A square prism with side of base 40 mm and axis height 60 mm is resting on HP
Given Data Side of prism = 40 mm Axis length = 60 mm Resting on one of its corner = HP Axis inclination with HP = 30°
Get the App
Experience doubtly.in on your mobile device! Our app offers everything you need for your academic success:
Answer
Given Data Side of prism = 40 mm Axis length = 60 mm Resting on one of its corner = HP Axis inclination with HP = 30°
Figure shows 2 views of casting , Draw an isometric view with suitable origin
Many times students get confused which line to be made dark (visible) and which line to be made dashed (hidden). Video courtesy:: Youtube For doubts use comment or ask a new question
Given Data:- TL = a’b1’ = ab2 = 70 mm a’ (↑) = 10 mm a (→) = 20 mm θ = 30° Φ= 45°
A perceptron is one of the earliest and most basic types of artificial neural networks. It was introduced by Frank Rosenblatt in 1957 and is designed to perform binary classification tasks. The perceptron neural network consists of a single neuron…
Hebb Net to Implement OR Function Introduction: A Hebb net is a type of artificial neural network that can be used to implement simple logical functions. In this example, we will design a Hebb net to implement the OR function…
Are you gearing up for your upcoming exams and in need of some extra practice? Look no further! We’re excited to share that Doubtly has just published a treasure trove of past year question papers to aid in your preparation…
Feature Supervised Learning Unsupervised Learning Definition A type of machine learning where the model learns from labeled data, meaning the data has both input and output variables. A type of machine learning where the model learns from unlabeled data, meaning…
The OSI model is based on a proposal developed by the International Standards Organization (ISO) as a first step toward international standardization of the protocols used in the various layers (Day and Zimmermann, 1983). It was revised in 1995 (Day,…
Nature of Dependent Variable: Linear regression is used when the dependent variable is continuous while logistic regression is used when the dependent variable is binary (two categories). Output: In linear regression, the output is continuous and can take any value,…