Classification - Science topic

Hypergraphs extend traditional graphs by allowing edges to connect multiple nodes, while superhypergraphs further generalize this concept to represent even more complex relationships. Neural networks, inspired by biological systems, are widely used for tasks such as pattern recognition, data classification, and prediction. Graph Neural Networks (G...

The object of this paper is to bringout the space r q B (g, p) of non-absolute pattern. Also, we will structure its completeness property. Also, the köthe-duals will be determined. Moreover, the Schauder basis for it will be constructed. 2020 Mathematical Subject Classification: 46A45; 40C05; 46J05.

Machine-and deep-learning techniques have been used in numerous real-world applications. One of the famous deep-learning methodologies is the Deep Convolutional Neural Network. AlexNet is a well-known global deep convolutional neural network architecture. AlexNet significantly contributes to solving different classification problems in different ap...

This paper analysed student’s perceptions on use of a mobile proctoring application (app). The study used case of South Africa where few universities were using a proctoring mobile application called The Invigilator. Using constructs from mobile app rating scale (MARS), users’ views from app stores, reports and online news articles were thematicall...

The classification and naming of plants and animals is said to follow a number of "universal" constraints cross-linguistically. While these constraints are generally accepted in the literature, few have been rigorously tested with a large language sample. In particular, the languages of mainland southeast Asia appear to have been neglected in such...

Cellulose-based composite fibres (CCFs) emerged by optimizing the application of fibres. There can often be classifications for it, which are basic or advanced. The availability of resources and the application of recyclable and environmentally friendly raw materials have caused studies in cellulose composites to explode in recent years. The demand...

This study proposes an innovative model (i.e., SensoryT5), which integrates sensory knowledge into the T5 (Text-to-Text Transfer Transformer) framework for emotion classification tasks. By embedding sensory knowledge within the T5 model's attention mechanism, SensoryT5 not only enhances the model's contextual understanding but also elevates its sen...

From two functions in the Hilbert space L 2 (R d) whose Fourier transform has certain decay, one defines a quasi-projection operator. In this paper, we prove necessary and sufficient conditions on those functions in order to the associated quasi-projection operator provides a desired approximation order and density order. To give our conditions we...

Causal cognition includes the ability and mental processes of feeling, perception, attention, learning, memory, thinking, reasoning, representation, etc. Causal cognition is embodied and situational, but the specific effects of body and environment on causal cognition are still vague. This paper introduces the classification of causal cognition, di...

Child trafficking is a deep-seated social issue with enduring consequences that remain concealed or less obvious to the general public. We argue that the intensity of child trafficking increases as an indirect and unintended consequence of improved urban infrastructure, such as the construction of highways that facilitate the expedient transfer of...

The digitalization of manufacturing is progressing steadily. This transition means that value creation in manufacturing is increasingly being orchestrated through digital platforms. The success of digital platforms depends heavily on the deployment of boundary resources by the platform provider. They allow the platform provider to maintain control...

We introduce VEMOCLAP: Video EMOtion Classifier using Pretrained features, the first readily available and open-source web application that analyzes the emotional content of any user-provided video. We improve our previous work, which exploits open-source pretrained models that work on video frames and audio, and then efficiently fuse the resulting...

This paper presents a descriptive study of the acoustic features of the monophthongs in Central Australian Aboriginal English (CAAE, Alice Springs). We extracted vowel tokens from conversational speech of six female speakers who spoke CAAE as one of their primary languages. We analysed the acoustic differences between the vowel categories using a c...

Article History

Risk-based artificial intelligence (AI) regulations define risk categories for AI-enabled systems. The operators of such systems must determine the risk category applicable to their AI systems. This requires detailed knowledge of the classification rules defined in the regulations. Only a few supporting tools have been developed to facilitate the t...

The emergence of adversarial examples poses a significant challenge to hyperspectral image (HSI) classification, as they can attack deep neural network-based models. Recent adversarial defense research tends to establish global connections of spatial pixels to resist adversarial attacks. However, it cannot yield satisfactory results when only spati...

The concepts of precision, and accuracy are domain and problem dependent. The simplified numeric hard and soft measures used in the fields of statistical learning, many types of machine learning, and binary or multiclass classification problems are known to be of limited use for understanding the meaningfulness of models or their relevance. Arguabl...

To view the online publication, please click here: https://www.frontiersin.org/articles/10.3389/fresc.2024.1498263

This article developed the idea from Gardašević et al [J. Con-temp. Math. Anal., Armen. Acad. Sci., 58(2), 2023, 105-115]. We give an answer to the open question from that paper with the additional condition that the orthogonal element set is ⊥-transitive. Firstly, we formulate and prove the theorem of the best proximity point under different condi...

ABSTRACT The aim of this study was to explore if enhancing conventional input images by adding computer-generated connected body keypoints (called hereafter Skeleton) will improve the accuracy of postural classification by deep learning. The ResNet-50 model based on PictureWithSkeleton (PS) data outperformed the others with an accuracy and F1-sco...

To deliver low-carbon transitions, we must understand the dynamics of capital. To this end, I develop a theory of energy-capital relations by reading Adam Smith's The Wealth of Nations from an energy-analysis perspective. I argue that, for Smith, capital is any resource used to support production with the intention of generating profits through mar...

This paper examines equilibria in dynamic two-sided matching games, extending Gale and Shapley's foundational model to a non-cooperative, decentralized, and dynamic framework. We focus on markets where agents have utility functions and commitments vary. Specifically, we analyze a dynamic matching game in which firms make offers to workers in each p...

We study the extension of homologically trivial symplectic or Hamiltonian cyclic actions to Hamiltonian circle actions on irrational ruled symplectic $4$-manifolds. On one hand, we construct symplectic involutions on minimal irrational ruled $4$-manifolds that cannot extend to a symplectic circle action even with a possibly different symplectic for...

Comparison between Asia-Indian and World Health Organization classification of obesity for pulmonary function in Healthy adults of Sikkim, India.

Autism Spectrum Disorder is a disorder associated with genetic and neurological component with a lifelong effect on communication and interaction with others. Autism Spectrum Disorders children have some disturbance activities. Understanding their necessities is one of the most challenging tasks for caregivers. The classification algorithms helps t...

The article raises the problem of the ambiguity and polysemantic nature of the complex and heterogeneous semantics of the concept of science. This concept includes theories and methods, models and classifications of reality, scientific laws and laws of nature, scientific thinking, scientific publications, experiments and laboratory activities, scie...

A system of linear equations $L$ is said to be norming if a natural functional $t_L(\cdot)$ giving a weighted count for the set of solutions to the system can be used to define a norm on the space of real-valued functions on $\mathbb{F}_q^n$ for every $n>0$. For example, Gowers uniformity norms arise in this way. In this paper, we initiate the syst...

Multiclass data classification with class imbalance causes classification performance to decrease, especially in the Neural network method. Research shows that the model proposed by eNN can improve model performance for imbalanced data in the selection of superior quality in beef and cattle data. The results of the Ensemble ANN study with adaboost...

Next to thematic coding, NVivo also allows coding with classifications. Classifications can be considered as a separate database in a project. In such a database, NVivo stores variables (called Attributes) that allow comparisons. Even though the classification tool is programmed in a relatively uniform way in the program, NVivo distinguishes betwee...

This study aims to analyze the role of artificial intelligence in enhancing the efficiency of international freight transport, focusing on how AI technologies can be employed to improve logistical operations, reduce costs, and bolster environmental sustainability. Furthermore, the study highlights leading international experiences in utilizing arti...

Objectives: The goal of this study to estimate the correlation between breast cancer and cyclin‑dependent kinase 4 (CDK4)\CDK6 enzyme concentrations in the occurrence of breast cancer and breast cancer subtypes. Methods: A total of 80 breast cancer patients are subdivided according to molecular classification into four groups, Luminal A, Luminal B,...

Mixture-of-Experts (MoE) models have shown promising potential for parameter-efficient scaling across various domains. However, the implementation in computer vision remains limited, and often requires large-scale datasets comprising billions of samples. In this study, we investigate the integration of MoE within computer vision models and explore...

Assuming Stanley’s P -partitions conjecture holds, the regular Schur labeled skew shape posets are precisely the finite posets P with underlying set $\{1, 2, \ldots , |P|\}$ such that the P -partition generating function is symmetric and the set of linear extensions of P , denoted $\Sigma _L(P)$ , is a left weak Bruhat interval in the symmetric gro...

The rising interest in Bayesian deep learning (BDL) has led to a plethora of methods for estimating the posterior distribution. However, efficient computation of inferences, such as predictions, has been largely overlooked with Monte Carlo integration remaining the standard. In this work we examine streamlining prediction in BDL through a single fo...

Given any unital, finite, classifiable $\mathrm{C}^*$ -algebra A with real rank zero and any compact simplex bundle with the fibre at zero being homeomorphic to the space of tracial states on A , we show that there exists a flow on A realizing this simplex. Moreover, we show that given any unital $\mathrm{UCT}$ Kirchberg algebra A and any proper si...

Background The study aimed to evaluate whether a new OhtoFix plate reduced stress around the D-hole compared with an old OhtoFix and TomoFix plate. The study also assessed whether the new OhtoFix plate had biomechanical stability in a lateral hinge fracture (LHF). Methods A finite element model of the proximal tibia was developed using cross-secti...

Data Mining is a process of mining and extracting new information from a huge set of raw data. Classification is a data mining technique that is used to classify each item in a data set into one of the classes or groups. Decision Tree builds classification models into a tree like structure that provides a neat description about the whole dataset. I...

The first part of the agricultural tractor classifications, explaining at the beginning the operational characteristics of the agricultural tractor, and what are the justifications for studying the tractor as a machine in itself, then presenting the foundations and standards for classifying agricultural tractors. Explaining the tractor classificati...

Diabetes mellitus is a chronic disease often caused by high blood glucose levels and insufficient insulin production. This research aims to address the classification problem of diabetes mellitus using the K-Nearest Neighbor (K-NN) method. The aim of this research is to create a machine learning model that can detect diabetes early. The study was c...

Retrieval-augmented generation (RAG) addresses the problem of knowledge cutoff and overcomes the inherent limitations of pre-trained language models by retrieving relevant information in real time. However, challenges related to efficiency and accuracy persist in current RAG strategies. A key issue is how to select appropriate methods for user quer...

This paper builds upon J. Nilsson's classification of rank one $\mathcal{U}(\mathfrak{h})$-free modules by extending the analysis to modules without rank restrictions, focusing on the category $\mathfrak{A}$ of $\mathcal{U}(\mathfrak{h})$-finite $\mathfrak{g}$-modules. A deeper investigation of the weighting functor $\mathcal{W}$ and its left deriv...

This study investigates the characteristics and intensity of El Niño–Southern Oscillation (ENSO) events from January 1875 to December 2023, employing an advanced method for intensity determination based on various ENSO indices defined as a continuous five-month period with temperatures exceeding 0.5 °C for warm events or falling below −0.5 °C for c...

The pinball loss is favored in support vector machines for its robustness against noise. However, its unbounded nature makes it sensitive to outliers. To address this, a rescaled pinball loss offering boundedness has been introduced. Despite this improvement, the model’s performance may be limited due to restricted parameter adjustments, and its no...

Genomic Language Models (GLMs), which learn from nucleotide sequences, have become essential tools for understanding the principles of life and have demonstrated outstanding performance in downstream tasks of genomic analysis, such as sequence generation and sequence classification. However, models that achieve state-of-the-art (SoTA) results in be...

Brain activity patterns in high-level visual cortex support accurate linear classification of visual concepts (e.g., objects or scenes). It has long been appreciated that the accuracy of linear classification in any brain area depends on the geometry of its concept manifolds---sets of brain activity patterns that encode images of a concept. However...

We study some compactness properties of the set of conformally flat singular metrics with constant, positive sixth order Q-curvature on a finitely punctured sphere. Based on a recent classification of the local asymptotic behavior near isolated singularities, we introduce a notion of necksize for these metrics in our moduli space, which we use to c...

Zusammenfassung Neurorehabilitation ist gekennzeichnet durch eine strukturierte, interdisziplinäre Zusammenarbeit verschiedener Professionen, orientiert an individuellen Teilhabezielen. Dabei müssen verschiedene Betrachtungsebenen von Funktionalität, Aktivität und Partizipation (International Classification of Functioning, Disability, and Health, I...

The remarkable progress in deep learning (DL) showcases outstanding results in various computer vision tasks. However, adaptation to real-time variations in data distributions remains an important challenge. Test-Time Training (TTT) was proposed as an effective solution to this issue, which increases the generalization ability of trained models by...

The Covid-19 pandemic has posed a challenge to the use of technology in the education sector in Indonesia. This situation has made university students independent learners through online classes. In the beginning of Covid-19 the students at Udayana University have implemented online learning. In this context, students are required to understand the...

This paper investigates the geometry of regular Hessenberg varieties associated with the minimal indecomposable Hessenberg space in the flag variety of a complex reductive group. These varieties form a flat family of irreducible subvarieties of the flag variety, encompassing notable examples such as the Peterson variety and toric varieties linked t...

In recent years, artificial intelligence (AI) has experienced remarkable growth, largely driven by significant advancements in algorithm structures. This paper provides a comprehensive review of the key algorithmic frameworks employed in AI, with a primary focus on traditional algorithms and their evolution in response to modern deep learning techn...

Botnets are a serious threat to computer networks. New botnets are created with the aim of evading detection by making modifications. The proposed methods are insufficient for detecting modified botnets. A Generative Adversarial Network (GAN) trained with generated and real data was used to improve detection performance against altered botnets. GAN...

Feature selection is aimed at reducing the dimensionality of datasets while maintaining or enhancing classification accuracy. Recent studies have increasingly approached feature selection through multi-modal, multi-objective optimization. However, for high-dimensional datasets, the large decision space limits the ability of traditional multi-modal,...

Land consolidation is carried out in our country with the aim of reducing land fragmentation, constructing roads and irrigation channels for each parcel, and establishing sustainable agricultural enterprises by increasing agricultural production. Land consolidation has conducte terms of sustainable agriculture. Many researchers have been investigat...

The Coskinolinidae comprises a family of Middle Jurassic-Paleogene, typically orbitoliniform larger benthic foraminifera, displaying a pseudokeriothecal wall structure. The type genus Coskinolina Stache, 1875 lacks an exoskeleton (i.e., beams, rafters) giving rise to an undivided marginal chamber zone. However, other taxa included in the family suc...

Machine learning models are susceptible to being misled by biases in training data that emphasize incidental correlations over the intended learning task. In this study, we demonstrate the impact of data bias on the performance of a machine learning model designed to predict the likelihood of synthesizability of crystal compounds. The model perform...

Fairness in both machine learning (ML) predictions and human decisions is critical, with ML models prone to algorithmic and data bias, and human decisions affected by subjectivity and cognitive bias. This study investigates fairness using a real-world university admission dataset with 870 profiles, leveraging three ML models, namely XGB, Bi-LSTM, a...

Noisy labels pose a substantial challenge in machine learning, often resulting in overfitting and poor generalization. Sharpness-Aware Minimization (SAM), as demonstrated in Foret et al. (2021), improves generalization over traditional Stochastic Gradient Descent (SGD) in classification tasks with noisy labels by implicitly slowing noisy learning....

Ce rapport, élaboré par l’Université du Québec à Montréal (UQAM), examine les programmes nationaux et les compétences professionnelles des encadrants d'activités de plein air (EAPA). Financé par le ministère de l'Éducation du Québec et le Réseau plein air Québec, il se concentre sur deux volets : 1) une revue systématique de la portée de la littéra...

Recently, time series classification has attracted the attention of a large number of researchers, and hundreds of methods have been proposed. However, these methods often ignore the spatial correlations among dimensions and the local correlations among features. To address this issue, the causal and local correlations based network (CaLoNet) is pr...

Predictive justice, which involves forecasting trial outcomes, presents significant challenges due to the complex structure of legal judgments. To address this, it is essential to first identify all claims across different categories before attempting to predict any result. This paper focuses on a classification task based on the detection of Artic...

A notion of support for objects in any Grothendieck category is introduced. This is based on the spectral category of a Grothendieck category and uses its Boolean lattice of localising subcategories. The support provides a classification of all subcategories that are closed under arbitrary coproducts, subobjects, and essential extensions. There is...

This paper analyzes the application of neural networks for evaluating public lighting projects, focusing on compliance with Brazilian Standard 5101/2018. The study uses Multilayer Perceptron (MLP) models to perform regression and classification tasks, aiming to predict illuminance and uniformity parameters and classify the project's compliance with...

This study focuses on cross-lingual short text classification tasks and aims to combine the advantages of BERT and Multi-layer Collaborative Convolutional Neural Network (MCNN) to build an efficient classification model. BERT model provides rich semantic information for text classification with its powerful language understanding and bidirectional...

Volcanic ash is made of particles smaller than 2 mm and is produced during volcanic eruptions. Studying the properties of volcanic ash is key for a range of applications, including volcano monitoring. However, given the large variety of textures, colors, and shapes of particles from different eruptions and volcanoes it is challenging to classify th...

We give a complete classification of torsion pairs in repetitive cluster categories of type \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$A_n$$\end{document}, which w...

With the continuous development of optical imaging technology and the growing demand for remote sensing applications, cross-scale high-resolution optical technology has been widely used in the field of remote sensing. In order to obtain more detailed information on the target, domestic and foreign researchers have carried out relevant research in d...

We complete the classification of semigraphical translators for mean curvature flow in $\mathbb{R}^3$ that was initiated by Hoffman-Mart\'in-White. Specifically, we show that there is no solution to the translator equation on the upper half-plane with alternating positive and negative infinite boundary values, and we prove the uniqueness of pitchfo...

Meta-learning algorithms learn from other learning algorithms to solve new tasks with only a few labeled instances. Despite being effective for quick learning, it has some limitations. During meta-training phase, inconsequential connections are frequently seen, which leads to an over-parameterized neural network with unnecessary extra gradient comp...

To enhance the classification efficiency of hydrocyclones, this study introduces a novel hydrocyclone design featuring a composite curved-inlet-body structure. Through numerical simulations, the internal flow field characteristics of this structure are thoroughly investigated. The results reveal several key findings: when the diameter of the overfl...

Automated assessing prosody of oral reading fluency presents challenges due to the inherent difficulty of quantifying prosody. This study proposed and evaluated an approach focusing on specific prosodic features using a deep-learning neural network. The current work focuses on cross-domain performance, researching how generalizable the prosody scor...

The present study aimed to evaluate the effects of chronic pimobendan monotherapy on cardiac size in dogs with stage B2 myxomatous mitral valve disease (MMVD). Data from 31 dogs diagnosed with MMVD and cardiomegaly (LA/Ao ≥ 1.6 and LVIDdn ≥ 1.7) were included. The intervention group were dogs treated with pimobendan (n = 24). Dogs not receiving any...

Aiming to address the problems of difficulty in selecting characteristic quantities and the reliance on manual experience in the diagnosis of transformer core loosening faults, a diagnosis method for transformer core looseness based on the Gram angle field (GAF), residual network (ResNet), and multi-head attention mechanism (MA) is proposed. This m...

In this paper, we study left invariant Randers metric F on six-dimensional nilpotent Lie group N6,11 with Lie algebra n6,11. We compute Levi-civita connection, Riemann curvature tensor, sectional curvature, Ricci curvature and scalar curvature on (N6,11, F). Moreover, we classify simply connected six-dimensional nilpotent Lie groups equipped with (...

We focus on the $G$-fans associated with cluster patterns whose initial exchange matrices are of infinite type. We study the asymptotic behavior of the $g$-vectors around the initial $G$-cone under the alternating mutations for two indices of infinite type. In the rank 3 case, we classify them into several patterns. As an application, the incomplet...