1,097 Results Found

In this paper, the question of evaluating the dimension of data space in an inverse source problem from near-field phaseless data is addressed. The study is developed for a $2D$ scalar geometry made up by a magnetic current strip whose square magnitude...

In this article, we tackle the question of evaluating the dimension of the data space in the phase retrieval problem. With the aim to achieve this task, we first exploit the lifting technique to recast the quadratic model as a linear one. After that,...

We consider a communication system whereby T-seconds time-limited codewords are transmitted over a W-Hz band-limited additive white Gaussian noise channel. In the asymptotic regime as $WT\to \infty$, it is known that the maximal achievable rates wit...

Picking an appropriate parameter setting (meta-parameters) for visualization and embedding techniques is a tedious task. However, especially when studying the latent representation generated by an autoencoder for unsupervised data analysis, it is als...

Space-time interpolation is widely used to estimate missing or unobserved values in a dataset integrating both spatial and temporal records. Although space-time interpolation plays a key role in space-time modeling, existing methods were mainly devel...

Regardless of the type of data, traditional Bloom filters treat each element of a set as a string, and by iterating every character of the string, they discretize all data randomly and uniformly. However, with the data size and dimension increases, t...

This paper proposes a novel approach for identification of nonlinear systems. By transforming the data space into a feature space, kernel methods can be used for modeling nonlinear systems. The spline kernel is adopted to produce a Hilbert space. How...

Spatiotemporal big data contain information in multiple dimensions such as space and time. Spatiotemporal data have the characteristics of large volume, intricate spatiotemporal relationship, and uneven spatiotemporal distribution. Index structure is...

As an important part of urban green infrastructure, the landscape effect of the urban waterfront green space varies, and sometimes, the green space with an excellent landscape aesthetic value fails to serve the needs of most citizens. This seriously...

Social sustainability has emerged as a critical factor in evaluating societal welfare and well-being. Consequently, researchers have initiated the development of a theoretical framework to delineate the components of social sustainability, achieving...

When performing classification tasks on high-dimensional data, traditional machine learning algorithms often fail to filter out valid information in the features adequately, leading to low levels of classification accuracy. Therefore, this paper expl...

Well-separated pair decomposition (WSPD) is a well known geometric decomposition used for encoding distances, introduced in a seminal paper by Paul B. Callahan and S. Rao Kosaraju in 1995. WSPD compresses $O\left(n^2\right)$ pairwise distances of n given points fr...

The core technology for building a smart space includes the capability to analyse the space for users using various sensors. The purpose of this study was to propose a personalised interactive smart space implementation model driven by the fusion of...

In this work, we focus on sparse representation of two-dimensional (2-D) radar signatures for man-made targets. Based on the damped exponential (DE) model, a 2-D augmented state–space approach (ASSA) is proposed to estimate the parameters of sc...

To improve the classification results of high-resolution remote sensing images (RSIs), it is necessary to use feature transfer methods to mine the relevant information between high-resolution RSIs and low-resolution RSIs to train the classifiers toge...

Catchment classification plays an important role in many applications associated with water resources and environment. In recent years, several studies have applied the concepts of nonlinear dynamics and chaos for catchment classification, mainly usi...

Amid the current global trend toward urbanization, there is a growing need for an improved quality of life. While rural public spaces are essential components of community life, their design and planning have traditionally focused on material aspects...

The self-similar structure-based analysis of digital images offers many new practical possibilities. The fractal dimension is one of the most frequently measured parameters if we want to use image data in measurable analyses in metric spaces. In prac...

This paper presents a relativistic version of Newtonian Fractional-Dimension Gravity (NFDG), an alternative gravitational model recently introduced and based on the theory of fractional-dimension spaces. This extended version—Relativistic Fractional-...

The Latent Space Perspicacity and Interpretation Enhancement (LS-PIE) framework enhances dimensionality reduction methods for linear latent variable models (LVMs). This paper extends LS-PIE by introducing an optimal latent discovery strategy to autom...

We will explore, in any space dimension $d\ge 4$, the decay in the energy space for the damped magnetic Schrödinger equation with non-local nonlinearity and radial initial data in $H^1\left({\mathbb{R}}^d\right)$. We will also display new Morawetz identities and correspond...

The structure of turbulent dynamics in a stable atmospheric boundary layer was studied by means of a phase-space description. Data from the CASES-99 experiment, decomposed in local modes (with increasing time scale) using empirical mode decomposition...

This paper focuses on the throughput performance enhancement in the single cell multi-user MIMO (MU-MIMO) downlink system model. For better quality of service, this paper proposes the scheme that increases system throughput and improves the spectral...

With the prevalence of mental health problems among college students, perceptual recovery and the sensory dimensions of perception (PSD) have emerged as crucial environment-related factors for psychological well-being. However, there has been relativ...

Feature extraction is a common problem in statistical pattern recognition. It refers to a process whereby a data space is transformed into a feature space that, in theory, has exactly the same dimension as the original data space. However, the transf...

Electroencephalography (EEG) signals can be analyzed in the temporal, spatial, or frequency domains. Noise and artifacts during the data acquisition phase contaminate these signals adding difficulties in their analysis. Techniques such as Independent...

To understand the complex phenomena in social space and monitor the dynamic changes in people’s tracks, we need more cross-scale data. However, when we retrieve data, we often ignore the impact of multi-scale, resulting in incomplete results. T...

We will show, in any space dimension $d\ge 3$, the decay and scattering in the energy space for the solution to the damped nonlinear Schrödinger equation posed on ${\mathbb{R}}^d\times \mathbb{T}$ and initial data in $H^1({\mathbb{R}}^d\times \mathbb{T})$. We will also derive new bilinear Mora...

The utilization of urban underground space resources (UUSR) are important approaches to effectively save land resources, improve the living environment, expand the urban space, and achieve sustainable urban development. To obtain accurate UUSR evalua...

This article presents methodology of land use change assessment in the context of sustainable development and the results of its application based on the transformations that occurred in individual areas of Europe in the years 2012–2018. This m...

SEM microfractographies of Zircaloy-4 are studied by fractal analysis and the time-series method. We first develop a computer application that associates the fractal dimension and lacunarity to each SEM micrograph picture, and produce a nonlinear ana...

The mental health of university students has received much attention due to the various pressures of studies, life, and employment. Several studies have confirmed that campus public spaces contain multiple restorative potentials. Yet, the campus publ...

Quantum contextuality supports quantum computation and communication. One of its main vehicles is hypergraphs. The most elaborated are the Kochen–Specker ones, but there is also another class of contextual sets that are not of this kind. Their...

In this work, we propose to study the collective behavior of different ensembles of neural networks. These sets define and live on complex manifolds that evolve through training. Each manifold is characterized by its intrinsic dimension, a measure of...

Outlier detection is an important task in the field of data mining and a highly active area of research in machine learning. In industrial automation, datasets are often high-dimensional, meaning an effort to study all dimensions directly leads to da...

A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and se...

Over the past decade and a half, dynamic functional imaging has revealed low-dimensional brain connectivity measures, identified potential common human spatial connectivity states, tracked the transition patterns of these states, and demonstrated mea...

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As...

Recently, attention has been drawn to the need to integrate sex/gender more comprehensively into environmental health research. Considering theoretical approaches, we define sex/gender as a multidimensional concept based on intersectionality. However...

This paper introduces a conceptual mathematical framework for evaluating trustworthiness in AI-based big data analysis, emphasizing the critical role trust plays in the adoption and effectiveness of AI systems. The proposed model leverages the trustw...

Public transportation serving urban tourism has a positive impact on sustainable urban development. With the rapid rise of “subway tourism” in China and the emergence of numerous popular attractions, the pedestrian spaces connecting subwa...

Climate has complex dynamics due to the plethora of phenomena underlying its evolution. These characteristics pose challenges to conducting solid quantitative analysis and reaching assertive conclusions. In this paper, the global temperature time ser...

A method of positioning a location on a specific object using a wireless sensor has been developed for a long time. However, due to the error of wavelengths and various interference factors occurring in three-dimensional space, accurate positioning i...

Automated target recognition is an important task in the littoral warfare domain, as distinguishing mundane objects from mines can be a matter of life and death. This is initial work towards the application of convolutional autoencoding to the littor...

Federated learning has gained popularity in recent years to enhance IoT security because the model allows decentralized devices to collaboratively learn a shared model without exchanging raw data. Despite its privacy advantages, federated learning is...

The online public opinion is the sum of public views, attitudes and emotions spread on major public health emergencies through the Internet, which maps out the scope of influence and the disaster situation of public health events in real space. Based...

Multi-label text classification refers to a text divided into multiple categories simultaneously, which corresponds to a text associated with multiple topics in the real world. The feature space generated by text data has the characteristics of high...

Synthesis of the title compound from 4-methoxyaniline was accomplished in three steps. The structure was supported by spectroscopic data and unambiguously confirmed by single crystal X-ray diffraction data. It crystallizes in the monoclinic space gro...

The collection of spatialised electricity consumption data is considered of crucial importance for planning electric power facilities and achieving the United Nations Sustainable Development Goal 7 (SDG7). However, the predominance of statistical dat...

Urban green spaces are a crucial element of sustainable urban development, but their uneven distribution exacerbates socio-spatial inequalities within cities. This study analyses spatial inequalities in the distribution and accessibility of urban gre...