Science topics: Computer Science and EngineeringData Structures
Science topic
Data Structures - Science topic
Data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently.
Publications related to Data Structures (10,000)
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A comprehensive neural model of language must accommodate four components: representations, operations, structures and encoding. Recent intracranial research has begun to map out the feature space associated with syntactic processes, but the field lacks a unified framework that can direct invasive neural analyses. This article proposes a neurocompu...
Research on blockchain has found that the technology is no silver bullet compared to traditional data structures due to limitations regarding decentralization, security, and scalability. These limitations are summarized in the blockchain trilemma, which today represents the greatest barrier to blockchain adoption and applicability. To address these...
Collaborative filtering (CF) based on graph neural networks (GNN) can capture higher-order relationships between nodes, which in turn improves recommendation performance. Although effective, GNN-based methods still face the challenges of sparsity and noise in real scenarios. In recent years, researchers have introduced graph self-supervised learnin...
Whether bilingualism results in improved executive function is controversial. According to some researchers, putative bilingual advantages can be explained by individual differences in unmeasured non-linguistic variables. Additionally, commonly used models containing exclusively fixed-effects do not account for the data structure inherent in multi-...
Background
Data extraction (DE) is a challenging step in systematic reviews (SRs). Complex SRs can involve multiple interventions and/or outcomes and encompass multiple research questions. Attempts have been made to clarify DE aspects focusing on the subsequent meta-analysis; there are, however, no guidelines for DE in complex SRs. Comparing datase...
Background
As a single reference genome cannot possibly represent all the variation present across human individuals, pangenome graphs have been introduced to incorporate population diversity within a wide range of genomic analyses. Several data structures have been proposed for representing collections of genomes as pangenomes, in particular graph...
The development of information technology has had a positive impact on the healthcare sector, particularly in disease analysis. Eye diseases are among the health issues that require early detection for effective prevention and treatment. In this context, this research proposes the development of a PHP and MySQL-based Eye Disease Analysis System uti...
In this article, on the basis of the creation, grouping and classification of the database in the ArcGIS program, the content of the elekrton digital card based on the cartographic basis, design and methodology of irrigation and hydrography networks of the Fergana region and irrigation networks in the region for territorial organization was develop...
Graph collaborative filtering can efficiently find the hidden interests of users for recommender systems in recent years. This method can learn complex interactions between nodes in the graph, identify user preferences, and provide satisfactory recommendations. However, recommender systems face the challenge of data sparsity. To address this, recen...
This research examines the impact of the Simples Nacional policy on the revenue of Micro and Small Enterprises (MSEs) and their payment of taxes on goods and services (ICMS) in the State of Ceará, Brazil. The Simples Nacional is a tax collection regime created by Complementary Law No. 123/2006, with the purpose of reducing the tax burden for compan...
The causative pathogen of coronavirus disease 2019 (COVID-19), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an enveloped virus assembled by a lipid envelope and multiple structural proteins. In this study, by integrating experimental data, structural modeling, as well as coarse-grained and all-atom molecular dynamics simulations...
A geração de sinais com frequência precisa e estável é um processo de grande importância para aplicações educacionais e de desenvolvimento de equipamentos eletrônicos. Para a obtenção dessa característica, os geradores de função devem apresentar um padrão de comunicação em tempo real, tecnologia essa presente no módulo AD9833.Com o intuito de contr...
With the rapid development of GPU (graphics processing unit) technologies and neural networks, we can explore more appropriate data structures and algorithms. Recent progress shows that neural networks can partly replace traditional data structures. In this paper, we proposed a novel DNN (deep neural network)-based learned locality-sensitive hashin...
The proportional hazards mixture cure model is a popular analysis method for survival data where a subgroup of patients are cured. When the data are interval-censored, the estimation of this model is challenging due to its complex data structure. In this article, we propose a computationally efficient semiparametric Bayesian approach, facilitated b...
Motivation
Microbiota data encounters challenges arising from technical noise and the curse of dimensionality, which affect the reliability of scientific findings. Furthermore, abundance matrices exhibit a zero-inflated distribution due to biological and technical influences. Consequently, there is a growing demand for advanced algorithms that can...
A new spatial keyword group query method is proposed in this paper to address the existing issue of user privacy leakage and exclusion of preferences in road networks. The proposed query method is based on the IGgram-tree index and minimum hash set. To deal with this problem effectively, this paper proposes a query method based on the IGgram-tree i...
Background
Automated feature selection methods such as the Least Absolute Shrinkage and Selection Operator (LASSO) have recently gained importance in the prediction of quality-related outcomes as well as the risk-adjustment of quality indicators in healthcare. The methods that have been used so far, however, do not account for the fact that patient...
We present an extension to the Brain Imaging Data Structure (BIDS) for motion data. Motion data is frequently recorded alongside human brain imaging and electrophysiological data. The goal of Motion-BIDS is to make motion data interoperable across different laboratories and with other data modalities in human brain and behavioral research. To this...
In the field of digital image processing, image segmentation technology has always been a key technology studied and discussed by many scholars. There may be certain contradictions in the implementation of image segmentation technology, namely the contradiction between segmentation accuracy and difficulty, as well as the contradiction between exces...
In order to maintain low-rank characteristics, existing low-rank representation methods concentrate on capturing data’s low-frequency signals, which are presumed to be the global data structure, and they delete the high ones, which are often a combination of corrupt elements and image edges. Such inefficient preservation of image edges could hamper...
In the rapidly evolving field of education, the need for a semantic search engine to efficiently retrieve graph-based data is crucial. Universities and colleges generate vast amounts of educational content research articles, and having a semantic search engine can enhance the accuracy of search results, ensuring that students and staff can access t...
Multivariate panel data of mixed type are routinely collected in many different areas of application, often jointly with additional covariates which complicate the statistical analysis. Moreover, it is often of interest to identify unknown groups of subjects in a study population using such data structure, i.e., to perform clustering. In the Bayesi...
This technical report presents an in-depth exploration of queue automata, a computational model that extends the classical notion of finite automata to incorporate a queue as an additional data structure. Through a detailed examination of a specific illustrative example, we delve into the capabilities and dynamics of queue automata in the context o...
Despite the widespread adoption of k-mer-based methods in bioinformatics, a fundamental question persists: How to elucidate the structural transition of a k-mer set when the order switches to k'? Attaining a generalized answer has significant implications to k-mer-based methods where the influence of k have been empirically analyzed (eg. in areas o...
The traditional offline teaching in the data structure courses had problems such as programming training, concept and application separation. The paper analyzed the current situation of mixed online and offline teaching research in the data structure courses, explored the implementation path of ideological and political education, used diversified...
This paper presents a novel approach to demonstrate the Collatz Conjecture, an unsolved problem in mathematics stating that all positive integers will eventually converge to 1 when subjected to a recursive sequence of operations. We introduce Algebraic Inverse Trees (AITs), innovative data structures that characterize relationships within the Colla...
The Kalman Filter based on uniform assumption has been a crucial motion estimation module in trackers. However, it has limitations in non-uniform motion modeling and computational efficiency when applied to large-scale object tracking scenarios. To address these issues, we propose a novel Parallel Kalman Filter (PKF), which simplifies conventional...
We suggest a new technique for developing noisy tree data structures. We call it a “walking tree”. As applications of the technique we present a noisy Self-Balanced Binary Search Tree (we use a Red–Black tree as an implementation) and a noisy segment tree. The asymptotic complexity of the main operations for the tree data structures does not change...
The growing awareness of environmental sustainability has led to new investments in the field of electric vehicles. One of the most expensive and important components of electric vehicles are their batteries, with battery management systems (BMS) being responsible for their control. New regulations, such as those of the European Union, aim to intro...
We propose RabbitKSSD, a high-speed genome distance estimation tool. Specifically, we leverage load-balanced task partitioning, fast I/O, efficient intermediate result accesses, and high-performance data structures to improve overall efficiency. Our performance evaluation demonstrates that RabbitKSSD achieves speedups ranging from 5.7× to 19.8× ove...
The Open Tree of Life (OToL) project produces a supertree that summarizes phylogenetic knowledge from tree estimates published in the primary literature. The supertree construction algorithm iteratively calls Aho's Build algorithm thousands of times in order to assess the compatability of different phylogenetic groupings. We describe an incremental...
Based on the annual data of degree-granting information accumulated by degree-granting institutions, this paper analyzes the storage structure of the database, excavates the critical information in the degree-granting information data structure, and puts forward a multi-dimensional graduate source analysis method, such as first-choice admission rat...
Due to the rapid growth of data from different sources in organizations, the traditional tools and techniques that cannot handle such huge data are known as big data which is in a scalable fashion. Similarly, many existing frequent itemset mining algorithms have good performance but scalability problems as they cannot exploit parallel processing po...
Fault-tolerant quantum computing requires classical hardware to perform the decoding necessary for error correction. The Union–Find decoder is one of the best candidates for this. It has remarkably organic characteristics, involving the growth and merger of data structures through nearest-neighbour steps; this naturally suggests the possibility of...
The selection of regression test cases is used to choose a subset of test suits that are used to exercise the altered program to ensure that the modified part has no unintended consequences on the unmodified part of the program. In previous works, the single objective is used for the selection of test cases. In this thesis, we preserved test case s...
Several problems arise due to the differences between dentistry and general medicine. The storage of dental data in information silos, the incompatibility of data between different dental clinics or institutions from other medical areas are the most significant ones. The authors propose a decentralized architecture that combines FHIR archetypes, sh...
This study aims to evaluate the asymmetric effect of the real effective exchange rate (REER), in addition to examining the effects of foreign income, domestic capacity, openness, imports, and credit to the private sector on Saudi non-oil exports during 1984-2020. The study uses two indices for the dependent variables , and the estimation method is...
The devastating Yogyakarta earthquake of 2006 had its epicenter on the Opak Fault. Several earthquake incidents also occurred in 2016 and were centered in the middle of urban Yogyakarta. The cause of the earthquake is still interpreted as a fault movement, which is suspected to have a different direction from the Opak Fault. Research on the Fault i...
When developing a new chemical, investigating its long-term influences on the environment is crucial to prevent harm. Unfortunately, these experiments are time-consuming. In silico methods can learn from already obtained data to predict biotransformation pathways, and thereby help focus all development efforts on only the most promising chemicals....
With the wide acceptance of open CNC systems and the rapid development of network technology, end-users can easily integrate control strategies or intelligent algorithm modules into open CNC systems. The openness performance, real-time performance, and expandability of the open CNC system are facing great challenges due to the increase of algorithm...
Cyberthreats continue their expansion, becoming more and more complex and varied. However, credentials and passwords are still a critical point in security. Password cracking can be a powerful tool to fight against cyber criminals if used by cybersecurity professionals and red teams, for instance, to evaluate compliance with security policies or in...
Coupling hydrological modelling systems (HMS) with a geographic information system (GIS) can significantly enhance hydrological research and expand its applications. The calculation for HMS requires geographic information data; however, the current GIS data structure is not equipped to support the object-oriented hydrological modelling. Due to diff...
Since graph analysis tasks often require compute-intensive operations, GPUs have been widely used to accelerate graph analysis tasks. However, many applications, such as social networking, fraud detection, and network security, involve massive and rapidly updated dynamic graphs. The graphs have to be rebuilt again and again. This behavior greatly a...
Obstacle avoidance based on a monocular camera is a challenging task due to the lack of 3D information for Unmanned Aerial Vehicle. Recent methods based on Convolutional Neural Networks for monocular depth estimation and obstacle detection become widely used. However, collision avoidance with depth estimation usually suffers from long computational...
O problema daárvore geradora mínima com restrição de grau (DMST)é definido sob um grafo G = (V, E), onde o objetivoé encontrar umaárvore geradora de G com peso mínimo e cujos vértices tenham grau menor ou igual a P. Este trabalho propõe uma nova meta-heurística para resolução da DMST, um algoritmo de seleção clonal. Este novo algoritmoé implementad...
Binary search trees (BSTs) are one of the most important data structures in the field of computer science. We may easily write a parallel construction program of a BST by extending the sequential algorithm straightly. However, in such conventional approaches, the order of nodes inserted into a BST is determined dynamically, depending on the occasio...
This paper addresses the Collatz Conjecture, an open question in mathematics that postulates all positive integers will eventually reach one when a pair of specific operations are repeatedly applied. Despite its apparent simplicity, the conjecture lacks a formal proof. To tackle this enigma, we introduce Algebraic Inverse Trees (AITs), data structu...
Cerebrovascular Reactivity (CVR) refers to the ability of cerebral blood vessels to dilate or constrict under the effect of vasoactive substances and can be estimated using functional Magnetic Resonance Imaging (fMRI). Computation of CVR maps is relevant in various brain diseases and requires specialized data processing. We introduce CVRmap, an ope...
Learning-based data structures, such as a learned Bloom filter and a learned functional Bloom filter (L-FBF), have recently been proposed to replace traditional structures. However, using these structures for dynamic data processing is difficult because a specific element cannot be deleted from a trained model. A counting Bloom filter with return v...
A numerical technique for solving the equations of fluid dynamics for multimaterial flows with arbitrary mesh motion in two dimensional cylindrical geometry was implemented in an ALE hydrodnamics code called Cercion, written in the C programming language using novel cell-centered data structures. The Lagrangian phase follows a well known approach u...
The case study evaluates the use of ChatGPT as a teaching assistant in a Computer Science course, focused on the subject of Data Structures. The aim is to understand how this AI tool can complement conventional teaching methods. ChatGPT proved effective in providing theoretical information and helped reduce direct queries to the professor. However,...
As the vast majority of people rely on groundwater for drinking purposes, an appropriate quantitative approach is essential to figure out the level of pollution and its spatial distribution. The Chota Nagpur Plateau's hard rock and an alluvial plain are both present in West Bengal's Bankura district, which was chosen for the case study. Various phy...
Animation visualization is one of the primary methods for analyzing unsteady flow fields. In this paper, we addressed the issue of data visualization for large-scale unsteady flow fields using animation. Loading and rendering individual time steps sequentially can result in substantial frame delay, whereas loading and rendering all time steps simul...
Efficient pangenome indexes are promising tools for many applications, including rapid classification of nanopore sequencing reads. Recently, a compressed-index data structure called the "move structure" was proposed as an alternative to other BWT-based indexes like the FM index and r-index. The move structure uniquely achieves both O(r) space and...
1.ABSTRACT Background: Coronavirus disease 2019 is the third coronavirus outbreak in the last two decades. The virus is thought to spread through respiratory aerosol from infected people's coughing and sneezing, or through close personal contact. Older people are at highest risk for COVID-19 due to physiological changes associated with ageing, decr...
Emerging technologies in artificial intelligence (AI) and advanced optimization methodologies have opened up a new frontier in the field of software engineering. Among these methodol-ogies, optimization algorithms such as the multi-verse optimizer (MVO) provide a compelling and structured technique for identifying software vulnerabilities, thereby...
The closed contiguous sequential pattern combines the advantages of closedness constraints and contiguity constraints and in recent years has been widely used in the fields of sequence classification, traffic trajectory visualization and football player trajectory analysis. Most of the previously developed closed contiguous sequential pattern minin...
Emerging technologies in artificial intelligence (AI) and advanced optimization methodologies have opened up a new frontier in the field of software engineering. Among these methodol-ogies, optimization algorithms such as the multi-verse optimizer (MVO) provide a compelling and structured technique for identifying software vulnerabilities, thereby...
Using a corpus of mainly Arabic political cartoons, this article investigates the relationship between multimodal impoliteness and metaphorical creativity. It offers an interesting and admittedly tentative argument that many aspects of creativity in language and verbo-visual arts may be related to what I call "frame flouting or exploitation"-a noti...
The graph model enables a broad range of analyses; thus, graph processing (GP) is an invaluable tool in data analytics. At the heart of every GP system lies a concurrent graph data structure that stores the graph. Such a data structure needs to be highly efficient for both graph algorithms and queries. Due to the continuous evolution, the sparsity,...
Criminal behavior, which takes its content from society, has been associated with social isolation, national quarantine, and mandatory stay-at-home measures during the COVID-19 pandemic, and it has been researched through crime rates. Moreover, it has been argued that changes in the level of social mobility also affect crime rates. Decreased crime...
A general review of quantum molecular similarity structure and applications is presented. The backbone of the discussion corresponds to the general problem of the data structure associated with the mathematical representation of a molecular set. How to standardize, and how to compare it to any other problem. This computational track describes the e...
Algorithms for the minimum-cost bipartite matching can be used to estimate Wasserstein distance between two distributions. Given two sets A and B of n points in a 2-dimensional Euclidean space, one can use a fast implementation of the Hungarian method to compute a minimum-cost bipartite matching of A and B in Õ(n^2) time. Let ∆ be the spread, i.e.,...
Archaeological data repositories usually manage excavation data collections as project-level entities with restricted capacities to facilitate search or aggregation of excavation data at the sub-collection level (trenches, finds, season reports or excavation diaries etc.). More granular access to excavation data collections would enable layered que...
Algorithm and Data Structure is a basic course in Informatics Study Program, at Khairun University. This subject needs to be mastered because it becomes the foundation that can support the learning process in the future. However, from the results of a survey conducted, as many as 40% of students felt bored with the teaching methods used by Algorith...
In general, judging the use/idle state of the wireless spectrum is the foundation for cognitive radio users (secondary users, SUs) to access limited spectrum resources efficiently. Rich information can be mined by the inherent correlation of electromagnetic spectrum data from SUs in time, frequency, space, and other dimensions. Therefore, how to ef...
This paper addresses the Collatz Conjecture, an open question in mathematics that postulates all positive integers will eventually reach one when a pair of specific operations are repeatedly applied. Despite its apparent simplicity, the conjecture lacks a formal proof. To tackle this enigma, we introduce Algebraic Inverse Trees (AITs), data structu...
In this work, we present a novel scene description to perform large-scale localization using only geometric constraints. Our work extends compact world anchors with a search data structure to efficiently perform localization and pose estimation of mobile augmented reality devices across multiple platforms (
eg.,
hololens, ipad). The algorithm uses...
The human body pose estimation is a challenging task that has been tackled by many different approaches over the last decades. The importance of solving this problem is rooted in an ability to automatically identify the pose of a subject in visual data. Even though numerous methods have been proposed to address the task, there is still ambiguity ov...
Unstructured meshes are characterized by data points irregularly distributed in the Euclidian space. Due to the irregular nature of these data, computing connectivity information between the mesh elements requires much more time and memory than on uniformly distributed data. To lower storage costs, dynamic data structures have been proposed. These...
无人平台对复杂环境的自主认知能力是制约其广泛应用的关键问题,已成为当前认知科学、人工智能、地图学等领域的研究热点。在机器地图的概念模型和认知特点的基础上,为进一步实现机器地图信息存储、处理、交互与学习的形式化表达,本文从人机优势融合的视角提出了机器地图信息加工模型。构建了包括感知地图、工作地图和长时地图的环境表达模型,从观测视角、参考系、信息抽象度、数据结构、描述精度和准确度等方面对分析了表达模型结构。提出了测制用一体信息交互过程,分析了包括环境感知、制图、推理和决策为一体的持续迭代环境信息处理过程。建立了持续自主学习模型,分析了该模型的在学习过程、学习内容和持续机制方面的特点。开展了2组实验,对信息加工模型的可行性进行了验证:一是通过模拟测制用一体交互过程,提高了基准模型的长距离自主导航能...
Ekosistem mangrove memiliki peran penting di kawasan pesisir, terutama dalam mitigasi bencana dan habitat jenis-jenis ikan dan udang. Kecamatan Pulau Maya, Kabupaten Kayong Utara dikelilingi kawasan mangrove, saat ini belum memiliki data yang komprehensif dan terbaru terkait dengan potensi struktur komunitas mangrove. Penelitian ini bertujuan untuk...
This paper addresses the Collatz Conjecture, an open question in mathematics that postulates all positive integers will eventually reach one when a pair of specific operations are repeatedly applied. Despite its apparent simplicity, the conjecture lacks a formal proof. To tackle this enigma, we introduce Algebraic Inverse Trees (AITs), data structu...
Over the past decade, DNA has emerged as a new storage medium with intriguing data volume and durability capabilities. Despite its advantages, DNA storage also has crucial limitations, such as intricate data access interfaces and restricted random accessibility. To overcome these limitations, DNAContainer has been introduced with a novel storage in...
Scientists and practitioners increasingly rely on machine learning to model data and draw conclusions. Compared to statistical modeling approaches, machine learning makes fewer explicit assumptions about data structures, such as linearity. Consequently, the parameters of machine learning models usually cannot be easily related to the data generatin...
This paper addresses the Collatz Conjecture, an open question in mathematics that postulates all positive integers will eventually reach one when a pair of specific operations are repeatedly applied. Despite its apparent simplicity, the conjecture lacks a formal proof. To tackle this enigma, we introduce Algebraic Inverse Trees (AITs), data structu...