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

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

Background: Phytotherapy is the usage of herbal species with medicinal properties for the management of various diseases. Gingivitis and periodontitis are diseases that involve the role of both the bacteria and the host immune response. Over the years, various researches have shown the importance of herbal products in the management of periodontal diseases. Aims of the study: To evaluate the efficacy of locally applied Salvia officinalis gel as adjunctive in the treatment of chronic periodontitis. Subjects and methods: Fourteen patients (10 males and 4 females) with chronic periodontitis were enrolled in the present study with total number of twenty-eight periodontal pockets utilizing a split mouth design, the pockets were divided i

The current study was conducted to evaluate the effect a mixture of threespecies of arbuscular mycorrhizal fungi (Glomus etunicatum, G. leptotichum andRhizophagus intraradices) double and triple mixture and organic matter by usingplastic pots in the greenhouse at some mycorrhiza and physiological limitationscharacteristics in tomato plant after four and eight weeks of cultivation. Theresults of the determinants mycorrhiza significant increase the percentage ofmycorrhizal frequency F% dry weight of roots mycorrhiza (g.plant-1) andorganic matter in all mycorrhiza single, double and triple mixture after four andeight weeks cultivation treatments. The highest percentage of mycorrhizalfrequency and increase the dry weight of the root in the trea

Background: The final stage of endodontic therapy is complete obturation of the root canal system to provide as perfect as possible at the cementodentinal junction of the apical foramen. The purpose of this in vitro study was to evaluate the sealing ability of injection molded thermoplasticized gutta percha and lateral condensation techniques with and without the use of sealers. Materials and Methods: Forty freshly extracted adult human maxillary central incisors with complete formed apices were utilized in this study. The teeth were randomly divided into four groups for evaluation of the apical seal. Group (1) lateral condensation gutta percha technique without sealer, (2) lateral condensation gutta percha technique with sealer, (3) Inject