Dr Shakir Khan
Dr. Shakir Khan is Ph.D. in Computer Science presently working as associate professor in college of computer and information sciences (CCIS), Imam Mohammad Ibn Saud Islamic University (IMSIU), and Riyadh, Saudi Arabia. He has 15+ years of rich national and international teaching, research and IT experience, including five years in King Saud University for research, training and teaching, Riyadh, Saudi Arabia. He has sound research knowledge along with supervision of more than a dozen master scholars in different fields of Computer Science. He has published more than 70 publications in reputed journals, conferences, 47 of them are SCI-indexed, and latest publication can be checked on Google Scholar. He has also published two books and three patents. He contributed in many International Journals and Conferences as Editor, Member of the Advisory board, Reviewer, Program Committee Member, and Keynote Speaker. His research interest includes Data Mining, Data Science, AI, Cloud Computing, IoT, Big Data & Analytics, Bioinformatics, E-learning, Machine Learning and Deep Learning. He has been acknowledged by Imam University and received research excellence award in 2019 and received as leader for a programming team in Prince Sultan University, Riyadh as the team was third winner out of 40 national teams from different Saudi universities. He has been awarded three-research grant from Deanship of Scientific Research, Imam University and one from ministry of education, Saudi Arabia. One grant is awarded as PI for International Research Partnership Program with one of the computer science professor in Aligarh Muslim University (AMU), India. Dr. Khan is delivering these projects timely and he is also doing collaborative research with the University of Electronic Science and Technology China (UESTC), and other professors globally.
less
InterestsView All (15)
Uploads
Papers by Dr Shakir Khan
healthcare is also broadly unified with the Internet of +ings to develop an industrial forthcoming system. Utilizing this type of
system can be facilitating optimum patient monitoring, competent diagnosis, intensive care, and including the appropriate
operation against the existing critical diseases. Due to enormous data theft or privacy leakage, security, and privacy towards
patient-based informative data, the preservation of personal patients’ informative data has now become a necessity in the digitized
community. +e produced article is underlined on handsomely monitoring, perceptively extracted keyframe, and further
processed lightweight cosine functions using hybrid way chaotic map keyframe image encryption. Initially, a regular concept of
extracted keyframe is deployed to salvage meaningful detected frames by transmitting an alert autonomously to the administration.
+en, lightweight cosine function for encryption is employed. +is encryption incorporates keyframe exceedingly secure
and safe from the outside world or any adversary. Our proposed methodology validates effectiveness throughout the IIoT
ecosystem. +e produced outcome is highly acceptable and has minimum execution time, robustness, and reasonably adopted
cost-effective, secure parameter than any other (keyframes) image encryption methods. Furthermore, this methodology has
optimally reduced bandwidth, essential communicating price, transmission cost, storage, and immediately judicious analysis of
each occurred activity from the outside world or any adversary to remain secure and confident about the real patient-based data in
the smartly developed environment.
inventory request. During the procedure of analyzing the colorful ways and variables to remember, we
plant that approaches similar as Random woodland, machine help Vector were not absolutely exploited.
On this composition, we will introduce and assessment a in addition practicable gadget to prognosticate
the motion of shares with lesser delicacy. The first issue we looked at turned into the previous time’s
stock price dataset. The dataset has been preprocessed and refined for actual analysis. For this reason,
our composition can even focus on preprocessing the raw data of the dataset. 2nd, after preprocessing
the facts, we are able to observe the use of the arbitrary wood, we can aid the vector machine on the dataset
and the results it generates. Similarly, the proposed composition examines the use of the soothsaying
device in actual surrounds and the problems related to the delicacy of the overall values handed. The
composition additionally provides a system literacy version for prognosticating the lifestyles of shares
in a aggressive request. Predicting the success of shares might be a main asset for stock request institutions
and could give actual effects to the troubles facing equity investors. By Using Stock Prediction algorithm
overall accuracy is 80.3%.
healthcare is also broadly unified with the Internet of +ings to develop an industrial forthcoming system. Utilizing this type of
system can be facilitating optimum patient monitoring, competent diagnosis, intensive care, and including the appropriate
operation against the existing critical diseases. Due to enormous data theft or privacy leakage, security, and privacy towards
patient-based informative data, the preservation of personal patients’ informative data has now become a necessity in the digitized
community. +e produced article is underlined on handsomely monitoring, perceptively extracted keyframe, and further
processed lightweight cosine functions using hybrid way chaotic map keyframe image encryption. Initially, a regular concept of
extracted keyframe is deployed to salvage meaningful detected frames by transmitting an alert autonomously to the administration.
+en, lightweight cosine function for encryption is employed. +is encryption incorporates keyframe exceedingly secure
and safe from the outside world or any adversary. Our proposed methodology validates effectiveness throughout the IIoT
ecosystem. +e produced outcome is highly acceptable and has minimum execution time, robustness, and reasonably adopted
cost-effective, secure parameter than any other (keyframes) image encryption methods. Furthermore, this methodology has
optimally reduced bandwidth, essential communicating price, transmission cost, storage, and immediately judicious analysis of
each occurred activity from the outside world or any adversary to remain secure and confident about the real patient-based data in
the smartly developed environment.
inventory request. During the procedure of analyzing the colorful ways and variables to remember, we
plant that approaches similar as Random woodland, machine help Vector were not absolutely exploited.
On this composition, we will introduce and assessment a in addition practicable gadget to prognosticate
the motion of shares with lesser delicacy. The first issue we looked at turned into the previous time’s
stock price dataset. The dataset has been preprocessed and refined for actual analysis. For this reason,
our composition can even focus on preprocessing the raw data of the dataset. 2nd, after preprocessing
the facts, we are able to observe the use of the arbitrary wood, we can aid the vector machine on the dataset
and the results it generates. Similarly, the proposed composition examines the use of the soothsaying
device in actual surrounds and the problems related to the delicacy of the overall values handed. The
composition additionally provides a system literacy version for prognosticating the lifestyles of shares
in a aggressive request. Predicting the success of shares might be a main asset for stock request institutions
and could give actual effects to the troubles facing equity investors. By Using Stock Prediction algorithm
overall accuracy is 80.3%.