By optimizing the efficiency of a modular simulation model of the PV module structure by genetic algorithm, under several weather conditions, as a portion of recognizing the ideal plan of a Near Zero Energy Household (NZEH), an ideal life cycle cost can be performed. The optimum design from combinations of NZEH-variable designs, are construction positioning, window-to-wall proportion, and glazing categories, which will help maximize the energy created by photovoltaic panels. Comprehensive simulation technique and modeling are utilized in the solar module I-V and for P-V output power. Both of them are constructed on the famous five-parameter model. In addition, the efficiency of the PV panel is established by the genetic algorithm under the standard test conditions (STC) and a comparison between the theoretical and experimental results is done to achieve maximum performance ranging from 0.15 to 0.16, particularly with an error of about - 0.333 for an experimental power of 30 Watts compared with the theoretical power of 30.1 Watts. The results obtained by the genetic algorithm give the best value for efficiency at the range of 16% to 17% of solar radiation, from 500–600 W/m2. These values are almost identical to the efficiency obtained from the results of the operation, where the best value for efficiency in the experimental results was seen to be 15.7%.
Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.
Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att
... Show MoreThe penalized least square method is a popular method to deal with high dimensional data ,where the number of explanatory variables is large than the sample size . The properties of penalized least square method are given high prediction accuracy and making estimation and variables selection
At once. The penalized least square method gives a sparse model ,that meaning a model with small variables so that can be interpreted easily .The penalized least square is not robust ,that means very sensitive to the presence of outlying observation , to deal with this problem, we can used a robust loss function to get the robust penalized least square method ,and get robust penalized estimator and
... Show MoreCompressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp
... Show MoreThe subject of the Internet of Things is very important, especially at present, which is why it has attracted the attention of researchers and scientists due to its importance in human life. Through it, a person can do several things easily, accurately, and in an organized manner. The research addressed important topics, the most important of which are the concept of the Internet of Things, the history of its emergence and development, the reasons for its interest and importance, and its most prominent advantages and characteristics. The research sheds light on the structure of the Internet of Things, its structural components, and its most important components. The research dealt with the most important search engines in the Intern
... Show MoreThe transfer of chemical pollutants from bottled water into water due to heat, sunlight and poor storage is one of the most serious threats to human health around the world, the objective of this study was to estimate the pH value and the transport of heavy metals from plastic bottles to water, for this purpose, 30 bottles of water for 10 local brands were collected and divided into three groups, the first was left at room temperature 25°C, The second was placed in a heat oven at 25°C and the third in another oven at 50°C for two weeks. The results showed significant differences at (P<0.05) between water samples, pH value and concentrations of heavy metals (Sb, Pb, Ni, Cu, Cr, Cd and Fe) we
... Show MoreSet dietary program for some of dietary supplements and training for badminton young players, and identifying effect of taking some of the dietary supplementary for badminton young players. The research population :( badminton young players group (Arminian club). For age group (16-18) years the sample is divided in to two experimental groups within each group (6) players, and two for the exploratory experiment which was within the research sample, they were divided in to two groups, the first group take some of the dietary supplements (multivitamin creating) .the set exercises by the researchers in the main part of the training unit and the second group (amino acids, vitamins) and the set exercises by the researcher. The scientific approach
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The study was conducted at the ruminant research station of the general commission for agricultural research/Ministry of Agriculture, as well as the laboratory of genetic resources of the department of livestock/Ministry of Agriculture and the laboratory of the college of agriculture engineering science, with the aim of determine the genotypic of the expression region (intron 2 and part of exon 3) of the LHX3 gene And its relationship to the fertility rate in local and Shami goats. For this purpose, the RFLP technique was used, and the percentages of genotypes for the LHX3 gene in the local goat sample were 29.17, 50.00, 20.83 for the TT, AT, and AA genotypes, respectively, while in the Shami goa
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