In this paper, the classical continuous triple optimal control problem (CCTOCP) for the triple nonlinear parabolic boundary value problem (TNLPBVP) with state vector constraints (SVCs) is studied.  The solvability theorem for the classical continuous triple optimal control vector CCTOCV with the SVCs is stated and proved. This is done under suitable conditions. The mathematical formulation of the adjoint triple boundary value problem (ATHBVP) associated with TNLPBVP is discovered. The Fréchet derivative of the Hamiltonian" is derived.  Under suitable conditions, theorems of necessary  and sufficient conditions for the optimality of the TNLPBVP with the SVCs are stated and proved.    

Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp

    Clustering is an unsupervised learning method that classified data according to similarity probabilities. DBScan as a high-quality algorithm has been introduced for clustering spatial data due to its ability to remove noise (outlier) and constructing arbitrarily shapes. However, it has a problem in determining a suitable value of Eps parameter. This paper proposes a new clustering method, termed as DBScanBAT, that it optimizes DBScan algorithm by BAT algorithm. The proposed method automatically sets the DBScan parameters (Eps) and finds the optimal value for it. The results of the proposed DBScanBAT automatically generates near original number of clusters better than DBScanPSO and original DBScan. Furthermore, the proposed method

Image compression has become one of the most important applications of the image processing field because of the rapid growth in computer power. The corresponding growth in the multimedia market, and the advent of the World Wide Web, which makes the internet easily accessible for everyone. Since the early 1980, digital image sequence processing has been an attractive research area because an image sequence, as acollection of images, may provide much compression than a single image frame. The increased computational complexity and memory space required for image sequence processing, has in fact, becoming more attainable. this research absolute Moment Block Truncation compression technique which is depend on adopting the good points of oth

The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

he assignment model represents a mathematical model that aims at expressing an important problem facing enterprises and companies in the public and private sectors, which are characterized by ensuring their activities, in order to take the appropriate decision to get the best allocation of tasks for machines or jobs or workers on the machines that he owns in order to increase profits or reduce costs and time As this model is called multi-objective assignment because it takes into account the factors of time and cost together and hence we have two goals for the assignment problem, so it is not possible to solve by the usual methods and has been resorted to the use of multiple programming The objectives were to solve the problem of

      Bioinformatics is one of the computer science and biology sub-subjects concerned with the processes applied to biological data, such as gathering, processing, storing, and analyzing it. Biological data (ribonucleic acid (RNA), deoxyribonucleic acid (DNA), and protein sequences) has many applications and uses in many fields (data security, data segmentation, feature extraction, etc.). DNA sequences are used in the cryptography field, using the properties of biomolecules as the carriers of the data. Messenger RNA (mRNA) is a single strand used to make proteins containing genetic information. The information recorded from DNA also carries messages from DNA to ribosomes in the cytosol. In this paper, a new encryption technique bas

  Survival analysis is the analysis of data that are in the form of times from the origin of time until the occurrence of the end event, and in medical research, the origin of time is the date of registration of the individual or the patient in a study such as clinical trials to compare two types of medicine or more if the endpoint It is the death of the patient or the disappearance of the individual. The data resulting from this process is called survival times. But if the end is not death, the resulting data is called time data until the event. That is, survival analysis is one of the statistical steps and procedures for analyzing data when the adopted variable is time to event and time. It could be d

Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M