This paper presents the results of investigating the vibrational characteristics of oblate dish with and without framed structure . A finite element method, was applied to the dynamic analysis of oblate spheroidal shell. Different types of elements were considered in one dimension and two dimensions. It was found that the natural frequencies of oblate shells had two types of behavior against increasing the shell thickness and eccentricity, which are the membrane mode and bending mode –Since – the membrane modes natural frequencies tend to increase with the increasing the eccentricity of oblate, while the bending modes natural frequencies decrease with the increasing the eccentricity till reach the optimum eccentricity.

تستهدف هذه الدراسة وبشكل أساس، الكشف عن طبيعة وخصائص البعد السياسي لهندسة/صناعة الخصائص الاجتماعية والسياسية للإنسان والمجتمع، بوصفها العملية المسؤولة عن تصميم هذه الخصائص وصناعتها وتغييرها جزئيا أو كليا، دون أبعادها الأخرى المتعددة والمتنوعة، لا لمجرد الانسياق وراء دوافع الرغبة الذاتية، أو اعتبارات التخصص الدقيق وأحكامه، لأن معهما أيضا، بل وقبلهما أحيانا، دوافع واعتبارات أخرى موضوع

Abstract: The premise of the study is that populism is a process of building political views and critical intellectual orientations among the general public. It is transformed into mass beliefs by mobilizing the society ideologically and continuously in order to reach or control the circle of authority. We distributed the study topics to four sections: In the second, we will discuss the contents of contemporary populism and how other forms of populism evolved historically. The third is to discuss the political discourse of populism among the military regimes and the comparative Islamic parties in the Middle East, especially in terms of the essence and the intellectual foundations. The fourth section seeks to examine the characteristics o

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

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

Merging 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

Vol. 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