Skin cancer develops due to the unusual growth of skin cells. Early detection is critical for recognition multiclass pigmented lesions (PSLs). At an early stage, manual work by ophthalmologists takes time recognize PSLs. Therefore, several “computer-aided diagnosis (CAD)” systems are developed using image processing, machine learning (ML), and deep (DL) techniques. Deep-CNN models outperformed traditional ML approaches in extracting complex features from In this study, a special transfer...

A dermatologist-like automatic classification system is developed in this paper to recognize nine different classes of pigmented skin lesions (PSLs), using a separable vision transformer (SVT) technique assist clinical experts early cancer detection. In the past, researchers have few systems PSLs. However, they often require enormous computations achieve high performance, which burdensome deploy on resource-constrained devices. paper, new approach designing SVT architecture based SqueezeNet...

The stage and duration of hypertension are connected to the occurrence Hypertensive Retinopathy (HR) eye disease. Currently, a few computerized systems have been developed recognize HR by using only two stages. It is difficult define specialized features five grades HR. In addition, deep used in past, but classification accuracy not up-to-the-mark. this research, new hypertensive retinopathy (HYPER-RETINO) framework grade based on grades. HYPER-RETINO system implemented pre-trained...

Abstract Accurate stock price forecasting is essential for making smart investing choices. In the context of Egyptian market, this study examines predictive capabilities several machine learning and deep models prediction. Five different datasets with historical information from significant companies are used in methods such as Random Forest, Linear Regression, LSTM, Bi-LSTM which were employed evaluated using performance metrics including Mean Squared Error (MSE), Absolute (MAE), R-Squared....

User authentication has become necessary in different life domains. Traditional methods like personal information numbers (PINs), password ID cards, and tokens are vulnerable to attacks. For secure authentication, biometrics have been developed the past. Biometric is hard lose, forget, duplicate, or share because it a part of human body. Many focused on electrocardiogram (ECG) signals achieved great success. In this paper, we cardiac for identification using deep learning (DL) approach....

Hypertensive retinopathy (HR) and diabetic (DR) are retinal diseases closely associated with high blood pressure. The severity duration of hypertension directly impact the prevalence HR. early identification assessment HR crucial to preventing blindness. Currently, limited computer-aided methods available for detecting DR. These existing systems rely on traditional machine learning approaches, which require complex image processing techniques often in their application. To address this...

Abstract Designing a wireless sensor network (WSN) energy‐aware routing protocol is thought‐provoking mission. Thus, this article presents an energy‐saving for WSNs. The proposed considers the energy level of nodes and distance to base station optimally determine best route. It also takes advantage inherent complementarity clustering techniques. scheme exploits data aggregation improve utilization reduce communication costs. To choose flawless route between source node station, ant colony...

Biometric authentication is a widely used method for verifying individuals’ identities using photoplethysmography (PPG) cardiac signals. The PPG signal non-invasive optical technique that measures the heart rate, which can vary from person to person. However, these signals also be changed due factors like stress, physical activity, illness, or medication. Ensuring system accurately identify and authenticate user despite variations significant challenge. To address issues, were preprocessed...

Cardiovascular disorders are often diagnosed using an electrocardiogram (ECG). It is a painless method that mimics the cyclical contraction and relaxation of heart’s muscles. By monitoring electrical activity, ECG can be used to identify irregular heartbeats, heart attacks, cardiac illnesses, or enlarged hearts. Numerous studies analyses signals problems have been conducted during past few years. Although heartbeat classification methods presented in literature, especially for unbalanced...

Frequency hopping (FH) is a common characteristic of wide variety communication systems. On the other hand, software-defined radio (SDR) an increasingly utilized technology for implementing modern The main challenge when trying to realize SDR FH system frequency tuning time, that is, higher rate, lower required time. In this paper, significant universal hardware driver options (within GNU Radio software) are investigated discover option gives minimum This paper proposes improved algorithm...

Compilers traditionally are not exposed to the energy details of processor. In this paper, we present a quantitative study wherein examine influence global performance optimizations -o0 -o3, code composer studio C/C++ compiler, on and power consumption. The results show that most aggressive optimization option -o3 reduce execution time, average, by 95%, while it increases consumption 25%. Moreover, inspect effect some other characteristics, such as memory references data cache miss rate....

In this contribution the modeling of power consumption for VLIW processor TMS320C6416T is presented taking into account typical software algorithms in signal and image processing. The performed at functional level making approach distinctly different from other approaches low technique. This means that can be identified an early stage design process, enabling designer to explore hardware architectures algorithms. Some processing are used purpose validating proposed model. estimated compared...

Cloud computing is a style of technology that increasingly used every day. It requires the use an important amount resources dynamically provided as service. The growth energy consumption associated to process resource allocation implemented in cloud issue needs be taken into consideration. Better performance will acquired by allowing same required workload performed using lower number servers, which could bring savings. So it requirement adopt efficient techniques order save and minimize...

The increasing demand for portable computing has elevated power consumption to be one of the most critical embedded systems design parameters. In this paper, we present a qualitative study wherein examine impact code transformations on energy and consumption. Three main categories are investigated, namely data, loop procedural oriented transformations. Moreover, evaluate influence employing single instruction multiple data (SIMD) dissipation via utilization compiler intrinsic C-functions....

Diabetic retinopathy (DR) diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features. This task is very difficult for ophthalmologists time-consuming. Therefore, computer-aided (CAD) systems were developed automate this screening process DR. In paper, a CAD-DR system proposed based on preprocessing pre-train transfer learning-based convolutional neural network (PCNN) five stages DR retinal images. To develop system,...

This paper introduces a VHDL realization of new efficient intra prediction scheme that aims to enhance the compression efficiency H.264 standard.The proposed algorithm is called Best Prediction Matrix Mode (BPMM).The main idea behind combine most usable modes, {vertical -horizontal -DC}, into mode.The performance with respect ratio, Peak Signal Noise Ratio (PSNR) and bit rate evaluated.The results show BPMM enhances ratio correspondingly it noticeably increases PSNR.

Since performance and power consumption optimizations are crucial issues in embedded systems, it is necessary to find a trade-off between these optimization goals. This paper explores the trade-offs of VLIW processor, specifically Texas Instruments TMS320C6416T DSP. We evaluate effect global as well specific architecture feature on targeted processor while running typical digital signal image processing algorithms. assess C64x+ feature, software pipelined loop (SPLOOP), well. The binaries...

Energy efficiency has become a main challenge in Wireless Sensor Networks (WSNs) and their applications. Localization is one of the indispensable stages WSN. generally refers to process locating position or more node(s) network. This paper develops evaluates an improved energy aware localization algorithm WSNs. Clustering techniques have been intensively presented literature as efficient techniques. The proposed approach enhances AlWadHA by integrating it with DUCA clustering scheme order...