- Jeddah, Makkah, Saudi Arabia
nazar mohamed
Fahad bin Sultan University, KSA, Computer Engineering, Faculty Member
Research Interests:
To evaluate and measure the effects of student’s preparation before studying an embedded system design course, a systematic literature analysis was conducted, spanning publications from 1992 to 2020. Furthermore, evaluating such effects... more
To evaluate and measure the effects of student’s preparation before studying an embedded system design course, a systematic literature analysis was conducted, spanning publications from 1992 to 2020. Furthermore, evaluating such effects may help to close the gap between academically taught abilities and industry-required skills. The goal of the review was to gather and evaluate all reputable and effective studies that have looked into students’ learning preparation issues and solutions in embedded system design courses. Nonetheless, the purpose of this work was to extract and discuss the key features and methodologies from the selected research publications in order to present researchers and practitioners with a clear set of recommendations and solutions. The findings revealed that no instrument has been developed yet to assess students’ readiness to take up an embedded system design course. Furthermore, the majority of the instruments offered lacked concept clarity.
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To assess different approaches to traffic light control design, a systematic literature review was conducted, covering publications from 2006 to 2020. The review’s aim was to gather and examine all studies that looked at road traffic and... more
To assess different approaches to traffic light control design, a systematic literature review was conducted, covering publications from 2006 to 2020. The review’s aim was to gather and examine all studies that looked at road traffic and congestion issues. As well, it aims to extract and analyze protruding techniques from selected research articles in order to provide researchers and practitioners with recommendations and solutions. The research approach has placed a strong emphasis on planning, performing the analysis, and reporting the results. According to the results of the study, there has yet to be developed a specific design that senses road traffic and provides intelligent solutions. Dynamic time intervals, learning capability, emergency priority management, and intelligent functionality are all missing from the conventional design approach. While learning skills in the adaptive self-organization strategy were missed. Nonetheless, the vast majority of intelligent design appr...
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A new technique for identification of patients with congestive heart failure (CHF) from normal controls is investigated in this paper using spectral analysis and neural networks. The identification system consists of two parts: feature... more
A new technique for identification of patients with congestive heart failure (CHF) from normal controls is investigated in this paper using spectral analysis and neural networks. The identification system consists of two parts: feature extraction part and classification part. The feature extraction part uses the method of approximate spectral density estimation of R-R-Intervals (RRI) data by implementing the soft decision sub-band decomposition technique. In the classification part, two different methods of machine learning approaches with neural networks are implemented and compared in their performances. Those approaches are: supervised neural network (back-propagation) and unsupervised neural network (Kohonen self organizing maps). The data used in this work is obtained from Massachusetts Institute of Technology (MIT) databases. A data set of 17 CHF and 53 normal subjects is used as original training data set, while another set of 12 CHF and 12 normal subjects is used as original...
Research Interests: Computer Science, Algorithms, Machine Learning, Concept Map, Medicine, and 15 moreHeart Failure, Humans, Clinical research, Congestive Heart Failure, Case Study, Female, Male, Health Science, Aged, Middle Aged, Adult, Health Care Technology, Epidemiologic Studies, Positive predictive value, and Classification Accuracy
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Self-organizing maps are unsupervised neural network models that lend themselves to the cluster analysis of high-dimensional input data. Interpreting a trained map is difficult because features responsible for specific cluster assignment... more
Self-organizing maps are unsupervised neural network models that lend themselves to the cluster analysis of high-dimensional input data. Interpreting a trained map is difficult because features responsible for specific cluster assignment are not evident from resulting map representation. This paper presents an approach to automated knowledge acquisition using Kohonen's self-organizing maps and k-means clustering. To demonstrate the architecture and validation, a data set representing animal world has been used as the training data set. The verification of the produced knowledge base is done by using conventional expert system.
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A new technique for identification of patients with Congestive Heart Failure (CHF) from normal controls is investigated in this paper using spectral analysis and neural networks. The data used in this work is obtained from Massachusetts... more
A new technique for identification of patients with Congestive Heart Failure (CHF) from normal controls is investigated in this paper using spectral analysis and neural networks. The data used in this work is obtained from Massachusetts Institute of Technology (MIT) databases. A data set of 17 CHF and 53 normal subjects is used as original learning data set. A larger
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Abstract Although the special characteristics of Wireless Sensor Networks (WSNs) help in reducing the cost of sensor nodes manufacturing and deployment, they added new challenges that directly affect the network functionality. This is... more
Abstract Although the special characteristics of Wireless Sensor Networks (WSNs) help in reducing the cost of sensor nodes manufacturing and deployment, they added new challenges that directly affect the network functionality. This is increases the probability of network ...
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This paper discusses a concept of integrating a handwritten signature and digital signature into an overall Public Key Infrastructure (PKI). The purpose of this proposed solution is to fulfill the cultural gap between traditional... more
This paper discusses a concept of integrating a handwritten signature and digital signature into an overall Public Key Infrastructure (PKI). The purpose of this proposed solution is to fulfill the cultural gap between traditional handwritten signatures and digital certificate/signature ...
Research Interests: Law, Visualization, Digital Signature, Public Key Infrastructure, E Government, and 15 moreAuthentication, Cultural Differences, Smart Cards, Data Privacy, Verification, DIGITAL CERTIFICATES, Public key cryptography, Smart Card, Certification, Digital Signatures, computer Communication, Data Confidentiality, Computer and Communication Systems Engineering, E Commerce, and Multifactor Authentication
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In this paper, the author presents an approach for automated knowledge acquisition system using Kohonen self-organizing maps and k-means clustering. The extracted knowledge in terms of rules are used as knowledge base for a rule based... more
In this paper, the author presents an approach for automated knowledge acquisition system using Kohonen self-organizing maps and k-means clustering. The extracted knowledge in terms of rules are used as knowledge base for a rule based expert system. For the sake of illustrating and validating the system overall architecture, a fall-time auto-correlated data patterns has been used as a learning data set. The verification of the produced knowledge based was conducted by conventional expert system.
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In this paper, the author presents an approach for automated knowledge extraction from rise time auto-correlated patterns by using self-organizing maps and k-means clustering. The extracted knowledge in terms of rules will be used as... more
In this paper, the author presents an approach for automated knowledge extraction from rise time auto-correlated patterns by using self-organizing maps and k-means clustering. The extracted knowledge in terms of rules will be used as knowledge base for an expert system. Rise-time auto-correlated data patterns are used as a learning data set. The produced knowledge based was verified by using a conventional expert system.
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Nowadays, the shift towards e-commerce is an inevitable trend. Digital signatures [1] are designed in e-commerce to fulfill the functions of traditional signatures for authentication, data integrity, and non repudiation purposes.... more
Nowadays, the shift towards e-commerce is an inevitable trend. Digital signatures [1] are designed in e-commerce to fulfill the functions of traditional signatures for authentication, data integrity, and non repudiation purposes. Historically, documents have always relied on a ...
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Research Interests: Expert Systems, Computer Engineering, Machine Learning, Systems Analysis, Neural Networks, and 14 moreVirtual Memory, Neural Network, Medical Decision Making, Performance Prediction, Electrical Electronic, Case Study, expert System, Knowledge Acquisition, Network Performance, Information Gathering, Knowledge base, Self Organized Map, Laboratory Tests, and Rule Extraction
A basic reason why we monitor the performance of a system is to define the overall state of the machine ("It's Ok or "It's slow" etc). In other words to determine whether the system is... more
A basic reason why we monitor the performance of a system is to define the overall state of the machine ("It's Ok or "It's slow" etc). In other words to determine whether the system is experienceing a bottleneck or not. This paper investigates the application of Self Organizing Maps ...
Research Interests: Expert Systems, Computer Engineering, Machine Learning, Systems Analysis, Neural Networks, and 14 moreVirtual Memory, Neural Network, Medical Decision Making, Performance Prediction, Electrical Electronic, Case Study, expert System, Knowledge Acquisition, Network Performance, Information Gathering, Knowledge base, Self Organized Map, Laboratory Tests, and Rule Extraction
Research Interests:
recently, many potential fields, such as the military, increasingly depend on Wireless Sensor Networks (WSN) for monitoring and controlling their different application processes as a result of the network special characteristics. Although... more
recently, many potential fields, such as the military, increasingly depend on Wireless Sensor Networks (WSN) for monitoring and controlling their different application processes as a result of the network special characteristics. Although these characteristics reduce the cost of network manufacture and deployment, they nevertheless add new challenges in terms of network operation deviation from norm. Unfortunately, this deviation, in some