The research aims to identify the availability of some basic competencies that are required to be available to workers in digital agricultural Extension from the point of view of senior management, middle management, and, employees with Post-graduate education degrees, represented by the following: Transition to digital agricultural Extension for sustainable and smart family farms, benefiting from international expertise and experiences in applying for Digital agricultural Extension, preparing and implementing Extension messages through platforms, factors affecting the effectiveness of digital agricultural Extension and its platforms, following up and evaluating the activities and programs of the digital Extension platform. The research population included agricultural Extension workers in senior management, middle management, and employees with Post-graduate education degrees in some of the governorates of the central region of Iraq, namely Baghdad, Holy Karbala, and Babel. A random sample was taken from the Post-graduate. The senior management, reached 46 respondents by 35%%, and 16 respondents, while the entire population was taken for senior management, which numbered 2, and the middle management, which numbered 41, and thus the sample subject to research became 59 respondents. A questionnaire was used to collect data from the respondents, consisting of 48 items, distributed over five areas: the transition to digital agricultural Extension for sustainable and smart family farms, benefiting from international expertise and experiences in the application of digital agricultural Extension, preparing and implementing Extension messages across platforms, factors Influencing the effectiveness of digital agricultural Extension and its media, following up and evaluating the activities and programs of the digital Extension platform at 11, 9, 10, 7, and 11 items, respectively, according to a quintuple scale, and the weighted mean, the weighted percentage, was used. The research concluded that there is a discrepancy in the respondents’ answers in the paragraphs of the five domains about the availability of some basic competencies among workers in digital agricultural Extension, which range from important to very important according to the scale of the importance level of quintiles, the highest value of which is 4 degrees and the lowest is zero, with a weighted average of the total for the five mentioned domains 3.25, 3.42 , 3.42, 3.42, 3.33 degrees and respectively The researcher recommends the necessity and importance of building human capital through the consolidation of these competencies through the continuous development and training of workers in digital Extension
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.
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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.
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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
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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
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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The undetected error probability is an important measure to assess the communication reliability provided by any error coding scheme. Two error coding schemes namely, Joint crosstalk avoidance and Triple Error Correction (JTEC) and JTEC with Simultaneous Quadruple Error Detection (JTEC-SQED), provide both crosstalk reduction and multi-bit error correction/detection features. The available undetected error probability model yields an upper bound value which does not give accurate estimation on the reliability provided. This paper presents an improved mathematical model to estimate the undetected error probability of these two joint coding schemes. According to the decoding algorithm the errors are classified into patterns and their decoding
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