image quality results obtained outperform state-of-the-art LF image reconstruction methods. Furthermore, our model presents a lower computational complexity, decreasing the execution time. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Hardy spaces Hp and BMO: A brief classic overview(Universidad Nacional de Trujillo, 2022-11-30)In this brief note we give an overview of Hardy spaces Hp and bounded mean oscillation spaces, BMO, two classic spaces that have played an important role in investigations of central branches in harmonic analysis. The given bibliography opens paths to follow in this field. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The Future of Artificial Intelligence in Education 4.0: How to Go Green in the Post-COVID-19 Context(IGI Global, 2023-08-18)In recent years, artificial intelligence (AI) has grown exponentially. Technologies using artificial intel¬ligence can sort through and decipher vast volumes of data from several sources to carry out a range of activities. The expansion of social production is facilitated by the development of artificial intelligence, but it also poses significant challenges to conventional wisdom in human education in the post-COVID-19 context. This chapter discusses how various educational techniques may have been influenced by the emergence of artificial intelligence technologies. The authors concentrate on the significance of using artificial intelligence in education 4.0 with a view to the green idea in light of the study. The study also looked at the kinds of green artificial intelligence technologies that are most commonly employed in the education sector. The study in this field discusses the value of technology, including artificial intelligence, and how instructors and students use them in the teaching and learning process. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, What Does it Mean for Non-Human Beings to Have Moral Value? Building Bridges Between Capabilitarian Theories(Taylor & Francis, 2026-01-01)In this article, I present a formal and relational definition of moral value, which is not based on any specific intrinsic or extrinsic property or relational criteria in particular. With this definition, human agents can recognise moral value in a particular non-human being for different reasons and acknowledge that different beings have moral value even if they do not share the same properties. I thus seek to demonstrate that my proposal is not only compatible with the reasons proposed by Capability scholars for recognising moral value in non-human beings but also allows us to build bridges between them. To that end, I will invert theorists' previous reasoning on an entity's moral value. Typically, scholars first propose that something has a moral value (based on a specific property) and then ask what kind of responsibilities or attitudes we should have towards this entity in response to this value. My approach instead establishes that the moral value of an entity is derived from the reasons an agent has for certain kinds of attitudes toward that being. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Too Traditional? Voting and Gender Gap in Peru, 2000–2021(Springer International Publishing, 2026-01-01)Between 2000 and 2021, Peru held seven presidential elections, and female candidates garnered significant support in six of them. Despite progress in gender equity values, a persistent traditional gender gap remains in political behavior. Female voters in Peru continue to lean toward conservative candidates and parties more often than men do. Using data from the World Values Survey (1996–2018) and the Comparative Study of Electoral Systems (2000–2021), this chapter explores the gender gap in electoral behavior, political participation, and attitudes toward gender equity. Whereas women in Peru exhibit more-progressive values, particularly among younger cohorts, these values do not consistently translate into progressive voting behavior. Instead, women tend to support conservative female candidates, particularly those opposed to gender equity and reproductive rights. This paradox may be explained by the instability and fragmentation of Peru’s party system, which hinders the consolidation of coherent political platforms, including progressive political agendas.1
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