This study is conducted to investigate the validity of using different levels of Rustumiya sewage water for irrigation and their effects on corn growth and some of the chemical properties of the soil such as electrical conductivity and soil pH in extract soil paste , the micro nutrient content in soil and plant which are ( Fe , Mn , Zn , Cu , Cd , Pb ). Three levels of sewage water ( 0 , 50 , 100 )% in two stages were used ,the three levels of wastewater ( without soil fertilization ) were used in the first stage , Where 80 Kg N /D+50Kg P2O5 /D was added to the soil as fertilizer in the control (0%) treatment and 40 Kg N/D+25Kg P2O5/D were added to 50 and 100% levels in the second stage .Corn seeds were planted in 12kg plastic pots in Com

Water supply networks are marred by serious risks of imperceptible pipeline leakage, posing ‎sustainability ‎and ‎performance ‎threats.  This article highlights the use of vibratory signal features to get around the drawbacks of traditional methods in a highly detailed framework for leak detection based on CatBoost. demonstrated excellent diagnostic performance and carried out a thorough test performance evaluation on five leakage configurations  . The expected system achieved an accuracy of 98.1% (variance (well within x/3% of expected):, beating traditional competitors such as Random Forest (97.3%) and Support Vector Machine (93.8%). ‎For example, the area under the receiver-operating characteristic curve was 0.995, in

تضمن هذا العمل تحضير ليكند قاعدة شيف جديدة مشتقة من مادة البولي أكريلاميد والكلوترالديهايد [(2S, 2'S) – N, N' - (pentane-1, 5-diylidene) bis (2- methylbutan amide)]  مع بعض المعادن الثقيلة (Cr + 3 Mn + 3 , Fe + 3 , ,Co + 2,  Ni + 2 ,Cu + 2  Zn + 2 , Cd + 2,) لتنتج المعقدات المقابلة. تم تشخيص قواعد شيف ومعقداتها المعدنية بأستخدام طيف الأشعة تحت الحمراء والأشعة المرئية وفوق البنفسجية، والتوصيلية ,وقيم المغناطيسية والتحليل الحراري الوزني وحيود الأشعة السينية ومجه

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

<span>We present the linearization of an ultra-wideband low noise amplifier (UWB-LNA) operating from 2GHz to 11GHz through combining two linearization methods. The used linearization techniques are the combination of post-distortion cancellation and derivative-superposition linearization methods. The linearized UWB-LNA shows an improved linearity (IIP3) of +12dBm, a minimum noise figure (NF_min.) of 3.6dB, input and output insertion losses (S₁₁ and S₂₂)  below -9dB over the entire working bandwidth, midband gain of 6dB at 5.8GHz, and overall circuit power consumption of 24mW supplied from a 1.5V voltage source. Both UWB-LNA and linearized UWB-LNA designs are

Hiding technique for dynamic encryption text using encoding table and symmetric encryption method (AES algorithm) is presented in this paper. The encoding table is generated dynamically from MSB of the cover image points that used as the first phase of encryption. The Harris corner point algorithm is applied on cover image to generate the corner points which are used to generate dynamic AES key to second phase of text encryption. The embedded process in the LSB for the image pixels except the Harris corner points for more robust. Experimental results have demonstrated that the proposed scheme have embedding quality, error-free text recovery, and high value in PSNR.

Deep Learning Techniques For Skull Stripping of Brain MR Images