- data mining and Big data analytics in science and engineering, Information Flow, Machine Learning, Data Mining, Aritificial Intelligence, Non Functional Requirement, and 9 moreTask analysis, Decision making process, Big Data, Farm management, E-learning, Open Source and Free Software Studies, Website Development, Web 2.0, and Web Development - HTML & CSSedit
- Dr. Shakir Khan is Ph.D. in Computer Science presently working as associate professor in college of computer and info... moreDr. 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.edit
With the rapid development of mobile medical care, medical institutions also have the hidden danger of privacy leakage while sharing personal medical data. Based on the k-anonymity and l-diversity supervised models, it is proposed to use... more
With the rapid development of mobile medical care, medical institutions also have the hidden danger of privacy leakage while sharing personal medical data. Based on the k-anonymity and l-diversity supervised models, it is proposed to use the classified personalized entropy l-diversity privacy protection model to protect user privacy in a fine-grained manner. By distinguishing solid and weak sensitive attribute values, the constraints on sensitive attributes are improved, and the sensitive information is reduced for the leakage probability of vital information to achieve the safety of medical data sharing. This research offers a customized information entropy l-diversity model and performs experiments to tackle the issues that the information entropy l-diversity model does not discriminate between strong and weak sensitive features. Data analysis and experimental results show that this method can minimize execution time while improving data accuracy and service quality, which is more...
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Our aim was to assess sleep quality in different subgroups of preclinical medical students, and then to identify specific lifestyle factors, academic and social factors as well as Corona virus related factors that were associated with... more
Our aim was to assess sleep quality in different subgroups of preclinical medical students, and then to identify specific lifestyle factors, academic and social factors as well as Corona virus related factors that were associated with poor sleeping quality and poor psychological health. Study participants were all medical students at King Saud University of Medical Sciences in the first and second years (648 students), and the study was conducted from December 2021 to January 2022. We administered the survey on paper as well as online. We used three types of questionnaires in this study. The first was a self-administered questionnaire, the second was a validated Insomnia Severity Index (ISI) for finding sleeping problems, and the third was a validated DASS 10 for determining Depression, Anxiety, and Stress. A total of 361 pre-clinical medical students consisted of 146 (40.4%) males and 215 (59.5%) females. The majority of the students, 246 (68.1%), were in their second year. Further...
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A fuzzy cloud resource scheduling model with time-cost constraints is built using fuzzy triangular numbers to represent uncertain task execution time. Task scheduling reduces total time and cost spent on a project. It connects virtual... more
A fuzzy cloud resource scheduling model with time-cost constraints is built using fuzzy triangular numbers to represent uncertain task execution time. Task scheduling reduces total time and cost spent on a project. It connects virtual machines and functions. Particle swarm optimization (HPO) is used to plan cloud resources (HSOA). The approach uses orthogonal particle swarm initialization to increase the quality of the initial particle exploration, rerandomization to regulate the particle search range, and real-time updating of inertia weights to control particle speed. The suggested problem model and optimization approach are evaluated using random simulation data provided by the CloudSim simulation platform. Less overall execution time and a lower cost are shown to have fast convergence and solution capabilities in experiments.
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The rapid growth and availability of social networking websites have changed the medical students approach to learn and manage the information about their academic, personal and professional lives. The aim of this study was to evaluate... more
The rapid growth and availability of social networking websites have changed the medical students approach to learn and manage the information about their academic, personal and professional lives. The aim of this study was to evaluate the medical student’s opinion on the using of social networking sites and learning and development of medical information. Self-administered, paper based questionnaire survey was conducted in the Department of Medical Education, College of Medicine, King Saud University, Riyadh, Saudi Arabia. 647 questionnaires were distributed among the first and second year male and female medical students. 432 (66.76%) of the students completed the questionnaire 246 (56.94%) were males and 186 (43.05%) were females. The questionnaire items on the students’ perception were about the social networking sites (SNSs) usage and its positive and negative impacts. Among 432 medical students 312 (72.2%) students showed that social networking sites are the necessity of the e...
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Research Interests:
Abstract: Cloud computing is rising speedily with applications in approximately any area, together with pharmaceutical education. E-learning systems generally need several hardware and software resources. There are a lot of educational... more
Abstract: Cloud computing is rising speedily with applications in approximately any area, together with pharmaceutical education. E-learning systems generally need several hardware and software resources. There are a lot of educational institutions that cannot have the funds for such investments and cloud computing is the most excellent answer for this. This paper provides the optimistic impact of using cloud computing architectures based on e-learning system development. It spotlights on the payback of cloud computing for e-learning solutions and the e-learning development organization confronts when this architecture is utilized.
Higher education policies are designed to facilitate students' learning progression and academic success. Following Tinto's integration theory and Bean's attrition model, this study proposes a research model to investigate whether... more
Higher education policies are designed to facilitate students' learning progression and academic success. Following Tinto's integration theory and Bean's attrition model, this study proposes a research model to investigate whether students prone to attrition can be pre-emptively identified through self-evaluating academic factors contributing to their learning progress. Theoretically, the learning progress is identified with student success, represented by factors amenable to intervention including the interaction with peers and instructors, teaching effectiveness, exam scores, absenteeism, students' effort, and academic course-related variables. An exploratory and confirmatory factor analysis of 530 undergraduate students revealed that the indicators of learning progress in such students were channeled into two constructs. The results indicated that the teacher effectiveness and learning materials contributed most to the learning progress. Structural equation modelling revealed that the learning progress variables have a significant impact on students' attrition status. A multi-group analysis confirmed the academic semesters to be a moderator in the mediating effects of the students' grade point average (GPA). This model functions as a framework to design a student-oriented learning system promoting students' learning experience and academic success.
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Detecting brain cancer at its early stages is a tremendous 9 medical problem, and many researchers have proposed var-10 ious diagnostic systems; however, these systems still do 11 not effectively detect brain cancer. To address this... more
Detecting brain cancer at its early stages is a tremendous 9 medical problem, and many researchers have proposed var-10 ious diagnostic systems; however, these systems still do 11 not effectively detect brain cancer. To address this issue, 12 we proposed an automatic diagnosing framework that will 13 assist medical experts in diagnosing brain cancer and en-14 suring proper treatment. In developing the proposed inte-15 grated framework, we first integrated a Convolutional Neu-16 ral Networks model to extract deep features from Magnetic 17 resonance imaging. The extracted features are forwarded 18 to a Long Short Term Memory model, which performs the 19 final classification. Augmentation techniques were applied 20 to increase the data size, thereby boosting the performance 21 of our model. We used the hold-out Cross-validation tech-22 nique for training and validating our method. In addition, we 23 used various metrics to evaluate the proposed model. The 24 results obtained from the experiments show that our model 25
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Purpose: When a website or application is designed and deployed rapidly as a response to an urgent need, it may not satisfy users. Therefore, we decided to investigate users' attitudes and (dis)satisfaction towards the UX of the Madrasati... more
Purpose: When a website or application is designed and deployed rapidly as a response to an urgent need, it may not satisfy users. Therefore, we decided to investigate users' attitudes and (dis)satisfaction towards the UX of the Madrasati platform, an e-learning system that was developed by the Saudi Ministry of Education as an alternative to traditional learning during the COVID-19 crisis. Method: The study utilizes Twitter to collect a large volume of data (177,358 tweets) related to Madrasati. Two relevant hashtags #Madrasati )#مدرستي( and #Minaset Madrasati مدرستي( )#منصة were used to collect data within the first two months after the launch of the platform. The two-month period was split into four phases: Pre-Semester Phase, Familiarization Phase, Interaction Phase, and Use Phase. The Microsoft Product Reaction Cards (MPRC) tool was implemented to judge user satisfaction/dissatisfaction. Results: The findings show a sudden dissatisfaction about the platform upon launch, but a gradual increase in positive UX over time. Various categories of negative UX (e.g., errors, user denial, and speed issues) gradually became less and less over the observed two months. More importantly, the results show how big data from Twitter can be used for analyzing the UX of a new product. Conclusion: UX is not static; it can change positively over time as users gain more experience with the system.
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The technological progression is raised as a hybrid ecosystem with the industrial Internet of Things (IIoT). Among them, healthcare is also broadly unified with the Internet of Things to develop an industrial forthcoming system. Utilizing... more
The technological progression is raised as a hybrid ecosystem with the industrial Internet of Things (IIoT). Among them, healthcare is also broadly unified with the Internet of Things 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. The 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 admini...
Research Interests:
Research Interests:
Biomedical researchers and biologists often search a large amount of literature to find the relationship between biological entities, such as drug-drug and compound-protein. With the proliferation of medical literature and the development... more
Biomedical researchers and biologists often search a large amount of literature to find the relationship between biological entities, such as drug-drug and compound-protein. With the proliferation of medical literature and the development of deep learning, the automatic extraction of biological entity interaction relationships from literature has shown great potential. The fundamental scope of this research is that the approach described in this research uses technologies like dynamic word vectors and multichannel convolution to learn a larger variety of relational expression semantics, allowing it to detect more entity connections. The extraction of biological entity relationships is the foundation for achieving intelligent medical care, which may increase the effectiveness of intelligent medical question answering and enhance the development of precision healthcare. In the past, deep learning methods have achieved specific results, but there are the following problems: the model u...
Research Interests:
— Cloud computing is basically altering the expectation for how and when computing, storage and networking assets should be allocated, managed and devoted. End-users are progressively more sensitive in response time of services they... more
— Cloud computing is basically altering the expectation for how and when computing, storage and networking assets should be allocated, managed and devoted. End-users are progressively more sensitive in response time of services they ingest. Service Developers wish for the Service Providers to make sure or give the ability for dynamically assigning and managing resources in respond to alter the demand patterns in real-time. Ultimately, Service Providers are under anxiety to build their infrastructure to facilitate real-time end-to-end visibility and energetic resource management with well grained control to decrease total cost of tenure for improving quickness. What is required to rethink of the underlying operating system and management infrastructure to put up the on-going renovation of data centre from the traditional server-centric architecture model to a cloud or network centric model? This paper projects and describes a indication model for a network centric data centre infrast...
Biomedical researchers and biologists often search a large amount of literature to find the relationship between biological entities, such as drug-drug and compound-protein. With the proliferation of medical literature and the development... more
Biomedical researchers and biologists often search a large amount of literature to find the relationship between biological entities, such as drug-drug and compound-protein. With the proliferation of medical literature and the development of deep learning, the automatic extraction of biological entity interaction relationships from literature has shown great potential. The fundamental scope of this research is that the approach described in this research uses technologies like dynamic word vectors and multichannel convolution to learn a larger variety of relational expression semantics, allowing it to detect more entity connections. The extraction of biological entity relationships is the foundation for achieving intelligent medical care, which may increase the effectiveness of intelligent medical question answering and enhance the development of precision healthcare. In the past, deep learning methods have achieved specific results, but there are the following problems: the model uses static word vectors, which cannot distinguish polysemy; the weight of words is not considered, and the extraction effect of long sentences is poor; the integration of various models can improve the sample imbalance problem, the model is more complex. The purpose of this work is to create a global approach for eliminating different physical entity links, such that the model can effectively extract the interpretation of the expression relationship without having to develop characteristics manually. To this end, a deep multichannel CNN model (MC-CNN) based on the residual structure is proposed, generating dynamic word vectors through BERT (Bidirectional Encoder Representation from Transformers) to improve the accuracy of lexical semantic representation and uses multihead attention to capture the dependencies of long sentences and by designing the Ranking loss function to replace the multimodel ensemble to reduce the impact of sample imbalance. Tested on multiple datasets, the results show that the proposed method has good performance.
Research Interests:
+e technological progression is raised as a hybrid ecosystem with the industrial Internet of +ings (IIoT). Among them, healthcare is also broadly unified with the Internet of +ings to develop an industrial forthcoming system. Utilizing... more
+e technological progression is raised as a hybrid ecosystem with the industrial Internet of +ings (IIoT). Among them,
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.
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.
Research Interests:
The World Health Organization (WHO) reported the COVID-19 epidemic a global health emergency on January 30 and confirmed its transformation into a pandemic on March 11. China has been the hardest hit since the virus's outbreak, which... more
The World Health Organization (WHO) reported the COVID-19 epidemic a global health emergency on January 30 and confirmed its transformation into a pandemic on March 11. China has been the hardest hit since the virus's outbreak, which may date back to late November. Saudi Arabia realized the danger of the Coronavirus in March 2020, took the initiative to take a set of pre-emptive decisions that preceded many countries of the world, and worked to harness all capabilities to confront the outbreak of the epidemic. Several researchers are currently using various mathematical and machine learning-based prediction models to estimate this pandemic's future trend. In this work, the SEIR model was applied to predict the epidemic situation in Saudi Arabia and evaluate the effectiveness of some epidemic control measures, and finally, providing some advice on preventive measures.
Research Interests:
Data visualization is graph representation of data. It produces interactive graphs that explain the relationships among the data to viewers of the graph. The aim of data visualization is to communicate data value clearly and effectively... more
Data visualization is graph representation of data. It produces interactive graphs that explain the relationships among the data to viewers of the graph. The aim of data visualization is to communicate data value clearly and effectively through graphs [1]. Here we take the advantage of data visualization to explore the countries dataset to provide a holistic and interpretive view about the world. In addition to examine some hypotheses about gross domestic product (GDP) and Literacy and more of the countries effects on different factors showing on the dataset such as the literacy and the migration.
The main perfect of this composition is to discover the stylish version to prognosticate the cost of the inventory request. During the procedure of analyzing the colorful ways and variables to remember, we plant that approaches similar... more
The main perfect of this composition is to discover the stylish version to prognosticate the cost of the
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%.
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%.
Research Interests:
Research Interests:
The World Health Organization (WHO) reported the COVID-19 epidemic a global health emergency on January 30 and confirmed its transformation into a pandemic on March 11. China has been the hardest hit since the virus's outbreak, which... more
The World Health Organization (WHO) reported the COVID-19 epidemic a global health emergency on January 30 and confirmed its transformation into a pandemic on March 11. China has been the hardest hit since the virus's outbreak, which may date back to late November. Saudi Arabia realized the danger of the Coronavirus in March 2020, took the initiative to take a set of pre-emptive decisions that preceded many countries of the world, and worked to harness all capabilities to confront the outbreak of the epidemic. Several researchers are currently using various mathematical and machine learning-based prediction models to estimate this pandemic's future trend. In this work, the SEIR model was applied to predict the epidemic situation in Saudi Arabia and evaluate the effectiveness of some epidemic control measures, and finally, providing some advice on preventive measures.
Research Interests:
Research Interests:
— Cloud computing is basically altering the expectation for how and when computing, storage and networking assets should be allocated, managed and devoted. End-users are progressively more sensitive in response time of services they... more
— Cloud computing is basically altering the expectation for how and when computing, storage and networking assets should be allocated, managed and devoted. End-users are progressively more sensitive in response time of services they ingest. Service Developers wish for the Service Providers to make sure or give the ability for dynamically assigning and managing resources in respond to alter the demand patterns in real-time. Ultimately, Service Providers are under anxiety to build their infrastructure to facilitate real-time end-to-end visibility and energetic resource management with well grained control to decrease total cost of tenure for improving quickness. What is required to rethink of the underlying operating system and management infrastructure to put up the on-going renovation of data centre from the traditional server-centric architecture model to a cloud or network centric model? This paper projects and describes a indication model for a network centric data centre infrast...
2 Abstract: A Student Response System (SRS), frequently referred to as a ''clicker,'' and it facilitates students to individually respond instructors questions on immediate basis with individual mobile devices. The system... more
2 Abstract: A Student Response System (SRS), frequently referred to as a ''clicker,'' and it facilitates students to individually respond instructors questions on immediate basis with individual mobile devices. The system also displays the collective responses as feedback to the class at the instructor's judgment. The responses can also be provided by the students online by opening the link forwarded by instructors through SMS and all these responses are recorded into the database and a graphical report is prepared based on these responses received from the students. While SRSs have been used in teaching for some time, we recognize the adoption rate in phamaconosy classes as still being reasonably low. This paper is a ''how to'' and ''why'' guide for phamaconosy faculty who are taking into consideration using SRSs and for skilled users who look for refining or expanding their SRS use. We briefly do analysis key features of present ...
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Virtualization technology in the form of cloud computing is on progressive deployment as more companies adopt it. The innovative technology and its adoption, however, have something in common: reducing challenges associated with managing... more
Virtualization technology in the form of cloud computing is on progressive deployment as more companies adopt it. The innovative technology and its adoption, however, have something in common: reducing challenges associated with managing the operations of conventional in-house systems in firms. This is because, in the conventional form of computing, companies require dedicated IT resources to manage all systems (Networks, Hardware, Software, and IT Services). However, with cloud networking, the cloud network provider thereby offloading internal IT workers to focus on other useful IT functions handles the work of network operations and management. The benefits of using cloud networking cannot be overstated. They include improved security, productivity, scalability, mobility, cost management, and system updating among others. The cloud administrators ensure that the management of fault, accounting, performance, security and configuration are handled for all cloud clients, which allows companies work without worrying about them anymore. The proposed hybrid cloud model ensures maximum benefits from virtualization, fault tolerance, and cost reduction. The model promotes realtime and anywhere access to applications in the cloud with improved performance and reduced overhead costs on scheduling.
Abstract-This paper describes the designing and real time implementation of web based Learning Management Systems (LMSs) based on Moodle open source. We are giving attention to Moodle based LMS system implementation in our college because... more
Abstract-This paper describes the designing and real time implementation of web based Learning Management Systems (LMSs) based on Moodle open source. We are giving attention to Moodle based LMS system implementation in our college because of its fast ...
COVID-19 is a transferable disease that is also a leading cause of death for a large number of people worldwide. This disease, caused by SARS-CoV-2, spreads very rapidly and quickly affects the respiratory system of the human being.... more
COVID-19 is a transferable disease that is also a leading cause of death for a large number of people worldwide. This disease, caused by SARS-CoV-2, spreads very rapidly and quickly affects the respiratory system of the human being. Therefore, it is necessary to diagnosis this disease at the early stage for proper treatment, recovery, and controlling the spread. The automatic diagnosis system is significantly necessary for COVID-19 detection. To diagnose COVID-19 from chest X-ray images, employing artificial intelligence techniques based methods are more effective and could correctly diagnosis it. The existing diagnosis methods of COVID-19 have the problem of lack of accuracy to diagnosis. To handle this problem we have proposed an efficient and accurate diagnosis model for COVID-19. In the proposed method, a two-dimensional Convolutional Neural Network (2DCNN) is designed for COVID-19 recognition employing chest X-ray images. Transfer learning (TL) pre-trained ResNet-50 model weigh...
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Big data is employed in widely different fields; we here study how education uses big data. We review the literature of the research about big data in education in the time interval from 2010 to 2020 then review the process of big... more
Big data is employed in widely different fields; we here study how education uses big data. We review the literature of the research about big data in education in the time interval from 2010 to 2020 then review the process of big educational data mining, the tools, and the applications of big data in education. This paper, with the help of these applications, explores the idea to improve the education process. Two methods are applied to validate education process and many parameters are discussed to complete the research.
The Internet of Things (IoT) is increasingly becoming a major component of contemporary societies and the next stage of the Internet’s development. Its applications have touched several aspects of our lives, including health, economy,... more
The Internet of Things (IoT) is increasingly becoming a major component of contemporary societies and the next stage of the Internet’s development. Its applications have touched several aspects of our lives, including health, economy, technology, education, environment, and transport. In addition, recent research shows that interest in the IoT is increasing, driven by the potential benefits that it brings, such as improving efficiency and productivity, saving time and effort, staying connected, better health services and care, improved safety and security, automation and control among other benefits. However, despite these advantages and due to the infancy of the IoT, research around this topic is still evolving, and more needs to be done to understand this paradigm of technology. This paper aims to review current applications and challenges associated with its adoption. It provides insights into current applications of the IoT in different domains, including smart cities, health ca...
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— In this paper we first look at data mining applications in safety measures and their suggestions for privacy. After that we then inspect the idea of privacy and give a synopsis of the developments particularly those on privacy... more
— In this paper we first look at data mining applications in safety measures and their suggestions for privacy. After that we then inspect the idea of privacy and give a synopsis of the developments particularly those on privacy preserving data mining. We then present an outline for research on confidentiality and data mining. Index Terms — Data mining, security, safety, security suggestions, preserving data mining, data mining applications 1
In the last decade, the consequence of Internet usage in education has increased progressively and new technologies have enhanced student's learning day by day. With the use of distance learning tools or especially open source... more
In the last decade, the consequence of Internet usage in education has increased progressively and new technologies have enhanced student's learning day by day. With the use of distance learning tools or especially open source tools, the student learning can be more elastic with respect to location and time constraints. So, students can access information at any time and everywhere either in libraries or during the lectures. It is widely known that distance learning is costly, and cost-effectiveness becomes more significant as the institutions become huge-level providers of distance education. Cost is the most significant disadvantages of distance learning comparatively to traditional learning surroundings can be detached with the wide features of the Open Source Software. Generalizing the practice of Open Source Software will supply progress of learning tools and enlarges the educational quality. As far as the literature is reviewed, not much research has already been conducted about the comparisons of open source learning management systems in remoteness education. In this study, some analyses and comparisons would be made about open source learning management systems i.e. Moodle was outstanding with many features among other LMS that aspires to get better the educational quality and contain the tools that an e-learning system should have along with library system i.e. Koha and Dspace would be studied.
Research Interests:
Cloud computing is rising speedily with applications in approximately any area, together with pharmaceutical education. E-learning systems generally need several hardware and software resources. There are a lot of educational institutions... more
Cloud computing is rising speedily with applications in approximately any area, together with pharmaceutical education. E-learning systems generally need several hardware and software resources. There are a lot of educational institutions that cannot have the funds for such investments and cloud computing is the most excellent answer for this. This paper provides the optimistic impact of using cloud computing architectures based on e- learning system development. It spotlights on the payback of cloud computing for e-learning solutions and the e-learning development organization confronts when this architecture is utilized. At present, most of the conventional education forms are becoming not being suitable for requirements of social progress and educational development and not being able to catch up with the changes of learning demand in time, thus computer networks have brought opportunities for it. In (2) are offered the major advantages of using cloud computing in schools. The su...
Research Interests:
In this paper we first look at data mining applications in safety measures and their suggestions for privacy. After that we then inspect the idea of privacy and give a synopsis of the developments particularly those on privacy preserving... more
In this paper we first look at data mining applications in safety measures and their suggestions for privacy. After that we then inspect the idea of privacy and give a synopsis of the developments particularly those on privacy preserving data mining. We then present an outline for research on confidentiality and data mining.
Research Interests:
In the past few years, Saudi universities have boarded to utilize e-learning tools and technologies to expand and look up their educational services. After a few years of carrying out e-learning programs, a discussion took place within... more
In the past few years, Saudi universities have boarded to utilize e-learning tools and technologies to expand and look up their educational services. After a few years of carrying out e-learning programs, a discussion took place within the directors, supervisors, executives and managers or decision makers of the e-learning associations regarding which activities are the most impact on the learning development for online students. This research is expected to inspect the impact of a number of e-learning actions on the students’ learning development. The results show that involvement in virtual classroom sessions has the most considerable impact on the students’ final scoring or grade. This paper presents the procedure of applying data mining methods to the web observing records of students’ behaviors in a practical learning environment. The main idea is to rank the learning activities supported on their importance in order to develop students’ performance by focusing on the most important ones.
Research Interests:
Research Interests:
Research Interests:
Cloud computing is rising speedily with applications in approximately any area, together with pharmaceutical education. E-learning systems generally need several hardware and software resources. There are a lot of educational institutions... more
Cloud computing is rising speedily with applications in approximately any area, together with pharmaceutical education. E-learning systems generally need several hardware and software resources. There are a lot of educational institutions that cannot have the funds for such investments and cloud computing is the most excellent answer for this. This paper provides the optimistic impact of using cloud computing architectures based on e- learning system development. It spotlights on the payback of cloud computing for e-learning solutions and the e-learning development organization confronts when this architecture is utilized. At present, most of the conventional education forms are becoming not being suitable for requirements of social progress and educational development and not being able to catch up with the changes of learning demand in time, thus computer networks have brought opportunities for it. In (2) are offered the major advantages of using cloud computing in schools. The subsequent sections target on cloud computing thoughts and the profit of cloud computing for e-learning solutions. The impact on e-learning solutions based on cloud computing project managing is also examined. This is extremely significant for the development of e-learning solutions based on cloud computing.