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Algorithms
Special Issues
Space-Efficient Algorithms and Data Structures
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Space-Efficient Algorithms and Data Structures

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (15 January 2023) | Viewed by 7476

Special Issue Editors

Dr. Srinivasa Rao Satti

E-Mail Website
Guest Editor
Department of Computer Science, Norwegian University of Science and Technology, Trondheim 7491, Norway
Interests: algorithms and data structures; graph compression and indexing; database indexing
Dr. Jérémy Barbay

E-Mail Website
Guest Editor
Department of Computer Science, University of Chile, Santiago 8370448, Chile
Interests: algorithms and data structures; learning management systems; animal computer interactions

Special Issue Information

Dear Colleagues,

We invite you to submit your latest research about space-efficient data structures and/or algorithms to this Special Issue of the journal Algorithms from MDPI, “Space-efficient algorithms and data structures”. This Special Issue is devoted to all aspects of compressed data structures and their connections to other research areas. The list of topics includes but is not limited to:

  • Space-efficient (succinct/ compact/ compressed) data structures;
  • Succinct/compact encodings;
  • Deferred data structures;
  • Algorithms on compressed data;
  • Streaming algorithms;
  • In place algorithms;
  • Text compression and indexing schemes;
  • Graph compression and indexing schemes; and
  • Applications of compressed data structures.

Both theoretical and experimental works will be considered.

Dr. Srinivasa Rao Satti
Dr. Jérémy Barbay
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • algorithms on compressed data
  • applications of compressed data structures
  • compact data structures
  • compact encodings
  • compressed data structures
  • deferred data structures
  • graph compression schemes
  • graph indexing schemes
  • in place algorithms
  • streaming algorithms
  • succinct data structures
  • text indexing schemes
  • text compression schemes

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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Further information on MDPI's Special Issue polices can be found here.

Published Papers (3 papers)

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Research

33 pages, 1874 KiB  
Article
Quantum Circuit-Width Reduction through Parameterisation and Specialisation
by Youssef Moawad, Wim Vanderbauwhede and René Steijl
Algorithms 2023, 16(5), 241; https://doi.org/10.3390/a16050241 - 5 May 2023
Viewed by 2620
Abstract
As quantum computing technology continues to develop, the need for research into novel quantum algorithms is growing. However, such algorithms cannot yet be reliably tested on actual quantum hardware, which is still limited in several ways, including qubit coherence times, connectivity, and available [...] Read more.
As quantum computing technology continues to develop, the need for research into novel quantum algorithms is growing. However, such algorithms cannot yet be reliably tested on actual quantum hardware, which is still limited in several ways, including qubit coherence times, connectivity, and available qubits. To facilitate the development of novel algorithms despite this, simulators on classical computing systems are used to verify the correctness of an algorithm, and study its behaviour under different error models. In general, this involves operating on a memory space that grows exponentially with the number of qubits. In this work, we introduce quantum circuit transformations that allow for the construction of parameterised circuits for quantum algorithms. The parameterised circuits are in an ideal form to be processed by quantum compilation tools, such that the circuit can be partially evaluated prior to simulation, and a smaller specialised circuit can be constructed by eliminating fixed input qubits. We show significant reduction in the number of qubits for various quantum arithmetic circuits. Divide-by-n-bits quantum integer dividers are used as an example demonstration. It is shown that the complexity reduces from 4n+2 to 3n+2 qubits in the specialised versions. For quantum algorithms involving divide-by-8 arithmetic operations, a reduction by 28=256 in required memory is achieved for classical simulation, reducing the memory required from 137 GB to 0.53 GB. Full article
(This article belongs to the Special Issue Space-Efficient Algorithms and Data Structures)
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36 pages, 3556 KiB  
Article
Time Series Analysis by Fuzzy Logic Methods
by Sergey M. Agayan, Dmitriy A. Kamaev, Shamil R. Bogoutdinov, Andron O. Aleksanyan and Boris V. Dzeranov
Algorithms 2023, 16(5), 238; https://doi.org/10.3390/a16050238 - 3 May 2023
Cited by 4 | Viewed by 1822
Abstract
The method of analyzing data known as Discrete Mathematical Analysis (DMA) incorporates fuzzy mathematics and logic. This paper focuses on applying DMA to study the morphology of time series by utilizing the language of fuzzy mathematics. The morphological characteristics of the time series, [...] Read more.
The method of analyzing data known as Discrete Mathematical Analysis (DMA) incorporates fuzzy mathematics and logic. This paper focuses on applying DMA to study the morphology of time series by utilizing the language of fuzzy mathematics. The morphological characteristics of the time series, such as background, slopes, and vertices, are considered fuzzy sets within the domain of its definition. This allows for the use of fuzzy logic in examining the morphology of time series, ultimately leading to the detection of anomalies. Full article
(This article belongs to the Special Issue Space-Efficient Algorithms and Data Structures)
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15 pages, 3326 KiB  
Article
Global Repeat Map (GRM) Application: Finding All DNA Tandem Repeat Units
by Matko Glunčić, Ines Vlahović, Leo Mršić and Vladimir Paar
Algorithms 2022, 15(12), 458; https://doi.org/10.3390/a15120458 - 5 Dec 2022
Cited by 4 | Viewed by 2197
Abstract
Tandem repeats (TRs) are important components of eukaryotic genomes; they have both structural and functional roles: (i) they form essential chromosome structures such as centromeres and telomeres; (ii) they modify chromatin structure and affect transcription, resulting in altered gene expression and protein abundance. [...] Read more.
Tandem repeats (TRs) are important components of eukaryotic genomes; they have both structural and functional roles: (i) they form essential chromosome structures such as centromeres and telomeres; (ii) they modify chromatin structure and affect transcription, resulting in altered gene expression and protein abundance. There are established links between variations in TRs and incompatibilities between species, evolutionary development, chromosome mis-segregation, aging, cancer outcomes and different diseases. Given the importance of TRs, it seemed essential to develop an efficient, sensitive and automated application for the identification of all kinds of TRs in various genomic sequences. Here, we present our new GRM application for identifying TRs, which is designed to overcome all the limitations of the currently existing algorithms. Our GRM algorithm provides a straightforward identification of TRs using the frequency domain but avoiding the mapping of the symbolic DNA sequence into numerical sequence, and using key string matching, but avoiding the statistical methods of locally optimizing individual key strings. Using the GRM application, we analyzed human, chimpanzee and mouse chromosome 19 genome sequences (RefSeqs), and showed that our application was very fast, efficient and simple, with a powerful graphical user interface. It can identify all types of TRs, from the smallest (2 bp) to the very large, as large as tens of kilobasepairs. It does not require any prior knowledge of sequence structure and does not require any user-defined parameters or thresholds. In this way, it ensures that a full spectrum of TRs can be detected in just one step. Furthermore, it is robust to all types of mutations in repeat copies and can identify TRs with various complexities in the sequence pattern. From this perspective, we can conclude that the GRM application is an efficient, sensitive and automated method for the identification of all kinds of TRs. Full article
(This article belongs to the Special Issue Space-Efficient Algorithms and Data Structures)
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