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

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

The spread of Coronavirus has forced populations around the globe to adopt strict measures such as lockdown, home quarantine, and home office. Moreover, in the current development of network communications, people can exploit internet and intranet features in many systems that need to be faster, more efficient, and available on time. Furthermore, with the benefits of using internet-of-things (IoT), through which things are generated, gained, discovered, and proposed without interference, the user could receive the last status without exertion and direct contact (i.e., in a contactless manner). These specifications can be used in a transaction system. This paper proposes an electronic transaction system (ETS) as a replacement for the curr

واحدة من أكثر مواد السيراميك الهيكلية الواعدة هي كربيد السيليكون(SiC) ، حيث له خصائص حرارية وكهروميكانيكية ممتازة. هذه الخصائص مفيدة ل CMC لتعزيز أداء المركب خاصة عند إضافات النانو المتكاملة. في هذا البحث, تم تصنيع مركب SiC من SiC بثلاثة تركيزات مع  ZnO و Si. تم اختبار الخواص المغناطيسية لجميع المخاليط باستخدام مراقبة العينة الاهتزازية (VSM). تم تلبيد العينات الخضراء في فرن التلبيد عند 1600 درجة مئوية في بيئة النيتروجي

Clobetasol propionate (CP) is a super potent corticosteroid widely used to treat various skin disorders such as atopic dermatitis and psoriasis. However, its utility for topical application is hampered due to its common side effects, such as skin atrophy, steroidal acne, hypopigmentation, and allergic contact dermatitis. Microsponge is a unique three-dimensional microstructure particle with micro and nano-meters-wide cavities, which can encapsulate both hydrophilic and lipophilic drugs providing increased efficacy and safety. The aim of the current study is to prepare and optimize clobetasol-loaded microsponges. The emulsion solvent diffusion method is used for the preparation of ethylcellulose (EC)-based microsponges. The impact of

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea

In this paper, a microcontroller-based electronic circuit have been designed and implemented for dental curing system using 8-bit MCS-51 microcontroller. Also a new control card is designed while considering advantages of microcontroller systems the time of curing was controlled automatically by preset values which were input from a push-button switch. An ignition based on PWM technique was used to reduce the high starting current needed for the halogen lamp. This paper and through the test result will show a good performance of the proposed system.