-74813b3e17f460286df-366b 20220430043751592 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 05 30 2022 11 6 Faculty, Department of Mathematics Education, Ain-Shams University, Cairo, Egypt. Nabil T. M. Eldabe Amira S. A. Asar Faculty, Department of Mathematics Arts & Science, Prince Sattam Bin Abdulaziz University, Wadi Adwassir, Saudi Arabia. Shaimaa F. Ramadan Faculty, Department of Mathematics Science (Girls), Al-Azhar University, Cairo, Egypt. In this paper, the effects of slip velocity and Hall currents on peristaltic motion of a non-Newtonian fluid with heat and mass transfer through a porous medium inside a symmetric horizontal channel with flexible walls are studied. The fluid obeys Maxwell model, the ohmic and viscous dissipations are taken into account. Some of partial differential equations describe the fluid motion with the appropriate boundary conditions are written in dimensionless form and simplified by using the approximations of long wavelength and low Reynolds number. These equations are solved analytically, and the stream function, pressure rise, temperature, and concentration distributions are obtained as functions of physical parameters of the problem. The effects of the parameters of the problem on these solutions are discussed numerically and illustrated graphically through a set of figures. It is found that the physical parameters played important roles in controling the obtained solutions. 05 30 2022 7 15 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.C9808.0511622 https://www.ijitee.org/portfolio-item/c98080311422/ Assistant Professor, Department of Data Structures and Algorithms, Pimpri Chinchwad College of Engineering, Pune (Maharashtra), India. Dr. Jyoti S. Kulkarni The sensors available nowadays are not generating images of all objects in a scene with the same clarity at various distances. The progress in sensor technology improved the quality of images over recent years. However, the target data generated by a single image is limited. For merging information from multiple input images, image fusion is used. The basis of image fusion is on the image acquisition as well as on the level of processing and under this many image fusion techniques are available. Several input image acquisition techniques are available such as multisensor, multifocus, and multitemporal. Also, image fusion is performed in four different stages. These levels are the level of the signal, pixel level, level of feature, and level of decision-making. Further, the fusion methods are divided into two domains i.e spatial and frequency domains. The fusion in spatial domain images uses inputs directly to work on pixels, while the transition refers to frequency domain image fusion on input images before fusion. The limitation of spatial domain image fusion is spectral degradation. To overcome this limitation, the fusion of transform domain images is preferred which uses several transforms. The results generated by transform methods are superior to spatial domain methods. But there is a scope to improve the results or to find the optimized results. Optimization can be achieved by using evolutionary approaches. The evolutionary computation approach is an effective way of finding the required solution for a complex problem. An evolutionary algorithm is a guided random search used for optimization. The biological model of evolution and natural selection inspires it. The different types of evolutionary computing algorithms include Genetic algorithm, Genetic Programming, Evolutionary programming, Learning Classifier System, Ant Colony Optimization, Artificial Bee Colony Optimization, Particle Swarm Optimization, Evolution strategy, Swarm intelligence, Tabu Search, Cuckoo Search, etc. Three genetic algorithm-based image fusion techniques are proposed: a genetic algorithm with one population, a genetic algorithm with separate populations, and a block method. In the block method, an array of numbers in one chromosome is generated. The result obtained by the proposed techniques are compared with existing methods and observed that the results are improved. The graphical representation of performance parameters reflects that the block method is better. 05 30 2022 16 21 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.F9895.0511622 https://www.ijitee.org/portfolio-item/f98950511622/ Research Scholar, Sri Siddhartha Institute of Technology, Tumkur (Karnataka), India. Mr. Madhu H. K. Dr. D. Ramesh Professor and HOD, Sri Siddhartha Academy of Higher Education, Tumkur (Karnataka), India. In the present pandemic situation, health care data is generated voluminously in an unstructured format posing challenge to technology in perspective of analysis, classification and prediction. The data generated is converted to structured format. Suitability of methodology keeping in mind low computational complexity and high accuracy is a major concern which has emerged as a problem in data science. In this research work real time heart disease data set is considered to evaluate the accuracy of six supervised methods –SVM (Support Vector Machine), KNN (K-Nearest Neighbor), GNB (Gaussian Naïve Bayes), LR (Logistic Regression), DT (Decision Tree) and RF (Random Forest). Analysis through ROC curve and confusion matrix predominantly justify RF classifier and LR gives efficient results compared to other methods. This is a preprocessing stage; every researcher has to perform before deciding the methodology to be considered for further processing. 05 30 2022 22 28 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.F9906.0511622 https://www.ijitee.org/portfolio-item/f99060511622/