International Research Journal on Advanced Science Hub

Segmentation of images has become a critical component of modern life. Seg- mentation is a critical phase of the picture investigation process. Numerous concepts and methods for segmenting images have been developed. Using thresholding to quickly and easily delete distinct areas of a photograph is a simple process. It aspires to global esteem, thereby widening the yield divide. The purpose of this study is to demonstrate how to use a multiregion threshold- ing technique to overcome the primary constraint on the thresholding process when images are debased with noise and disruption. Using a fuzzy member- ship function, picture element from the photographs is connected to various component centroids, avoiding any underlying hard choice. In this project, we use fluffy- c implies means thresholding for picture division. The fundamen- tal objective of this technique is to separate the essential development from a given image by altering the pixels. To mitigate noise and artefacts, this tech- nique employs spatial information in a nearby accumulation step, where the support level of each picture element is arranged by neighborhood informa- tion that takes into account the enlists of picture element early. Following that, the consequences are looked at and are analogized to established methods to determine whether they are satisfactory.

This paper aims at controlling the vehicle using speech recognition method. Vehicle is controlled through voice commands given by the end user which stops and moves in various directions such as forward, backward, right and left. The vehicle is mounted with camera and an LCD screen to view the com- mands and distance between the vehicle and the obstacles. Application works on voice commands with in a distance of 1 meter. Vehicle is attached with GPS. Vehicles can also be controlled remotely or autonomously with the help of controller and sensors. Vehicle provides signals whenever it founds obsta- cles during mobility. Vehicle moves with predefined commands

The focus of this study was on the effect of channel angle on stress distribution in the material aluminum alloy 5083. The mechanical properties of a mate- rial are related to the grain size. Equal channel angular pressing (ECAP) is a method for deforming materials in such a way that a strong mechanical prop- erties material is formed while the dimensions of the work piece stay fixed in order to make ultra-fine-grained materials. One of the parameters of ECAP is the channel angle. It’s crucial to understand the impact of a die channel angle on material stress distribution before designing one. When the work piece passes through the channel angle, the die channel angle is built differently to see the effect of stress distribution. At the place where the die’s channels angle intersected, the grain structure was evaluated. The result of the influence of die channel angle on stress distribution is shown in this study’s analysis. It is well established that the channel angle has an impact on mechanical behaviour. The inhomogeneity index (C_i)and standard deviation (S.D.) are two approaches for assessing strain homogeneity. C_iis demonstrated to be an ineffective tool for analysing strain distribution homogeneity. Furthermore, it is advised that constructing Equal Channel Angular Pressing die geometry to obtain the best strain circulation homogeneity rather also the best efficient strain consequence is preferable.

With the advancement in the artificial intelligence technologies and develop- ment of fifth generation networks, a network may face many hazards and chal- lenges as the number of users are accessing the network simultaneously which makes the user to think of losing the confidentiality of the data and hence the network to be considered for security. Threats on the network can be classified in many ways and to detect such threats an Intrusion detection system (IDS) is the one which is mainly used. A network can be attacked in two ways as minor attack and major attack. Denial-of-Service (DoS) and Prob attacks belong to major kind and User-to-Root (U2R) and Remote-to-Login (R2L) goes to minor attack categories. The minor attacks are also called as rare attacks which are very injurious for a host and it is very difficult to recognize these attacks. This paper consists of a survey made on IDS and different algorithms used to imple- ment these IDSs using machine learning.