The aim of the research is to identify the educational and psychological effects of the positive and negative aspects of using social networking websites. The researcher administered a number of questions to (250) users of different types of social networking websites. He analyzed his research results and obtained a number of results. The research has reached a number of recommendations and suggestion: Regulating the use of social media. Monitoring the parents of the sites used by children in a way that they do not feel they are observers. It is necessary to devote an hour daily to show the importance of real social life for children other than using social media. It is necessary to show the importance of choosing friends who have a good reputation. It is necessary to assign a little time each week to meet family outside the house or visit relatives that help children to communicate with other changing the electronic communication to the real social media. It is necessary to show television programs to alert young people to the dangers of addiction to the psychological and educational internet. It is necessary to prepare annual calendar posters that alert students in schools and universities to the type of risks, including the risks of incorrect use of the Internet. It is necessary to prepare an educational curriculum that is not intended for the exam and does not fall within the exams and grades in the schools and universities, as much as it aims to build psychological and educational values according to the customs and traditions of ancient Iraq.
This paper deals with the F-compact operator defined on probabilistic Hilbert space and gives some of its main properties.
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
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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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