Hassan Mostafa
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View article: Physicians’ defensive medicine practices: a cross sectional study in Cairo
Physicians’ defensive medicine practices: a cross sectional study in Cairo Open
View article: EGYPTIAN ARTIFACTS’ MATERIALS CLASSIFIER BASED ON LIGHTWEIGHT DEEP LEARNING ARCHITECTURES
EGYPTIAN ARTIFACTS’ MATERIALS CLASSIFIER BASED ON LIGHTWEIGHT DEEP LEARNING ARCHITECTURES Open
View article: Comparative Analysis of On-Chip FPGA Memory Architectures for Viterbi Decoder Implementation in DVB Systems
Comparative Analysis of On-Chip FPGA Memory Architectures for Viterbi Decoder Implementation in DVB Systems Open
High-definition Digital Video Broadcasting (DVB) systems demand high data rates, resulting in increased hardware complexity and power consumption, with the Viterbi decoder (VD) being a key contributor. The substantial memory resources requ…
View article: Explainable artificial intelligence for wind power forecasting model based on long short-term memory
Explainable artificial intelligence for wind power forecasting model based on long short-term memory Open
Expanding the world’s economy leads to higher requirements for energy storage. Traditional energy resources decline at the same time that environmental contamination levels increase in the world. Wind power is the most potential energy res…
View article: Effect of Gamma Rays on Adropin as a Potential Hepatokine Marker for Liver Damage in Male Albino Rats
Effect of Gamma Rays on Adropin as a Potential Hepatokine Marker for Liver Damage in Male Albino Rats Open
Purpose This work was the first study to show the impact of γ- radiation on adropin levels in the serum and liver tissue of male albino rats. Methods Liver tissue and blood samples of rats were collected at 1, 3, 7 and 14 days after whole-…
View article: Physicians’ knowledge, attitude and practice regarding medical liability: cross-sectional study, Cairo, Egypt
Physicians’ knowledge, attitude and practice regarding medical liability: cross-sectional study, Cairo, Egypt Open
Background Medical liability refers to the responsibility for damage caused to a patient by healthcare providers while delivering medical services. It raises significant concerns, not only due to its impact on the quality of care but also …
View article: A Modular Reconfigurable ADC for Multiplexed Industrial Sensor Fusion Applications using the Coarse-Fine Methodology
A Modular Reconfigurable ADC for Multiplexed Industrial Sensor Fusion Applications using the Coarse-Fine Methodology Open
This paper presents a reconfigurable ADC that converts more than one analog signal into digital output bits with reconfigurable resolution. The proposed reconfigurable ADC uses successive approximation register technique (SAR) that provide…
View article: A Modular Reconfigurable ADC for Multiplexed Industrial Sensor Fusion Applications Using the Coarse-Fine Methodology
A Modular Reconfigurable ADC for Multiplexed Industrial Sensor Fusion Applications Using the Coarse-Fine Methodology Open
This paper presents a reconfigurable ADC that converts more than one analogue signal into digital output bits with reconfigurable resolution. The proposed reconfigurable ADC uses successive approximation register technique (SAR) that provi…
View article: Design of a Reconfigurable CDC for a Multiplexed Industrial Sensor Fusion
Design of a Reconfigurable CDC for a Multiplexed Industrial Sensor Fusion Open
View article: An Experimental Model with Gnns Assisted Lidar Based Algorithms for Ground Segmentation and Mapping of Autonomous Vehicle in Uneven Environment with Unpaved Roads
An Experimental Model with Gnns Assisted Lidar Based Algorithms for Ground Segmentation and Mapping of Autonomous Vehicle in Uneven Environment with Unpaved Roads Open
View article: Beamwidth Design Tradeoffs in Radar-Aided Millimeter-Wave Cellular Networks: A Stochastic Geometry Approach
Beamwidth Design Tradeoffs in Radar-Aided Millimeter-Wave Cellular Networks: A Stochastic Geometry Approach Open
This paper develops a novel stochastic geometry model to investigate design tradeoffs in a large-scale radar-aided millimeter-wave cellular network to eliminate the beam training overhead. In the proposed system, each base station comprise…
View article: A Design for Increasing the Capacity Fourfold in NB-IoT Systems using A Modified Symbol Time Compression Approach
A Design for Increasing the Capacity Fourfold in NB-IoT Systems using A Modified Symbol Time Compression Approach Open
One of the most significant obstacles facing the Internet of Things (IoT) is how to offer support for communication to an expanding number of linked items. Narrow-band Internet of Things (NB-IoT), which is currently an aspect of fifth-gene…
View article: Doubling the Number of Connected Devices in Narrow-band Internet of Things while Maintaining System Performance: An STC-based Approach
Doubling the Number of Connected Devices in Narrow-band Internet of Things while Maintaining System Performance: An STC-based Approach Open
Narrow-band Internet of Things (NB-IoT) is a low-power wide-area network (LPWAN) method that was first launched by the 3rd generation partnership project (3GPP) Rel-13 with the purpose of enabling low-cost, low-power, and wide-area cellula…
View article: An effective technique for increasing capacity and improving bandwidth in 5G narrow-band internet of things
An effective technique for increasing capacity and improving bandwidth in 5G narrow-band internet of things Open
In recent years, the wireless spectrum has become increasingly scarce as demand for wireless services has grown, requiring imaginative approaches to increase capacity within a limited spectral resource. This article proposes a new method t…
View article: Design and FPGA-Based Hardware Implementation of NB-IoT Physical Uplink Shared Channel Transmitter and Physical Downlink Shared Channel Receiver
Design and FPGA-Based Hardware Implementation of NB-IoT Physical Uplink Shared Channel Transmitter and Physical Downlink Shared Channel Receiver Open
With the anticipated growth of the internet of things (IoT) market, many low-power wide-area (LPWA) technologies have been introduced to connect a wide range of IoT devices with varying performance requirements. The narrowband internet of …
View article: Ultra-Reliable Device-Centric Uplink Communications in Airborne Networks: A Spatiotemporal Analysis
Ultra-Reliable Device-Centric Uplink Communications in Airborne Networks: A Spatiotemporal Analysis Open
This paper proposes an ultra-reliable device-centric uplink (URDC-UL) communication scheme for airborne networks. In particular, base stations (BSs) are mounted on unmanned aerial vehicles (UAVs) that travel to schedule UL transmissions an…
View article: Doubling the Number of Connected Devices in Narrow-band Internet of Things while Maintaining System Performance: An STC-based Approach
Doubling the Number of Connected Devices in Narrow-band Internet of Things while Maintaining System Performance: An STC-based Approach Open
Narrow-band Internet of Things (NB-IoT) is a low-power wide-area network (LPWAN) method that was first launched by the 3rd generation partnership project (3GPP) Rel- 13 with the purpose of enabling low-cost, low-power and wide-area cellula…
View article: An Effective Technique for Increasing Capacity and Improving Bandwidth in 5g Nb-Iot
An Effective Technique for Increasing Capacity and Improving Bandwidth in 5g Nb-Iot Open
View article: UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm
UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm Open
Unmanned Aerial Vehicles (UAVs) provide a reliable and energy-efficient solution for data collection from the Narrowband Internet of Things (NB-IoT) devices. However, the UAV’s deployment optimization, including locations of the UAV’s stop…
View article: Energy-Efficient Precision-Scaled CNN Implementation With Dynamic Partial Reconfiguration
Energy-Efficient Precision-Scaled CNN Implementation With Dynamic Partial Reconfiguration Open
A convolutional neural network (CNN) classifies images with high accuracy. However, CNN operation requires a large number of computations which consume a significant amount of power when implemented on hardware. Precision scaling has been …
View article: Implementation of a DPU-Based Intelligent Thermal Imaging Hardware Accelerator on FPGA
Implementation of a DPU-Based Intelligent Thermal Imaging Hardware Accelerator on FPGA Open
Thermal imaging has many applications that all leverage from the heat map that can be constructed using this type of imaging. It can be used in Internet of Things (IoT) applications to detect the features of surroundings. In such a case, D…
View article: Radio Optical Network Simulation Tool (RONST)
Radio Optical Network Simulation Tool (RONST) Open
This paper presents a radio optical network simulation tool (RONST) for modeling optical-wireless systems. For a typical optical and electrical chain environment, performance should be optimized concurrently before system implementation. A…
View article: Data Aggregation in Synchronous Large-scale IoT Networks: Granularity, Reliability, and Delay Tradeoffs
Data Aggregation in Synchronous Large-scale IoT Networks: Granularity, Reliability, and Delay Tradeoffs Open
This paper studies data aggregation in large-scale regularly deployed Internet of Things (IoT) networks, where devices generate synchronized time-triggered traffic (e.g., measurements or updates). The data granularity, in terms of informat…
View article: A 0.002‐mm <sup>2</sup> 8‐bit 1‐MS/s low‐power time‐based DAC (T‐DAC)
A 0.002‐mm <sup>2</sup> 8‐bit 1‐MS/s low‐power time‐based DAC (T‐DAC) Open
Digital‐to‐analogue converters (DACs) are essential blocks for interfacing the digital environment with the real world. A novel architecture, using a digital‐to‐time converter (DTC) and a time‐to‐voltage converter (TVC), is employed to for…
View article: Power Efficient Design of High-Performance Convolutional Neural Networks Hardware Accelerator on FPGA: A Case Study With GoogLeNet
Power Efficient Design of High-Performance Convolutional Neural Networks Hardware Accelerator on FPGA: A Case Study With GoogLeNet Open
Convolutional neural networks (CNNs) have dominated image recognition and object detection models in the last few years. They can achieve the highest accuracies with several applications such as automotive and biomedical applications. CNNs…
View article: Hardware Acceleration of High Sensitivity Power-Aware Epileptic Seizure Detection System Using Dynamic Partial Reconfiguration
Hardware Acceleration of High Sensitivity Power-Aware Epileptic Seizure Detection System Using Dynamic Partial Reconfiguration Open
In this paper, a high-sensitivity low-cost power-aware Support Vector Machine (SVM) training and classification based system, is hardware implemented for a neural seizure detection application. The training accelerator algorithm, adopted i…
View article: A Novel Companding Technique to Reduce High Peak to Average Power Ratio in OFDM Systems
A Novel Companding Technique to Reduce High Peak to Average Power Ratio in OFDM Systems Open
The reduction of the high peak-to-average-power ratio (PAPR) is important to the efficiency of the orthogonal frequency division multiplexing (OFDM) technique. Excessive PAPR contributes to non-linear clipping induced harmonic distortions …
View article: Early breast cancer diagnostics based on hierarchical machine learning classification for mammography images
Early breast cancer diagnostics based on hierarchical machine learning classification for mammography images Open
Breast cancer constitutes a significant threat to women’s health and is considered the second leading cause of their death. Breast cancer is a result of abnormal behavior in the functionality of the normal breast cells. Therefore, breast c…
View article: A Novel Highly Linear Voltage-To-Time Converter (VTC) Circuit for Time-Based Analog-To-Digital Converters (ADC) Using Body Biasing
A Novel Highly Linear Voltage-To-Time Converter (VTC) Circuit for Time-Based Analog-To-Digital Converters (ADC) Using Body Biasing Open
Time-based analog-to-digital converter is considered a crucial part in the design of software-defined radio receivers for its higher performance than other analog-to-digital converters in terms of operation speed, input dynamic range and p…
View article: Applying Machine Learning Technology in the Prediction of Crop Infestation with Cotton Leafworm in Greenhouse
Applying Machine Learning Technology in the Prediction of Crop Infestation with Cotton Leafworm in Greenhouse Open
The use of technology in agriculture has grown in recent years with the era of data analytics affecting every industry. The main challenge in using technology in agriculture is identification of effectiveness of big data analytics algorith…