Abstract: Objectives: To investigate the effect of temperature elevation on the bonding strength of resin cement to the zirconia ceramic using fractional CO2 laser. Background: Fractional CO2 laser is an effective surface treatment of zirconia ceramic, as it increases the bonding strength of zirconia to resin cement. Methods: Thirty sintered zirconia discs (10 mm diameter, 2 mm thickness) were prepared and divided to three groups (N=10) and five diffident pulse durations were used in each group (0.1, 0.5, 1, 5 and 10 ms). Group A was treated with 10 W power setting, group B with 20 W and group C with 30 W. During laser irradiation, temperature elevation measurement was recorded for each specimen. Luting cement was bonded to the treated zirconia surfaces and cured for 30 seconds. Shear bond strength was evaluated by a testing machine (universal) with bond failure mode determination. Results: The lowest temperature elevation measurement of the irradiated specimen which gave maximum shear bond strength was about 1.6±0.3 Ċ higher than ambient room temperature (27±0.2 ºC). Apparent micromechanical irregularities were seen in the treated samples and cracks formation with increased pulse duration and power setting were also observed. Conclusions: The temperature elevation is a vital factor in the surface roughness of zirconia ceramic with fractional CO2 laser irradiation and the lowest temperature elevation at best shear bond strength of zirconia ceramic to the resin cement is satisfied with the shorter pulse duration of 0.1 millisecond.
The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o
... Show MoreIn this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.
Secure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre
... Show MoreMerging biometrics with cryptography has become more familiar and a great scientific field was born for researchers. Biometrics adds distinctive property to the security systems, due biometrics is unique and individual features for every person. In this study, a new method is presented for ciphering data based on fingerprint features. This research is done by addressing plaintext message based on positions of extracted minutiae from fingerprint into a generated random text file regardless the size of data. The proposed method can be explained in three scenarios. In the first scenario the message was used inside random text directly at positions of minutiae in the second scenario the message was encrypted with a choosen word before ciphering
... Show MoreVol. 6, Issue 1 (2025)
Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on
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