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"Ahmed, Khaled"
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Smart Pothole Detection Using Deep Learning Based on Dilated Convolution
Roads make a huge contribution to the economy and act as a platform for transportation. Potholes in roads are one of the major concerns in transportation infrastructure. A lot of research has proposed using computer vision techniques to automate pothole detection that include a wide range of image processing and object detection algorithms. There is a need to automate the pothole detection process with adequate accuracy and speed and implement the process easily and with low setup cost. In this paper, we have developed efficient deep learning convolution neural networks (CNNs) to detect potholes in real-time with adequate accuracy. To reduce the computational cost and improve the training results, this paper proposes a modified VGG16 (MVGG16) network by removing some convolution layers and using different dilation rates. Moreover, this paper uses the MVGG16 as a backbone network for the Faster R-CNN. In addition, this work compares the performance of YOLOv5 (Large (Yl), Medium (Ym), and Small (Ys)) models with ResNet101 backbone and Faster R-CNN with ResNet50(FPN), VGG16, MobileNetV2, InceptionV3, and MVGG16 backbones. The experimental results show that the Ys model is more applicable for real-time pothole detection because of its speed. In addition, using the MVGG16 network as the backbone of the Faster R-CNN provides better mean precision and shorter inference time than using VGG16, InceptionV3, or MobilNetV2 backbones. The proposed MVGG16 succeeds in balancing the pothole detection accuracy and speed.
Journal Article
MicroLEDs Devices and Systems
MicroLEDs Overview, MicroLED Design--Physics and Technology, MicroLED Forward Current-Voltage (I-V) Characteristics, High-Speed Modulation of MicroLEDs, MicroLED Display System, MicroLED Data Communication Systems, Techno-Economics of MicroLEDs, Advanced MicroLED Concepts, Potential Applications for MicroLEDs, Epitaxial Growth of III-Nitride Light-Emitting Diodes
eBook
MicroLED Devices and Systems
This book introduces a theoretical framework, validated by experiments, in the form of a number of white-box analytic or semi-analytic mathematical models that are based on physics. It aims to assist in the design and manufacture of the best MicroLED devices for various applications, such as mobile displays, TV displays, augmented reality, and data communication systems. This resource demonstrates the importance of MicroLEDs in addressing power consumption in mobile displays, brightness in TV displays, augmented reality, and parallel optical interconnect in data centers and artificial intelligence computer systems. With the mobile display industry's revenue exceeding $50 billion in 2020 and projected to be a significant portion of the display market by 2026, the importance of MicroLED technology is highlighted in this resource. It provides models for display systems and data communication systems to help system engineers understand and assess the gaps between commercially available MicroLEDs versus what is needed for a specific system. Furthermore, the book addresses the emerging role of MicroLEDs in data communication, highlighting their potential to improve energy consumption, data rate, latency, and cost in semiconductor chip communication. This book is intended for engineers who desire to begin with physics-based intuition to design MicroLED-based systems within 80% accuracy, then follow with running experiments and more sophisticated models to capture the top 20% of design accuracy. This 80-20 approach is proven to work in many fields including the semiconductor industry.
eBook
DSTEELNet: A Real-Time Parallel Dilated CNN with Atrous Spatial Pyramid Pooling for Detecting and Classifying Defects in Surface Steel Strips
Automatic defects inspection and classification demonstrate significant importance in improving quality in the steel industry. This paper proposed and developed DSTEELNet convolution neural network (CNN) architecture to improve detection accuracy and the required time to detect defects in surface steel strips. DSTEELNet includes three parallel stacks of convolution blocks with atrous spatial pyramid pooling. Each convolution block used a different dilation rate that expands the receptive fields, increases the feature resolutions and covers square regions of input 2D image without any holes or missing edges and without increases in computations. This work illustrates the performance of DSTEELNet with a different number of parallel stacks and a different order of dilation rates. The experimental results indicate significant improvements in accuracy and illustrate that the DSTEELNet achieves of 97% mAP in detecting defects in surface steel strips on the augmented dataset GNEU and Severstal datasets and is able to detect defects in a single image in 23ms.
Journal Article
High-voltage direct-current transmission : converters, systems and DC grids
This comprehensive reference guides the reader through all HVDC technologies, including LCC (Line Commutated Converter), 2-level VSC and VSC HVDC based on modular multilevel converters (MMC) for an in-depth understanding of converters, system level design, operating principles and modeling. Written in a tutorial style, the book also describes the key principles of design, control, protection and operation of DC transmission grids, which will be substantially different from the practice with AC transmission grids. The first dedicated reference to the latest HVDC technologies and DC grid developments; this is an essential resource for graduate students and researchers as well as engineers and professionals working on the design, modeling and operation of DC grids and HVDC. Key features: Provides comprehensive coverage of LCC, VSC and (half and full bridge) MMC-based VSC technologies and DC transmission grids. Presents phasor and dynamic analytical models for each HVDC technology and DC grids. Includes HVDC protection, studies of DC and AC faults, as well as system-level studies of AC-DC interactions and impact on AC grids for each HVDC technology. Companion website hosts SIMULINK SimPowerSystems models with examples for all HVDC topologies.
eBook
A cross-sectional study assessing customers’ perception, satisfaction, and attitude toward e-pharmacy services in Saudi Arabia
Background
Electronic pharmacy (e-pharmacy) services are growing rapidly, offering increased accessibility, privacy, and value. Understanding e-pharmacy customer satisfaction, attitudes, and perceptions in Saudi Arabia is crucial for improving the services and enhancing health outcomes. This study aims to examine customers’ perceptions, preferences, satisfaction, and experiences with electronic pharmacy services, including community pharmacy e-commerce.
Methods
A quantitative cross-sectional design was utilized and conducted in Saudi Arabia. A self-administered online questionnaire was distributed via social media, and convenience sampling was used to collect data from December 2022 to January 2023. The questionnaire was adapted from validated academic questionnaires and consisted of five sections. The online form data was retrieved and analyzed using the IBM SPSS Statistics program.
Results
The sample comprised 351 respondents, most of whom were Saudi citizens (90.3%), aged 41–60 years (36.5%), and non-healthcare professionals (35%). Of the participants, 256 (72.93%) were aware of e-pharmacies. Younger participants and those with higher education levels were more aware of e-pharmacies (
p
< 0.05), with no significant effect of gender or nationality on awareness. Positive perceptions of e-pharmacies exist, but there is limited knowledge about individualized care services (61.8% uncertain). Of the participants, 134 (38.17%) had never used e-pharmacies, and only 24.2% preferred buying medications online, while 75.8% favored physical pharmacies.
On a Likert Scale, participants reported moderate levels of satisfaction with e-pharmacies’ values/prices and delivery speeds. Many e-pharmacy customers had a positive experience (only 1.1% negative). The findings reveal that service quality, product availability, perceived value, and price could be the potential factors that affect customer satisfaction. Moreover, these factors, along with the provision of personalized care, could shape customers' attitudes toward and perceptions of e-pharmacy.
Conclusions
There is potential for development in e-pharmacy services as seen by the persistence of a preference for traditional pharmacies despite moderate satisfaction ratings. To increase customer satisfaction in Saudi Arabia, we recommend improving personalized care services by raising awareness about e-pharmacy benefits to improve customer satisfaction and adoption.
Journal Article
Determination of damping coefficient of soft tissues using piezoelectric transducer
Measuring viscoelastic properties of soft tissues becomes a new biomarker in the medical diagnosis field. It can help in early diagnosis and related fields, such as minimally-invasive-surgery (MIS) applications and cell mechanics. The current work presents a tactile sensor for measuring the damping coefficient of the soft tissues. The proposed sensor can be miniaturized easily and used in MIS applications. Besides the proposed sensor, a mathematical model, based on Jacobsen’s approach, is built to calculate the damping coefficient of the specimens and the surrounding. These damping sources significantly influence the proposed sensor, such as air damping and hysteretic damping. The sensor system principally depends on a piezoelectric transducer, which is cheap, commonly available, and easily integrated into MEMS. To conceptually prove the sensor feasibility, silicon rubber samples with different stiffnesses have been fabricated and tested by the new sensor. The obtained results prove the newly proposed sensor’s capability to differentiate the damping coefficients for soft materials effectively.
Journal Article
Relationship between chlorine decay and nanobubble application in secondary treated wastewater
There has been numerous research on the uses of treated wastewater that needs chlorine disinfection, but none have looked at the impacts of injecting nanobubbles (NBs) on the decomposition of residual chlorine. Gas NB injection in treated wastewater improves its properties. The kinetics of disinfectant decay could be impacted by changes in treated wastewater properties. This paper studies the effect of various NB injections on the residual chlorine decay of secondary treated wastewater (STWW). It also outlines the empirical equations that were developed to represent these impacts. The results show that each type of NBs in treated wastewater had a distinct initial chlorine concentration. The outcomes demonstrated a clear impact on the decrease of the needed chlorine quantity and the reduction of chlorine decay rate when utilizing NB injection for the STWW. As a result, the residual chlorine will remain for a longer time and will resist any microbiological growth under the application of NBs on treated wastewater. Moreover, NBs in secondary treated effluent reduce chlorine usage, lowering wastewater disinfection costs.
Journal Article