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Information
Special Issues
Editorial Board Members’ Collection Series: "Information Processes"
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Editorial Board Members’ Collection Series: "Information Processes"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 7453

Special Issue Editors

Prof. Emilio Matricciani

E-Mail Website
Guest Editor
Department of Electronics, Information, and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
Interests: satellite and deep space telecommunications; radio propagation; information theory; mathematics of alphabetical texts
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Heming Jia

E-Mail Website
Guest Editor
Department of Information Engineering, Sanming University, Sanming 365004, China
Interests: optimization; remora optimization algorithm (ROA); bio-inspired computing; nature-inspired computing; swarm intelligence; artificial intelligence; meta-heuristic modeling and optimization algorithms; evolutionary computations; multilevel image segmentation; feature selection; combinatorial problems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zhigang Chu

E-Mail Website
Guest Editor
College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
Interests: array signal processing; analysis and control on sound and vibration; mechanical systems and signal processing; com-pressive sensing; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Information Processes publishes cutting-edge original research on methods or applications pertaining to a range of areas including, but not limited to, advertising, business, engineering, health, information science, IT marketing, and social computing.

Specifically, there are four types of manuscripts that the Editorial Board Members’ Collection Series is interested in:

  • The intersection of computing, engineering, and information science;
  • The application of new methods at the intersection of computer, engineering, and information science;
  • The critical and in-depth intersection of computer, engineering, and information science, providing information on integration of the prior research, and recommendations for further work in the multidisciplinary area;
  • Systems design research involving the intersection of computer, engineering, and information science.

Prof. Dr. Emilio Matricciani
Prof. Dr. Heming Jia
Prof. Dr. Zhigang Chu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • knowledge management
  • social media and social networks
  • big data and cloud computing
  • artificial intelligence
  • Internet of Things/Internet of Everything
  • digital signal processing
  • data mining
  • information extraction
  • human–machine interface
  • information in society and social development
  • business process management
  • blockchain and emerging technologies
  • communication systems and networks
  • wireless sensor network
  • mobile communication services

Published Papers (4 papers)

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Research

12 pages, 4072 KiB  
Article
Early Parkinson’s Disease Diagnosis through Hand-Drawn Spiral and Wave Analysis Using Deep Learning Techniques
by Yingcong Huang, Kunal Chaturvedi, Al-Akhir Nayan, Mohammad Hesam Hesamian, Ali Braytee and Mukesh Prasad
Information 2024, 15(4), 220; https://doi.org/10.3390/info15040220 - 13 Apr 2024
Viewed by 685
Abstract
Parkinson’s disease (PD) is a chronic brain disorder affecting millions worldwide. It occurs when brain cells that produce dopamine, a chemical controlling movement, die or become damaged. This leads to PD, which causes problems with movement, balance, and posture. Early detection is crucial [...] Read more.
Parkinson’s disease (PD) is a chronic brain disorder affecting millions worldwide. It occurs when brain cells that produce dopamine, a chemical controlling movement, die or become damaged. This leads to PD, which causes problems with movement, balance, and posture. Early detection is crucial to slow its progression and improve the quality of life for PD patients. This paper proposes a handwriting-based prediction approach combining a cosine annealing scheduler with deep transfer learning. It utilizes the NIATS dataset, which contains handwriting samples from individuals with and without PD, to evaluate six different models: VGG16, VGG19, ResNet18, ResNet50, ResNet101, and Vit. This paper compares the performance of these models based on three metrics: accuracy, precision, and F1 score. The results showed that the VGG19 model, combined with the proposed method, achieved the highest average accuracy of 96.67%. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: "Information Processes")
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17 pages, 1071 KiB  
Article
Leveraging the TOE Framework: Examining the Potential of Mobile Health (mHealth) to Mitigate Health Inequalities
by Salman Bin Naeem, Mehreen Azam, Maged N. Kamel Boulos and Rubina Bhatti
Information 2024, 15(4), 176; https://doi.org/10.3390/info15040176 - 23 Mar 2024
Viewed by 953
Abstract
(1) Aims and Objectives: Mobile health (mHealth) is increasingly becoming a favorite healthcare delivery solution in underserved areas around the globe. This study aims to identify the influence of technology–organization–environment (TOE) factors on mHealth adoption and to assess the influence of mHealth on [...] Read more.
(1) Aims and Objectives: Mobile health (mHealth) is increasingly becoming a favorite healthcare delivery solution in underserved areas around the globe. This study aims to identify the influence of technology–organization–environment (TOE) factors on mHealth adoption and to assess the influence of mHealth on the reduction in health disparities in the context of healthcare delivery in low-resource settings. (2) Methods: A cross-sectional survey of physicians and nurses was carried out at six hospitals in the public and private health sectors in Pakistan. The survey’s theoretical foundation is based on the technology–organization–environment (TOE) framework. TOE constructs (relative advantage, compatibility, management support, organizational readiness, external support, and government regulations) were used to develop hypotheses. The hypotheses were tested using structural equation modeling (SEM). (3) Results: Findings from this study show that management support and external support are the two main predictors of mHealth adoption among healthcare professionals. The study proposes an mHealth adoption model that can significantly contribute towards improving medical outcomes, reducing inefficiencies, expanding access, lowering costs, raising quality, making medicine more personalized for patients, and gaining advantages from mHealth solutions in order to reduce health disparities. (4) Conclusion: The study suggests that there is no single approach that could support mHealth adoption. Instead, a holistic approach is required that considers cultural, economic, technological, organizational, and environmental factors for successful mHealth adoption in low-resource settings. Our proposed mHealth model offers guidance to policymakers, health organizations, governments, and political leaders to make informed decisions regarding mHealth implementation plans. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: "Information Processes")
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27 pages, 9431 KiB  
Article
Generative Pre-Trained Transformer (GPT) in Research: A Systematic Review on Data Augmentation
by Fahim Sufi
Information 2024, 15(2), 99; https://doi.org/10.3390/info15020099 - 08 Feb 2024
Cited by 2 | Viewed by 3942
Abstract
GPT (Generative Pre-trained Transformer) represents advanced language models that have significantly reshaped the academic writing landscape. These sophisticated language models offer invaluable support throughout all phases of research work, facilitating idea generation, enhancing drafting processes, and overcoming challenges like writer’s block. Their capabilities [...] Read more.
GPT (Generative Pre-trained Transformer) represents advanced language models that have significantly reshaped the academic writing landscape. These sophisticated language models offer invaluable support throughout all phases of research work, facilitating idea generation, enhancing drafting processes, and overcoming challenges like writer’s block. Their capabilities extend beyond conventional applications, contributing to critical analysis, data augmentation, and research design, thereby elevating the efficiency and quality of scholarly endeavors. Strategically narrowing its focus, this review explores alternative dimensions of GPT and LLM applications, specifically data augmentation and the generation of synthetic data for research. Employing a meticulous examination of 412 scholarly works, it distills a selection of 77 contributions addressing three critical research questions: (1) GPT on Generating Research data, (2) GPT on Data Analysis, and (3) GPT on Research Design. The systematic literature review adeptly highlights the central focus on data augmentation, encapsulating 48 pertinent scholarly contributions, and extends to the proactive role of GPT in critical analysis of research data and shaping research design. Pioneering a comprehensive classification framework for “GPT’s use on Research Data”, the study classifies existing literature into six categories and 14 sub-categories, providing profound insights into the multifaceted applications of GPT in research data. This study meticulously compares 54 pieces of literature, evaluating research domains, methodologies, and advantages and disadvantages, providing scholars with profound insights crucial for the seamless integration of GPT across diverse phases of their scholarly pursuits. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: "Information Processes")
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28 pages, 5371 KiB  
Article
Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature
by Emilio Matricciani
Information 2023, 14(7), 405; https://doi.org/10.3390/info14070405 - 14 Jul 2023
Cited by 1 | Viewed by 1027
Abstract
We studied two fundamental linguistic channels—the sentences and the interpunctions channels—and showed they can reveal deeper connections between texts. The applied theory does not follow the actual paradigm of linguistic studies. As a study case, we considered the Greek New Testament, with the [...] Read more.
We studied two fundamental linguistic channels—the sentences and the interpunctions channels—and showed they can reveal deeper connections between texts. The applied theory does not follow the actual paradigm of linguistic studies. As a study case, we considered the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in the writing style (mathematically defined) of the writers and in the reading skill required of their readers. The analysis was based on deep-language parameters and communication/information theory. To set the New Testament texts in the larger Greek classical literature, we considered texts written by Aesop, Polybius, Flavius Josephus, and Plutarch. The results largely confirmed what scholars have found about the New Testament texts, therefore giving credibility to the theory. The Gospel according to John is very similar to the fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse are each other’s “photocopies” in the two linguistic channels and not linked to all other texts. These two texts deserve further study by historians of the early Christian church literature at the level of meaning, readers, and possible Old Testament texts that might have influenced them. The theory can guide scholars to study any literary corpus. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: "Information Processes")
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