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Space communication systems are traditionally operated with microwave in satellite-to-satellite links. Now, more efficient and reliable operation is required, which lead to use optical links for Inter Satellite Links (ISLs). This paper investigates the system performance of an optical ISL proposed between satellites over Low Earth Orbit (LEO). In this study, the proposed link is simulated to obtain a maximum bit rate and minimum bit error rate (BER) over different links distances. The system performance is improved by investigating its dependency on the photo detector type, operating wavelength, transmitted optical power, RZ and NRZ schemes. Our work results that best Q- factor are approximately 40 leading to a minimum BER for the LEO orbit, at 600 km when utilizing an APD. While at our investigation of the system performance at visible light bands, it is found that Q-factor will be approximately 60 achieving minimum BER with neglecting the eye-safety precautions in addition to the ability to transmit 2 Gbps at 10−9 BER within many bands.

Our paper introduces a new technique for diagnosis of various heart diseases without the need of highly experts to investigate the electrocardiogram (ECG). Using the same electrodes of the ECG machine, it will be able to transmit directly the electrical activity inside the heart to a moving picture. Our technique is based on artificial intelligence algorithm using artificial neural networks (ANN). Finding the trans-membrane potential (TMP) inside the heart from the body surface potential (BSP) is known as the inverse problem of ECG. To have a unique solution for the inverse problem the data used should be obtained from a forward model. A three dimensional (3-D) model of cellular activation whole heart embedded in torso is simulated and solved using COMSOL Multiphysics software. In our previous paper, one ANN succeeded in displaying the wave propagation on the surface of a normal heart. In this paper, we used a configuration of ANNs to display different cases of heart with myocardial infarction (MI). To check the system accuracy, eight MI cases with different sizes and locations in the heart are simulated in the forward model. This configuration proved to be highly accurate in displaying each MI case -size and location- presenting the infarction as an area with no electrical activity.

Lung cancer became a significant health problem worldwide over the past decades. This paper introduces a new generalized framework for lung cancer detection where many different strategies are explored for the classification. The ResNet50 model is applied to classify CT lung images into benign or malignant. Also, the U-Net, which is one of the most used architectures in deep learning for image segmentation, is employed to segment CT images before classification to increase system performance. Moreover, Image Size Dependent Normalization Technique (ISDNT) and Wiener filter are utilized as the preprocessing phase to enhance the images and suppress the noise. Our proposed framework which comprises preprocessing, segmentation and classification phases, is applied on two databases: Lung Nodule Analysis 2016 (Luna 16) and National Lung Screening Trial (NLST). Data augmentation technique is applied to solve the problem of lung CT images deficiency, and consequently, the overfitting of deep models will be avoided. The classification results show that the preprocessing for the CT lung image as the input for ResNet50-U-Net hybrid model achieves the best performance. The proposed model achieves 98.98% accuracy (ACC), 98.65% area under the ROC curve (AUC), 98.99% sensitivity (Se), 98.43% precision (Pr), 98.86% F1- score and 1.9876 s computational time.

This article uses computational models to evaluate the potential of copper-indium-gallium-diselenide (CIGS) thin film solar cells. The use of cadmium sulphide (CdS) renders the solar cell environmentally hazardous. A zinc sulphide (ZnS) that is non-toxic and has a large bandgap is studied as a potential replacement for cadmium sulphide in CIGS-based solar cells. The present research focuses on the impact of the CIGS-based solar cell bandgap absorber layer by increasing the absorber layer thickness (0.1-2 μm) using the solar cell simulator simulation tool SCAPS. The basic simulation produces 18.2 % efficiency with a CdS buffer layer, which is 9.95% better than the previously published work. The Simulated efficiency is 22.16% for the CIGS solar cell using ZnS. The simulation of solar cell characteristics of how the thickness of the absorber layer, the gallium grading (efficiency ranges up to 22.25 %) is demonstrated, showing the effect of buffer layer (ZnS) on the current of short-circuit density (JSC), open-circuit voltage (Voc), fill factor (FF), and efficiency (η) of the solar cell.

In this paper, an artificial intelligence technique which is fuzzy logic is used as an online prediction of a patient (especially Alzheimer patient) motion status. It depends on the input variables: GPS, GPRS, accelerometer, gyroscope, temperature, heartbeat rate, and the motion status (standing, walking, and running) as an output variable. Fuzzy logic can detect the motion status based on 385 rules for all inputs and output variables. A low-cost smart shoe with embedded positioning tracking is implemented based on sensors and microcontrollers to help Alzheimer patients. The first phase of the experimental work is based on GPS, GPRS, GSM, accelerometer, heartbeat rate sensor, temperature sensor, and a microcontroller, mounted on the shoe side to navigate according to the pedestrian or patient movement. All sensors data are collected by the microcontroller and are transmitted to the GSM receiver in SMS message. The GSM module is connected to the PC via a USB serial port. Transmitting data is periodically sent upon a specific time. The detected data is stored in the database as a function of time. The data includes the position of the patient (latitude and longitude) located on the Google map software, health status (heartbeat rate), gyroscope and accelerometer (x, y, z) of movement as a function of time.

In the past years, record efficiency of copper-indium-gallium-diselenide (CIGS) based solar cells has improved reaching 22.6%. This result shows that CIGS absorbent is idealistic for thin-film solar cells. The most attractive feature in CIGS is the tunable bandgap of the absorber layer that varies from 1.06 eV to 1.7 eV depending on the gallium fraction. This feature leads to best match the solar spectrum. In the present work, the influence of the bandgap of the absorber is investigated using solar cell capacitance simulator (SCAPS). An optimum bandgap of 1.39 eV results in a maximum efficiency of 24.288%. In order to get a Cd-free CIGS based thin film solar cell the CdS buffer layer is replaced by In2S3. The results show that In2S3 is a proper alternative that does not degrade th 3 e cell performance.

In this paper, three optical communication systems have been proposed to mitigate Four Wave Mixing (FWM). Three techniques are used, namely; low input power with high gain amplifier, a collective Optical Time Division Multiplexing (OTDM) and Dense Wavelength Division Multiplexing (DWDM) system, and the use of alternative circular polarization. The first technique involves reduction in input power to -20 dBm and then amplifying it 40 dB before demultiplexing. The second technique divides the input signal into four time slots and then combine them with a power combiner. In the third technique, the polarization of light coming from input channels is changed after modulation into right and left handed circular polarization. Exhaustive sets of simulations are performaed using Optisys. The performance analysis includes Q-factor, Optical Signal to Noise Ratio (OSNR), received optical power, minmum Bit Error Rate (BER) and eye diagram.