Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

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. This paper investigates the feasibility of using chaotic communications over Multiple-Input Multiple-Output (MIMO) channels by combining chaos modulation with a suitable Space Time Block Code (STBC). It is well known that the use of Chaotic Modulation techniques can enhance communication security. However, the performance of systems using Chaos modulation has been observed to be inferior in BER performance as compared to conventional communication

Luminescent solar concentrator (LSC) are used to enhance       photoresponsivity of solar cell. The Quantumdots luminescent solar concentrator (QDLSC) consists of CdSe/CdS core/shell nanoparticles embedded in polyacrylamide polymer matrix positioned on the top surface of the silicon solar cell. This procedure improves the conversion efficiency of the bare silicon solar cell. The conversion efficiency of the solar cell has increased from 7.3% to 10.3%.  this improvement is referred to the widening of the response spectral region window  of the a- Si. Solar cell.

       Copper Phthalocyanine (CuPc) thin film with and without multi-walled carbon nanotubes (MWCNTs) is prepared using the solution based method and used in gas sensor and solar cell applications. The structural characteristics of the CuPc thin films showed a single peak around 7^o with the preferred orientation for charge transportation. Using atomic force microscopy (AFM), morphological properties show a rough surface with some aggregates and ribbons. The optical absorption properties were determined using UV-Visible absorption spectroscopy; the optical band gap has varied after adding MWCNTs to CuPc. Electrical conductivity of CuPc:MWCNTs composite is higher than that of the pure CuPc. The CuPc thin film sensr have sh

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

In this research paper, a new blind and robust fingerprint image watermarking scheme based on a combination of dual-tree complex wavelet transform (DTCWT) and discrete cosine transform (DCT) domains is demonstrated. The major concern is to afford a solution in reducing the consequence of geometric attacks. It is due to the fingerprint features that may be impacted by the incorporated watermark, fingerprint rotations, and displacements that result in multiple feature sets. To integrate the bits of the watermark sequence into a differential process, two DCT-transformed sub-vectors are implemented. The initial sub-vectors were obtained by sub-sampling in the host fingerprint image of both real and imaginary parts of the DTCWT wavelet coeffi