In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.
Large quantities of contaminated carwash wastewater are produced per day from carwash places. Extensively it contains large quantities of chemicals from detergents, oil, grease, heavy metals, suspended solids, types of hydrocarbons, and biological contents. A novel electrocoagulation treatment by foil electrodes was conducted to remove COD, turbidity, Total Dissolved Solids (TDS) from contaminated carwash wastewater and decrease its Electrical Conductivity (EC). A thin layer of aluminum foil is used as an electrode in this treatment process. The effects of different voltage and treatment times were studied. The best result was found at a voltage of 30 volts and treatment time 90 minute where the removal efficiency of COD
... Show MoreThe manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co
... Show MoreThe Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process
Wireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8
Different injection material types were tried in the injection of soft clay, such as lime (L), silica fume (SF), and leycobond-h (LH). In this study, experiments were made to study the effect of injection on soft clay consolidation settlement. A sample of natural soft clayey soil was investigated in the laboratory and the sample was injected with each of the grout materials used, L, SF, L + SF, and L + SF + LH. A 20 cm3 of each slurry grout was conducted into the soil, which was compacted in California Bearing Ratio (CBR) mold and cured for 7 days, and then the sample was loaded to 80 N load by a circular steel footing 60 mm in diameter. The settlement was r
In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
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