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Personal and Ubiquitous Computing
H-index 21

Personal and Ubiquitous Computing

1617-4909

Published by: Springer

https://www.springer.com/journal/779

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 272 87 102 21

Additional Metrics

Number of Best Scientists*: 115
Documents by Best Scientists*: 119
Top 100 Ranked Scientists*: 1
SCIMAGO H-index: 102
SCIMAGO SJR: 0.535
Impact Factor: N/A

Overview

Top Research Topics at Personal and Ubiquitous Computing?

The objective of the journal is to combine knowledge in the areas of Mobile computing, Human–computer interaction, Artificial intelligence, Multimedia and Context (language use). While work presented in Personal and Ubiquitous Computing provided substantial information on Mobile computing, it also covered topics in Computer security, World Wide Web, The Internet, Mobile device and Data science. The in-depth study on Human–computer interaction also explores topics in the intersecting field of Wearable computer.

Topics in Artificial intelligence explored in Personal and Ubiquitous Computing were investigated in conjunction with research in Machine learning, Computer vision and Pattern recognition.

  • Mobile computing (63.09%)
  • Human–computer interaction (16.09%)
  • Artificial intelligence (16.09%)

What are the most cited papers published in the journal?

  • Implicit human computer interaction through context (541 citations)
  • PDAs and shared public displays: Making personal information public, and public information personal (212 citations)
  • Supporting group collaboration with interpersonal awareness devices (142 citations)

Research areas of the most cited articles at Personal and Ubiquitous Computing:

The most cited publications focus on Mobile computing, Human–computer interaction, Multimedia, Artificial intelligence and Wearable computer. The works on Mobile computing tackled in the most cited papers bring together disciplines like Wireless, Personal information manager, Field (computer science) and World Wide Web, The Internet. The majority of Human–computer interaction studies presented in the journal articles zero in on Ubiquitous computing.

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

  • Artificial intelligence
  • Operating system
  • The Internet

The previous edition focused in particular on these issues:

Personal and Ubiquitous Computing mostly deals with topics like Mobile computing, Artificial intelligence, Human–computer interaction, Deep learning and Computer security. The work on Mobile computing tackled in Personal and Ubiquitous Computing brings together disciplines like Task (project management), The Internet, Cloud computing, Data science and Big data. The research on Artificial intelligence tackled can also make contributions to studies in the areas of Identification (information), Machine learning, Computer vision and Pattern recognition.

It focuses on Human–computer interaction research which is adjacent to topics in Context (language use). Key (cryptography) is part of Computer security studies tackled in Personal and Ubiquitous Computing.

The most cited articles from the last journal are:

  • Prediction of muscular paralysis disease based on hybrid feature extraction with machine learning technique for COVID-19 and post-COVID-19 patients. (35 citations)
  • GAN-based imbalanced data intrusion detection system (25 citations)
  • MBS: Multilevel Blockchain System for IoT (12 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.

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

  • Ansar-Ul-Haque Yasar (13 papers) published 6 papers at the last edition,
  • Kyung-Yong Chung (9 papers) published 4 papers at the last edition,
  • Yunchuan Sun (7 papers) published 4 papers at the last edition,
  • Fatma Outay (6 papers) published 5 papers at the last edition,
  • Muhammad Adnan (6 papers) published 5 papers 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.

Only papers with recognized affiliations are considered

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

  • University of Hasselt (16 papers) published 11 papers at the last edition,
  • Beijing Normal University (9 papers) published 6 papers at the last edition,
  • University of Nottingham (9 papers) published 5 papers at the last edition, 3 more than at the previous edition,
  • Kyonggi University (9 papers) published 4 papers at the last edition,
  • Lancaster University (8 papers) published 1 paper at the last edition the same number as at the previous 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, 12.86% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 21.86% were posted by at least one author from the top 10 institutions publishing in the journal. Another 11.48% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.39% of all publications and 50.27% 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.

Educational Applications of Personal and Ubiquitous Computing

Besides primarily being a field of interest for tech enthusiasts and experts, Personal and Ubiquitous Computing also finds substantial applications in the education sector. The subject is instrumental in equipping students with insights into futuristic technology concepts and improving their understanding of how research affects the real-world scenarios. One significant area of its application is in the teaching career, more specifically, in the role of a high school teacher. For instance, high school history teachers can leverage the concepts of ubiquitous computing to bring historical events to life using augmented reality and other multimedia tools. It can make teaching history more interactive and exciting by providing students with a more engaging learning experience. In South Dakota, for example, a high school history teacher could employ these technologies to enhance their teaching methods, making the subject more comprehensive and interesting for students. This could be another advantageous outcome of the interdisciplinary nature of Personal and Ubiquitous Computing. To get a more in-depth look at how to qualify for the role and understand the requirements better, you may refer to our detailed guide on how to become a high school history teacher in South Dakota. Through this, you can learn how integrating Personal and Ubiquitous Computing in teaching methodologies can create a dynamic and better teaching-learning environment.

Top Publications

  • A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment.

    Samira Akhbarifar;Hamid Haj Seyyed Javadi;Amir Masoud Rahmani;Mehdi Hosseinzadeh;Mehdi Hosseinzadeh

    (2020)
    126 Citations
  • Diagnosis and combating COVID-19 using wearable Oura smart ring with deep learning methods.

    M. Poongodi;Mounir Hamdi;Mohit Malviya;Ashutosh Sharma

    (2021)
    79 Citations
  • Drug traceability and transparency in medical supply chain using blockchain for easing the process and creating trust between stakeholders and consumers

    Sandeep Kumar Panda;Suresh Chandra Satapathy

    (2021)
    77 Citations
  • Time series forecasting of COVID-19 transmission in Asia Pacific countries using deep neural networks.

    Hafiz Tayyab Rauf;M. Ikram Ullah Lali;Muhammad Attique Khan;Seifedine Kadry

    (2021)
    75 Citations
  • Touching the audience: musical haptic wearables for augmented and participatory live music performances

    Luca Turchet;Travis J. West;Marcelo M. Wanderley

    (2021)
    74 Citations
  • Enhancing cultural heritage outdoor experience with augmented-reality smart glasses

    Eran Litvak;Tsvi Kuflik

    (2020)
    74 Citations
  • Forecasting major impacts of COVID-19 pandemic on country-driven sectors: challenges, lessons, and future roadmap.

    Saket Kumar;Rajkumar Viral;Vikas Deep;Purushottam Sharma

    (2021)
    71 Citations
  • Synergic deep learning model–based automated detection and classification of brain intracranial hemorrhage images in wearable networks

    C. S. S. Anupama;M. Sivaram;E. Laxmi Lydia;Deepak Gupta

    (2020)
    56 Citations
  • Semi-supervised and personalized federated activity recognition based on active learning and label propagation

    (2021)
    53 Citations
  • Blockchain-assisted secure image transmission and diagnosis model on Internet of Medical Things Environment

    Bassam A. Y. Alqaralleh;Thavavel Vaiyapuri;Velmurugan Subbiah Parvathy;Deepak Gupta

    (2021)
    52 Citations

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