Error control schemes became a necessity in network-on-chip (NoC) to improve reliability as the on-chip interconnect errors increase with the continuous shrinking of geometry. Accordingly, many researchers are trying to present multi-bit error correction coding schemes that perform a high error correction capability with the simplest design possible to minimize area and power consumption. A recent work, Multi-bit Error Correcting Coding with Reduced Link Bandwidth (MECCRLB), showed a huge reduction in area and power consumption compared to a well-known scheme, namely, Hamming product code (HPC) with Type-II HARQ. Moreover, the authors showed that the proposed scheme can correct 11 random errors which is considered a high

Grapes and grape seeds are important samples employed for environmental medical studies . The air of this work was to identify and concentration calculation of the elements in grapes fruit and thier seeds by using X-Ray fluoresces technique (XRF) . Samples were collected from Abo Ghraib of Baghdad city ,the grape seeds were obtained from those samples . Both samples were taken under experimental procedure to obtain the sample which were ready for analysis . The samples were then submitted to experimental conditions using a radiation source and then samples were applied for counting analysis shows the elements Na , Mg , Al , Si , P , S , Cl , K , Ca , and Sr as major components of the samples. Fe , Sr , I , Ba and V were

وفقأ للدراسات السابقة تم تحضير ليكاند آزو جديد (ن-(3-اسيتايل-2-هيدروكسي-5-مثيل-فنيل)ن-(4-كاربوكسي-سايكلوهكسيل مثيل)-ملح الدايازونيوم) وبعد التحقق من الصيغة المقترحة وفق نتائج التحاليل وبعد استخدام الليكاند لتحضير سلسلة ن المعقدات باستخدام نسب مولية متساوية (1:1) من الليكاند وتفاعلها مع كل من املاح المنغنيز والكوبلت والنيكل والنحاس والخارصين وبعد التحقق وفق تقنيات التحاليل الطيفية والتشخيصية(الاشعة فوق البنف

Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

Arabic calligraphy has a special status as one of the most important oriental arts, which has been enhanced by the Islamic value. The Arabic fonts have been diverse in their classification into soft lines such as Diwani, thuluth and patch lines and others, and geometrical lines such as Kufic lines and their various types. The contemporary artist was also able to adapt the Arabic calligraphy of all kinds in the construction of the painting or line formations, especially after the development of the artistic digital techniques and computer software. Here comes the role of the industrial designer as being more in touch with the practical, technical and productive life, which requires great care in adapting the line formations of the Arabic

The reciprocal relationship between the text and the mask in the printed product is one of the most important relationships that frame the level of communication between the appearance and the interior, although it is not cared for by some designers and publishing institutions. Therefore, the problem of research is determined by the following question (What is the dialectical relationship between the text and the mask in the literary books covers design?). The research aims to shed light on this problematic relationship at the level of reception and aesthetics at the same moment. The theoretical framework included two sections: the first (mask and text ... the concept and the mutual relationship), while the second section (trends in the

Organism is considered one of the intellectual products that search for compatibility and harmony with the natural environment. Man has adopted on since the ancient times in choosing his residence through imitating nature such as animal burrows, hives, bird nests and others of the natural manifestations being spontaneous inspirations. With the development of the age, these concepts turned into an analysis that examines the philosophy that deals with the shapes and functions of various elements in the nature as a source of inspiration, and discusses the call for contemplation and achieving benefits physically and spiritually in line with the nature of the organic thought that seeks to keep up with modern technologies that are characterize

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes