The research aims to investigate the relationship and impact of e-governance as an independent variable in achieving creative performance as a dependent variable. These variables have been studied in the Directorate of Passports Affairs, and seek to come up with a set of recommendations that help in promoting e-governance in the researched organization, and the researcher adopted the descriptive-analytical approach, included The sample (122) of the total (194) individuals distributed in several administrative levels (officers, associates, and administrative staff). By adopting the questionnaire, which included (49) paragraphs as the main tool for the collection of data and information, as well as personal interviews and field observations as a tool to collect them, and for the processing of data and information, the research adopted the program (SPSS V., 24 & AMOS V., 24), the main conclusions The hypotheses have been demonstrated by the importance of the Directorate of Passport Affairs for its creative performance due to its interest in e-governance, especially through possessing the capabilities and human resources, and supporting it in monitoring and evaluation tools, adherence to standards and applications, and managing its financial resources and technology infrastructure.
In 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.
In this paper we show that if ? Xi is monotonically T2-space then each Xi is monotonically T2-space, too. Moreover, we show that if ? Xi is monotonically normal space then each Xi is monotonically normal space, too. Among these results we give a new proof to show that the monotonically T2-space property and monotonically normal space property are hereditary property and topologically property and give an example of T2-space but not monotonically T2-space.
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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In this paper, we introduce the concepts of Large-lifting and Large-supplemented modules as a generalization of lifting and supplemented modules. We also give some results and properties of this new kind of modules.
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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