This paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA)) for measureing the closeness between curves. Root Mean Square Errors is used for the implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables model, results are more preferable than the independent response method. The models are demonstrated by both a simulation data and real data.
This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.
The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show MoreIn data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
The present paper focuses on the study of some characteristics of
comets ions by photometry method which represent by CCD camera
which it provide seeing these images in a graded light. From 0-255
when Zero (low a light intensity) and 255 (highlight intensity). These
differences of photonic intensity can be giving us a curve which
appear from any line of this image.
From these equations the focus is concentrating on determine the
temperature distribution, velocity distribution, and intensity number
distribution which is give number of particles per unit volume.
The results explained the interaction near the cometary nucleus
which is mainly affected by the new ions added to the density of the
solar wind, th
Functional strength is one of the most important elements of physical preparation and an important physical characteristic in our daily life in general and sports training in particular, as it is the most influential characteristic in all sporting events, which the athlete must possess in order to reach the highest levels and achieve the best results. The research aimed to prepare functional strength training exercises According to the gradual increase in load in the development of some physical abilities and achievement for men's 100 meter competition runners , And to identify the effect of functional strength training according to the gradual increase in load in developing some physical abilities and achievement for men’s 100-
... Show MoreThere are significant differences between the pre and post-tests in favor of the post-test in the tests) stroke volume (S.V), cardiac thrust (C.O.P), left ventricular volume, maximum oxygen consumption Vo2max), which indicates the effect of the proposed training approach.There are significant differences between the pre and post-tests in favor of the post-test in the achievement level test with air rifle shooting for young female shooters, which indicates the effect of the proposed training curriculum.There are no significant differences between the pre and post-tests in the tests (heart rate (HR) before exercise, heart rate (HR) after exercise, systolic blood pressure rate before exercise, systolic blood pressure rate after exercis
... Show MoreIn this research, the problem of multi- objective modal transport was formulated with mixed constraints to find the optimal solution. The foggy approach of the Multi-objective Transfer Model (MOTP) was applied. There are three objectives to reduce costs to the minimum cost of transportation, administrative cost and cost of the goods. The linear membership function, the Exponential membership function, and the Hyperbolic membership function. Where the proposed model was used in the General Company for the manufacture of grain to reduce the cost of transport to the minimum and to find the best plan to transfer the product according to the restrictions imposed on the model.