Color image compression is a good way to encode digital images by decreasing the number of bits wanted to supply the image. The main objective is to reduce storage space, reduce transportation costs and maintain good quality. In current research work, a simple effective methodology is proposed for the purpose of compressing color art digital images and obtaining a low bit rate by compressing the matrix resulting from the scalar quantization process (reducing the number of bits from 24 to 8 bits) using displacement coding and then compressing the remainder using the Mabel ZF algorithm Welch LZW. The proposed methodology maintains the quality of the reconstructed image. Macroscopic and quantitative experimental results on technical color images show that the proposed methodology gives reconstructed images with a high PSNR value compared to standard image compression techniques.
The current study deals with one of the ancient and modern techniques of ceramic art, which has evolved dramatically. This technique is interested in the muddy Body and its coloring, rather than interesting in the coloring of the layer on the surface of the glass port on the ceramic object. It is classified as ceramic techniques of the single heartburn, where use many coloring oxides. As well as, the use of (Pigment), which is often made of metal compounds, or metal oxides such as iron and manganese, copper and cobalt and more others.
The first chapter includes the problem, the importance, the goal, and the boundaries of the study. In addition, focuses on determining the terms such as (Sgrafitto). The second chapter consists of two to
The aim of this research is to find approaches between the communicative process and the teaching of art education. Postgraduate/Masters studies for the academic year 2022-2023.
In the light of this tool, the researcher reached a number of results, most notably: The art education teacher performs his communicative role correctly, as well as his ability to use verbal and non-verbal expressions and positive reinforcement clearly for the benefit of his students, and stimulates the largest number of their senses
Soil 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 MoreIn this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
... Show MoreReverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCG
... Show MoreThis study presents the concept of communicating as criticism analytical vision of art in general and contemporary composition particularly. Art is a means of communication for that activity to participate in the information or meanings, where the artwork is the message that includes what the artist sends ideas ,to the recipient . Thus, the language of communication between the artist and the receiver are made through the artwork (whatever his specialty: theatrically, plastic art, musically) and the magnitude of the meaning of outwardly or inwardly, is determined by the relationship between the artist and the recipient of which lead us turn to the issue of communication between them . .
At that determined search through which we seek
Domestic Technique in Batik Art
RA Ali, LK Abood, Int J Sci Res, 2017 - Cited by 2
Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this
paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will
be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to
solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the
domain of optimization and operation research. Several research papers dealt with methods of solving this
issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested
employing the improved algorithm to confirm its effectiveness and evaluate its ex
Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in
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