Collagen triple helix repeat containing-1 (CTHRC1) is an essential marker for Rheumatoid Arthritis (RA), but its relationship with pro-inflammatory, anti-inflammatory, and inflammatory markers has been scantily covered in extant literature. To evaluate the level of CTHRC1 protein in the sera of 100 RA patients and 25 control and compare levels of tumour necrosis factor alpha (TNF-α), interleukin 10 (IL-10), RA disease activity (DAS28), and inflammatory factors. Higher significant serum levels of CTHRC1 (29.367 ng/ml), TNF-α (63.488 pg/ml), and IL-10 (67.1 pg/ml) were found in patient sera as compared to that in control sera (CTHRC1 = 15.732 ng/ml, TNF-α = 33.788 pg/ml, and IL-10 = 25.122 pg/ml). There was no significant correlation be

Collagen triple helix repeat containing-1 (CTHRC1) is an essential marker for Rheumatoid Arthritis (RA), but its relationship with pro-inflammatory, anti-inflammatory, and inflammatory markers has been scantily covered in extant literature. To evaluate the level of CTHRC1 protein in the sera of 100 RA patients and 25 control and compare levels of tumour necrosis factor alpha (TNF-α), interleukin 10 (IL-10), RA disease activity (DAS28), and inflammatory factors. Higher significant serum levels of CTHRC1 (29.367 ng/ml), TNF-α (63.488 pg/ml), and IL-10 (67.1 pg/ml) were found in patient sera as compared to that in control sera (CTHRC1 = 15.732 ng/ml, TNF-α = 33.788 pg/ml, and IL-10 = 25.122 pg/ml). There was no significant correlati

      In education, exams are used to asses students’ acquired knowledge; however, the manual assessment of exams consumes a lot of teachers’ time and effort. In addition, educational institutions recently leaned toward distance education and e-learning due the Coronavirus pandemic. Thus, they needed to conduct exams electronically, which requires an automated assessment system. Although it is easy to develop an automated assessment system for objective questions. However, subjective questions require answers comprised of free text and are harder to automatically assess since grading them needs to semantically compare the students’ answers with the correct ones. In this paper, we present an automatic short answer grading metho

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

The digital multimedia systems become standard at this time because of their extremely sensory activity effects and also the advanced development in its corresponding technology. Recently, biological techniques applied to several varieties of applications such as authentication protocols, organic chemistry, and cryptography. Deoxyribonucleic Acid (DNA) is a tool to hide the key information in multimedia platforms.
In this paper, an embedding algorithm is introduced; first, the image is divided into equally sized blocks, these blocks checked for a small amount color in all the separated blocks. The selected blocks are used to localize the necessary image information. In the second stage, a comparison is between the initial image pixel

Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

    Multiple applications use offline handwritten signatures for human verification. This fact increases the need for building a computerized system for signature recognition and verification schemes to ensure the highest possible level of security from counterfeit signatures. This research is devoted to developing a system for offline signature verification based on a combination of local ridge features and other features obtained from applying two-level Haar wavelet transform. The proposed system involves many preprocessing steps that include a group of image processing techniques (including: many enhancement techniques, region of interest allocation, converting to a binary image, and Thinning). In feature extraction and