Background: The bond strength of the root canal sealers to dentin seems to be a very important property for maintaining the integrity and the seal of root canal filling. The aim of this study was to evaluate the shear bond strength of four different obturation systems using push-out test. Materials and methods: Forty straight palatal roots of the maxillary first molars teeth were used in this study, these roots were instrumented using crown down technique and ProTaper system, instrumentation were done with copious irrigation of 2.5% sodium hypochlorite and 17% buffered solution of EDTA was used as final irrigant followed by distilled water, roots were randomly divided into four groups according to the obturation system (ten teeth for each group): Group I: AH26 sealer and lateral condensation technique, Group II: AH26 sealer and single cone obturation technique, Group III: AH26 sealer and thermafil obturation technique and Group IV: RealSeal SE sealer and lateral condensation technique, the roots then stored in moist environment at 37°C for one week The roots were embedded in clear acrylic resin and each root sectioned into three levels apical, middle and cervical. The measurement of each section was taken to prepare the supporting jig for the sections and the punch used in pushout test, the bond strength was measured using computerized universal testing machine each section fixed in the machine so that the load applied from apical to cervical direction at 0.5mm/min. speed and the computer drew curve to show the higher bond force before dislodgment of the filling material. These forces were divided by the surface area to obtain the bond strength in MPa. Results: Statistical analysis was performed and the result showed avery highly significant differences between the four obturation systems at each level and there were non significant differences between all level apical, middle and cervical within each obturation system except a significant difference found between cervical and apical level in single cone obturation system. Conclusion: This study showed that the shear bond strength of AH26 sealer was higher than RealSeal SE sealer when the same obturation technique was used. The shear bond strength was affected by the obturation technique and lateral condensation technique showed higher bond strength than thermafil and single cone obturation technique when the same type of sealer was used and the bond strength was not or little affected by the tooth level
The aim of this paper is to design a PID controller based on an on-line tuning bat optimization algorithm for the step-down DC/DC buck converter system which is used in the battery operation of the mobile applications. In this paper, the bat optimization algorithm has been utilized to obtain the optimal parameters of the PID controller as a simple and fast on-line tuning technique to get the best control action for the system. The simulation results using (Matlab Package) show the robustness and the effectiveness of the proposed control system in terms of obtaining a suitable voltage control action as a smooth and unsaturated state of the buck converter input voltage of ( ) volt that will stabilize the buck converter sys
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In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an
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In this paper a system is designed on an FPGA using a Nios II soft-core processor, to detect the colour of a specific surface and moving a robot arm accordingly. The surface being detected is bounded by a starting mark and an ending mark, to define the region of interest. The surface is also divided into sections as rows and columns and each section can have any colour. Such a system has so many uses like for example warehouses or even in stores where their storing areas can be divided to sections and each section is coloured and a robot arm collects objects from these sections according to the section’s colour also the robot arm can organize objects in sections according to the section’s colour.
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s
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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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The competition in the hotel sector, globalization and the development of new information have forced the sector to continuously seek new techniques and arrangements to remain competitive through hotel industry companies, including Benchmarking and the application of this method in the hotel sector. The selection of the Rashid International Hotel by the Ministry of Tourism as a leading hotel or benchmark for comparison of other hotels in Iraq, and the selection of two hotels in Baghdad for comparison, namely (Ishtar International Hotel, Baghdad International Hotel) and the choice also by the Ministry of Tourism, N is to correct the course of practice to manage the cost and diagnosis of the weakness of the strengths and weaknesses in the
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