The aim of the research is to identify the effect of instructional design according to Kagan structure among the first intermediate school student’s, and how skills could help in generating information in mathematics. In accordance with the research objectives, the researcher has followed the experimental research method by adopting an experimental design with two equivalent groups of post-test to measure skills in generating information. Accordingly, the researcher raised two main null hypotheses: there were no statistically significant differences at the level of significance (0.05) between the average scores of the experimental group who studied the material according to Kagan structure and th

 Finding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved.  In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)

APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023

Face Identification system is an active research area in these years. However, the accuracy and its dependency in real life systems are still questionable. Earlier research in face identification systems demonstrated that LBP based face recognition systems are preferred than others and give adequate accuracy. It is robust against illumination changes and considered as a high-speed algorithm. Performance metrics for such systems are calculated from time delay and accuracy. This paper introduces an improved face recognition system that is build using C++ programming language with the help of OpenCV library. Accuracy can be increased if a filter or combinations of filters are applied to the images. The accuracy increases from 95.5% (without ap

 Neuroimaging is a description, whether in two-dimensions (2D) or three-dimensions (3D), of the structure and functions of the brain. Neuroimaging provides a valuable diagnostic tool, in which a limited approach is used to create images of the focal sensory system by medicine professionals. For the clinical diagnosis of patients with Alzheimer's Disease (AD) or Mild Cognitive Impairs (MCI), the accurate identification of patients from normal control persons (NCs) is critical. Recently, numerous researches have been undertaken on the identification of AD based on neuroimaging data, including images with radiographs and algorithms for master learning. In the previous decade, these techniques were also used slowly to differentiate AD a

Most tubes are made from butyl rubbers, but certain types, such as giant tubes, are based on natural rubber because very high green strength is required when handling the uncured compound. By using blends of natural rubber (NR) and brominated butyl rubber (BIIR), it is possible to maintain high green strength in the uncured compound and improve impermeability and heat resistance of the cured tube.  The best formulations are obtained in the presence of 50 phr of (BIIR) to achieve desired mechanical properties. Improved impermeability was obtained by using 50 and 75 phr of (BIIR) rubber in compounds. Blending of brominated butyl rubber (BIIR) with natural rubber (NR) enhances air retention with acceptable sacrifices in green strength.

In this paper, an adaptive polynomial compression technique is introduced of hard and soft thresholding of transformed residual image that efficiently exploited both the spatial and frequency domains, where the technique starts by applying the polynomial coding in the spatial domain and then followed by the frequency domain of discrete wavelet transform (DWT) that utilized to decompose the residual image of hard and soft thresholding base. The results showed the improvement of adaptive techniques compared to the traditional polynomial coding technique.

A principal problem of any internet user is the increasing number of spam, which became a great problem today. Therefore, spam filtering has become a research fo-cus that attracts the attention of several security researchers and practitioners. Spam filtering can be viewed as a two-class classification problem. To this end, this paper proposes a spam filtering approach based on Possibilistic c-Means (PCM) algorithm and weighted distance coined as (WFCM) that can efficiently distinguish between spam and legitimate email messages. The objective of the formulated fuzzy problem is to construct two fuzzy clusters: spam and email clusters. The weight assignment is set by information gain algorithm. Experimental results on spam based benchmark