Mohamed Abdel-Nasser
Aswan University
Publications 51
Worldwide, the penetrations of photovoltaic (PV) and energy storage systems are increased in power systems. Due to the intermittent nature of PVs, these sustainable power systems require efficient managing and prediction techniques to ensure economic and secure operations. In this paper, a comprehensive dynamic economic dispatch (DED) framework is proposed that includes fuel-based generators, PV, and energy storage devices in sustainable power systems, considering various profiles of PV (clear a...
#2Al-Attar Ali Mohamed (Aswan University)H-Index: 6
Last.Mohamed Hassan (Cairo University)H-Index: 14
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#1Farhan Akram (Agency for Science, Technology and Research)H-Index: 1
#2Vivek SinghH-Index: 28
Last.Domenec PuigH-Index: 16
view all 7 authors...
In this paper, we propose an efficient blood vessel segmentation method for the eye fundus images using adversarial learning with multiscale features and kernel factorization. In the generator network of the adversarial framework, spatial pyramid pooling, kernel factorization and squeeze excitation block are employed to enhance the feature representation in spatial domain on different scales with reduced computational complexity. In turn, the discriminator network of the adversarial framework is...
#1Karar Mahmoud (Aswan University)H-Index: 8
#2Mohamed Abdel-Nasser (Aswan University)H-Index: 5
The penetration of photovoltaic (PV) has obviously been increased in distribution systems throughout the world. To sufficiently assess the energy losses with PV, comprehensive simulations with high time-resolution data are required. These simulations have a heavy computational burden, which makes it difficult to analyze distribution systems and evaluate PV impacts with fine resolutions. To cope with this issue, most related works down-sample, cluster, or quantize the full data to reduce the comp...
#1Mohamed Abdel-Nasser (Aswan University)H-Index: 5
#2Karar Mahmoud (Aswan University)H-Index: 8
Photovoltaic (PV) is one of the most promising renewable energy sources. To ensure secure operation and economic integration of PV in smart grids, accurate forecasting of PV power is an important issue. In this paper, we propose the use of long short-term memory recurrent neural network (LSTM-RNN) to accurately forecast the output power of PV systems. The LSTM networks can model the temporal changes in PV output power because of their recurrent architecture and memory units. The proposed method ...
31 CitationsSource
#1Mohamed Abdel-Nasser (URV: Rovira i Virgili University)H-Index: 5
#2Antonio Moreno Jiménez (URV: Rovira i Virgili University)H-Index: 34
Last.Domenec Puig (URV: Rovira i Virgili University)H-Index: 16
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Matching candidate points from multiple mammographic views corresponding to the same patient may lead to an improvement in the accuracy of Computer Aided Diagnosis systems and it can help the radiologists to detect breast cancer in early stages, leading to a reduction of the percentage of mortality. In this paper, we propose a matching approach in order to detect correspondences between some candidate points from multiple mammographic views. Initially, a Scale Invariant Feature Transform detecto...
#1Ahmed Rashad (Aswan University)H-Index: 1
#2Salah Kamel (Aswan University)H-Index: 9
Last.Karar Mahmoud (Aswan University)H-Index: 8
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AbstractAlthough the wind farms based on squirrel cage induction generators (SCIG) is cheaper than the wind farms based on doubly fed induction generators (DFIG), it is always in desperate need for...
Last.Domenec PuigH-Index: 16
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Nowadays, breast cancer is one of the most common cancers diagnosed in women. Mammography is the standard screening imaging technique for the early detection of breast cancer. However, thermal infrared images (thermographies) can be used to reveal lesions in dense breasts. In these images, the temperature of the regions that contain tumors is warmer than the normal tissue. To detect that difference in temperature between normal and cancerous regions, a dynamic thermography procedure uses thermal...
4 CitationsSource
#1Md. Mostafa Kamal Sarker (URV: Rovira i Virgili University)H-Index: 4
#2Hatem A. RashwanH-Index: 8
Last.Domenec PuigH-Index: 16
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Skin lesion segmentation in dermoscopic images is a challenge due to their blurry and irregular boundaries. Most of the segmentation approaches based on deep learning are time and memory consuming due to the hundreds of millions of parameters. Consequently, it is difficult to apply them to real dermatoscope devices with limited GPU and memory resources. In this paper, we propose a lightweight and efficient Generative Adversarial Networks (GAN) model, called MobileGAN for skin lesion segmentation...
#2Syeda Furruka BanuH-Index: 2
Last.Domenec PuigH-Index: 2
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