Subject: NA Digest, V. 22, # 25

NA Digest  Sunday, July 24, 2022  Volume 22 : Issue 25

Today's Editor:

        Daniel M. Dunlavy
        Sandia National Labs
        [log in to unmask]

Today's Topics:

        Software Release, pyMOR 2022.1
        GAMM Applied and Numerical Linear Algebra, Czech Republic, Sep 2022
        REU Symposium, USA, Dec 2022
        Scale Space and Variational Methods in Computer Vision, Italy, May 2023
        Scientific Software Engineering Positions, Naval Nuclear Laboratory
        Assistant Professor Position, Data Science, Univ of Memphis
        Lecturer Position, Numerical Analysis, Darmstadt Univ, Germany
        Research Associate/Postdoc Position, Durham Univ, UK
        Postdoc Position, Computational Geometry, Univ of Pavia
        Postdoc Position, Mathematics of Data Science, Oxford Univ
        Postdoc/PhD Position, Data-Driven Modeling, Czech Technical Univ
        PhD Position, Mathematics, Utrecht Univ
        PhD Position, Numerical Analysis and Scientific computing
        PhD Position, Optimization, Czech Technical Univ, Prague
        PhD Position, Physics-informed Machine Learning
        PhD Position, Scalable Algorithms for Hybrid AMR
        PhD Positions, Computational Mathematics, Univ of Stuttgart
        PhD Positions, Scuola Normale Superiore, Pisa, Italy
        Contents, Intl J Mathematics and Computer Science, 17 (4)

Subscribe, unsubscribe, change address, or for na-digest archives:
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Submissions for NA Digest:
        http://icl.utk.edu/na-digest/

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From: René Fritze [log in to unmask]
Date: July 21, 2022
Subject: Software Release, pyMOR 2022.1

pyMOR 2022.1 (July 21, 2022)

We are proud to announce the release of pyMOR 2022.1!

pyMOR now comes with support for discrete-time systems and
structure-preserving MOR for symplectic systems.  The neural network
based reductors gained many new features, while the VectorArray
implementation got simplified.  We have added an experimental FEniCS
discretizer and extended functionality for randomized linear algebra.

Over 760 single commits have entered this release.  pyMOR 2022.1
contains contributions by Patric Buchfink, Monica Dessole, Hendrik
Kleikamp, Peter Oehme, Art Pelling and Sven Ullmann.

Read the full release notes at
https://docs.pymor.org/2022-1- 0/release_notes/all.html

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From: Erin Claire Carson [log in to unmask]
Date: July 21, 2022
Subject: GAMM Applied and Numerical Linear Algebra, Czech Republic, Sep 2022

The 22nd Workshop of the GAMM Activity Group on Applied and Numerical
Linear Algebra (GAMM ANLA) will take place in Prague, Czech Republic
from September 22-23, 2022. We anticipate an in-person meeting. The
workshop will begin around 13:00 on Thursday, September 22, to allow
those who may be traveling from other conferences time to arrive.

The workshop will feature recent advances in Applied and Numerical
Linear Algebra with a special focus on Krylov subspace methods. We
welcome contributions on topics including but not limited to:
eigenvalue problems, matrix functions, linear systems, least squares
problems, tensor methods, matrix equations, high performance
computing, inverse problems, and applications.

The invited speakers are:
Jorg Liesen (TU Berlin)
Jan Pape~ (Czech Academy of Sciences)
Kirk Soodhalter (Trinity College Dublin)
Valeria Simoncini (University of Bologna)

Registration is free and is now open. The registration form and
further details can be found on the workshop website:
https://sites.google.com/view/gammanla2022/

Important deadlines:
15 August: Deadline for Submitting Abstracts for Contributed Talks
31 August: Registration Deadline

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From: Matthias K Gobbert [log in to unmask]
Date: July 24, 2022
Subject: REU Symposium, USA, Dec 2022

On behalf of the organization committee for the 2022 Symposium for
Undergraduate Research in Data Science, Systems, and Security (REU
Symposium 2022), it is our pleasure to invite undergraduate students
to submit their research results in presentation and paper forms. This
year, the symposium will be held in Portland, Oregon, USA, one day in
December 6-9, 2022, as part of the 9th IEEE/ACM International
Conference on Big Data Computing, Applications and Technologies (BDCAT
2022). The symposium's website is at
https://bigdatareu.umbc.edu/reu-symposium/ and the BDCAT 2022
conference's website is at: https://bdcat-conference.org/.

Experiencing the full lifecycle of publication at a conference
(prepare paper, submit paper, receive review, revise paper, attend and
present at conference, etc.) can help and motivate your REU students
in their research. Please, encourage your undergraduate students to
submit their work.  The symposium requires the submission's lead
author must be an undergraduate student funded as part of the NSF REU
program, either as an REU supplement or REU Site.

First paper submission deadline is August 08, 2022, but could be
extended.


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From: Marco Prato [log in to unmask]
Date: July 18, 2022
Subject: Scale Space and Variational Methods in Computer Vision, Italy, May 2023

The 9th International Conference on "Scale Space and Variational
Methods in Computer Vision" will take place in May 21-25, Santa
Margherita di Pula, Sardinia, Italy

Call for papers: We kindly invite you to submit your
contribution. Submitted contributions should be maximum 12 page long
and formatted according to the LNCS Springer standards. Papers
accepted for the conference will appear in the conference proceedings
that will be published in Springer's Lecture Notes in Computer Science
series.  Prospective authors are invited to submit their contribution
electronically via the SSVM'23 Paper Submission Web Page (more details
will be announced in due course). All papers will undergo a
double-blind peer- review procedure.  Accepted papers will be
presented at the conference either in the format of posters or talks.

Important dates
- Paper submission: January 23, 2023
- Notification of acceptance: February 27, 2023
- Camera-ready paper deadline: March 13, 2023
- Conference dates: May 21 - May 25, 2023

The conference will award a best student paper prize.

Info & contacts: https://events.unibo.it/ssvm2023/

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From: Jonathan Hannay [log in to unmask]
Date: July 18, 2022
Subject: Scientific Software Engineering Positions, Naval Nuclear Laboratory

U.S. Citizens Only: Naval Nuclear Laboratory's (NNL) is seeking
full-time scientific software developers with a passion for software
engineering. The newest team member will have the opportunity to work
on assignments that could include designing, implementing, testing,
verifying, deploying, and maintaining engineering software targeted
for medium to large-scale supercomputing systems.

Relevant Skills (NOT ALL REQUIRED): 1) software engineering (e.g.,
unit testing, continuous integration, version control, debugging,
profiling, compiler operation / optimization).  2) programming with
both compiled (e.g., C, C++, Fortran) and interpreted (e.g., Python,
Java) scientific computing languages.  3) parallel programming,
running parallel jobs on supercomputing systems.  4) numerical
analysis: e.g., partial differential equations, ordinary differential
equations, nonlinear solvers, verification / validation / uncertainty
quantification, optimization, machine learning, data analytics.  5)
domain knowledge of nuclear reactor physics, fluid dynamics,
thermodynamics, solid mechanics.

Experienced: https://nnl.mua.hrdepartment.com/hr/ats/Posting/view/29899
Entry Level: https://nnl.mua.hrdepartment.com/hr/ats/Posting/view/29900
More info: https://navalnuclearlab.energy.gov/

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From: E. Olusegun George [log in to unmask]
Date: July 17, 2022
Subject: Assistant Professor Position, Data Science, Univ of Memphis

THE UNIVERSITY OF MEMPHIS, ASSISTANT PROFESSOR OF MATHEMATICAL
SCIENCES AND DATA SCIENCE, Department of Mathematical Sciences

he Department of Mathematical Sciences at the University of Memphis
anticipates hiring a tenure-track Assistant Professor in Statistics
and Data Science to begin in the January of 2023.  Applications are
invited from candidates with a PhD in Statistics and Data Science, or
related areas in Mathematical Sciences with research interests in
statistical analysis of complex, dependent high dimensional data and
the use of graph theory and combinatorics for high dimensional
statistical graphical networks. The successful candidate will
typically teach two courses per semester in subjects related to data
science, which include statistics, graph theory, or other related
fields.  The candidate will also be expected to conduct collaborative
research especially in the context of projects related to data science
and big data modeling and analysis. To apply, complete an application
at https://workforum.memphis.edu/postings/ . Applicants will be
required to upload a cover letter, research and teaching statements,
curriculum vitae, and contact information for three letters of
recommendation.

The University of Memphis is an Equal Opportunity/Affirmative Action
Employer. We urge all qualified applicants to apply for this position.
Appointment will be based on qualifications as they relate to position
requirements without regard to race, color, national origin, religion,
age, sex, disability or veteran status. Successful candidates must
meet guidelines of the Immigration Reform and Control Act of 1986. For
any questions regarding this position, please contact the chair of the
search committee: Dr. E. O. George, email: [log in to unmask]

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From: Thomas März [log in to unmask]
Date: July 21, 2022
Subject: Lecturer Position, Numerical Analysis, Darmstadt Univ, Germany

The Department of Mathematics and Natural Sciences of the Darmstadt
University of Applied Sciences is recruiting a professor in the
subject area of Numerical Analysis to take up duties in the summer
term 2023 (1st April 2023).

Further details regarding this position can be found here
https://h-da.de/hochschule/arbeiten-an-der-hochschule/detailansicht/mn-16-22-p-professur-im-fachgebiet-numerische-mathematik

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From: Tobias Weinzierl [log in to unmask]
Date: July 18, 2022
Subject: Research Associate/Postdoc Position, Durham Univ, UK

The Scientific Computing research group at Durham University has an
opening for a Research Associate for immediate start, funded by the
UK's exascale programme ExCALIBUR. The position can be upgraded to a
Postdoc Research Associate, but we would also be happy to consider
applications by candidates without a PhD. Details can be found at
https://durham.taleo.net/careersection/du_ext/jobdetail.ftl?job=22000021

Please contact the group head Tobias Weinzierl for any questions.

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From: Giulia Scalet [log in to unmask]
Date: July 16, 2022
Subject: Postdoc Position, Computational Geometry, Univ of Pavia

A postdoctoral position in computational geometry will open soon at
the University of Pavia in Italy.

Description: The postdoc will work on new conformal and
quasi-conformal approaches for morphing structures using theoretical
and numerical methods. The position will be part of an ERC Starting
Grant "COmputational DEsign for 4D BIOfabrication: harnessing
programmable materials for dynamic pre-clinical cancer models" led by
Dr Giulia Scalet (https://www.code4bio.com).

Qualifications: Applicants must have (or about to receive) a PhD
degree in mathematics or computer science (or a closely related
discipline). The candidate should have a strong mathematical
background on partial differential equations (PDEs), numerical PDE,
programming skills (preferably, Matlab, C++, Pytorch). Experience on
differential geometry, conformal geometry and quasi-conformal geometry
will be a plus.

Duration: the initial term will be one/two years, preferably starting
January 2023. The contract can be extended up to three years based on
performance.

Salary: commensurate to candidate's experience.

For more information, please contact
[log in to unmask] Interested candidates are encouraged to
include a CV and a summary of relevant experience.

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From: Coralia Cartis [log in to unmask]
Date: July 17, 2022
Subject: Postdoc Position, Mathematics of Data Science, Oxford Univ

Postdoctoral Research Associate in the Mathematical Foundations of
Data Science
https://my.corehr.com/pls/uoxrecruit/erq_jobspec_details_form.jobspec?
p_id=158900

We invite applications for a Postdoctoral Research Associate to work
on an exciting new project to address significant mathematical and
engineering challenges arising from multidimensional big data.

The position will be based at the Mathematical Institute, and form a
key part of a substantial new Centre for Intelligent Multidimensional
Data Analysis (CIMDA) funded by the Hong Kong Innovation and
Technology Commission. It is available full time for 12 months in the
first instance, though funding for the project is expected to be
renewed and if so, it may be possible to extend the length of this
appointment by another year. The position is available for an
immediate start.

The successful candidate will work with leading researchers in
stochastic analysis and data science at Oxford as part of a larger,
multidisciplinary team. They will manage and conduct their own
academic research and administrative activities, write up their
results for publication and participate fully in the activities of the
research community at Oxford. Potential research directions include,
but are not limited to, scalable optimization algorithm development
and analysis; stochastic processes and rough paths; reduced precision
and parallel-in-time computations; high- dimensional matrices and
tensors and their decompositions; hypergraphs models; learning of
non-Euclidean data; and sparse deep neural networks.  The faculty team
comprises Profs Terry Lyons (PI), Coralia Cartis, Mike Giles, Raphael
Hauser, Harald Oberhauser, Endre Suli, Jared Tanner and Andrew Wathen.

Applicants will have, or be close to completing, a PhD in mathematics
or a related discipline, and possess sufficient specialist knowledge
and research experience in one or more of the areas of data science,
machine learning, numerical analysis, optimization, scientific
computing and their applications, to work within established research
programmes. They will have excellent communication skills, including
the ability to write for publication, present research proposals and
results, and represent the research group at meetings.


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From: Jan Zeman [log in to unmask]
Date: July 22, 2022
Subject: Postdoc/PhD Position, Data-Driven Modeling, Czech Technical Univ

A fully-funded postdoctoral/Ph.D. position in the field of data-driven
modeling of engineering materials is available at the Department of
Mechanics, Faculty of Civil Engineering, Czech Technical University in
Prague. The project involves research activities in the fields of
techniques microstructure reconstruction, uncertainty quantification,
and inverse problems under the supervision of Dr. Anna Kucerova, in
close collaboration with the Luxembourg Institute of Science and
Technology.

Full details on the job are available at
https://euraxess.ec.europa.eu/jobs/814657, and the call closes on 31
August 2022.

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From: Sjoerd Dirksen [log in to unmask]
Date: July 17, 2022
Subject: PhD Position, Mathematics, Utrecht Univ

The Mathematical Institute of Utrecht University has a vacancy for a
4-year PhD position funded by the new NWO project "Probabilistic wind
speed forecasting with deep learning". The project is a close
collaboration with the data science and statistical post-processing
groups at the Royal Netherlands Meteorological Institute (KNMI). The
project will be jointly supervised by Sjoerd Dirksen (Utrecht
University, daily supervisor), Kirien Whan (KNMI), and Maurice
Schmeits (KNMI).

More details on the position and the application procedure can be
found under
https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/phd-position-on-probabilistic-wind-speed-forecasting-with-deep-learning-10-fte

The application deadline is August 15.

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From: Simone Deparis [log in to unmask]
Date: July 22, 2022
Subject: PhD Position, Numerical Analysis and Scientific computing

We are looking for a PhD students working on time dependent PDEs for
fluid problems on coronaries. The project includes the manipulation of
real patient geometries, numerical simulations and reduced order
modeling based on the reduced basis method. The final aim is to build
a dataset for training of networks for the prognosis of cardiac
problems.  The ideal candidate needs to have a MSc in
Applied/Computational Mathematics or Computational Sciences, or
Mechanical Engineering, with a strong background in Galerkin methods
for PDEs, as well as proficiency in programming.

Please submit your applications to [log in to unmask]
and attach your CV with the title of your project(s); BSc and MSc
transcripts; 2 references that we can contact if needed.

The position is open until we find a suitable candidate. A first round
of online interviews will happen on Aug 26th so interested candidates
are welcome to submit their applications before that date.

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From: Jakub Marecek [log in to unmask]
Date: July 23, 2022
Subject: PhD Position, Optimization, Czech Technical Univ, Prague

In order to deliver AI systems with full consideration of social
welfare, we are developing training algorithms with guarantees of
appropriate measures of aspects of social concern. This may entail:
guarantees for deep learning via optimization in tame geometry
(extending https://arxiv.org/abs/2206.11533); commutative and
non-commutative polynomial optimization in system identification and
causal discovery (extending https://arxiv.org/abs/2002.01444,
https://arxiv.org/abs/2006.07315, https://arxiv.org/abs/2203.17164);
on-line and time-varying optimization therein (extending
https://arxiv.org/abs/1809.05870, https://arxiv.org/abs/2104.05445).
There are multiple PhD studentship available in related topics, to be
supervised by Jakub Marecek and Vyacheslav Kungurtsev (Dept. of
Computer Science) at the Czech Technical University in close
collaboration with the teams of Shie Mannor (Technion), Robert Shorten
(Imperial), Dimitris Gunopulos (NKUA), and Ioannis Emiris (Athena RC),
working together on project AutoFair, funded by the European
Commission (EC).  The project is a part of an EC initiative towards
ensuring AI development that is trustworthy and transparent.

We seek candidates with a Masters degrees in Computer Science,
Mathematics, Operations Research or related disciplines, with
excellent mathematical aptitude, as demonstrated by involvement in
mathematical olympiads, relevant coursework, or undergraduate
research. A preference is given to: candidates with experience with
non-trivial analysis of (optimization) algorithms; candidates with
experience with deep learning; candidates with experience in
programming in Python.  The position is full time and limited to 3
years, but can be extended in case of mutual interest. The studentship
comes with a monthly salary adjusted to approximately match the
average salary in Prague, the Czech Republic (which currently stands
at approximately EUR 23K p.a. before a notably low tax), and a travel
budget. CTU's offices are in a centrally-located palace with a view of
Prague Castle.

Czech Technical University (CTU) is the oldest non-military technical
university in Europe. In the academic year 2020/21, CTU offered 130
degree programs in Czech and 84 in English. QS 2021 ranking of
Computer Science programs worldwide has CTU at rank 150. CTU's
Artificial Intelligence Center (AIC) with a staff of 150 is widely
recognized as one of the best in the region. The Czech capital
regularly ranks among the top five cities in Europe to live in
(cf. Time Out Magazine index for 2021). For more information, please
see https://www.aic.fel.cvut.cz/research-areas/optimization
https://www.jobs.ac.uk/job/CQZ866/phd-position-mathematical-
optimization-and-control-in-human-compatible-ai

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From: Martin Burger [log in to unmask]
Date: July 21, 2022
Subject: PhD Position, Physics-informed Machine Learning

Within the project "Automated Simulation Abstraction Pipeline" in
cooperation with Schaeffler Technologies AG & Co. KG we offer a
Doctorate position (75 %, TV-L 13, for 3 years) at the Department of
Mathematics at the Friedrich-Alexander-Universitat Erlangen-Nurnberg,
chair for Applied Mathematics (Prof. Martin Burger), starting as soon
as possible.

The focus of the proposed PhD project is the development of physics-
informed machine learning approaches for the abstraction of simulation
tools for roller bearings. State-of-the-Art techniques from machine
learning, including deep neural networks, shall be made available to
learn the relation between various and input- and output-parameters
relevant for roller bearings, based on synthetic data from available
simulation tools. A key issue in method development is to develop
adaptive sampling strategies for the training data.

The project deals with the combination of machine learning techniques
and numerical schemes for partial differential equations. Therefore,
an above-average master's degree in mathematics, data science, or a
related discipline is required. We further expect sound knowledge in
numerical methods and machine learning, including experience with
programming and implementation of algorithms. A background in
continuum mechanics and finite element methods is useful.

Please send your application by August 31th, 2022 (cover letter, CV,
an official listing of your grades, and contact details of a
reference, if possible) electronically to [log in to unmask] .

Compatibility of family and work is promoted at both universities.
Female candidates are particularly encouraged to apply. Equal
opportunity is an essential element of our personnel
policy. Applications from handicapped or equated applicants are
welcome.

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From: Carsten Burstedde [log in to unmask]
Date: July 17, 2022
Subject: PhD Position, Scalable Algorithms for Hybrid AMR

A PhD position is available immediately at the Institute for Numerical
Simulation (INS) at the University of Bonn, Germany.  The envisioned
research aims at developing new parallel algorithms for adaptive mesh
refinement using various shape primitives, such as cubes, tetrahedra,
prisms, and pyramids. These algorithms shall be prototyped,
demonstrated, and published as part of the p4est and t8code software
libraries.  This particular project is collaborative with the German
Aerospace Center (DLR) with applications to atmosphere simulations and
numerical weather studies.

A successful candidate would present a Master's degree in Mathematics,
Computer Science, or a closely related field.  They should be familiar
with the basic theories on the numerical solution of partial
differential equations, experienced in parallel programming with MPI,
and skilled in the collaborative development of open source scientific
software.

The INS is part of Bonn Mathematics and covers research and teaching
of scientific computing, numerical simulation, and numerical analysis.
The PhD position will be embedded in the graduate school of the
Hausdorff Center for Mathematics (HCM), a stimulating research
environment and support structure.

If interested, please email Carsten Burstedde .

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From: Benjamin Stamm [log in to unmask]
Date: July 16, 2022
Subject: PhD Positions, Computational Mathematics, Univ of Stuttgart

The chair of Numerical Mathematics for High-Performance Computing [1]
at the University of Stuttgart invites applicants for several PhD
positions (75% TVL-E13 at the German salary scale) in the area of
computational mathematics [2].

The chair develops new methods for problems arising in theoretical
chemistry, physics, and material science with a focus on a solid
mathematical framework, but many projects of the group are
interdisciplinary such as the projects associated with the current
openings.

For these openings, an MSc in Applied Mathematics, Computational
Engineering Science, or Simulation Science is expected. Applicants
from Physics with strong grades in Mathematics will also be
considered.  Excellent knowledge in computational mathematics and
scientific computing as well as advanced programming skills are
expected. Please send the application including the CV and a statement
of motivation to [log in to unmask] If you have
further questions, please contact Prof. Dr. B. Stamm
([log in to unmask]).

The University of Stuttgart particularly welcomes and encourages
applications from women, disabled people, and ethnic minority groups.

[1]: https://www.ians.uni-stuttgart.de/nmh/
[2]: https://www.ians.uni-stuttgart.de/institute/news/Open-PhD-Positions-
00006/

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From: Michele Benzi [log in to unmask]
Date: July 19, 2022
Subject: PhD Positions, Scuola Normale Superiore, Pisa, Italy

Five PhD Fellowships are available for students interested in pursuing
a PhD degree in Computational Methods and Mathematical Modeling for
the Sciences and Finance. Areas of specialization include Numerical
Analysis and Scientific Computing, Quantitative Finance, Stochastic
Analysis, and Computational Physics/Chemistry/Biology.

An additional special theme PhD fellowship on application of ML
techniques to finance is also available (co-sponsored by CONSOB).

The application deadline is August 25, 2022; start date is November 1,
2022.

Instructions on how to apply can be found at
https://www.sns.it/en/phd-admission-competition


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From: Badih Ghusayni [log in to unmask]
Date: July 19, 2022
Subject: Contents, Intl J Mathematics and Computer Science, 17 (4)

The following papers can be downloaded for free via
http://ijmcs.future-in-tech.net/Volume17.4.htm

Wipawee Tangjai, Suveera Chaeoueng, Naruemon Phumchaichot, On a
Diophantine equation 7^x+5.p^y=z^2 where p\equiv 1,2,4\pmod 7.

Rattiya Rittichuai, Aiyared Iampan, Ronnason Chinram, Pattarawan
Singavananda, Almost subsemirings and fuzzifications

Thanittha Kowan, Chutima Mahalapkorkiat, Tiyaporn Samakrat, Patcharee
Sumritnorrapong, Probability Distributions for Modeling of COVID-19
cases and deaths in Thailand

Saad Shakir Mahmood, Ali A. Abdulsahib, Jaafer Hmood Eidi, New
Conjugate Direction Method for Unconstrained Optimization

Issaraporn Thiamsorn, Satsayamon Suksaengrakcharoen, On some
properties of power Garima-Topp Leone power Lomax distribution with
application to lifetime data

Alvaro H. Salas, Jairo E. Castillo, Lorenzo J. Martinez, Analytical
and Numerical Solutions to the Kapitza Pendulum Equation

Apisit Pakapongpun, Bunthita Chattae, On the Diophantine Equation p^x
+ 7^y = z^2, where p is prime and x,y,z are non-negative integers

Thodsaporn Kumduang, Songpon Sriwongsa, A note on superassociative
algebra of terms determined by singular mappings on a finite set

A. V. Ramakrishna, T. V. N. Prasanna, Near Ring Multiplications on a
Locally Compact Topological Ring

Sakolwan Peetaneelavat, Somjai Boonsiri, Extroversion Text
Classification Model Using Logistic Regression

Zhour Oumazouz, Driss Karim, The analysis and implementation of the
symmetric key cryptographic algorithm based on the algebraic Paley
graphs

Bilal N. Al-Hasanat, Asma Almazaydeh, On classification of groups of
order p^4, where p is an odd prime

Bilal N. Al-Hasanat, Asma Almazaydeh, Normal Cover of Finite Groups

M. Khalifa Saad, S. A. Mohamed, Dual Spherical Curves According to
Bishop Frame in the Dual 3-Space

Ichlas Adhiguna, Izdihar Salsabila Noor Arifin, Fajar Yuliawan, Intan
Muchtadi-Alamsyah, On Orthogonal Circulant MDS Matrices

Nongluk Viriyapong, Chokchai Viriyapong, On the Diophantine equation
n^x+19^y=z^2, where n \equiv 2 \mod 57

Alvaro H. Salas, Elementary Solution to a Damped and Forced Cubic-
Quintic Duffing Equation

Lorenzo J. Martinez, Felipe A. Gallego, Alvaro H. Salas, Analytical
Solution to a Damped and Forced Oscillator Equation with Power Law
Nonlinearity

Nabeel E. Arif, Hosoya, Schultz and modified Schultz polynomials and
their topological indices of prime graphs of commutative ring Z_n

Shatha A. Salman, Fatema A. Sadiq, Viean A. Zain Al-Aabdeen, Muntaha
K. Abbas, Mayada N. Mohammedali, Some Properties for the Product and
Free Sum of Two Polytope

Wachirarak Orosram, Sawian Jaidee, Wipawee Tangjai, On the exponential
Diophantine equation (p+2)^x +(2p+1)^y =z^2, where p, p+2, and 2p+1
are primes

Chokchai Viriyapong, Chawalit Boonpok, (\Lambda,sp)-continuity and
\delta(\Lambda,sp)-closed sets

Chokchai Viriyapong, Chawalit Boonpok, Upper and lower faintly
(\Lambda,sp)-continuous multifunctions

M. I. Khan, Abdelfattah Mustafa, The Transmuted Power Hazard Rate
Distribution and its Applications

Matthew O. Oluwayemi, S. O. Olatunji, T. O. Ogunlade, On a Certain
Subclass of Univalent Functions Involving the Beta Function

Zulfaneti, Hilda Assiyatun, Edy Tri Baskoro, On
metric-location-domination number of graphs

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End of Digest
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