Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under detection is one of the results of the proposed classifier. The work demanded the collection of about 5000 color codes which in turn were subjected to algorithms for training and testing. The open-source platform TensorFlow for ML and the open-source neural network library Keras were used to construct the algorithm for the study. The results showed an acceptable efficiency of the built classifier represented by an accuracy of 90% which can be considered applicable, especially after some improvements in the future to makes it more effective as a trusted colorimeter.
The agricultural activity has a great significance in the all four dimensions of sustainable development. Firstly, the economic dimension which it contributes with the GDP, as well as, it is considered as an important source to attract the investment. Secondly, the environmental dimension which also contributes with conserving of the biodiversity, combating the desertification, and increasing the farmlands. Thirdly, for its role in the social dimension to achieve the food security, to eradicate the poverty, and providing jobs. Fourthly, toward the institutional dimension as well it is considered as a source that allows all people to participate effectively, and to exchange of the local and universal experiences and perspectives. For conf
... Show MoreSupervised By : Prof. dr. Shaker Jaseem Mohammed This research aims to identify the (effectiveness of Bayer's strategy in the development of deductive thinking among students in the fifth grade literary material European history) and to achieve the goal set researcher null hypothesis of the following: • There is no statistically significant difference between the average scores of the experimental group which studied the use of Bayer's strategy and the control group, which studied the use of the usual way in the development of deductive reasoning. The study sample consisted of (84 students) of the students in the fifth grade literary breeding Baghdad / Karkh second Directorate for the academic year 2015-2016 were distributed Aanhaldras
... Show Morethe reality of small and medium enterprises analysis reflects weaknesses plaguing these enterprises and strengths that are characterized by, and thus the formulation of appropriate solutions to the obstacles faced by these enterprises to enhance its contribution to the achievement of economic and social development. Iraqi small and medium enterprises suffer from several obstacles stand in front of development and support their competitiveness, the finance one of the main obstacles which impede growth and development of these enterprises, noting the banking system in Iraq reluctance to lend to small and medium-sized enterprises, as a result of the high cost of lending these enterprises compared to large projects, as well as
... Show MoreThis paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord
... Show MoreThe interest in art for young ages is seen as an obvious breakthrough and as revealing of psychological and health feelings in addition to emotions, and it is a treatment for those who suffer from behavioral disorders. The problem arose with the following question: What is the role of artistic expression in diagnosing behavioral disorders for primary school pupils? The aim of the research is to detect the behavioral disorders in the artistic expression of the female students' paintings from the teachers' point of view. The descriptive analytical approach was adopted as it is the appropriate method for identifying and estimating the characteristics and features related to people, places and things, and analyzing situations or phenomena as a
... Show MorePurpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa
... Show MoreEvolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E
... Show MoreThe COVID-19 pandemic has had a huge influence on human lives all around the world. The virus spread quickly and impacted millions of individuals, resulting in a large number of hospitalizations and fatalities. The pandemic has also impacted economics, education, and social connections, among other aspects of life. Coronavirus-generated Computed Tomography (CT) scans have Regions of Interest (ROIs). The use of a modified U-Net model structure to categorize the region of interest at the pixel level is a promising strategy that may increase the accuracy of detecting COVID-19-associated anomalies in CT images. The suggested method seeks to detect and isolate ROIs in CT scans that show the existence of ground-glass opacity, which is fre
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