Lecture 3.pptx
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This document discusses asymptotic analysis of algorithms, which analyzes how an algorithm's running time increases with the size of the input as the input grows very large. It examines big-O notation for asymptotic upper bounds, Ω notation for lower bounds, and θ notation for tight bounds. The analysis aims to determine the order of growth of an algorithm's running time to understand its efficiency for large inputs.
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Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
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Chapter 3
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Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
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Chapter 5
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Chapter 6
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Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
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Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
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1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
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- 1. Analysis of Algorithms Asymptotic Analysis
- 2. Asymptotic Analysis of algorithm • The input sizes large enough to make only the order of growth of the running time relevant: asymptotic efficiency of algorithms. • We are concerned with how the running time of an algorithm increases with the size of the input in the limit, as the size of the input increases without bound. • Usually, an algorithm that is asymptotically more efficient will be the best choice for all but very small inputs
- 4. Lower bound
- 5. Upper bound
- 8. Big Ο Notation (asymptotic upper bound)
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Editor's Notes
- Theta(g(n)) is representing set of functions here. >>>> an intuitive picture of functions f .n/ and g.n/, where f .n/ D ‚.g.n//. For all values of n at and to the right of n0, the value of f .n/ lies at or above c1g.n/ and at or below c2g.n/. In other words, for all n n0, the function f .n/ is equal to g.n/ to within a constant factor. We say that g.n/ is an asymptotically tight bound for f .n/.
- Theta is a set of functions. For this we searched for g(n). It is not necessary that g(n) is always n^2. but some for g(n) , this set can’t be formed or in other words, in theta g(n), few f9n0s can’t be included.
- Big O notation means order (order n or order nlogn). O means order.
- Is algorithm ki performance is limit se ziada behter nahi ho skti. It is the lower bound.
- >>>> We can say that f(n) and g(n) ratio is a constant (which is >0 but not infinity), then f(n) is being bound by g(n) from below and from above. (for theta) >>>> (Big O) : for c>=0 and not infinite, can also be zero , g(n) remains above f(n) but f(n) never goes above g(n). G(n) bounded f(n) from upper side. >>>> (Omega) g(n) is bounding f(n) from below