Search · four archives
Search · four archives
24 papers · ranked by Valyu relevance
Yutong Wang, Yujing Wu, Yihu Xu, Kaihang Zhang + 2 more
The Internet of Vehicles plays a crucial role in advancing intelligent transportation systems, with In-Vehicle Ethernet serving as the fundamental backbone network of the new generation of in-vehicle communication. However, In-Vehicle Ethernet faces various network security threats, including data theft, data…
Xiaoyong Zhang, Guojun Zhang, Zhenzhen Shang, Shan Zhu + 4 more
'Renxin Wang' 'Wendong Zhang' 'Huikai Xie'] The principle of acoustic energy flux detection method using a single micro electromechanical system (MEMS) vector hydrophone is analyzed in this paper. The probability distribution of acoustic energy flux and the weighted histogram algorithm are discussed. Then, an improved…
Mahdieh Poostchi, Ali Shafiekhani, Kannappan Palaniappan, Guna Seetharaman
'Guna Seetharaman'] Weighting pixel contribution considering its location is a key feature in many fundamental image processing tasks including filtering, object modeling and distance matching. Several techniques have been proposed that incorporate Spatial information to increase the accuracy and boost the performance…
N. Gagunashvili
Weighted histograms are used for the estimation of probability density functions. Computer simulation is the main domain of application of this type of histogram. A review of chi-square goodness of fit tests for weighted histograms is presented in this paper. Improvements are proposed to these tests that have size more…
Thaweesak Trongtirakul, Sos С. Agaian
Low-contrast image enhancement is essential for high-quality image display and other visual applications. However, it is a challenging task as the enhancement is expected to increase the visibility of an image while maintaining its naturalness. In this paper, the weighted histogram equalization using the entropy of the…
Will P. M. Rowe, Anna Paola Carrieri, Cristina Alcon-Giner, Shabhonam Caim + 6 more
The growth in publically available microbiome data in recent years has yielded an invaluable resource for genomic research; allowing for the design of new studies, augmentation of novel datasets and reanalysis of published works. This vast amount of microbiome data, as well as the widespread proliferation of microbiome…
Anshumali Shrivastava
Weighted minwise hashing (WMH) is one of the fundamental subroutine, required by many celebrated approximation algorithms, commonly adopted in industrial practice for large scale-search and learning. The resource bottleneck of the algorithms is the computation of multiple (typically a few hundreds to thousands)…
Wei Wu, Bin Li, Ling Chen, Junbin Gao + 1 more
—Data similarity (or distance) computation is a fundamental research topic which underpins many high-level applications based on similarity measures in machine learning and data mining. However, in large-scale real-world scenarios, the exact similarity computation has become daunting due to "3V" nature (volume…
Nikolay D. Gagunashvili
Histograms with weighted entries are used to estimate probability density functions. Computer simulation is the main application of this type of histograms. A review on chi-square tests for comparing weighted histograms is presented in this paper. Improvements to these tests that have a size closer to its nominal value…
Rui Fan, Qinghua Cui
Gene functional enrichment analysis represents one of the most popular bioinformatics methods for annotating the pathways and function categories of a given gene list. Current algorithms for enrichment computation such as Fisher’s exact test and hypergeometric test totally depend on the category count numbers of the…
Omer Faruk Gulban, Marian Schneider, Ingo Marquardt, Roy A.M. Haast + 1 more
High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray…
Sana Qaiyum, Izzatdin Aziz, Mohd Hilmi Hasan, Asif Irshad Khan + 1 more
'Abdulmohsen Almalawi'] Data Streams create new challenges for fuzzy clustering algorithms, specifically Interval Type-2 Fuzzy C-Means (IT2FCM). One problem associated with IT2FCM is that it tends to be sensitive to initialization conditions and therefore, fails to return global optima. This problem has been addressed…
N. M. Kilany
The Lomax distribution (Pareto Type-II) is widely applicable in reliability and life testing problems in engineering as well as in survival analysis as an alternative distribution. In this paper, Weighted Lomax distribution is proposed and studied. The density function and its behavior, moments, hazard and survival…
Authors not listed
Single particle inductively coupled plasma-mass spectrometry (SP ICP-MS) has emerged as a powerful technique for characterising nanoparticles (NPs) and is increasingly used to target microparticles including microplastics (MPs). The accuracy of determining size distributions and number concentrations in SP ICP-MS is…
Authors not listed
Electrochemical impedance spectroscopy (EIS) is one of the most widely deployed methods to characterise electrochemical systems such as batteries, fuel cells or electrolyzers. The distribution of relaxation times (DRT) represents a technique to simplify EIS data by deconvolution with a suitable kernel, while with…
Authors not listed
We present a unified, set–theoretic framework that extends molecular graphs to hypergraphs and superhypergraphs via iterated power sets. We define Molecular Graphs, Molecular HyperGraphs, and Molecular SuperHyperGraphs, and develop four complements over them: Weighted, Rough, Neural, and Multipolar frameworks. We prove…
Mojtaba Ostovari, Alireza Zarei
This article introduces a quick and simple combinatorial approximation algorithm for the weighted correlation clustering problem. In this problem, we have a set of vertices and two weight values for each pair of vertices denoting their difference and similarity. The goal is to cluster the vertices with minimum total…
Kati Rozman, An Ghysels, Dušanka Janežič, Janez Konc
We introduce a new algorithm MaxCliqueWeight for identifying a maximum weight clique in a weighted graph, and its variant MaxCliqueDynWeight with dynamically varying bounds. This algorithm uses an efficient branch-and-bound approach with a new weighted graph coloring algorithm that efficiently determines upper weight…
Adi Alhudhaif, Mehmet Cunkas
Background This article aims to determine the coefficients that will reduce the in-class distance and increase the distance between the classes, collecting the data around the cluster centers with meta-heuristic optimization algorithms, thus increasing the classification performance. Methods The proposed mathematical…
Evangelos Karatzas, Maria Gkonta, Joana Hotova, Fotis A. Baltoumas + 4 more
Clustering is the process of grouping together different data objects based on similar properties. Clustering has applications in various case studies from several fields such as graph theory, image analysis, pattern recognition, statistics and others. Nowadays, there are numerous algorithms and tools able to generate…
Denis Tikhonov
Here, we present a new approach for obtaining radial distribution functions (RDF) from the electron diffraction data using a regularized weighted sine least-squares spectral analysis (rwsLSSA). It allows for explicitly transferring the measured experimental uncertainties in the reduced molecular scattering function to…
Dima Kagan, Juman Jubran, Esti Yeger-Lotem, Michael Fire
Anomaly detection in graphs is critical in various domains, notably in medicine and biology, where anomalies often encapsulate pivotal information. Here, we focused on network analysis of molecular interactions between proteins, which is commonly used to study and infer the impact of proteins on health and disease. In…
Mehrsa Pourya, Shayan Aziznejad, Michael Unser, Daniel Sage
We propose a novel method for the clustering of point-cloud data that originate from single-molecule localization microscopy (SMLM). Our scheme has the ability to infer a hierarchical structure from the data. It takes a particular relevance when quantitatively analyzing the biological particles of interest at different…
Filip Milisav, Vincent Bazinet, Richard F. Betzel, Bratislav Misic
Scientific discovery in connectomics relies on the use of network null models. To systematically evaluate the prominence of brain network features, empirical measures are compared against null statistics computed in randomized networks. Modern imaging and tracing technologies provide an increasingly rich repertoire of…