Question
Asked 31 October 2023

The method is simple and effective. How to write a CS paper that will help it be accepted?

The method is simple and effective. How to write a computer science paper that will help it be accepted?

All Answers (1)

Mohit Tiwari
Bharati Vidyapeeth College of Engineering, Delhi
Writing a computer science paper that stands a good chance of being accepted involves several key steps and considerations. Here's a concise guide to help you:
1. Select a Relevant and Interesting Topic:
  • Choose a topic that is relevant to the current trends and challenges in computer science.
  • Ensure it's an area that genuinely interests you, as your passion will reflect in your writing.
2. Extensive Literature Review:
  • Conduct a thorough review of existing literature to understand the state of the art in your chosen area.
  • Identify gaps or areas where your work can make a meaningful contribution.
3. Define Clear Objectives:
  • Clearly state the objectives of your research at the beginning of the paper.
  • Define the problem you're addressing and what you aim to achieve.
4. Develop a Strong Methodology:
  • Describe your research methodology in detail, making it clear and replicable.
  • Justify your approach and explain why it's appropriate for your research.
5. Results and Analysis:
  • Present your results clearly and comprehensively.
  • Use visual aids like graphs and charts to enhance understanding.
  • Analyze the results, discussing their implications and significance.
6. Write a Clear and Engaging Paper:
  • Structure your paper logically with sections like introduction, methodology, results, discussion, and conclusion.
  • Write in clear and concise language, avoiding unnecessary jargon.
  • Keep the reader engaged with a well-organized narrative.
7. Cite Properly:
  • Ensure proper citation of all sources and adhere to a recognized citation style (e.g., APA, IEEE).
  • Give credit to previous work and acknowledge contributions.
8. Proofread and Edit:
  • Carefully proofread your paper for grammar, spelling, and formatting errors.
  • Consider seeking feedback from peers or mentors.
9. Address Reviewer Comments:
  • If your paper receives feedback from reviewers, carefully address their comments and revise accordingly.
10. Ethical Considerations:
  • Ensure ethical research practices, including proper data handling and authorship attribution.
11. Submit to Reputable Journals or Conferences:
  • Target reputable journals or conferences in your field for submission.
  • Follow their guidelines and deadlines meticulously.
12. Persistence:
  • Be prepared for potential rejections and don't be discouraged. Many great papers go through multiple submissions and revisions before acceptance.
Remember that the peer review process is rigorous, so patience and perseverance are key. By following these steps and continuously improving your writing and research skills, you can increase your chances of having your computer science paper accepted.
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How do you calculate the Frequency using FEM for Imperial units?
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3 answers
  • Deleted profile
Hello everyone,
I’m currently working on Truss optimization for my master’s thesis. To solve the truss, I am using the Finite Element Method (FEM) in Python and calculating the natural frequencies as part of the optimization process. Here’s what I’ve implemented so far:
  1. I construct the global stiffness matrix using truss element properties (Young's modulus, cross-sectional area, element lengths).
  2. I assemble the mass matrix (using lumped mass assumption).
  3. I solve the eigenvalue problem to compute natural frequencies using the equation K * U = λ * M * U.
When I use SI units, the computed natural frequencies match the expected values. However, when I switch to imperial units, the frequencies deviate significantly.
Here are the steps I follow:
  • For SI units, I input properties like Young’s modulus in Pa, density in kg/m³, cross-sectional area in m², etc., and everything works as expected.
  • For imperial units, I input properties like Young’s modulus in psi, density in lb/in³, and cross-sectional area in in². I convert lbm to slugs for the mass matrix (1 lbm = 1/32.174 slugs).
Despite these conversions, the natural frequencies computed with imperial units are quite different from the ones I obtain using SI units, and this discrepancy is affecting the optimization process.
Here are the results I get:
  • Natural frequencies using SI units: [23.01, 81.35, 85.36, 152.40, 211.83, 214.21, 247.88, 256.48, 263.05, 293.44, 306.17, 349.90] Hz
  • Natural frequencies using imperial units: [21.00, 74.25, 77.91, 139.10, 193.33, 195.51, 226.24, 234.09, 240.09, 267.83, 279.45, 319.35] Hz
Has anyone encountered similar issues while working with FEM for truss analysis? Could there be unit-specific considerations or common pitfalls I am overlooking in handling imperial units in this context?
Any advice or suggestions would be greatly appreciated!
Thank you in advance!
Do directed graphs have a unique structure and topology?
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  • Enis OlgacEnis Olgac
To start with the answer, "definitely".
I will try to explain why, and I am looking for the discussion of pros and cons.
The definition of structure is my starting point. According to Merriam-Webster, structure is:
  • something arranged in a definite pattern of organization
  • the arrangement of particles or parts in a substance or body
  • organization of parts as dominated by the general character of the whole
  • coherent form or organization
  • the aggregate of elements of an entity in their relationships to each other
And the definition of the topology according to P. Alexandroff is:
"The topology of a directed graph is generated by the minimal neighborhoods of its vertices. The minimal neighborhood of vertex v being the set of all nodes reachable from v in the direction of the edges of the graph G. The transitive closure of the edge-relation on the vertices generates the same topology" is my starting point.
Given a directed graph (no matter acyclic or cyclic) by its edge relations, its topology is unique because its transitive closure is unique. For any two vertices, they are either connected or not, i.e. there exists at least one chain of edges between them.
Unfortunately, topology does not include any hints about how the vertices of the graph are organized.
The domination-tree of a directed graph (from here on, I will use the term graph) is the unique structure (skeleton) of the underlying graph with several features based on it.
Together, they allow iterative, bidirectional analysis of any model a graph is representing.

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