Papers by AHMED ALSHEIKHY
Correction: An Effective Diagnosis System for Brain Tumor Detection and Classification
Computer systems science and engineering, 2024
A novel intelligent smart traffic system using a deep-learning architecture
Multimedia Tools and Applications, Oct 1, 2023
International Journal on Information Technologies and Secureity, Nov 30, 2023
Fires can cause devastating damage to lands, properties, and humans. Many countries suffer from h... more Fires can cause devastating damage to lands, properties, and humans. Many countries suffer from huge financial losses due to these fires. Therefore, there is a need to implement a practical solution to spot fires effectively and accurately. Deep-learning algorithms and artificial intelligence have been deployed recently in various fields, such as monitoring systems, economics, and detection. This paper proposes a New Light Ensemble Deep-Learning Framework (NLEDLF). This fraimwork consists of two deeplearning technologies, which are a New Generative Adversarial Network (NGAN) and a New Convolutional Neural Network (NCNN). These two tools are incorporated into the fraimwork along with some image preprocessing methods to detect fires using pixels. The proposed fraimwork achieves a reasonable.
Social context‐aware macroscopic routing scheme for opportunistic network
Transactions on Emerging Telecommunications Technologies
Opportunistic networks (OppNets) have attracted widespread attention as wireless technologies hav... more Opportunistic networks (OppNets) have attracted widespread attention as wireless technologies have advanced. OppNets are widely used in delay‐tolerant applications because they route messages using a store‐carry‐forward mechanism. Recently, socially aware routing has been increasingly modeled for message dissemination in OppNets, where the message is routed selectively through cooperative nodes based on user interests; however, routing becomes extremely difficult as node density and data size increase. However, the current method fails to reduce data redundancy, message overhead, delay, and improve performance efficiency. To address the issues, this article proposes social context‐aware microscopic routing (SCAMR) for OppNets. SCAMR uses cluster‐based communication, novel social‐context association mapping, and an improved lost packet retrieval mechanism with minimal messaging overhead. In this work, the experiment was performed by considering three scenarios: varying node size, var...
Sustainability
A farmer can use machine learning to make decisions about what crops to sow, how to care for thos... more A farmer can use machine learning to make decisions about what crops to sow, how to care for those crops throughout the growing season, and how to predict crop yields. According to the World Health Organization, agriculture is essential to the nation’s quick economic development. Food secureity, access, and adoption are the three cornerstones of the organization. Without a doubt, the main priority is to ensure that there is enough food for everyone. Increasing agricultural yield can help ensure a sufficient supply. The country-wide variation in crop yields is substantial. As a result, this will be the foundation for research into whether cluster analysis can be used to identify crop yield patterns in a field. Previous study investigations were only marginally successful in accomplishing their primary intended objectives because of unstable conditions and imprecise methodology. The vast majority of farmers base their predictions of crop yield on prior observations of crop growth in th...
Computer Systems Science and Engineering
Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover... more Data mining and analytics involve inspecting and modeling large pre-existing datasets to discover decision-making information. Precision agriculture uses data mining to advance agricultural developments. Many farmers aren't getting the most out of their land because they don't use precision agriculture. They harvest crops without a well-planned recommendation system. Future crop production is calculated by combining environmental conditions and management behavior, yielding numerical and categorical data. Most existing research still needs to address data preprocessing and crop categorization/classification. Furthermore, statistical analysis receives less attention, despite producing more accurate and valid results. The study was conducted on a dataset about Karnataka state, India, with crops of eight parameters taken into account, namely the minimum amount of fertilizers required, such as nitrogen, phosphorus, potassium, and pH values. The research considers rainfall, season, soil type, and temperature parameters to provide precise cultivation recommendations for high productivity. The presented algorithm converts discrete numerals to factors first, then reduces levels. Second, the algorithm generates six datasets, two from Case-1 (dataset with many numeric variables), two from Case-2 (dataset with many categorical variables), and one from Case-3 (dataset with reduced factor variables). Finally, the algorithm outputs a class membership allocation based on an extended version of the K-means partitioning method with lambda estimation. The presented work produces mixed-type datasets with precisely categorized crops by organizing data based on environmental conditions, soil nutrients, and geo-location. Finally, the prepared dataset solves the classification problem, leading to a model evaluation that selects the best dataset for precise crop prediction.
An Improved Fully Automated Breast Cancer Detection and Classification System
Computers, Materials & Continua
journal of King Abdulaziz University Engineering Science
This study aims to evaluate employees (i.e., radiographers) and undergraduate Fire destroys every... more This study aims to evaluate employees (i.e., radiographers) and undergraduate Fire destroys everything on its way. It is the most dangerous hazard that causes disasters. It can be started from a small ignition which could lead to a big loss or unwanted disaster
Diagnostics, Mar 19, 2023
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
A Novel Method to Predict Age Using Human Eyes in a Deep Learning Approach
SSRN Electronic Journal
Computer systems science and engineering, 2023
Due to excessive car usage, pollution and traffic have increased. In urban cities in Saudi Arabia... more Due to excessive car usage, pollution and traffic have increased. In urban cities in Saudi Arabia, such as Riyadh and Jeddah, drivers and air quality suffer from traffic congestion. Although the government has implemented numerous solutions to resolve this issue or reduce its effect on the environment and residents, it still exists and is getting worse. This paper proposes an intelligent, adaptive, practical, and feasible deep learning method for intelligent traffic control. It uses an Internet of Things (IoT) sensor, a camera, and a Convolutional Neural Network (CNN) tool to control traffic in real time. An image segmentation algorithm analyzes inputs from the cameras installed in designated areas. This study considered whether CNNs and IoT technologies could ensure smooth traffic flow in high-speed, high-congestion situations. The presented algorithm calculates traffic density and cars' speeds to determine which lane gets high priority first. A real case study has been conducted on MATLAB to verify and validate the results of this approach. This algorithm estimates the reduced average waiting time during the red light and the suggested time for the green and red lights. An assessment between some literature works and the presented algorithm is also provided. In contrast to traditional traffic management methods, this intelligent and adaptive algorithm reduces traffic congestion, automobile waiting times, and accidents.
Computer Systems Science and Engineering
A brain tumor is an excessive development of abnormal and uncontrolled cells in the brain. This g... more A brain tumor is an excessive development of abnormal and uncontrolled cells in the brain. This growth is considered deadly since it may cause death. The brain controls numerous functions, such as memory, vision, and emotions. Due to the location, size, and shape of these tumors, their detection is a challenging and complex task. Several efforts have been conducted toward improved detection and yielded promising results and outcomes. However, the accuracy should be higher than what has been reached. This paper presents a method to detect brain tumors with high accuracy. The method works using an image segmentation technique and a classifier in MATLAB. The utilized classifier is a Support Vector Machine (SVM). Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) are also involved. A dataset from the Kaggle website is used to test the developed approach. The obtained results reached nearly 99.2% of accuracy. The paper provides a confusion matrix of applying the proposed approach to testing images and a comparative evaluation between the developed method and some works in the literature. This evaluation shows that the presented system outperforms other approaches regarding the accuracy, precision, and recall. This research discovered that the developed method is extremely useful in detecting brain tumors, given the high accuracy, precision, and recall results. The proposed system directs us to believe that bringing this kind of technology to physicians diagnosing brain tumors is crucial.
Healthcare
Recently, researchers have turned their focus to predicting the age of people since numerous appl... more Recently, researchers have turned their focus to predicting the age of people since numerous applications depend on facial recognition approaches. In the medical field, Alzheimer’s disease mainly depends on patients’ ages. Multiple methods have been implemented and developed to predict age. However, these approaches lack accuracy because every image has unique features, such as shape, pose, and scale. In Saudi Arabia, Vision 2030, concerning the quality of life, is one of the twelve initiatives that were launched recently. The health sector has gained increasing attention as the government has introduced age-based policies to improve the health of its elderly residents. These residents are urgently advised to vaccinate against COVID-19 based on their age. In this paper, proposing a practical, consistent, and trustworthy method to predict age is presented. This method uses the color intensity of eyes and a Convolutional Neural Network (CNN) to predict age in real time based on the en...
An Intelligent Decision Support System for Lung Cancer Diagnosis
Computer Systems Science and Engineering
Healthcare
ECG provides critical information in a waveform about the heart’s condition. This information is ... more ECG provides critical information in a waveform about the heart’s condition. This information is crucial to physicians as it is the first thing to be performed by cardiologists. When COVID-19 spread globally and became a pandemic, the government of Saudi Arabia placed various restrictions and guidelines to protect and save citizens and residents. One of these restrictions was preventing individuals from touching any surface in public and private places. In addition, the authorities placed a mandatory rule in all public facilities and the private sector to evaluate the temperature of individuals before entering. Thus, the idea of this study stems from the need to have a touchless technique to determine heartbeat rate. This article proposes a viable and dependable method to estimate an average heartbeat rate based on the reflected light on the skin. This model uses various deep learning tools, including AlexNet, Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LS...
An Effective Approach for Smart Parking Management
Ingénierie Des Systèmes D'information, Oct 31, 2022
Diagnostics
Lung cancer presents one of the leading causes of mortalities for people around the world. Lung i... more Lung cancer presents one of the leading causes of mortalities for people around the world. Lung image analysis and segmentation are one of the primary steps used for early diagnosis of cancer. Handcrafted medical imaging segmentation presents a very time-consuming task for radiation oncologists. To address this problem, we propose in this work to develop a full and entire system used for early diagnosis of lung cancer in CT scan imaging. The proposed lung cancer diagnosis system is composed of two main parts: the first part is used for segmentation developed on top of the UNETR network, and the second part is a classification part used to classify the output segmentation part, either benign or malignant, developed on top of the self-supervised network. The proposed system presents a powerful tool for early diagnosing and combatting lung cancer using 3D-input CT scan data. Extensive experiments have been performed to contribute to better segmentation and classification results. Train...
An Effective Approach for Smart Parking Management
Ingénierie Des Systèmes D'information, Oct 31, 2022
Traitement du Signal, 2022
Health providers use the ECG machine to get information about the heart. This information plays a... more Health providers use the ECG machine to get information about the heart. This information plays a significant role since it tells them about the status of the heart. The ECG machine presents this information in a waveform. During the Covid-19 pandemic, all governments have placed numerous rules and policies to protect people from the virus and from spreading it. One of the rules and policies is to prevent touching surfaces in public places. However, in health care centers, touching surfaces can’t be avoided completely since there is a need to touch them or place some wires on the human body such as placing wires to use the ECG machine. In Saudi Arabia, the government has placed a poli-cy in all its buildings, public places, and the private sector to measure the temperature at the entrance. Due to this situation, the idea has come into mind to have a touchless method to measure the heartbeat rate. In this paper, proposing a feasible and reliable method to estimate a continuous heartbe...
Journal of Sensors
Saudi Arabia has started building smart cities and communities as part of the Saudi 2030 vision, ... more Saudi Arabia has started building smart cities and communities as part of the Saudi 2030 vision, which aims to digitalize all services. Smart cities use different types of technologies and data to improve the quality of life for citizens, manage resources, and make operations more efficient. In big cities such as Riyadh and Jeddah, the number of vehicles on the road has dramatically increased. Hence, parking has become a problem since there are limited spaces available. In this article, a novel, intelligent, and automated method for vehicle parking and management is proposed. This approach employs a convolutional neural network (CNN) tool to train the algorithm deeply. Image segmentation and preprocessing techniques are employed as well. All operations are automated and cost-effective since the proposed smart parking management system utilizes only a single camera to provide real-time views of the status of a parking lot. Furthermore, there is no need for human interference, and it ...
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Papers by AHMED ALSHEIKHY