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    <link>https://scholar.ptuk.edu.ps/handle/123456789/246</link>
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    <pubDate>Wed, 29 Apr 2026 15:34:49 GMT</pubDate>
    <dc:date>2026-04-29T15:34:49Z</dc:date>
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      <title>Sixth Palestinian Conference for Modern Trends in Mathematics and Physics  Special issue</title>
      <link>https://scholar.ptuk.edu.ps/handle/123456789/702</link>
      <description>Title: Sixth Palestinian Conference for Modern Trends in Mathematics and Physics  Special issue
Abstract: Michael Atiyah      &#xD;
Michael Berry, Bristol University, UK. - &#xD;
- Conrad Schmuedgan, Leipzig, Germany.&#xD;
- C.K. Raju, Indian Institute of education, India.&#xD;
- Giorgio Paolucci, Scientific Director Of  SESAME&#xD;
- Matteo Rini,  editor of the American Physical society, USA    &#xD;
- &#xD;
Main Speakers &#xD;
-  Edriss Titi. Texas A&amp;M University, USA.&#xD;
 &#xD;
-  Ulrich Eckern , University of Augsburg, Germany&#xD;
&#xD;
-  Jim Cushing,  University of Arizona, USA&#xD;
&#xD;
-  Saber Elaydi .Trinity University, USA.&#xD;
&#xD;
-  Ruedi Seiler, Technische Universität Berlin, Germany.&#xD;
&#xD;
-  Ackleh Azmy,  University of Louisiana at Lafayette, USA&#xD;
&#xD;
- Stefanovska, Aneta,  Lancaster University, UK&#xD;
&#xD;
- Stephen Baigent, University College London, UK&#xD;
&#xD;
- Ahmad Hujeirat,  Heidelberg, Germany.&#xD;
&#xD;
- Jens Hating ,Forschungszentrum Jülich, Helmholtz Institute Erlangen-Nürnberg for&#xD;
                        Renewable Energy, Fürther ,Germany.&#xD;
   &#xD;
- Fuad Kittaneh , Jordan University, Jordan.</description>
      <pubDate>Mon, 01 Jan 2018 00:00:00 GMT</pubDate>
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      <dc:date>2018-01-01T00:00:00Z</dc:date>
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    <item>
      <title>Decolonising Mathematics: How and why it makes science better (and enables students to solve harder problems)</title>
      <link>https://scholar.ptuk.edu.ps/handle/123456789/684</link>
      <description>Title: Decolonising Mathematics: How and why it makes science better (and enables students to solve harder problems)
Authors: Raju, C. K
Abstract: Mathematics is not universal. Traditional normal mathematics accepted both empirical proofs and&#xD;
reasoning, as does science, but formal mathematics prohibits the empirical. Prohibiting the empirical is&#xD;
obviously disadvantageous for applications of mathematics to science, but colonial education anyway&#xD;
replaced normal by formal math, declaring the latter to be superior without any critical examination, and&#xD;
globalised it.</description>
      <pubDate>Tue, 20 Nov 2018 00:00:00 GMT</pubDate>
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      <dc:date>2018-11-20T00:00:00Z</dc:date>
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    <item>
      <title>Complex potentials and the inverse problem</title>
      <link>https://scholar.ptuk.edu.ps/handle/123456789/683</link>
      <description>Title: Complex potentials and the inverse problem
Authors: Lombard, R.J; Mezhoud, R; Yekken, R
Abstract: The occurrence of complex potentials with real eigenvalues has implications concerning the&#xD;
inverse problem, i.e. the determination of a potential from its spectrum. First, any complex potential with real&#xD;
eigenvalues has at least one equivalent local potential. Secondly, a real spectrum does not necessarily&#xD;
corresponds to a local real potential. A basic ambiguity arises from the possibility the spectrum to be&#xD;
generated by a complex potential. The purpose of this work is to discuss several aspects of this problem.</description>
      <pubDate>Tue, 20 Nov 2018 00:00:00 GMT</pubDate>
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      <dc:date>2018-11-20T00:00:00Z</dc:date>
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    <item>
      <title>Breaking the F-barrier: How the use of a visual representation of Fisher’s F-ratio can aid student comprehension of orthodox statistics</title>
      <link>https://scholar.ptuk.edu.ps/handle/123456789/682</link>
      <description>Title: Breaking the F-barrier: How the use of a visual representation of Fisher’s F-ratio can aid student comprehension of orthodox statistics
Authors: Allen, Rory
Abstract: Universal laws are notoriously hard to discover in the social sciences, but there is one which can be&#xD;
stated with a fair degree of confidence: “all students hate statistics”. Students in the social sciences often need&#xD;
to learn basic statistics as part of a research methods module, and anyone who has ever been responsible for&#xD;
teaching statistics to these students will soon discover that they find it to be the hardest and least popular part&#xD;
of any social science syllabus.&#xD;
A typical problem for students is the use of Fisher’s F-test as a significance test, which even in the simple case&#xD;
of a one-factor analysis of variance (ANOVA) presents difficulties. These are two in number. Firstly, the test is&#xD;
presented as a test of the null hypothesis, that is, that there is no effect of one variable (the independent variable,&#xD;
IV) on the other, dependent variable (DV). This highlights the opposite of what one generally wants to prove,&#xD;
the experimental hypothesis, which is usually that there is an effect of the IV on the DV. Students, if they think&#xD;
about the question at all, may be tempted to ask “why not try to prove the experimental hypothesis directly&#xD;
rather than using this back-to-front approach?”&#xD;
Secondly, the F-ratio itself is presented in the form of an algebraic manipulation, involving the ratio of two mean&#xD;
sums of squares, and these means are themselves moderately complicated to understand. Even students&#xD;
specializing in mathematics often find algebra difficult, and to non-mathematicians this formula is simply baffling.&#xD;
Instructors do not usually make a serious attempt to remedy this confusion by attempting to explain what the&#xD;
F-ratio is attempting to measure, and when they do, the explanation is not usually very enlightening. Students&#xD;
may struggle with the statement that the F-ratio is the ratio of “two different estimates of the variance of the&#xD;
population being sampled from, under the null hypothesis”. So what?&#xD;
The result is that students frequently end up applying statistical analysis programs such as SPSS and R, without&#xD;
having the faintest understanding of how the mathematics works. They use the results in a mechanical way,&#xD;
according to a procedure learned by rote memory, and may overlook different tests which might be more&#xD;
appropriate for their data. This might be called the cookbook approach to data analysis, and it is the opposite&#xD;
of the ultimate aim of high quality teaching, which is to provide a deep understanding of principles, which will&#xD;
allow the student to use these principles flexibly in real life challenges, without violating the assumptions of the&#xD;
statistical tests being employed</description>
      <pubDate>Tue, 20 Nov 2018 00:00:00 GMT</pubDate>
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      <dc:date>2018-11-20T00:00:00Z</dc:date>
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