The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits
... Show MoreIn the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.
This research aims to investigate and improve multi-user free space optic systems (FSO) based on a hybrid subcarrier multiplexing spectral amplitude coding-optical code division multiple access (SCM-SAC-OCDMA) technique using MS code with a direct decoding technique. The performance is observed under different weather conditions including clear, rain, and haze conditions. The investigation includes analyzing the proposed system mathematically using MATLAB and OptiSystem software. The simulation is carried out using a laser diode. Furthermore, the performances of the MS code in terms of angles of bit rate, beam divergence and noise are evaluated based on bit error rate (BER), received
The principal factor in the proofs of many so-called intersection results and associated best approximation theorems—such as the famed Brouwer fixed-point theorem) is Knaster-Kuratowski-Mazurkiewicz theorem (KKM), which was extended from Rl to Hausdorff vector spaces by Ky Fan. This kind of theory necessitates introducing some form of abstract convex structure on a topological space. In both pure and applied mathematics, the theory of approximation plays a central role. The connection between best approximation and fixed-point theory provides a powerful tool for analyzing the nonlinear maps, the convergence of iterative processes, and the solving of variational problems. This paper is dedicated to presenting a new extension of the
... Show MoreIn this paper, some basic notions and facts in the b-modular space similar to those in the modular spaces as a type of generalization are given. For example, concepts of convergence, best approximate, uniformly convexity etc. And then, two results about relation between semi compactness and approximation are proved which are used to prove a theorem on the existence of best approximation for a semi-compact subset of b-modular space.
Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand
... Show MoreSoil tillage is a critical agricultural practice that creates favorable conditions for seedbed preparation and plant growth. This study presents an innovative application of artificial intelligence (AI) in agriculture by employing the YOLOv7 algorithm to classify and assess post-tillage soil surface conditions, a domain underexplored in current research. The integration of mechanical operation parameters with AI-based image classification enables optimization of tillage quality and mitigation of soil compaction, highlighting the novelty of this approach. The study aims to improve the efficiency of moldboard plow operations by examining the effects of tillage speed and depth on soil clod distribution, fuel consumption, and power requ
... Show MoreMoment invariants have wide applications in image recognition since they were proposed.