We propose a generalization of trapezoidal fuzzy numbers based on modal interval theory, which we name “modal interval trapezoidal fuzzy numbers”. In this generalization, we accept that the alpha cuts associated with a trapezoidal fuzzy number can be...
Performance in semantic verbal fluency (SVF) tasks, mainly measured by the number of words of a particular semantic category produced within a limited time, is a widely accepted measure of cognitive functioning used in the neuropsychological assessme...
This article aims at providing some extension of the modal square of opposition in the light of Ockham’s account of modal operators. Moreover, we set forth some significant remarks on the de re–de dicto distinction and on the modal operat...
Number–color synesthesia is a condition in which synesthetes perceive numbers with concurrent experience of specific, corresponding colors. It has been proposed that synesthetic association exists primarily between representations of Arabic dig...
The conditioning theory of the generalized inverse
Convex bodies are naturally symmetrical. There is also a correlation between the two variables of symmetry and convexity. Their use, in either case, has been feasible in recent years because of their interchangeable and similar properties. The propos...
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The refractive index structure constant (
Firstly, we present a more explicit formulation of the complete system
Measles is a highly contagious viral disease that can lead to serious complications, including death, particularly in young children. In this study, we developed a mathematical model that incorporates a seasonal transmission parameter to examine the...
A gap a of a numerical semigroup S is fundamental if
The semantic segmentation of the 3D operating environment represents the key to intelligent mining shovels’ autonomous digging and loading operation. However, the complexity of the operating environment of intelligent mining shovels presents ch...
Continuous movements of the hand contain discrete expressions of meaning, forming a variety of semantic gestures. For example, it is generally considered that the bending of the finger includes three semantic states of bending, half bending, and stra...
In the realm of linguistics, the concept of “semanticity” was recently introduced as a novel measure designed to study linguistic networks. In a given text, semanticity is defined as the ratio of the potential number of meanings associate...
The use of Generative Adversarial Networks (GANs) has led to significant advancements in the field of compositional image synthesis. In particular, recent progress has focused on achieving synthesis at the semantic part level. However, to enhance per...
A key to semantic analysis is a precise and practically useful definition of meaning that is general for all domains of knowledge. We previously introduced the notion of weak semantic map: a metric space allocating concepts along their most general (...
With the advent of the 6G era, the number of IoT devices has experienced explosive growth, leading to the generation of massive amounts of data at the network edge. Semantic communication, as an innovative solution to handling this data deluge, can s...
Semantic communication has recently gained significant attention in theoretical analysis due to its potential to improve communication efficiency by focusing on meaning rather than exact signal reconstruction. In this paper, we extend the Blahut&ndas...
In this paper, we study the semi-supervised semantic segmentation problem via limited labeled samples and a large number of unlabeled samples. We propose a self-learning semi-supervised approach for the semantic segmentation of high-resolution remote...
Point cloud semantic segmentation is crucial for identifying and analyzing transmission lines. Due to the number of point clouds being huge, complex scenes, and unbalanced sample proportion, the mainstream machine learning methods of point cloud segm...
If one believes that
Durational action timed automata (daTAs) are state transition systems like timed automata (TAs) that capture information regarding the concurrent execution of actions and their durations using maximality-based semantics. As the underlying semantics o...
Topic modeling is a popular approach for clustering text documents. However, current tools have a number of unsolved problems such as instability and a lack of criteria for selecting the values of model parameters. In this work, we propose a method t...
Clear and straightforward communication is a key aspect of all human activities related to crisis management. Since crisis management activities involve professionals from various disciplines using different terminology, clear and straightforward com...
In addition to geometric accuracy, topological information, appearance and georeferenced data, semantic capabilities are key strengths of digital 3D city models. This provides the foundation for a growing number of use cases, far beyond visualization...
Manual facial rigging is time-consuming. Traditional automatic rigging methods lack either 3D datasets or explainable semantic parameters, which makes it difficult to retarget a certain 3D expression to a new face. To address the problem, we automati...
1 August 2009
The number of Web services are growing at an explosive speed, which brings great challenges to the accurate, efficient and automatic retrieval of target services for users. This paper presents a service discovery method with semantic matchmaking whic...
Linguistic knowledge helps a lot in scene text recognition by providing semantic information to refine the character sequence. The visual model only focuses on the visual texture of characters without actively learning linguistic information, which l...
The hallmarks of cancer represent an essential concept for discovering novel knowledge about cancer and for extracting the complexity of cancer. Due to the lack of topic analysis frameworks optimized specifically for cancer data, the studies on topic...
Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in e...
Research on image classification sparked the latest deep-learning boom. Many downstream tasks, including semantic segmentation, benefit from it. The state-of-the-art semantic segmentation models are all based on deep learning, and they sometimes make...
The classification of land use and land cover (LULC) is a well-studied task within the domain of remote sensing and geographic information science. It traditionally relies on remotely sensed imagery and therefore models land cover classes with respec...
This work focuses on determining semantically close words and using semantic similarity in general in order to improve performance in information retrieval tasks. The semantic similarity of words is an important task with many applications from infor...
Structural representations in English have been shown to be quite abstract, with structural information being represented independently from semantic information. Mandarin has a relatively sparse marking of syntactic information, with no inflections...
Word processing is one of the most popular digital activities. Despite its popularity, it is haunted by false assumptions, misconceptions, and ineffective and inefficient practices leading to erroneous digital text-based documents. The focus of the p...
This paper introduces the Intensional Conceptualization Model for Open Environments (ICMOE), a formal framework designed to enable semantic integration in dynamic and distributed systems. Grounded in intensional logic and formalized via a domain-spec...
In this work, a system is developed for semantic labeling of locations based on what people do. This system is useful for semantic navigation of mobile robots. The system differentiates environments according to what people do in them. Background sou...
In this paper we explore ChatGPT’s ability to produce a summary, a precis, and/or an essay on the basis of excerpts from a novel—The Solid Mandala—by Nobel Prize Australian writer Patrick White. We use a number of prompts to test a...
The present investigation sought to expand our understanding of the cognitive processes underlying the recognition of antonyms and to evaluate whether these processes differed in patients with schizophrenia and in healthy controls. Antonymy is the mo...
Neural machine translation (NMT) typically relies on a substantial number of bilingual parallel corpora for effective training. Mongolian, as a low-resource language, has relatively few parallel corpora, resulting in poor translation performance. Dat...
We propose a new efficient architecture for semantic segmentation, based on a “Waterfall” Atrous Spatial Pooling architecture, that achieves a considerable accuracy increase while decreasing the number of network parameters and memory foo...
In current Open Banking services, the European Payment Services Directive (PSD2) allows the secure collection of bank customer information, on their behalf and with their consent, to analyze their financial status and needs. The PSD2 directive has le...
Theories of embodied cognition suggest that hand motions and cognition are closely interconnected. An emerging technique of tracking how participants move a computer mouse (i.e., the mouse-tracking technique) has shown advantages over the traditional...
Few-shot knowledge graph completion (FKGC) tasks involve determining the authenticity of triple candidates using a small number of reference triples with a given relation. Intuitively, the expression of relation features contributes to the close corr...
Background: In this narrative review, we have surveyed results obtained from a research program dealing with the role of semantic memory disorders as a predictor of progression from mild cognitive impairment (MCI) to Alzheimer’s disease (AD). O...
Image feature description and matching is widely used in computer vision, such as camera pose estimation. Traditional feature descriptions lack the semantic and spatial information, and give rise to a large number of feature mismatches. In order to i...
To cope with the growing number of multimedia assets on smartphones and social media, an integrated approach for semantic indexing and retrieval is required. Here, we introduce a generic framework to fuse existing image and video analysis tools and a...
Convolutional neural networks have attracted much attention for their use in the semantic segmentation of remote sensing imagery. The effectiveness of semantic segmentation of remote sensing images is significantly influenced by contextual informatio...
Semantic segmentation is a growing topic in high-resolution remote sensing image processing. The information in remote sensing images is complex, and the effectiveness of most remote sensing image semantic segmentation methods depends on the number o...
Image matching-based visual simultaneous localization and mapping (vSLAM) extracts low-level pixel features to reconstruct camera trajectories and maps through the epipolar geometry method. However, it fails to achieve correct trajectories and mappin...
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