Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. As more and more information is transacted over wireless media, there has been increasing criminal activity directed against such systems. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. We have studied the performance of differential chaos shift keying (DCSK) with 2×2 Alamouti scheme and 2×1 Alamouti scheme for different chaotic maps over additive white Gaussian noise (

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could b

Present investigation aimed to study plasma BNP hormone estimation as predictor of brain stroke and neurocognitive in relative with other limitations in CKD patient. The case control experimental study was conducted on CKD patient at Yarmuk Hospital at Baghdad Province, Iraq from February to April 2020. The results showed that there were significant variances (P< 0.05) between CKD patients and control group, there was significant increase in BNP hormone and cystatin-C levels at patient, while ihematological parameters were significantly decreased. The parameters of lipid profile were significantly increased (P<0.05). The result revealed that there was relationship between BNP hormone level and CKD. This support that BNP level is related wit

Inflammatory response had a role in cancer progression, presence of noticeable inflammation within the tumor and its margin may play an important prognostic role in colorectal carcinoma.

This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod