Q1 Journal Walkthrough: How did I think about computing research?
I have never found someone surrounding myself who can guide me about research, and people indeed tend to give support for a certain period and then everything has to be done by your own's efforts. Once upon a time, I realized that a conference paper is good enough for being a researcher. Still, when I grew up, I kept communicating with various professors in my home country and learned about Q1 journals slowly. Creating software or solving real-life problems should be the primary concern for a software engineer.
But I came out of the conventional world in the hope of doing something new :) However, if you are a researcher and want to make your Q1 research paper, follow the guidelines, and I will share my experiences obtained from lots of rejection.
Q1 Journal Walkthrough: Problem Statement
In the introduction, the motivation of the practical use of the result obtained should be clearly addressed. The best way to show this is by practical example or explanation. Also, In the related work, there needs to add some previous studies, and I would suggest adding some studies for comparison with your
paper. I'm expecting that you have written a research paper and did the abstract review, introduction, literature review accordingly; now, take a close look at the following questions and ask your brain to analyze effectively….
- Did you design any hypothesis to support the problem statement you have been conducting your empirical study? To what extent research community will be able to understand that the particular research has been justified beforehand and has a potential impact on society?
- You have carried out the literature review (LR), which is extremely significant for any research work, but have you justified and figured out the potential gaps while writing the LR? To what extent I will believe that the particular study has been accomplished based on the specific drawbacks and beforehand, which limitation did not resolve?
- Have you ever asked yourself whether your abstract reflect the paper's content?
- Does the paper's title linked with the abstract and conclusion?
- Does your paper have clarity on how used emergent technologies in the discussed results can reflect on the embodiment of a scheme with the help of Machine Learning?
Q1 Journal Walkthrough: Constructive Criticism for Methodology
Suppose a publicly available dataset has been utilized as a part of the research work and for this purpose, let's assume you have used the Light Gradient Boosting Machine (LightGBM) algorithm to predict kidney disease. Now please take a look at the following questions and answer your opinion:
- Light Gradient Boosting Machine is adopted in the kidney disease prediction approach. What are the other feasible alternatives? What are the advantages of adopting this soft computing technique over others in this case? How will this affect the results?
- I think you have applied various electronic datasets to execute and test their feasibilities in this phase. Several electronic databases are adopted to recognize similar published research papers. What are the other feasible alternatives? Can you please tell me now what is the benefit of adopting these databases over others in this case? How will this have an effect on the results?
- What is your main contribution on top of the Light Gradient Boosting Machine model? We can explore various models online; what changes have significantly influenced your research?
- Have you used any mathematical interpretation? If yes, then which layer has been customized? Probably, you have been thinking about why it is required to apply the mathematical interpretation where I can apply various pre-trained models than using the LightGBM. Here is the technical contribution. Researchers often design their own algorithms based on their work if it is a novel work; for example, you can apply the Resnet-50 model without any hassle, but have you ever tried to customize the layer? If not, then how did you clarify that it is your model?
- If I said that only using machine learning techniques are not novel at all; as a result, I cannot find any technical challenges in the designed framework. In addition, let's assume that apart from the LightGBM algorithm, Decision Tree and Logistic Regression have been adopted, but the effectiveness is not clear, so what would be your direction in terms of my thought?
Talking about the research dataset
I have seen that typical researchers consolidate a dataset that does not contain any unique values. More importantly, I cannot find the well-known procedure's value to the datasets. Besides, the data imbalance in raw datasets sometimes needs to be explained, and the proposed approaches must be investigated. For example, your dataset has two classes: normal and Covid-19. If the precision and recall for the Covid-19 class appeared with poor values and others are high, in that case, high accuracy does not have actual effects. Furthermore, only a single dataset cannot show the effectiveness of the proposed method. Moreover, these key factors are considerably significant while selecting or working on top of the research dataset that I firmly confide.
Talking about the research discussion
Other crucial step that researchers do not take into consideration while researching, which is highlighting their findings clearly. The discussion section contains the results and outcomes of a study. An effective discussion informs readers of what can be learned from your experiment and provides context for the results. The discussion chapter is where you elucidate the meaning, significance, and applicability of your findings. It should concentrate on discussing and analyzing what you discovered, demonstrating how it pertains to your literature review and research objectives, and building a case for your ultimate conclusion.
Conclusion
To conclude, this article discusses the essential steps that have to be taken into consideration while writing a research work for Q1 journal as a high-quality journal has an extensive peer-review and rigorous process so that each research article is thoroughly and deeply justified. I believe that anyone can submit their research work to Q1 Journal if the mentioned steps are addressed especially. I have tried to write this article in the light of my own experience so that the research community can get a good guideline.
Check out my recent Q1 journal paper:
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