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.
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show MoreIn aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we
... Show MoreThe idea of rhythm is basically associated with movement, as it is a regular frequency of movement combining between unity and change. Rhythm can be defined as a repetition of a certain element. Rhythm has a major role in the guiding poster which we are today in dire need for in light of escalation of coronavirus pandemic and its dire repercussions on entire international community, as the current research highlights the aesthetics of color rhythm in the guiding poster to confront coronavirus pandemic.
The spread of this invisible unknown horror preoccupied the world in different fields of scientific and human knowledge to the extent that man today has started looking for effective medical solutions to put an end to this pandemic
... Show MoreThis work is concerned with designing two types of controllers, a PID and a Fuzzy PID, to be used
for flying and stabilizing a quadcopter. The designed controllers have been tuned, tested, and
compared using two performance indices which are the Integral Square Error (ISE) and the Integral
Absolute Error (IAE), and also some response characteristics like the rise time, overshoot, settling
time, and the steady state error. To try and test the controllers, a quadcopter mathematical model has
been developed. The model concentrated on the rotational dynamics of the quadcopter, i.e. the roll,
pitch, and yaw variables. The work has been simulated with “MATLAB”. To make testing the
simulated model and the controllers m
This study explores eggshell waste as a low-cost, eco-friendly adsorbent for removing Aniline Blue dye from water. Batch and continuous experiments under various conditions showed effective performance. FTIR and SEM analyses confirmed porosity and functional groups. The adsorption followed the Sips isotherm and pseudo-first-order kinetics. The porous calcium carbonate structure enhanced dye removal. Thermodynamic results indicated an endothermic and spontaneous process. Lower flow rates improved performance in fixed-bed columns. The study supporting environmentally friendly solutions aligned with the Sustainable Development Goals (SDGs).
Two locally isolated microalgae (Chlorella vulgaris Bejerinck and Nitzschia palea (Kützing) W. Smith) were used in the current study to test their ability to production biodiesel through stimulated in different nitrogen concentration treatments (0, 2, 4, 8 gl ), and effect of nitrogen concentration on the quantity of primary product (carbohydrate, protein ), also the quantity and quality of lipid. The results revealed that starvation of nitrogen led to high lipid yielding, in C. vulgaris and N. palea the lipid content increased from 6.6% to 40% and 40% to 60% of dry weight (DW) respectively.Also in C. vulgaris, the highest carbohydrate was 23% of DW from zero nitrate medium and the highest protein was 50% of DW in the treatment 8gl. Whil
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The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca
Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.