Die Forschung geht  um das wichtigste Thema für die literarischen Studien, die um die literarische Übersetzung und die Deutlichkeit dem Leser gekreist sind. Die literarische Übersetzung ist ein schwieriger Prozess, der auf vielseitigen Faktoren beruht ist, damit es erfolgreich gelungen ist. Dies ist auch ein gemeinsamer Prozess durch das Kunstwerk zwischen dem Autor und Übersetzer, so dass der erste Schritt in der vorliegenden Forschung wie folgendes lautet: muss es der Autor genau bestimmt wird, wie er die methodischen Grundprinzipien des Wekes im Dienst der zentralen Idee formuliert, und wie er die literarische Gestalt durch die voll erfassende Vorstellung des Wekes dichtet. Denn die literarische Arbeit besteht aus zwei Teilen

This search concerns study the crack growth in the wall of pipes made of low carbon steel under the impact load and using the effect of moisture (rate of moisture 50%). The environmental conditions were controlled using high accuracy digital control with sensors. The pipe has a crack already. The test was performed and on two type of specimens, one has a length of 100cm and other have length 50cm. The results were, when the humidity was applied to the pipe, the crack would enhance to grow (i.e. the number of cycles needed to grow the crack will reduce). In addition, when the test performed on the specimens of length 50cm the number of cycles needed to grow the crack is increased due to the effect of bending stress on the

Average interstellar extinction curves for Galaxy and Large Magellanic Cloud (LMC) over the range of wavelengths (1100 A0 – 3200 A0) were obtained from observations via IUE satellite. The two extinctions of our galaxy and LMC are normalized to Av=0 and E (B-V)=1, to meat standard criteria. It is found that the differences between the two extinction curves appeared obviously at the middle and far ultraviolet regions due to the presence of different populations of small grains, which have very little contribution at longer wavelengths. Using new IUE-Reduction techniques lead to more accurate result.

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

The aim of this paper is to present a weak form of -light functions by using -open set which is -light function, and to offer new concepts of disconnected spaces and totally disconnected spaces. The relation between them have been studied. Also, a new form of -totally disconnected and inversely -totally disconnected function have been defined, some examples and facts was submitted.

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com