The present study aims to identify the extent to which biology book of sixth grade achieves the basic scientific aspects in light of its scientific objectives. To achieve this goal, the researcher needed to build two questionnaires to evaluate the biology book for sixth-grade. To answer the questions of the study, the researcher used the following statistical methods : the weighted average, and percentages; and to identify the extent to match the perspective of teachers of the material with the perspective of a researcher in each paragraph of the questionnaire as well as the degree of severity of each paragraph in the book neighborhoods sixth-grade has reached Aalbagesh to several of the most important results: 1. All the teachers were w

     Peaceful coexistence is not seen as a new topic of secretions of modern civilization, a requirement to solve the problems of our era or one of the indications of urgent immediate needs, rather, tolerance is considered basis for building a state. Therefore, we can touch on the principles and basics of tolerance in the Holy Qur’an, the speeches of the Messenger (may God bless him and grant him peace) and his hadiths, and the principle of brotherhood that he established

Supply Chain Management (SCM) attempts to a create a synchronization of the firm’s processes and those of the supplier to match the flow of materials, services, and information with the customer demand. Due to its importance, the SCM has become inevitable to modern companies. Therefore this research work has been conducted to set a theoretical and applied basis to assist the 1 AYAR factory in adopting the Electronic Supply Chain (e-SC).  To accomplish that the searchers applied many tools such as: quantitative and qualitative analysis, process analysis, Visual Basic software, Monte Carlo Simulation to simulation the designed supply chain to compare its performance against the actual performance of the current supply chain

Performance measures are a central component of management control system, making good planning and control decisions requires information about how different subunits of organizations have performed. To be effective, performance measures (both financial and nonfinancial) must also motivate managers and employees at all levels of organization to strive to achieve organization goals.

To give aclear picture about performance must be used compound measure, that was best than single measure.

Altman model can be used as a compound performance measure that measures the performance by tied a sum of variables, due to make weight for every variable to reach for performance.

Eight different Dichloro(bis{2-[1-(4-R-phenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})iron(II) compounds, 2–9, have been synthesised and characterised, where group R=CH3 (L2), OCH3 (L3), COOH (L4), F (L5), Cl (L6), CN (L7), H (L8) and CF3 (L9). The single crystal X-ray structure was determined for the L3 which was complemented with Density Functional Theory calculations for all complexes. The structure exhibits a distorted octahedral geometry, with the two triazole ligands coordinated to the iron centre positioned in the equatorial plane and the two chloro atoms in the axial positions. The values of the FeII/III redox couple, observed at ca. −0.3 V versus Fc/ Fc+ for complexes 2–9, varied over a very small potential range of 0.05 V.

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec