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► Journal BrowserSpecial Issue "Data Science and Big Data in Biology, Physical Science and Engineering"
A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".
Deadline for manuscript submissions: 30 September 2023 | Viewed by 17859
Special Issue Editor

Interests: data science; big data; machine learning; deep learning; artificial intelligence (AI); cybersecurity
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Nowadays, Big Data analysis represents one of the most important contemporary areas of development and research. Tremendous amounts of data are generated every single day from digital technologies and modern information systems, such as cloud computing and Internet of Things (IoT) devices. Analysis of these enormous amounts of data has become of crucial significance and requires a great deal of effort in order to extract valuable knowledge for decision-making which, in turn, will make important contributions in both academia and industry.
Big Data and data science have emerged due to the significant need for generating, storing, organising and processing immense amounts of data. Data scientists strive to use artificial intelligence (AI) and machine learning (ML) approaches and models to allow computers to detect and identify what the data represents and be able to detect patterns more quickly, efficiently and reliably than humans.
The goal behind this Special Issue is to explore and discuss various principles, tools and models in the context of data science, besides the diverse and varied concepts and techniques relating to Big Data in biology, chemistry, biomedical engineering, physics, mathematics and other areas that work with Big Data.
Prof. Dr. Mohammed Mahmoud
Guest Editor
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. Technologies is an international peer-reviewed open access semimonthly 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 1400 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.
Prof. Dr. Mohammed Mahmoud
Guest Editor
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. Technologies is an international peer-reviewed open access semimonthly 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 1400 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
- Data science
- Big Data
- Machine learning
- Artificial intelligence
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Current Advances in Radiographic Methods for Personal Iden-tification of Unknown Decedents
Authors: Sharon M. Derrick 1, Ruby Mehrubeoglu 2, and Longzhuang Li 3
Affiliation: 1 Texas A&M University-Corpus Christi 1; [email protected] 2 Texas A&M University-Corpus Christi 2; [email protected] 3 Texas A&M University-Corpus Christi 3; [email protected] * Correspondence: [email protected]; Tel.: (361-825-3637, smd)
Abstract: Forensic practitioners and researchers have been cognizant for decades that quantitative and ac-cessible methods of decedent identification, processed promptly within the medical examin-er/coroner office, are needed but sorely lacking. The most available on-site use of biometric technology has been fingerprint comparison through AFIS,1 a massive repository of fingerprint data, but AFIS is not useful if the person has no fingerprints in the system or if the decedent’s hands are decomposed/skeletal. Rapid advances in radiographic technology and software over the last decade, in conjunction with an increase in digital X-ray machines and CT instrumenta-tion purchased as standard equipment in medical examiner/coroner offices, have elicited a plethora of research into new quantitative methods of radiographic identification. Large data-bases of digital antemortem and postmortem standard radiograph and CT images, which can be de-identified for research purposes, are available for access by these researchers. A review of major papers published from 2010-2021 describing novel radiographic comparison methods provides an encouraging view of the present and future use of radiography in forensic identifi-cation.
Keywords: forensic; identification; radiography