<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>
Data centric techniques, like data aggregation via modified algorithm based on fuzzy clustering algorithm with voronoi diagram which is called modified Voronoi Fuzzy Clustering Algorithm (VFCA) is presented in this paper. In the modified algorithm, the sensed area divided into number of voronoi cells by applying voronoi diagram, these cells are clustered by a fuzzy C-means method (FCM) to reduce the transmission distance. Then an appropriate cluster head (CH) for each cluster is elected. Three parameters are used for this election process, the energy, distance between CH and its neighbor sensors and packet loss values. Furthermore, data aggregation is employed in each CH to reduce the amount of data transmission which le
... Show MoreMany approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so
... Show MoreAn application of neural network technique was introduced in modeling the point efficiency of sieve tray, based on a
data bank of around 33l data points collected from the open literature.Two models proposed,using back-propagation
algorithm, the first model network consists: volumetric liquid flow rate (QL), F foctor for gas (FS), liquid density (pL),
gas density (pg), liquid viscosity (pL), gas viscosity (pg), hole diameter (dH), weir height (hw), pressure (P) and surface
tension between liquid phase and gas phase (o). In the second network, there are six parameters as dimensionless
group: Flowfactor (F), Reynolds number for liquid (ReL), Reynolds number for gas through hole (Reg), ratio of weir
height to hole diqmeter
In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t
... Show MoreThis investigation was carried out to study the treatment and recycling of wastewater in the cotton textile industry for an effluent containing three dyes: direct blue, sulphur black and vat yellow. The reuse of such effluent can only be made possible by appropriate treatment method such as chemical coagulation. Ferrous and ferric sulphate with and without calcium hydroxide were employed in this study as the chemical coagulants.
The results showed that the percentage removal of direct blue ranged between 91.4 and 94 , for sulphur black ranged between 98.7 and 99.5 while for vat yellow it was between 97 and 99.
Steganography can be defined as the art and science of hiding information in the data that could be read by computer. This science cannot recognize stego-cover and the original one whether by eye or by computer when seeing the statistical samples. This paper presents a new method to hide text in text characters. The systematic method uses the structure of invisible character to hide and extract secret texts. The creation of secret message comprises four main stages such using the letter from the original message, selecting the suitable cover text, dividing the cover text into blocks, hiding the secret text using the invisible character and comparing the cover-text and stego-object. This study uses an invisible character (white space
... Show MoreFace Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
... Show MoreAspect-Oriented Software Development (AOSD) is a technology that helps achieving
better Separation of Concern (SOC) by providing mechanisms to identify all relevant points
in a program at which aspectual adaptations need to take place. This paper introduces a
banking application using of AOSD with security concern in information hiding.
Background: This study aimed to determine the gender of a sample of Iraqi adults using the mesio-distal width of mandibular canines, inter-canine width and standard mandibular canine index, and to determine the percentage of dimorphism as an aid in forensic dentistry. Materials and methods: The sample included 200 sets of study models belong to 200 subjects (100 males and 100 females) with an age ranged between 17-23 years. The mesio-distal crown dimension was measured manually, from the contact points for the mandibular canines (both sides), in addition to the inter-canine width using digital vernier. Descriptive statistics were obtained for the measurements for both genders; paired sample t-test was used to evaluate the side difference of
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