Nojood O Aljehane

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research-article
Efficient resource allocation and user association in NOMA-enabled vehicular-aided HetNets with high altitude platforms
- Ali Nauman
  Department of Information and Communication Engineering, Yeungnam University, Republic of Korea
  ,
- Mashael Maashi
  Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Po box 103786, Riyadh 11543, Saudi Arabia
  ,
- Hend K. Alkahtani
  Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
  ,
- Fahd N. Al-Wesabi
  Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia
  ,
- Nojood O. Aljehane
  Department of Computer Science, Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia
  ,
- Mohammed Assiri
  Department of Computer Science, College of Sciences and Humanities- Aflaj, Prince Sattam bin Abdulaziz University, Aflaj 16273, Saudi Arabia
  ,
- Sara Saadeldeen Ibrahim
  Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, AlKharj, Saudi Arabia
  ,
- Wali Ullah Khan
  Interdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, Luxembourg
Computer Communications, Volume 216, Issue C•Feb 2024, pp 374-386 • https://doi.org/10.1016/j.comcom.2024.01.021
Abstract
The increasing demand for massive connectivity and high data rates has made the efficient use of existing spectrum resources an increasingly challenging problem. Non-orthogonal multiple access (NOMA) is a potential solution for future ...
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Multi-step influenza forecasting through singular value decomposition and kernel ridge regression with MARCOS-guided gradient-based optimization
- Guo Hongliang
  College of Information Technology, Jilin Agricultural University, Changchun, 130118, China
  ,
- Zhang Zhiyao
  College of Information Technology, Jilin Agricultural University, Changchun, 130118, China
  ,
- Iman Ahmadianfar
  Information and Communication Technology Research Group, Scientific Research Center, Al-Ayen University, Thi-Qar, Nasiriyah, 64001, Iraq
  ,
- José Escorcia-Gutierrez
  Department of Computational Science and Electronics, Universidad de La Costa, CUC, Barranquilla, 080002, Colombia
  ,
- Nojood O. Aljehane
  Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia, Tabuk University, KSA
  ,
- Chengye Li
  Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China
Computers in Biology and Medicine, Volume 169, Issue C•Feb 2024 • https://doi.org/10.1016/j.compbiomed.2023.107888
Abstract
This research delves into the significance of influenza outbreaks in public health, particularly the importance of accurate forecasts using weekly Influenza-like illness (ILI) rates. The present work develops a novel hybrid machine-learning model ...
Highlights

Developing a hybrid Kernel Ridge regression with singular value decomposition.
MARCOS method is utilized to specify the best model to forecast influenza rate.
HSKRR effectively predicts influenza transmission, forming a robust and ...
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CDRIME-MTIS: An enhanced rime optimization-driven multi-threshold segmentation for COVID-19 X-ray images
- Yupeng Li
  College of Computer Science and Technology, Changchun Normal University, Changchun, Jilin, 130032, China
  ,
- Dong Zhao
  College of Computer Science and Technology, Changchun Normal University, Changchun, Jilin, 130032, China
  ,
- Chao Ma
  School of Digital Media, Shenzhen Institute of Information Technology, Shenzhen, 518172, China
  ,
- José Escorcia-Gutierrez
  Department of Computational Science and Electronics, Universidad de la Costa, CUC, Barranquilla, 080002, Colombia
  ,
- Nojood O. Aljehane
  Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Kingdom of Saudi Arabia
  ,
- Xia Ye
  School of the 1st Clinical Medical Sciences (School of Information and Engineering), Wenzhou Medical University, Wenzhou, 325000, China
Computers in Biology and Medicine, Volume 169, Issue C•Feb 2024 • https://doi.org/10.1016/j.compbiomed.2023.107838
Abstract
To improve the detection of COVID-19, this paper researches and proposes an effective swarm intelligence algorithm-driven multi-threshold image segmentation (MTIS) method. First, this paper proposes a novel RIME structure integrating the Co-...
Highlights

An improved Rime optimization algorithm is proposed, called CDRIME.
A CDRIME-driven multi-threshold segmentation method is proposed, called CDRIME-MTIS.
CDRIME has excellent exploration, exploitation, and convergence capabilities ...
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research-article
Dynamic resource management in integrated NOMA terrestrial–satellite networks using multi-agent reinforcement learning
- Ali Nauman
  Department of Information and Communication Engineering, Yeungnam University, Republic of Korea
  ,
- Haya Mesfer Alshahrani
  Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
  ,
- Nadhem Nemri
  Department of Information Systems, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia
  ,
- Kamal M. Othman
  Department of Electrical Engineering, College of Engineering, Umm Al-Qura University, Makkah, Saudi Arabia
  ,
- Nojood O. Aljehane
  Department of Computer Science, Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia
  ,
- Mashael Maashi
  Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Po Box 103786, Riyadh 11543, Saudi Arabia
  ,
- Ashit Kumar Dutta
  Department of Computer Science and Information System, College of Applied Sciences, AlMaarefa University, Riyadh 11597, Saudi Arabia
  ,
- Mohammed Assiri
  Department of Computer Science, College of Sciences and Humanities- Aflaj, Prince Sattam bin Abdulaziz University, Aflaj 16273, Saudi Arabia
  ,
- Wali Ullah Khan
  Interdisciplinary Center for Security, Reliability and Trust (SnT), University of Luxembourg, 1855 Luxembourg City, Luxembourg
Journal of Network and Computer Applications, Volume 221, Issue C•Jan 2024 • https://doi.org/10.1016/j.jnca.2023.103770
Abstract
The integration of terrestrial and satellite wireless communication networks offers a practical solution to enhance network coverage, connectivity, and cost-effectiveness. Moreover, in today’s interconnected world, connectivity’s reliable and ...
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OCRUN: An oppositional Runge Kutta optimizer with cuckoo search for global optimization and feature selection
- Meilin Zhang
  Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University, Wenzhou 325035, China
  ,
- Huiling Chen
  Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University, Wenzhou 325035, China
  ,
- Ali Asghar Heidari
  Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University, Wenzhou 325035, China
  ,
- Zhennao Cai
  Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University, Wenzhou 325035, China
  ,
- Nojood O. Aljehane
  Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia
  ,
- Romany F. Mansour
  Department of Mathematics, Faculty of Science New Valley University, El-Kharga 72511, Egypt
Applied Soft Computing, Volume 146, Issue C•Oct 2023 • https://doi.org/10.1016/j.asoc.2023.110664
Abstract
The recently proposed swarm intelligence algorithm, Runge–Kutta Optimization (RUN), is rooted in the fourth-order Runge–Kutta method. Compared with its counterparts, RUN boasts an advantage of having a more concrete theoretical ...
Highlights

Oppositional Runge–Kutta Optimizer with Cuckoo Search (OCRUN) for feature selection
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Knowledge discovery for course choice decision in Massive Open Online Courses using machine learning approaches
- Mehrbakhsh Nilashi
  Centre for Global Sustainability Studies (CGSS), Universiti Sains Malaysia, 11800 George Town, Malaysia
  School of Computer Engineering, University of Science and Technology, Tehran, Iran
  UCSI Graduate Business School, UCSI University, No. 1 Jalan Menara Gading, UCSI Heights, Cheras, Kuala Lumpur, 56000, Malaysia
  ,
- Behrouz Minaei-Bidgoli
  School of Computer Engineering, University of Science and Technology, Tehran, Iran
  ,
- Abdullah Alghamdi
  Information Systems Dept, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia
  ,
- Mesfer Alrizq
  Information Systems Department, College of Computer Science and Information Systems, Najran University, Najran, Saudi Arabia
  ,
- Omar Alghamdi
  Business Administration Dept, Applied College, Najran University, Najran, Saudi Arabia
  ,
- Fatima Khan Nayer
  Artificial Intelligence and Data Analytics (AIDA) Research Lab, College of Computer and Information Sciences, Prince Sultan University, Saudi Arabia
  ,
- Nojood O Aljehane
  Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia
  ,
- Arash Khosravi
  Faculty of Engineering, Mahallat Institute of Higher Education, Mahallat, Iran
  ,
- Saidatulakmal Mohd
  Centre for Global Sustainability Studies & School of Social Sciences, Universiti Sains Malaysia, Malaysia
Expert Systems with Applications: An International Journal, Volume 199, Issue C•Aug 2022 • https://doi.org/10.1016/j.eswa.2022.117092
Highlights

A multi-criteria collaborative recommender system is proposed for MOOCs.
Text ...
Abstract
Massive Open Online Courses (MOOCs) provide learners with high-quality and flexible online courses with no limitations regarding time and location. Detecting users’ behavior in MOOCs is an important task for course recommendations. ...
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research-article
An image encryption algorithm based on new generalized fusion fractal structure
- Musheer Ahmad
  Department of Computer Engineering, Jamia Millia Islamia, New Delhi 110025, India
  ,
- Shafali Agarwal
  Researcher, 9600 Coit Road, Plano, TX 75025, USA
  ,
- Ahmed Alkhayyat
  Department of Computer Technical Engineering, College of Technical Engineering, The Islamic University, Najaf 54001, Iraq
  ,
- Adi Alhudhaif
  Department of Computer Science, College of Computer Engineering and Sciences in Al-kharj, Prince Sattam Bin Abdulaziz University, P.O. Box 151, Al-Kharj 11942, Saudi Arabia
  ,
- Fayadh Alenezi
  Department of Electrical Engineering, College of Engineering, Jouf University, Saudi Arabia
  ,
- Amjad Hussain Zahid
  Department of Informatics and Systems, University of Management and Technology, Lahore 54700, Pakistan
  ,
- Nojood O. Aljehane
  Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia
Information Sciences: an International Journal, Volume 592, Issue C•May 2022, pp 1-20 • https://doi.org/10.1016/j.ins.2022.01.042
Highlights

A new generalized fusion fractal PLFF structure is proposed.
Image cryptosystem ...
Abstract
The design and utilization of suitable fractal structures is one of the prominent areas of security for the protection of digital data. This paper proposes a generalized fusion fractal structure by combining two one-dimensional ...
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Eye State Identification Utilizing EEG Signals: A Combined Method Using Self-Organizing Map and Deep Belief Network
- Sheng Bin,
- Neda Ahmadi
  Communications and Intelligent Systems GroupSchool of Physics, Engineering and Computer ScienceUniversity of HertfordshireHatfieldUKherts.ac.uk
  ,
- Mehrbakhsh Nilashi
  Centre for Global Sustainability Studies (CGSS)Universiti Sains Malaysia (USM)Penang 11800Malaysiausm.my
  Department of Computer EngineeringIran University of Science and TechnologyTehranIraniust.ac.ir
  ,
- Behrouz Minaei-Bidgoli
  Department of Computer EngineeringIran University of Science and TechnologyTehranIraniust.ac.ir
  ,
- Murtaza Farooque
  Department of MISDhofar UniversitySalalahOmandu.edu.om
  ,
- Sarminah Samad
  Department of Business AdministrationCollege of Business and AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabiapnu.edu.sa
  ,
- Nojood O. Aljehane
  Faculty of Computers and Information TechnologyUniversity of TabukTabukSaudi Arabiaut.edu.sa
  ,
- Waleed Abdu Zogaan
  Department of Computer ScienceFaculty of Computer Science and Information TechnologyJazan UniversityJazan 45142Saudi Arabiajazanu.edu.sa
  ,
- Hossein Ahmadi
  Centre for Health TechnologyFaculty of HealthUniversity of PlymouthPlymouth PL4 8AAUKplymouth.ac.uk
Scientific Programming, Volume 2022•2022 • https://doi.org/10.1155/2022/4439189
Measuring brain activity through Electroencephalogram (EEG) analysis for eye state prediction has attracted attention from machine learning researchers. There have been many methods for EEG analysis using supervised and unsupervised machine learning ...
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An optimal segmentation with deep learning based inception network model for intracranial hemorrhage diagnosis
- Romany F. Mansour
  Department of Mathematics, Faculty of Science, New Valley University, 72511, El-Kharga, Egypt
  ,
- Nojood O. Aljehane
  College of Computer Science and Information Technology, Tabuk University, Tabuk, Saudi Arabia
Neural Computing and Applications, Volume 33, Issue 20•Oct 2021, pp 13831-13843 • https://doi.org/10.1007/s00521-021-06020-8
Abstract
Traumatic Brain Injury (TBI) leads to intracranial hemorrhages (ICH), which is a severe illness resulted in death if it is not properly diagnosed and treated in the earlier stage. Presently, computer tomography (CT) images are widely used by ...
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A self-embedding technique for tamper detection and localization of medical images for smart-health
- Solihah Gull
  Post Graduate Department of Electronics and Instrumentation Technology, University of Kashmir, 190006, Srinagar, JK, India
  ,
- Romany F. Mansour
  Faculty of Science, New Valley University, 72511, El-Kharja, Egypt
  ,
- Nojood O. Aljehane
  Computer Science and Information Department Tabuk University, KSA, Tabuk, Saudi Arabia
  ,
- Shabir A. Parah
  Post Graduate Department of Electronics and Instrumentation Technology, University of Kashmir, 190006, Srinagar, JK, India
Multimedia Tools and Applications, Volume 80, Issue 19•Aug 2021, pp 29939-29964 • https://doi.org/10.1007/s11042-021-11170-x
Abstract
With the prodigious headway of the Internet of Things (IoT), cloud computing, Artificial Intelligence (AI), and big data, smart healthcare is expected to provide potential and competent healthcare services. Smart healthcare is changing the ...
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Doctoral Theses
Grammar-Based Preprocessing for PPM Compression and Classification
- Nojood Aljehane
  Bangor University (United Kingdom)
  ,
- Teahan, William J
  Bangor University (United Kingdom)
Abstract
The aim of this study is to investigate the efficiency of novel methods using context-free grammars and Prediction by Partial Matching (PPM) in order to build and evaluate the quality of compression models for text files such as English, Arabic, ...
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Author Profile Pages

Description: The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM bibliographic database, the Guide. Coverage of ACM publications is comprehensive from the 1950's. Coverage of other publishers generally starts in the mid 1980's. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community.
Please see the following 2007 Turing Award winners' profiles as examples:
History: Disambiguation of author names is of course required for precise identification of all the works, and only those works, by a unique individual. Of equal importance to ACM, author name normalization is also one critical prerequisite to building accurate citation and download statistics. For the past several years, ACM has worked to normalize author names, expand reference capture, and gather detailed usage statistics, all intended to provide the community with a robust set of publication metrics. The Author Profile Pages reveal the first result of these efforts.
Normalization: ACM uses normalization algorithms to weigh several types of evidence for merging and splitting names.
These include:
- co-authors: if we have two names and cannot disambiguate them based on name alone, then we see if they have a co-author in common. If so, this weighs towards the two names being the same person.
- affiliations: names in common with same affiliation weighs toward the two names being the same person.
- publication title: names in common whose works are published in same journal weighs toward the two names being the same person.
- keywords: names in common whose works address the same subject matter as determined from title and keywords, weigh toward being the same person.
The more conservative the merging algorithms, the more bits of evidence are required before a merge is made, resulting in greater precision but lower recall of works for a given Author Profile. Many bibliographic records have only author initials. Many names lack affiliations. With very common family names, typical in Asia, more liberal algorithms result in mistaken merges.

Automatic normalization of author names is not exact. Hence it is clear that manual intervention based on human knowledge is required to perfect algorithmic results. ACM is meeting this challenge, continuing to work to improve the automated merges by tweaking the weighting of the evidence in light of experience.
Bibliometrics: In 1926, Alfred Lotka formulated his power law (known as Lotka's Law) describing the frequency of publication by authors in a given field. According to this bibliometric law of scientific productivity, only a very small percentage (~6%) of authors in a field will produce more than 10 articles while the majority (perhaps 60%) will have but a single article published. With ACM's first cut at author name normalization in place, the distribution of our authors with 1, 2, 3..n publications does not match Lotka's Law precisely, but neither is the distribution curve far off. For a definition of ACM's first set of publication statistics, see Bibliometrics
Future Direction: The initial release of the Author Edit Screen is open to anyone in the community with an ACM account, but it is limited to personal information. An author's photograph, a Home Page URL, and an email may be added, deleted or edited. Changes are reviewed before they are made available on the live site.
ACM will expand this edit facility to accommodate more types of data and facilitate ease of community participation with appropriate safeguards. In particular, authors or members of the community will be able to indicate works in their profile that do not belong there and merge others that do belong but are currently missing.

A direct search interface for Author Profiles will be built.

An institutional view of works emerging from their faculty and researchers will be provided along with a relevant set of metrics.

It is possible, too, that the Author Profile page may evolve to allow interested authors to upload unpublished professional materials to an area available for search and free educational use, but distinct from the ACM Digital Library proper. It is hard to predict what shape such an area for user-generated content may take, but it carries interesting potential for input from the community.

Bibliometrics

The ACM DL is a comprehensive repository of publications from the entire field of computing.

It is ACM's intention to make the derivation of any publication statistics it generates clear to the user.

Average citations per article = The total Citation Count divided by the total Publication Count.
Citation Count = cumulative total number of times all authored works by this author were cited by other works within ACM's bibliographic database. Almost all reference lists in articles published by ACM have been captured. References lists from other publishers are less well-represented in the database. Unresolved references are not included in the Citation Count. The Citation Count is citations TO any type of work, but the references counted are only FROM journal and proceedings articles. Reference lists from books, dissertations, and technical reports have not generally been captured in the database. (Citation Counts for individual works are displayed with the individual record listed on the Author Page.)
Publication Count = all works of any genre within the universe of ACM's bibliographic database of computing literature of which this person was an author. Works where the person has role as editor, advisor, chair, etc. are listed on the page but are not part of the Publication Count.
Publication Years = the span from the earliest year of publication on a work by this author to the most recent year of publication of a work by this author captured within the ACM bibliographic database of computing literature (The ACM Guide to Computing Literature, also known as "the Guide".
Available for download = the total number of works by this author whose full texts may be downloaded from an ACM full-text article server. Downloads from external full-text sources linked to from within the ACM bibliographic space are not counted as 'available for download'.
Average downloads per article = The total number of cumulative downloads divided by the number of articles (including multimedia objects) available for download from ACM's servers.
Downloads (cumulative) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server since the downloads were first counted in May 2003. The counts displayed are updated monthly and are therefore 0-31 days behind the current date. Robotic activity is scrubbed from the download statistics.
Downloads (12 months) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 12-month period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (12-month download counts for individual works are displayed with the individual record.)
Downloads (6 weeks) = The cumulative number of times all works by this author have been downloaded from an ACM full-text article server over the last 6-week period for which statistics are available. The counts displayed are usually 1-2 weeks behind the current date. (6-week download counts for individual works are displayed with the individual record.)

ACM Author-Izer Service

Summary Description

ACM Author-Izer is a unique service that enables ACM authors to generate and post links on both their homepage and institutional repository for visitors to download the definitive version of their articles from the ACM Digital Library at no charge.

Downloads from these sites are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to definitive version of ACM articles should reduce user confusion over article versioning.

ACM Author-Izer also extends ACM’s reputation as an innovative “Green Path” publisher, making ACM one of the first publishers of scholarly works to offer this model to its authors.

To access ACM Author-Izer, authors need to establish a free ACM web account. Should authors change institutions or sites, they can utilize the new ACM service to disable old links and re-authorize new links for free downloads from a different site.

How ACM Author-Izer Works

Authors may post ACM Author-Izer links in their own bibliographies maintained on their website and their own institution’s repository. The links take visitors to your page directly to the definitive version of individual articles inside the ACM Digital Library to download these articles for free.

The Service can be applied to all the articles you have ever published with ACM.

Depending on your previous activities within the ACM DL, you may need to take up to three steps to use ACM Author-Izer.

For authors who do not have a free ACM Web Account:

Go to the ACM DL http://dl.acm.org/ and click SIGN UP. Once your account is established, proceed to next step.

For authors who have an ACM web account, but have not edited their ACM Author Profile page:

Sign in to your ACM web account and go to your Author Profile page. Click "Add personal information" and add photograph, homepage address, etc. Click ADD AUTHOR INFORMATION to submit change. Once you receive email notification that your changes were accepted, you may utilize ACM Author-izer.

For authors who have an account and have already edited their Profile Page:

Sign in to your ACM web account, go to your Author Profile page in the Digital Library, look for the ACM Author-izer link below each ACM published article, and begin the authorization process. If you have published many ACM articles, you may find a batch Authorization process useful. It is labeled: "Export as: ACM Author-Izer Service"

ACM Author-Izer also provides code snippets for authors to display download and citation statistics for each “authorized” article on their personal pages. Downloads from these pages are captured in official ACM statistics, improving the accuracy of usage and impact measurements. Consistently linking to the definitive version of ACM articles should reduce user confusion over article versioning.

Note: You still retain the right to post your author-prepared preprint versions on your home pages and in your institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library. But any download of your preprint versions will not be counted in ACM usage statistics. If you use these AUTHOR-IZER links instead, usage by visitors to your page will be recorded in the ACM Digital Library and displayed on your page.

FAQ

Q. What is ACM Author-Izer?
A. ACM Author-Izer is a unique, link-based, self-archiving service that enables ACM authors to generate and post links on either their home page or institutional repository for visitors to download the definitive version of their articles for free.
Q. What articles are eligible for ACM Author-Izer?
A. ACM Author-Izer can be applied to all the articles authors have ever published with ACM. It is also available to authors who will have articles published in ACM publications in the future.

Q. Are there any restrictions on authors to use this service?
A. No. An author does not need to subscribe to the ACM Digital Library nor even be a member of ACM.

Q. What are the requirements to use this service?
A. To access ACM Author-Izer, authors need to have a free ACM web account, must have an ACM Author Profile page in the Digital Library, and must take ownership of their Author Profile page.

Q. What is an ACM Author Profile Page?
A. The Author Profile Page initially collects all the professional information known about authors from the publications record as known by the ACM Digital Library. The Author Profile Page supplies a quick snapshot of an author's contribution to the field and some rudimentary measures of influence upon it. Over time, the contents of the Author Profile page may expand at the direction of the community. Please visit the ACM Author Profile documentation page for more background information on these pages.

Q. How do I find my Author Profile page and take ownership?
A. You will need to take the following steps:
- Create a free ACM Web Account
- Sign-In to the ACM Digital Library
- Find your Author Profile Page by searching the ACM Digital Library for your name
- Find the result you authored (where your author name is a clickable link)
- Click on your name to go to the Author Profile Page
- Click the "Add Personal Information" link on the Author Profile Page
- Wait for ACM review and approval; generally less than 24 hours

Q. Why does my photo not appear?
A. Make sure that the image you submit is in .jpg or .gif format and that the file name does not contain special characters

Q. What if I cannot find the Add Personal Information function on my author page?
A. The ACM account linked to your profile page is different than the one you are logged into. Please logout and login to the account associated with your Author Profile Page.

Q. What happens if an author changes the location of his bibliography or moves to a new institution?
A. Should authors change institutions or sites, they can utilize ACM Author-Izer to disable old links and re-authorize new links for free downloads from a new location.

Q. What happens if an author provides a URL that redirects to the author’s personal bibliography page?
A. The service will not provide a free download from the ACM Digital Library. Instead the person who uses that link will simply go to the Citation Page for that article in the ACM Digital Library where the article may be accessed under the usual subscription rules.

However, if the author provides the target page URL, any link that redirects to that target page will enable a free download from the Service.

Q. What happens if the author’s bibliography lives on a page with several aliases?
A. Only one alias will work, whichever one is registered as the page containing the author’s bibliography. ACM has no technical solution to this problem at this time.

Q. Why should authors use ACM Author-Izer?
A. ACM Author-Izer lets visitors to authors’ personal home pages download articles for no charge from the ACM Digital Library. It allows authors to dynamically display real-time download and citation statistics for each “authorized” article on their personal site.

Q. Does ACM Author-Izer provide benefits for authors?
A. Downloads of definitive articles via Author-Izer links on the authors’ personal web page are captured in official ACM statistics to more accurately reflect usage and impact measurements.

Authors who do not use ACM Author-Izer links will not have downloads from their local, personal bibliographies counted. They do, however, retain the existing right to post author-prepared preprint versions on their home pages or institutional repositories with DOI pointers to the definitive version permanently maintained in the ACM Digital Library.

Q. How does ACM Author-Izer benefit the computing community?
A. ACM Author-Izer expands the visibility and dissemination of the definitive version of ACM articles. It is based on ACM’s strong belief that the computing community should have the widest possible access to the definitive versions of scholarly literature. By linking authors’ personal bibliography with the ACM Digital Library, user confusion over article versioning should be reduced over time.

In making ACM Author-Izer a free service to both authors and visitors to their websites, ACM is emphasizing its continuing commitment to the interests of its authors and to the computing community in ways that are consistent with its existing subscription-based access model.

Q. How do authors access ACM Author-Izer?
A. See How to Use

Q. Why can’t I find my most recent publication in my ACM Author Profile Page?
A. There is a time delay between publication and the process which associates that publication with an Author Profile Page. Right now, that process usually takes 4-8 weeks.

Q. How does ACM Author-Izer expand ACM’s “Green Path” Access Policies?
A. ACM Author-Izer extends the rights and permissions that authors retain even after copyright transfer to ACM, which has been among the “greenest” publishers. ACM enables its author community to retain a wide range of rights related to copyright and reuse of materials. They include:
- Posting rights that ensure free access to their work outside the ACM Digital Library and print publications
- Rights to reuse any portion of their work in new works that they may create
- Copyright to artistic images in ACM’s graphics-oriented publications that authors may want to exploit in commercial contexts
- All patent rights, which remain with the original owner