Applied Computing and Informatics

Top Research Topics at Applied Computing and Informatics?

Applied Computing and Informatics covers a variety of subjects, including Artificial intelligence, Machine learning, Pattern recognition, Data mining and Algorithm. Most of the works presented in Applied Computing and Informatics deals with Artificial intelligence but it intersects with the subject of Computer vision. Computer vision research is concerned with Segmentation in particular.

The journal aims to address concerns in Pattern recognition, specifically in the areas of Discriminative model and Feature extraction.

• Artificial intelligence (30.58%)
• Machine learning (13.59%)
• Pattern recognition (10.19%)

What are the most cited papers published in the journal?

• Classification assessment methods (441 citations)
• Automated web usage data mining and recommendation system using K-Nearest Neighbor (KNN) classification method (185 citations)
• Empirical investigation of e-learning acceptance and assimilation: A structural equation model (184 citations)

Research areas of the most cited articles at Applied Computing and Informatics:

The most cited publications investigate areas of study like Artificial intelligence, Knowledge management, Machine learning, The Internet and E-learning (theory). Aside from investigating topics in Support vector machine under Artificial intelligence, the published papers also explore concepts in Seizure detection. The most cited papers cover research in Machine learning, particularly Recommender system and Artificial neural network and how it is related with concepts in Global error and Seizure activity.

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Operating system
• Machine learning

The previous edition focused in particular on these issues:

Applied Computing and Informatics investigates areas of study like Artificial intelligence, Machine learning, Pattern recognition, Convolutional neural network and Data mining. The work on Artificial intelligence addressed in Applied Computing and Informatics expands to the thematically related Computer vision. The journal covers research in Machine learning, particularly Artificial neural network, Feature selection and Supervised learning and how they are related with concepts in Stage (hydrology) and Personality.

Issues in Pattern recognition were discussed, taking into consideration concepts from other disciplines like Field (computer science), Goertzel algorithm, Discrete Fourier transform, Test data and Data set. While work presented in Applied Computing and Informatics provided substantial information on Convolutional neural network, it also covered topics in Network topology, Boosting (machine learning), Discriminative model and Matlab code. Univariate, Binary number and Robustness (computer science) are some topics wherein Data mining research discussed in it have an impact.

The most cited articles from the last journal are:

• Classification assessment methods (441 citations)
• Ensemble of convolutional neural networks for bioimage classification (53 citations)
• Independent component analysis: An introduction (35 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Applied Computing and Informatics (based on the number of publications) are:

• Loris Nanni (8 papers) published 3 papers at the last edition, 2 more than at the previous edition,
• Sheryl Brahnam (5 papers) published 2 papers at the last edition,
• Alessandra Lumini (4 papers) absent at the last edition,
• Jose Aguilar (3 papers) absent at the last edition,
• Fadi Thabtah (3 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Applied Computing and Informatics (based on the number of publications) are:

• University of Padua (6 papers) published 1 paper at the last edition the same number as at the previous edition,
• Missouri State University (4 papers) published 1 paper at the last edition,
• University of Bologna (4 papers) absent at the last edition,
• Kuwait University (4 papers) absent at the last edition,
• King Saud University (4 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 55.56% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 12.50% were posted by at least one author from the top 10 institutions publishing in the journal. Another 18.75% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 68.75% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Prospects in Applied Computing and Informatics

With a variety of research topics covered by Applied Computing and Informatics, it provides a wealth of career opportunities in different sector. Prospective employees with interests in Artificial intelligence, Machine learning, Pattern recognition and other relevant areas can find engaging opportunities in academia, corporate research, technology companies, and more.

The first step towards a career in these fields is usually pursuing an appropriate educational qualification. For instance, those interested in teaching such subjects may consider pursuing a bachelor's degree and subsequently a master's degree in the relevant field. For further details, consider reading this comprehensive guide on how to become a teacher in vermont with a bachelor's degree here.

In addition to teaching, researchers specializing in Applied Computing and Informatics often find opportunities in developing new algorithms, systems, or approaches that have practical applications in various industries. They can also work in data analysis, where they use their skills to extract useful information from large data sets.

In conclusion, a career path in Applied Computing and Informatics can be fulfilling and challenging, offering endless opportunities to contribute to advancements in technology. Start your journey today and step into the world of innovation and discovery.