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NADIGEST Home

NADIGEST Home

NADIGEST  September 2020, Week 4

NADIGEST September 2020, Week 4

Subject:

NA Digest, V. 20, # 37

From:

NA Digest Editor <[log in to unmask]>

Reply-To:

NA-Digest <[log in to unmask]>

Date:

Sun, 27 Sep 2020 15:57:44 -0600

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (695 lines)

[External Email]

Subject: NA Digest, V. 20, # 37

NA Digest  Sunday, September 27, 2020  Volume 20 : Issue 37

Today's Editor:

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

Today's Topics:

        New Self-Paced Linear Algebra Course (Update)
        New Book, Location Estimation from the Ground Up
        Black Heroes of Mathematics, ONLINE, Oct 2020
        Mathematical methods for reactive multiphase flows, ONLINE, Oct 2020
        Topological Methods in Data Science, ONLINE, Oct 2020
        Numerical Approximation and Applications, ONLINE, Nov 2020
        Multi-scale, Multi-physics and Coupled Problems, South Korea, Jan 2021
        R&D Engineer II Position, Ansys, USA
        Faculty Positions, Computational Science and Engineering, Georgia Tech
        Postdoc Position, Optimization for Deep Learning, Berkeley Lab
        Postdoc Position, Reduced Modeling and Machine Learning, France
        Postdoc Positions. Mathematics Munster Cluster of Excellence, Germany
        PhD/Postdoc Positions, Univ Osnabrueck, Germany
        PhD Position, Mathematical Optimization and Energy Economics
        PhD Positions, Computational Science, USA
        Contents, Mathematics and Computer Science, 15 (4)
        Contents, Numerical Analysis and Approximation Theory, 49 (1)

Subscribe, unsubscribe, change address, or for na-digest archives:
        http://www.netlib.org/na-digest-html/faq.html

Submissions for NA Digest:
        http://icl.utk.edu/na-digest/

-------------------------------------------------------

From: Pavel Solin [log in to unmask]
Date: September 20, 2020
Subject: New Self-Paced Linear Algebra Course (Update)

In NA Digest, V. 19, # 48 we introduced a novel self-paced Linear
Algebra course where students learn by doing, at their own pace,
receiving real-time feedback from the NCLab platform. The instructor
does not lecture and works with each students individually
instead. The course is perfect for both in-person and online
instruction. NCLab's Python backend allows students to experiment in
real time with advanced computational applications of Linear Algebra
including Fourier series, best approximation, and data denoising and
image compression with SVD.

The course has been in use for three consecutive semesters now with
great success. Students consistently like the self-paced learning
model much more than traditional classroom teaching. Our findings are
summarized in the recent paper "Self-Paced, Instructor-Assisted
Approach to Teaching Linear Algebra"
(http://femhub.com/pavel/work/paper-linear-algebra.pdf).

The course has been continuously improved based on the feedback of
our partner instructors:

- The popular Matrix App was made fully AA accessible. It is now
  operable using fingers on touch screens, and mouse / keyboard on
  traditional displays. Watch a short illustrative video at
  https://youtu.be/2DjUTkqK5Fk and try it yourself at
  https://viewer.nclab.com/42d820651a1e4e3da76815f70d97b187.
- Instructors can clone the course and tweak it to their own needs.
- Solutions to Review Exercises were added.
- The rest of the course is now AA accessible as well.

For free access to the course contact Pavel Solin at [log in to unmask]
Let's revolutionize the instruction of Linear Algebra!


-------------------------------------------------------

From: Sivan Toledo [log in to unmask]
Date: September 24, 2020
Subject: New Book, Location Estimation from the Ground Up

2020 / xvi + 200 pages / Softcover and e-book / ISBN 978-1-611976-28-1
SIAM / List $67.00 / Members $47.90

Print (and free access to a sample chapter and the table of contents):
https://bookstore.siam.org/fa17
e-book: https://doi.org/10.1137/1.9781611976298
More previews on Google Books: https://books.google.co.il/books?
id=JJf9DwAAQBAJ

The book explains the mathematical formulation of location-estimation
problems, the statistical properties of these mathematical models, and
the algorithms that are used to resolve these models to obtain
location estimates.

The presentation emphasizes least squares and linear algebra
techniques, so NA-Digest readers will find the book to be a highly
readable resource on location estimation and on classical estimation
in general. It covers GNSS (GPS) models and algorithms ranging from
the very basic to RTK, a model with integer ambiguities that produces
centimeter-level accurate estimates. It also covers other important
modelling, analytical, and algorithmic techniques, like the Cramer-Rao
bound, separable least- square problem, and Kalman filtering (covered
in a unique way in the sample chapter).  The book is suitable for self
study, as a main textbook for courses on location estimation, or as a
source of motivating problems and interesting algorithms for courses
on linear algebra, numerical linear algebra, optimization, and
statistics.


-------------------------------------------------------

From: Pamela Bye [log in to unmask]
Date: September 22, 2020
Subject: Black Heroes of Mathematics, ONLINE, Oct 2020

Online Event: Black Heroes of Mathematics Conference
Date: Monday October 26, 2020 - Tuesday October 27, 2020
Online Conference held via Zoom

https://ima.org.uk/15025/black-heroes-of-mathematics-conference/

The British Society for the History of Mathematics, The International
Centre for Mathematical Sciences, the Institute of Mathematics and its
Applications and the London Mathematical Society, are holding a two
day conference on Black Heroes of Mathematics.  The Vision of the
conference is "To celebrate the inspirational contributions of black
role models to the field of mathematics".  There will be a balance of
technical talks by internationally renowned black speakers that
include some detail of career paths and experience to provide a
testimonial dimension. We plan to achieve a balance of career stage
and gender. Our speakers include Professor Edray Goins [Pomona
College], Professor Nkechi Agwu [CUNY], Professor Tannie Liverpool
[University of Bristol] and Dr Angela Tabiri [AIMS Ghana] to name a few.

Invited Speakers and Talk Titles (Abstracts can be found on our
website): Professor Nkechi Agwu (CUNY); Dr Spencer Becker-Kahn
(University of Cambridge); Professor Edray Goins (Pomona College); Dr
Howard Haughton (King's College London); Professor Tannie Liverpool
(University of Bristol); Dr Angela Tabiri (Aims Ghana).

Contact information
E-mail: [log in to unmask]    Tel: +44 (0) 1702 354 020


-------------------------------------------------------

From: Volker Mehrmann [log in to unmask]
Date: September 25, 2020
Subject: Mathematical methods for reactive multiphase flows, ONLINE, Oct 2020

Within the upcoming Thematic Einstein Semester ``Energy-based
mathematical methods for reactive multiphase flows'' of the Excellence
Cluster Math+ in Berlin, an online student compact course
``Variational Methods for Fluids and Solids'' takes place from Oct
12-23, 2020. The course will give an in-depth background on the topics
of the Thematic Einstein Semester, including lectures on variational
thermomechanics and applications, modeling by Port-Hamiltonian systems
and GENERIC, analytical and numerical methods, see

https://mathplus.de/topic-development-lab/tes-winter-2020-21/

If you are interested, please register using our website, write to
[log in to unmask], or contact any of the organizers.

Matthias Liero, Volker Mehrmann, Alexander Mielke, Dirk Peschka,
Marita Thomas, Barbara Wagner


-------------------------------------------------------

From: Pamela Bye [log in to unmask]
Date: September 22, 2020
Subject: Topological Methods in Data Science, ONLINE, Oct 2020

LMS-IMA Joint Meeting: Topological Methods in Data Science
Date: Thursday October 1, 2020 - Friday October 2, 2020
Online Conference via Zoom
https://ima.org.uk/15000/lms-ima-joint-meeting-topological-methods-in-data-science/

The London Mathematical Society and the Institute of Mathematics and
its Applications will hold their next Joint Meeting online on 1st and
2nd October 2020. This year's topic is "Topological methods in Data
Science". The meeting will take place over two days; the afternoon of
1st October the morning of 2nd October, and will comprise five talks
of 45 minutes each including questions.

Speakers and Titles (Abstracts can be found on our website): Kathryn
Hess (EPFL) - Trees, barcodes, and symmetric groups; Gueorgui Mihaylov
(King's College London) - A gauge theory of complex systems; Vidit
Nanda (University of Oxford) - Geometric anomaly detection in data;
Ran Levi (University of Aberdeen) - Combinatorial Structures in Neural
Networks; Ulrike Tillmann (University of Oxford) - Title TBC.

Contact information
E-mail: [log in to unmask]    Tel: +44 (0) 1702 354 020


-------------------------------------------------------

From: Rosanna Campagna [log in to unmask]
Date: September 23, 2020
Subject: Numerical Approximation and Applications, ONLINE, Nov 2020

We are pleased to announce a new series of on-line seminars entitled
"Online Seminars on Numerical Approximation and Applications OSNA^2".

The online series of seminars promotes the interchange among
researchers working in the domain of numerical approximation and its
applications, limited by the COVID-19 pandemic. Since participation in
traditional conferences is difficult, the primary goal of these
webinars is to share novel and attractive ideas via web suggested by
experienced and early-career researchers. As the second aim, the
colloquia intend to bridge the gap between theoretical aspects of
approximation theory and its applications.

OSNA^2 will start on November 9, 2020, at 17:00 (GMT+2) with two talks
per day and a week along four weeks.  For more information including
the schedule of the talks please visit the website:
https://sites.google.com/unifi.it/osna2/home-page and contact us for
any questions at [log in to unmask]

Registration is needed to receive e-mails and virtual connection
access to follow the seminars.


-------------------------------------------------------

From: Neda Ebrahimi Pour [log in to unmask]
Date: September 27, 2020
Subject: Multi-scale, Multi-physics and Coupled Problems, South Korea, Jan 2021

Submission deadline: 30th of October 2020

Workshop on "Multi-scale, Multi-physics and Coupled Problems on Highly
Parallel Systems (MMCP)" at HPC Asia 2021, January 20-22, Jeju, South
Korea

This workshop will provide a platform for presentations and
discussions on advances in numerical simulation for complex
multi-scale, multi-physics and coupled problems. The goal of the
workshop is to gather researchers (computer scientists, engineers,
mathematicians, physicists, chemists, biologists, material sciences
etc.) working on different disciplines but all facing challenges in
multi-scale and multi-physics as well as coupled simulations on HPC
systems. The main focus will be set on computational issues regarding
performance and suitability for high-performance
computing. Furthermore, the underlying strategies to enable these
simulations will be highlighted. Keeping these aims in mind,
contributions from all aspects of engineering applications will be
considered. Topics of applications will include (but not be limited
to): Multi-scale problems; Multi-physics problems; Molecular dynamics;
Multi-domain/Concurrency; Multi-scale and/or multi-physics modelling
for biomedical or biological systems; Novel approaches to combine
different scales and physics models in one problem solution;
Challenging applications in industry and academia, e.g. multiphase
flows, fluid-structure interactions, chemical engineering, material
science, biophysics, automotive industry, etc.; Load balancing;
Adaptivity; Heterogeneous architectures; New algorithms for
parallel-distributed computing, specific to this topic.

More information regarding this workshop and the submission procedure
can be found on our webpage:
https://www.mb.uni-siegen.de/sts/workshops/mmcp2021/


-------------------------------------------------------

From: Zhen Wang [log in to unmask]
Date: September 26, 2020
Subject: R&D Engineer II Position, Ansys, USA

Ansys is seeking an outstanding candidate to join the team responsible
for the industry leading computational electromagnetic (CEM) engines
in the gold standard ANSYS HFSS simulation software product.  This
position focuses on HFSS HPC solver infrastructure that employs MPI
and related distributed computing technologies.  In addition, the
position entails software architecture and implementation of software
modules which communicate with solvers and UI product codes.  The
successful candidate will have a solid background in scientific
software development, the ability to develop novel solution
approaches, and experience in the application of scientific principles
to analyzing problems. They will additionally possess experience
writing CEM software and applying such software to solving practical
problems such as antenna design, signal integrity, or electromagnetic
scattering.  The hired applicant will join a team of R&D developers
and is expected to work collaboratively with them in developing
best-in-class commercial software for engineering simulation.

More details:
https://careers.ansys.com/job/Canonsburg-R&D-Engineer-II-PA-15317/669764500/?
locale=en_US

-------------------------------------------------------

From: Edmond Chow [log in to unmask]
Date: September 24, 2020
Subject: Faculty Positions, Computational Science and Engineering, Georgia Tech

The School of Computational Science and Engineering (CSE) at the
Georgia Institute of Technology invites applications for multiple
openings at the Assistant Professor level (tenure-track); exceptional
candidates at the Associate Professor and Professor level also will be
considered. CSE focuses on foundational research of an
interdisciplinary nature that enables advances in science,
engineering, medical, and social domains. Applicants are expected to
develop and sustain a research program in one or more of our core
areas: high-performance computing, scientific and numerical computing,
modeling and simulation, discrete algorithms, and large-scale data
analytics (including machine learning and artificial intelligence).

All areas of research will be considered, especially: scientific
artificial intelligence (AI methods unique to scientific computing),
urban computing (enabling effective design and operation of cities and
urban communities), application-driven post-Moore's law computing, and
data science for fighting disease. Applicants must have an outstanding
record of research and a commitment to teaching.

Applicants are expected to engage in substantive research with
collaborators in other disciplines. For example, current faculty have
domain expertise and/or collaborations in computational chemistry;
earth sciences; biomedical and health sciences; urban systems and
smart cities; social good and sustainable development; materials and
manufacturing; and others.

Applications should be submitted online through:
https://academicjobsonline.org/ajo/jobs/16901.
For full consideration, applications are due by December 1, 2020.

-------------------------------------------------------

From: Juliane Mueller [log in to unmask]
Date: September 22, 2020
Subject: Postdoc Position, Optimization for Deep Learning, Berkeley Lab

Berkeley Lab's Center for Computational Sciences and Engineering
(CCSE) in the Computational Research Division has an opening for a
Postdoctoral Scholar in Optimization for Deep Learning. Researchers in
CCSE develop and apply advanced computational methodologies to solve
large-scale scientific and engineering problems arising in Department
of Energy mission areas involving energy, environment, and industrial
technology. This position will actively contribute to CCSE's
optimization research and algorithm development.

This is a research position in applied mathematics and computational
science. The successful candidate will develop new efficient
algorithms for the automated optimization of Deep Learning (DL) model
architectures and the uncertainty quantification of the associated DL
model's predictions.  The postdoc will implement, benchmark, analyze,
and apply the developments to science problems relevant to Berkeley
Lab and the Department of Energy, for example predicting the traffic
of the Energy Sciences network (ESnet).

For more information about the opening, visit
https://lbl.taleo.net/careersection/2/jobdetail.ftl?lang=en&job=91104
and reach out to [log in to unmask] with any questions you may
have.

We value and strive for diversity in backgrounds, experiences, and
perspectives.


-------------------------------------------------------

From: Olga Mula [log in to unmask]
Date: September 23, 2020
Subject: Postdoc Position, Reduced Modeling and Machine Learning, France

We are looking for a postdoctoral applied mathematician/computational
scientist to join the research group Models & Measures financed by the
Emergences grant project of the Paris City Council lead by Prof.Olga
Mula.

Current activities of the group focus on addressing forward and
inverse problems with methods combining modern computational methods,
such as reduced modelling of parametric PDEs, and recent machine
learning techniques, in particular based on neural networks and
optimal transport metrics. The developments seek to overcome known
bottlenecks of classical algorithms and introduce new paradigms to
solve problems of relevance to science and engineering. The
postdoctoral fellow is expected to engage in different projects in
line with the above vision. As a support for our numerical tests, we
will consider applications related to air pollution, fluid dynamics,
and epidemiology.

The ideal candidate will have the following skills: A PhD in Applied
Mathematics, Data Science, or Statistics.  Solid experience in the
development of numerical methods or data analysis with Python, Julia,
R or C++.  Solid working knowledge in at least one of the following
topics: reduced modeling of PDEs, optimal transport, machine learning,
uncertainty quantification, optimization.  The effort is of a
collaborative nature so strong interpersonal and communication skills
are required. Working language is English or French.

We offer a 1 year contract with the possibility of an
extension. Starting date is flexible but ideally between December 2020
and March 2021.

To express your interest, please send a letter of motivation, a
resume, and at least 2 names of references to
[log in to unmask] Evaluation of applications will continue
until the position is filled.


-------------------------------------------------------

From: Imke Franzmeier [log in to unmask]
Date: September 25, 2020
Subject: Postdoc Positions. Mathematics Munster Cluster of Excellence, Germany

Open Call for Postdoc Positions

- Salary level E13 TV-L, 100%
- In all research areas related to the Cluster of Excellence
- The duration of the postdoctoral positions is up to three years.
- The expected starting date is no later than October 2021.

Young Research Groups (postdoctoral level)

- Salary level E13 TV-L, 100% for up to four years.
- In all research areas related to the Cluster.
- The expected starting date is no later than October 2021.
- Postdoc applicants are invited to collaborate as a Young Research
  Group on a joint research project relevant to the topics of
  Mathematics Munster. Apply individually through the postdoc
  application form


Please find all relevant information about the position and the
application requirements online at:
https://www.uni-muenster.de/MathematicsMuenster/careers/postdocs/index.shtml

http://www.mathematics-muenster.de


-------------------------------------------------------

From: Stefan Kunis [log in to unmask]
Date: September 25, 2020
Subject: PhD/Postdoc Positions, Univ Osnabrueck, Germany

The Applied Analysis Group at the University of Osnabruck invites
applications for 2 Research Assistants (PhD student or PostDoc)
starting as soon as possible. The PhD student positions are limited to
three years, the PostDoc position has an adapted duration.

Your responsibilities:
- Development, mathematical analysis, and implementation of new
  algorithms for moment problems and super-resolution imaging.

Required qualifications:
- Successfully completed university degree (Master or equivalent) in
  Mathematics or related fields.
- Good knowledge in applied harmonic analysis, inverse problems,
  optimization, or applied algebraic geometry.
- Programming skills and hands on experience in modern image
  processing tools.

For further information, please contact Prof. Dr. Stefan Kunis (email:
Stefan Kunis [log in to unmask], homepage:
www.math.uos.de/kunis). Please send your application (including a
letter of motivation, CV, publication list, copies of certificates, as
well as names and contact details of 2 referees) as one PDF file via
Email: [log in to unmask] Application deadline is 14.10.2020.

-------------------------------------------------------

From: Martin Schmidt [log in to unmask]
Date: September 22, 2020
Subject: PhD Position, Mathematical Optimization and Energy Economics

Research assistant at the interface of mathematical optimization and
energy economics (Friedrich-Alexander-Universitat Erlangen-Nurnberg
and/or Trier University)

In the DFG Collaborative Research Center (CRC) 154 "Mathematical
Modelling, Simulation and Optimization using the Example of Gas
Networks", the position of a research assistant is to be filled
starting from March 2021 on. Remuneration is based on salary group E
13 TV-L (75%) and the position is filled for an initial period of 16
months. An extension is possible.

The PhD student will do research at the interface of mathematical
optimization, equilibrium modeling, and theoretical economics with
applications to energy markets and to gas markets, in particular. A
rigorous mathematical modeling of today's liberalized energy markets
leads to multilevel mixed-integer nonlinear optimization problems that
are extremely challenging both from a theoretical as well as from a
computational point of view. In this context, the work's focus will be
on mathematical modeling of multilevel equilibrium problems for energy
markets, on the theoretical analysis of these models, on the
development of tailored solution methods for their resolution, and on
the economic analysis and interpretation of the results to obtain
insights on real-world markets.

Applications with the usual documents (letter of motivation,
curriculum vitae, certificates and, if applicable, a list of
publications) in a single PDF are requested via e-mail to Martin
Schmidt ([log in to unmask]) or to Veronika Grimm
([log in to unmask]).


-------------------------------------------------------

From: Jose E Castillo [log in to unmask]
Date: September 21, 2020
Subject: PhD Positions, Computational Science, USA

The Interdisciplinary Ph.D. Program in Computational Science is aimed
at training scientists and engineers who will create advanced
computational methods and tools to model and solve challenging
problems at the intersections of scientific disciplines. The doctoral
program offers coursework and research in a broad range of subjects
that develop expertise in Mathematical Modeling and Scientific
Computing with applications to Biological Science, Earth Science,
Engineering Science, Health, Physical and/or Chemical Science. UCI and
SDSU campuses are recognized as Hispanic Serving Institutions offering
a welcoming and supportive environment for diverse students. Admitted
graduate students are offered a range of financial assistance options
while they are pursuing advanced degrees, including Teaching,
Graduate, and Research Assistantships and Fellowships. Applicants with
strong backgrounds in mathematics, physical, biological and geological
sciences, computer science, and engineering are invited to apply.
Please check our website for details regarding the doctoral program
and the application process.

Website: http://www.csrc.sdsu.edu/csrc/doctoral.html

-------------------------------------------------------

From: Badih Ghusayni [log in to unmask]
Date: September 21, 2020
Subject: Contents, Mathematics and Computer Science, 15 (4)

Contents, International Journal of Mathematics and Computer Science,
Volume 15, no, 4:

Chawalit Boonpok, Chokchai Viriyapong, closed sets in ideal strong
generalized topological spaces

Mohammad Nazrul Islam Khan, Complete and horizontal lifts of Metallic
Structures

Marwa J. M. Zedan, Fawziya Mahmood Ramo, Predicting Alzheimer's
Disease using Grey Wolf Intelligent Algorithm

A. Alshabeeb, N. G. Ali,S. A. Naser, W. M. Shakir, A Clustering
Algorithm Application in Parkinson Disease based on k-means Method

Fairouz Sherali, Sarhan Falah, An Efficient Two Factor User
Authentication and Key Exchange Protocol for Telecare Medical
Information System

Haitham Qawaqneh, New contraction embedded with simulation function
andn cyclic -admissible in metric-like spaces

S. Kawsumarng, T. Khemaratchatakumthorn, P. Noppakaew, P.  Pongsriiam,
Distribution of Wythoff Sequences Modulo One

V. Shalini, Indra Rajasingh, Domination and Inverse Domination in
Wrapped Butterfly Networks

Joice Punitha M., A. Josephine Lissie, Even Strongly Multiplicative
Labeling in Certain Splitting Graphs

Anwar Khaleel Faraj, Areej M. Abduldaim, Some Results Concerning
Multiplicative (Generalized)-Derivations and Multiplicative Left
Centralizers

T. Augustine, S. Roy, e-Lucky Labeling of Certain Graphs

Kateryna Nesvit, Maryna Nesvit, Mathematical Education with efficient
Virtual Teacher

 E. Vidhya, R. Rathipriya, Key Generation for DNA Cryptography Using
Genetic Operators and Diffie-Hellman Key Exchange Algorithm

K. Agilan, V. Parthiban, Existence of Solutions of Fuzzy Fractional
panto-graph Equations

Boonyong Sriponpaew, Lee Sassanapitax, On k-Step Fibonacci Functions
and k-Step Fibonacci Numbers

K. U. Sreeja, P. B. Vinodkumar, P. B. Ramkumar, A graph polynomial for
independent sets of Fibonacci trees


G. Dheepa, P. L. Chithra, A Fully-Automated Detection of Brain Tumor
in MRI Images using Input Cascaded CNN

A. V. Ramakrishna, T. V. N. Prasanna, D. V. Lakshmi, Turning Near
rings into New Near rings

 V. Annamma, N. Hameeda Begum, Prime Labeling of some Star Related
Mirror Graphs

A. S. Shanthi, F. Azher, Natural Difference Labeling on Certain Graphs

El Mostafa Rajaallah, Classification of phases based on a Principal
Component Analysis for Intrusion Detection Methods

S. Dhanalakshmi, Mean Square Cordial Labeling of a Shell-butterfly
Graph

S. S. Devi, K. Ganesan, Higher Order Fuzzy Initial Value Problem
Through Taylor's Method

Carlos Ogouyandjou, Nestor Wadagni, Wasserstein Riemannian geometry of
Gamma densities

Rami AlAhmad, Sum of powers of the natural numbers via Stirling
numbers of the second kind

R. Vincent, P. Bhatia, M. Rajesh, A. K. Sivaraman, M. S. S. A. Bahri,
Indian Currency Recognition and Verification using Transfer Learning

V. Cynthia, S. Therese, Packing of Certain Nanotubes and Nanosheet

K. E. Hilda, J. J. Jesintha, Disjoint Union of Two SSG(2) is Odd
Graceful

S. Deepa, A. Gnanam, Extraction of Cantor One-Third Set from
Stern-Brocot Sequence

V. Annamma, Jawahar Nisha M. I., Geometric Mean Cordial Labeling of
certain Graphs

M. Ibrahim, A. Senguttuvan, D. Mohankumar, R. G. Raman, On Classes of
Janowski Functions of Complex Order Involving a q-Derivative Operator

R. K. Kumari, R. Arulprakasam, V. R. Dare, Language of Lyndon Partial
Word

V. Sankar, P. B. Ramkumar, D. Daison, G. Thampi, R. Panicker, Fuzzy
Logic Based Optimization Method for Mechanical Systems and its
Application

S. M. Arul, R. M. Umamageswari, On the Achromatic Number of Certain
Distance Graphs

D. Sophia Navis Mary, S. Gopinathan, Performance of Merkle Signature
Scheme in Data Integrity Verification at Client

Mohammed Yahya Alghamdi, An Investigative Analysis of Students' Use of
Web 2.0 Applications at Albaha University

T. H. Jasim, S. I. Abdullah, K. S.  Eke, Contra Continuity on Double
Fuzzy Topological Space

N. Mohana, K. Desikan, Parallelisable String-Based SP-Local Languages
and their properties

M. Sowjanya, A. GangadharaRao, T. Radharani, V. Padmaja, Results on
r-regular near-rings

V. Manoranjithem, M. Venkatesulu, KNN Classification in Chronic Kidney
Disease Dataset

-------------------------------------------------------

From: JNAAT [log in to unmask]
Date: September 26, 2020
Subject: Contents, Numerical Analysis and Approximation Theory, 49 (1)

Journal of Numerical Analysis and Approximation Theory
published since 1972
http://ictp.acad.ro/jnaat

Preconditioned conjugate gradient methods for absolute value
equations, N. Anane, M. Achache

Comparative numerical study between line search methods and majorant
functions in barrier logarithmic methods for linear programming,
S. Chaghoub, D. Benterki

Low-rank matrix approximations over canonical subspaces, A. Dax

On the convergence rates of pairs of adjacent sequences, D. Duca,
A. Vernescu

Quantitative approximation by nonlinear Angheluta-Choquet singular
integrals, S. Gal, I. Iancu

Infinitely homoclinic solutions in discrete hamiltonian systems
without coercive conditions, F. Khelifi

Comparison of some optimal derivative-free three-point iterations,
T. Zhanlav, K. Otgondorj

-------------------------------------------------------
End of Digest
**************************

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March 2023, Week 2
February 2023, Week 4
February 2023, Week 2
February 2023, Week 1
January 2023, Week 5
January 2023, Week 3
January 2023, Week 1
December 2022, Week 4
December 2022, Week 3
December 2022, Week 2
December 2022, Week 1
November 2022, Week 4
November 2022, Week 1
October 2022, Week 5
October 2022, Week 4
October 2022, Week 3
October 2022, Week 2
October 2022, Week 1
September 2022, Week 4
September 2022, Week 3
September 2022, Week 2
September 2022, Week 1
August 2022, Week 5
August 2022, Week 1
July 2022, Week 4
July 2022, Week 3
July 2022, Week 1
June 2022, Week 5
June 2022, Week 3
June 2022, Week 2
June 2022, Week 1
May 2022, Week 5
May 2022, Week 4
May 2022, Week 3
May 2022, Week 2
May 2022, Week 1
April 2022, Week 4
April 2022, Week 3
March 2022, Week 5
March 2022, Week 2
March 2022, Week 1
February 2022, Week 4
February 2022, Week 2
January 2022, Week 5
January 2022, Week 4
January 2022, Week 3
January 2022, Week 2
January 2022, Week 1
December 2021, Week 4
December 2021, Week 3
December 2021, Week 1
November 2021, Week 4
November 2021, Week 3
November 2021, Week 2
October 2021, Week 4
October 2021, Week 3
October 2021, Week 2
October 2021, Week 1
September 2021, Week 4
September 2021, Week 3
September 2021, Week 1
August 2021, Week 5
August 2021, Week 4
August 2021, Week 3
August 2021, Week 2
August 2021, Week 1
July 2021, Week 4
July 2021, Week 3
July 2021, Week 2
July 2021, Week 1
June 2021, Week 4
June 2021, Week 3
June 2021, Week 2
June 2021, Week 1
May 2021, Week 5
May 2021, Week 4
May 2021, Week 3
May 2021, Week 2
May 2021, Week 1
April 2021, Week 4
April 2021, Week 3
April 2021, Week 2
April 2021, Week 1
March 2021, Week 4
March 2021, Week 3
March 2021, Week 2
February 2021, Week 3
February 2021, Week 2
January 2021, Week 5
January 2021, Week 4
January 2021, Week 2
January 2021, Week 1
December 2020, Week 4
December 2020, Week 3
December 2020, Week 2
December 2020, Week 1
November 2020, Week 4
November 2020, Week 3
November 2020, Week 2
November 2020, Week 1
October 2020, Week 4
October 2020, Week 3
October 2020, Week 2
October 2020, Week 1
September 2020, Week 4
September 2020, Week 3
September 2020, Week 2
September 2020, Week 1
August 2020, Week 5
August 2020, Week 4
August 2020, Week 3
August 2020, Week 2
August 2020, Week 1
July 2020, Week 4
July 2020, Week 3
July 2020, Week 2
June 2020, Week 4
June 2020, Week 2
June 2020, Week 1
May 2020, Week 5
May 2020, Week 4
May 2020, Week 3
May 2020, Week 2
May 2020, Week 1
April 2020, Week 4
April 2020, Week 3
April 2020, Week 2
April 2020, Week 1
March 2020, Week 5
March 2020, Week 3
March 2020, Week 2
March 2020, Week 1
February 2020, Week 4
February 2020, Week 3
February 2020, Week 2
February 2020, Week 1
January 2020, Week 4
January 2020, Week 3
January 2020, Week 2
January 2020, Week 1
December 2019, Week 5
December 2019, Week 4
December 2019, Week 3
December 2019, Week 2
December 2019, Week 1
November 2019, Week 4
November 2019, Week 3
November 2019, Week 2
November 2019, Week 1
October 2019, Week 5
October 2019, Week 3
October 2019, Week 2
October 2019, Week 1
September 2019, Week 5
September 2019, Week 4
September 2019, Week 1
August 2019, Week 4
August 2019, Week 3
August 2019, Week 2
August 2019, Week 1
July 2019, Week 4
July 2019, Week 2
July 2019, Week 1
June 2019, Week 3
June 2019, Week 2
June 2019, Week 1
May 2019, Week 4
May 2019, Week 3
May 2019, Week 2
May 2019, Week 1
April 2019, Week 4
April 2019, Week 3
April 2019, Week 2
April 2019, Week 1
March 2019, Week 5
March 2019, Week 4
March 2019, Week 3
March 2019, Week 2
March 2019, Week 1
February 2019, Week 4
February 2019, Week 3
February 2019, Week 2
February 2019, Week 1
January 2019, Week 5
January 2019, Week 3
January 2019, Week 2
January 2019, Week 1
December 2018, Week 5
December 2018, Week 4
December 2018, Week 3
December 2018, Week 2
December 2018, Week 1
November 2018, Week 4
November 2018, Week 3
November 2018, Week 2
November 2018, Week 1
October 2018, Week 5
October 2018, Week 3
October 2018, Week 1
September 2018, Week 5
September 2018, Week 4
September 2018, Week 3
September 2018, Week 2
September 2018, Week 1
August 2018, Week 4
August 2018, Week 3
August 2018, Week 2
August 2018, Week 1
July 2018, Week 5
July 2018, Week 4
July 2018, Week 3
July 2018, Week 2
July 2018, Week 1
June 2018, Week 4
June 2018, Week 3
June 2018, Week 2
June 2018, Week 1
May 2018, Week 4
May 2018, Week 3
May 2018, Week 2
May 2018, Week 1
April 2018, Week 5
April 2018, Week 4
April 2018, Week 3
April 2018, Week 2
April 2018, Week 1
March 2018, Week 4
March 2018, Week 3
March 2018, Week 2
March 2018, Week 1
February 2018, Week 4
February 2018, Week 3
February 2018, Week 2
February 2018, Week 1
January 2018, Week 4
January 2018, Week 3
January 2018, Week 2
January 2018, Week 1
December 2017, Week 5
December 2017, Week 4
December 2017, Week 3
December 2017, Week 2
November 2017, Week 4
November 2017, Week 1
October 2017, Week 4
October 2017, Week 3
October 2017, Week 1
September 2017, Week 4
September 2017, Week 3
September 2017, Week 2
September 2017, Week 1
August 2017, Week 4
August 2017, Week 3
July 2017, Week 2
July 2017, Week 1
June 2017, Week 4
June 2017, Week 2
June 2017, Week 1
May 2017, Week 4
May 2017, Week 3
May 2017, Week 2
May 2017, Week 1
April 2017, Week 4
March 2017, Week 4
March 2017, Week 2
March 2017, Week 1
February 2017, Week 4
February 2017, Week 2
February 2017, Week 1
January 2017, Week 3
January 2017, Week 2
December 2016, Week 5
December 2016, Week 3
December 2016, Week 2
December 2016, Week 1
November 2016, Week 3
November 2016, Week 2
November 2016, Week 1
October 2016, Week 4
October 2016, Week 3
October 2016, Week 2
October 2016, Week 1
September 2016, Week 4
September 2016, Week 3
September 2016, Week 2
September 2016, Week 1
August 2016, Week 5
August 2016, Week 4
August 2016, Week 2
August 2016, Week 1
July 2016, Week 4
July 2016, Week 3
July 2016, Week 1
June 2016, Week 4
June 2016, Week 3
June 2016, Week 1
May 2016, Week 5
May 2016, Week 4
May 2016, Week 3
May 2016, Week 2
May 2016, Week 1
April 2016, Week 4
April 2016, Week 3
April 2016, Week 2
April 2016, Week 1
March 2016, Week 5
March 2016, Week 4
March 2016, Week 2
March 2016, Week 1
February 2016, Week 5
February 2016, Week 3
February 2016, Week 1
January 2016, Week 5
January 2016, Week 4
January 2016, Week 3
January 2016, Week 2
January 2016, Week 1
December 2015, Week 5
December 2015, Week 2
November 2015, Week 5
November 2015, Week 4
November 2015, Week 3
November 2015, Week 1
October 2015, Week 4
October 2015, Week 3
October 2015, Week 2
September 2015, Week 5
September 2015, Week 4
September 2015, Week 2
September 2015, Week 1
August 2015, Week 4
August 2015, Week 2
July 2015, Week 5
July 2015, Week 3
July 2015, Week 2
June 2015, Week 5
June 2015, Week 4
June 2015, Week 3
June 2015, Week 2
June 2015, Week 1
May 2015, Week 4
May 2015, Week 3
May 2015, Week 2
May 2015, Week 1
April 2015, Week 4
April 2015, Week 2
April 2015, Week 1
March 2015, Week 5
March 2015, Week 4
March 2015, Week 3
March 2015, Week 2
March 2015, Week 1
February 2015, Week 4
February 2015, Week 3
February 2015, Week 2
February 2015, Week 1
January 2015, Week 4
January 2015, Week 3
January 2015, Week 1
December 2014, Week 5
December 2014, Week 4
December 2014, Week 3
December 2014, Week 2
December 2014, Week 1
November 2014, Week 4
November 2014, Week 3
November 2014, Week 2
October 2014, Week 5
October 2014, Week 4
October 2014, Week 3
October 2014, Week 2
October 2014, Week 1
September 2014, Week 4
September 2014, Week 3
September 2014, Week 2
September 2014, Week 1
August 2014, Week 4
August 2014, Week 3
August 2014, Week 2
August 2014, Week 1
July 2014, Week 5
July 2014, Week 3
July 2014, Week 2
June 2014, Week 5
June 2014, Week 4
June 2014, Week 3
June 2014, Week 2
June 2014, Week 1
May 2014, Week 4
May 2014, Week 3
May 2014, Week 2
May 2014, Week 1
April 2014, Week 4
April 2014, Week 3
April 2014, Week 2
April 2014, Week 1
March 2014, Week 5
March 2014, Week 4
March 2014, Week 3
February 2014, Week 3
February 2014, Week 1
January 2014, Week 3
January 2014, Week 1
December 2013, Week 3
December 2013, Week 2
December 2013, Week 1
November 2013, Week 4
November 2013, Week 3
November 2013, Week 2
November 2013, Week 1
October 2013, Week 4
October 2013, Week 2
October 2013, Week 1
September 2013, Week 4
September 2013, Week 3
September 2013, Week 2
August 2013, Week 4
August 2013, Week 3
July 2013, Week 5

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