Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

Homomorphic encryption became popular and powerful cryptographic primitive for various cloud computing applications. In the recent decades several developments has been made. Few schemes based on coding theory have been proposed but none of them support unlimited operations with security.   We propose a modified Reed-Muller Code based symmetric key fully homomorphic encryption to improve its security by using message expansion technique. Message expansion with prepended random fixed length string provides one-to-many mapping between message and codeword, thus one-to many mapping between plaintext and ciphertext. The proposed scheme supports both (MOD 2) additive and multiplication operations unlimitedly.   We make an effort to prove

Translation is both a social and cultural phenomenon, it can neither exist outside a social community and it is within society, nor it can be viewed as a medium of cross-cultural fertilization. This paper aims to investigate the difficulties that a translator may face when dealing with legal texts such as marriage and divorce contracts. These difficulties can be classified according to the present paper into syntactic, semantic, and cultural. The syntactic difficulties include word order, syntactic arrangement, unusual sentence structure, the use of model verbs in English, and difference in legal system. As to the semantic difficulties, they involve lack of established terminology, finding functional and lexical equivalence, word for word t

Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use

Obesity is a common disease that resulted from over-nutrition in adults and children. It rarely causes damage to the centers of food in the brain. Obesity is defined as an increased body weight from its natural limit which is resulted from the accumulation of excessive amounts of fatty tissue incredibly up to 20% in males, 30 % in females unless this increase is not due to an increase in muscles as in athletes or accumulation of water in the body which is resulted from Mesothelioma or the magnitude of the skeleton.Obesity is the increase of the total average of fat in the body compared to other tissues, which causes an increasing body weight, thereby increasing body mass. The fatty child has an increase in the stored fatty layer under th

The human being is a social being and human communication is a fundamental axis in the process of social interaction, and the characteristic of social shyness grows through the interaction of the individual with his environment. Identifying the level of shyness among university students, and identifying the differences in shyness among university students according to specialization (scientific, humanities). In order to achieve the objectives of the research, the researcher prepared a measure of shyness based on Zimbardo's theory, and the components that he identified are the (behavioral, cognitive, and emotional components). The validity and reliability were calculated using the Cronbach's alpha method, reaching (0.94), and the scale in