Top Research Papers on Data Structures and Algorithms PDF

By focusing on the architecture of algorithms, mathematical modeling and analysis, and experimental confirmation of theoretical results, this book helps students see computer science is about problem solving, not simply memorizing and reciting languages.

This study found that machine learning algorithms can optimize the efficiency of data structure analysis systems, thus completing the design and construction of a mature data structure analysis system.

Analytical details of adapting spatial correlation algorithm (SCA) to coherent nature of microwave imaging, which was originally designed to work in an incoherent target scenario, are provided.

Four algorithms that were motivated by specific hardware nuances, but are generally useful: reservoir sampling, majority of a stream, B-heap, and compacting an array in $\Theta (\log n)$Θ(logn) time.

Partial table of contents: Finite Figures Consisting Of Regular Polygons (J. Akiyama, et al.). Eigenvalues, Geometric Expanders and Sorting in Rounds (N. Alon). Long Path Enumeration Algorithms for Timing Verification on Large Digital Systems (T. Asano and S. Sato). On Upsets in Bipartite Tournaments (K. Bagga). Some Results on Binary Matrices Obtained via Bipartite Tournaments (K. Bagga and L. Beineke). Partitioning the Nodes of a Graph (E. Barnes). A Graph Theoretical Characterization of Minimal Deadlocks in Petri Nets (J. Bermond and G. Memmi). On Graceful Directed Graphs that Are Computati...

The author describes a new three credit-hour course at the Colorado School of Mines, MACS 410: Scientific Programming in C, targeted for students in engineering or the physical sciences who have finished the CSM core courses in computing and not expect to either major or minor in CS.

The multithreading technology is introduced, a multithreaded inverted sorted cited table is designed on the basis of the data chain table structure, and the optimization strategy of the data structure linearity provides a reference scheme to accelerate the speed of computer algorithms in solving the difficult problems.

A general cache-oblivious framework for cache-efficient sequential and parallel solution of any problem in GEP, and experimental results suggest that the GEP framework offers an attractive trade-off between efficiency and portability.

A textbook for an undergraduate course on algorithms and data structures that covers the fundamentals of both the software and the programming aspects of computer engineering.

An Ω( n log n) lower bound is proved for the computational problem of finding a median and an optimal O(nlog n) algorithm for computing the depth of the deepest point inside any cell of an arrangement of n lines in the plane is presented.

This thesis introduces the simplex tree, an efficient data structure to construct and maintain high dimensional simplicial complexes, and presents an algorithm to compute zigzag persistent homology, an algebraic generalization of persistence.

Once students have been introduced to the concept of big-O, a common assignment is one in which students are asked to put several functions in order according to growth, showing that these functions grow at different rates.

Once students have been introduced to the concept of big-O, a common assignment is one in which students are asked to put several functions in order according to growth, showing that these functions grow at different rates.

This article is composed of two parts; the ultra-large-scale electronic structure theory is reviewed for its fundamental numerical algorithm and its role in nano-material science.

A book review of  Analysis of Algorithms and Data Structures  by  Lech Banachowski, Antoni Kreczmar, and Wojciech Rytter

This document is made freely available in PDF form for educational and other non-commercial use and requires the written consent of the author.

This document is made freely available in PDF form for educational and other non-commercial use and requires the written consent of the author.

Introduction Algorithm Analysis. Lists, Stacks, and Queues. Trees. Hashing. Priority Queues. Sorting. The Disjoint Set ADT. Graph Algorithms. Algorithm Design Techniques. Amortized Analysis. Advanced Data Structures and Implementation.

How to estimate precision for some collection of functions most commonly used for array manipulations and training of neural networks is described and a fast estimation of precision is provided for highly optimized functions like matrix multiplication.

Algorithms for the analysis of heart rate variability, which is a dynamic, non-stationary variable, are presented and can be useful in the clinical practice of cardiologists.

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Five limited-data computed tomography algorithms are compared and the multiplicative algebraic reconstruction technique algorithm gave the best results overall; the algebraic Reconstruction technique gave thebest results for very smooth objects or very noisy data.

The goal of the session is to inspire other CS faculty to work similar content into corresponding courses at their own institutions, while also fostering a community of practice for responsible computing in core CS courses beyond machine learning.

Two general methods are presented for reducing the computer resources required in scientific computing: a numerical database system which is built on a space and time optimal data structure called a weighted search tree and a matrix algorithm based on a new space optimal representation of sparse matrices.

When describing and modeling the crystal structure of a material, interatomic interaction potentials are used. To solve the problems of parametric identification of potentials, which consists of the selection of potential parameters, the use of various optimization methods has recently become increasingly important. In this case, it becomes necessary to determine the gradients of some quantities characterizing the substance with respect to parameters of potential. Based on the Fast Automatic Differentiation-technique, an algorithm has been built to determine the exact values of the gradients o...

The book is innovative even for specialists in game theory and operations research, decision making and applied socioeconomics research in various fields, and in practical implementations SV has been successfully applied in marketing research.

Three Fog Computing data placement algorithms are evaluated via experiments carried out with the iFogSim simulator to show that edge placement strategies are beneficial to assist cloud computing in lowering latency and cloud energy expenditure.

The objectives include analyzing and designing application features that attract students to learn DSA in an interactive manner, developing an AR application that facilitates user-application interaction, and investigating the effectiveness of the AR application in terms of usability, acceptability during the DSA learning process.

In this paper, examples that demonstrate that algorithm engineering is the perfect basis for algorithmic data science are seen.

It is proposed that, given the current state of development of cognitive science, the greatest synergies between this field and artificial intelligence arise when one adopts a high level of abstraction, and that a focus on artificial general intelligencedesign is advocated.

The qualitative data obtained from students and the instructor show desirable positive effect of TPS in affective, behavioral and cognitive dimensions on students.

Data structures and algorithm analysis in ada will lead you to always think more and more and this book will be always right for you.

Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium.

This book discusses Algorithm Design Techniques, Smart Union Algorithms, and How to Analyze Running Time Calculations, as well as Advanced Data Structures and Implementation, and some Library Routines.

This book provides a proven approach to algorithms and data structures using the exciting Java programming language as the implementation tool and highlights conceptual topics, focusing on ADTs and the analysis of algorithms for efficiency as well as performance and running time.

This paper presents different data structures and algorithms used in this study, particularly interested by algebraic structures, eg homotopy and homology groups, the Betti numbers, the Euler characteristic, or the Morse-Smale complex.

This work proposes an implementation of adjacency lists for graph structures using a hash table with arrays, where the arrays indicate edges to vertices, and proposes dedicated objects for both vertices and edges, allowing for easily adding information to both vertice and edges.

Data Structures and Algorithm Analysis in C++ is an advanced algorithms book that bridges the gap between traditional CS2 and Algorithms Analysis courses and teaches readers to develop well-constructed, maximally efficient programs using the C++ programming language.

The paper is to study the comparison of two methods RSA (Ronald Rivest Algorithm) and DSA (Digital Signature Algorithm) to assure privacy and security of data cryptographic.

This study attempts to quantify SLOs of a graduate level foundation course named Algorithms and Data Structures and shows better success because of appropriate course modality, teaching pedagogy and engagement among many others.

This paper proposes a secure cloud storage system supporting privacy-preserving public by using DSA algorithms to give the data which is secured, imposter prevention and authentication.

A model that can be successfully used as a null model for simplicial complexes as it fixes the size distribution of facets is introduced and a categorical reasoning is proposed which enlightens the cause leading to misconceptions about topological data analysis.

This work gives an expository discussion of data stream models and the algorithmic challenges that these models pose for computational statistical analysis, then presents an overview of three streaming algorithms and a discussion of the computational challenges with each.

This book takes an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s, with speculation on the future direction of statistics and data science.

A review of recent studies on SIGCSE about teaching programming (CS1) and data structures (CS2) for university students in computer science courses presents the identification of three categories and their respective subcategories for teaching programming: characterization of contents, identification of pedagogical strategies and grouping of support tools.

A new data structure is presented, minimal interval set, to represent the match patterns of rulesets, which serves the basis for composition algebra construction and fast misconfiguration checking and is implemented in Covisor with optimisations to further reduce the overhead.

This book takes an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s, with speculation on the future direction of statistics and data science.

This review study analyses CC security threats, problems, and solutions that use one or more algorithms that are used to overcome cloud security issues, including supervised, unsupervised, semi‐ supervised, and reinforcement learning.

A flexible framework for the selection of populations from a given candidate pool to assist a target population in mortality forecasting using the deletion-substitution-addition (DSA) algorithm, which is entirely data driven and versatile to work with any multiple-population model for mortality prediction.

It is illustrated that granular computing gives a unified view of these two approaches of conventional style of rule mining, which may lead to theoretical foundations of data mining in the near future.