Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

The psychological scientific studies suggest that basic human situations stem from human emotional abilities and those with a lack of emotional intelligence are unable to cope with life, which might lead to anxiety and psychological depression. The current study aimed to investigate this problem by identifying the level of emotional intelligence and psychological depression among the students of the University of Anbar. To achieve the objectives of the study, the researchers created two questionnaires: 1) to measure emotional intelligence. 2) to measure psychological depression and applied these questionnaires on (300) students. The results revealed that the participants showed a high level of emotional intelligence with a low level of p

This work analyzes the effectiveness of an artificial intelligence (AI) community- building workshop designed for high school teachers and it focuses on contemporary issues related to AI concepts and applications. A group of high school teachers from local education districts attended a one-day AI hands-on workshop at our university. The workshop included several AI-related topics and hands-on examples and exercises aiming to introduce AI concepts and tools relevant to pre-college education. The participating teachers were expected to become a part of a collaborative network created to design, develop, and implement novel AI learning modules for high school students. Initial and a post-training surveys have been used to measure the

Hormones, their receptors, and the associated signaling pathways make compelling drug targets because of their wide-ranging biological significance to study the role of asprosin in obese male patients with diabetic mellitus type II. ELISA method was used to assay asprosin and insulin. Blood was taken with drawn sample from 30 obese normal patients with age range (40-60) years, 30 diabetic patients with age range (40-60) years at duration of disease (1-5) years and 30 normal healthy patients. The mean difference between T2DM according to insulin % (23.8±0.6) was increased than the mean of IFG (17.7±1.0) (P 0.000). The mean difference between T2DM according to asprosin (122.1±21.8) was increased than the mean of IFG (51.4±2.7) (P 0

Abstract

The research aims to measure family negligence and its relationship with internet addiction among university students. The researcher has developed a scale of (20) items to measure the negligence of family, which was applied to (308) male and female university students in the first and fourth stages. The research concluded that University students suffer from family negligence. The research sample has an addiction to the Internet. There is a relationship between family neglect and addiction to the Internet among university students. The researcher came out with a number of suggestions and recommendations.

In this paper, we proved that if R is a prime ring, U be a nonzero Lie ideal of R , d be a nonzero (?,?)-derivation of R. Then if Ua?Z(R) (or aU?Z(R)) for a?R, then either or U is commutative Also, we assumed that Uis a ring to prove that: (i) If Ua?Z(R) (or aU?Z(R)) for a?R, then either a=0 or U is commutative. (ii) If ad(U)=0 (or d(U)a=0) for a?R, then either a=0 or U is commutative. (iii) If d is a homomorphism on U such that ad(U) ?Z(R)(or d(U)a?Z(R), then a=0 or U is commutative.

Home New Trends in Information and Communications Technology Applications Conference paper Audio Compression Using Transform Coding with LZW and Double Shift Coding Zainab J. Ahmed & Loay E. George Conference paper First Online: 11 January 2022 126 Accesses Part of the Communications in Computer and Information Science book series (CCIS,volume 1511) Abstract The need for audio compression is still a vital issue, because of its significance in reducing the data size of one of the most common digital media that is exchanged between distant parties. In this paper, the efficiencies of two audio compression modules were investigated; the first module is based on discrete cosine transform and the second module is based on discrete wavelet tr