Internships in Aeronautical Engineering



Bangalore Internships - Aeronautical Engineering

Sanfoundry located at Bangalore offers internships to deserving B.Tech/M.Tech Students in Aeronautical Engineering Branch. In Aeronautical Engineering internships offered by Sanfoundry, shortlisted interns will be working towards the creation of useful artifacts like questions and answers, tutorials, articles, real-world problems and solutions on Aeronautical Engineering. Moreover, every intern working on Aeronautical Engineering internship will focus on one specific subject under the Aeronautical branch. This will help the intern to develop an in-depth understanding of that particular subject in their branch.

Here’s the list of topics for Internship in “Aeronautical Engineering”.

  • Machine Design
  • Kinematic of Machines
  • Dynamics of Machines
  • Manufacturing Engineering I
  • Manufacturing Engineering II
  • Fluid Mechanics
  • Avionics
  • Aerodynamics – I
  • Machine Drawing
  • Aircraft Structures – I
  • Aircraft Structures – II
  • Aircraft Performance
  • Applied Thermodynamics of Materials at Macro and Nano Scale
  • Aero, Marine, Metallurgical and Molecular Thermodynamics
  • Computational Fluid Dynamics
  • Aero Engine Maintenance and Repair
  • Industrial Pollution Control Engineering
  • Aircraft Materials and Processes
  • Elements of Aeronautics
  • Modeling and Finite Element Analysis
  • Finite Element Method and Analysis
  • Advanced Flight Dynamics
  • Flight Vehicle Design
  • Fluid Mechanics and Machinery
  • Advance Gas Turbine Engines Theory
  • Design of Composite Materials
  • Entrepreneurship Development, Management and Apparel Entrepreneurship
  • CFD in Manufacturing Processes
  • Numerical Modelling of Manufacturing Processes
  • Wind Energy Technology
  • Aerospace Materials and Manufacturing Processes
  • Advance Manufacturing Process Simulation and Management
  • Mechanics of Machines
  • Mechanics of Materials
  • Advance Mechanics of Materials
  • Applied Numerical Methods
  • Propulsion – I
  • Propulsion – II
  • Solid Mechanics for Technologists
  • Advance Theory of Vibrations
  • New Total Quality Management
  • Mechanical Vibrations
  • Aerodynamics – II
  • Computer Aided Machine Drawing
  • Applied Gasdynamics
  • Aircraft Stability and Control
  • Artificial Intelligence
  • Microprocessor and Peripherals
  • Hydraulics
  • Agile Manufacturing Technologies
  • Air Traffic Control Services and Procedures
  • Aircraft General Engineering and Maintenance Practices
  • Aircraft Maintenance, Repair and Overhaul
  • UAV Systems
  • Aircraft Safety Rules and Regulations
  • Airframe Maintenance and Repair
  • Total Quality Management
  • Boundary Layer Theory
  • Advanced Thermodynamics and Combustion
  • Theory and Design of Plates and Shells
  • Computer Integrated Manufacturing and Automation
  • Disaster Mitigation and Management
  • Experimental Aerodynamics
  • Fatigue and Fracture Mechanics
  • Flight Testing
  • Fracture Mechanics, Fatigue and Analysis of Engineering Failures
  • Guidance and Navigation
  • Two Phase Flow and Heat Transfer
  • Helicopter Dynamics
  • Helicopter Theory
  • Hypersonic Aerodynamics
  • Aerospace Quality Assurance
  • Micro and Smart Systems Technology
  • Numerical Methods in Fluid Flow Problems
  • Computer Science and Operation Research
  • Modelling and Optimisation in Flexible Manufacturing System
  • Reliability Engineering Basic Principles
  • Industrial Robotics
  • Rockets and Missiles
  • Smart Materials and Structures
  • Vibration and Structural Dynamics
  • Introduction to Aeroelasticity
  • Aeroelasticity
  • Advanced Aeroelasticity
  • Pneumatics
  • Engineering Mathematics
  • Engineering Physics
  • Engineering Chemistry
  • Engineering Mechanics
  • Engineering Drawing
  • Environmental Science and Engineering
  • Basic Electrical Engineering
  • Elements of Civil Engineering
  • Algorithms and Data Structures – 1
  • Algorithms and Data Structures – 2
  • Applied Chemistry
  • Differential and Difference Equations
  • Advance Engineering Mathematics
  • Basic Electronics Engineering
  • Partial Differential Equations and Transform Theorems
  • Computer Aided Engineering Drawing
  • Multivariable Calculus and Differential Equations
  • Probability and Statistics
  • Applications of Differential and Difference Equations
  • Elements of Mechanical Engineering
  • Sanfoundry is looking for Interns who are passionate about their field of study and like core subjects in Aeronautical Engineering. Every intern contributes to Sanfoundry’s Global learning project during their internship and is Mentored and Guided by our Founder and CTO. If you are interested to contribute and apply, here’s full detail of Sanfoundry’s Internship Program.

     
    Sanfoundry Global Education & Learning Series – Aeronautical Engineering Internships!




    Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @
    LinkedIn | Facebook | Twitter



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    Internships in Nano Technology Engineering



    Bangalore Internships - Nano Technology Engineering

    Sanfoundry located at Bangalore offers internships to deserving B.Tech/M.Tech Students in Nano Technology Engineering Branch. In Nano Technology Engineering internships offered by Sanfoundry, shortlisted interns will be working towards the creation of useful artifacts like questions and answers, tutorials, articles, real-world problems and solutions on Nano Technology Engineering. Moreover, every intern working on Nano Technology Engineering internship will focus on one specific subject under the Nano Technology branch. This will help the intern to develop an in-depth understanding of that particular subject in their branch.

    Here’s the list of topics for Internship in “Nano Technology Engineering”.

  • Basic Civil Engineering
  • Basic Electrical Engineering
  • Basic Mechanical Engineering
  • Biology for Engineers
  • Analog Electronic Circuits
  • Elements of Mechatronics Systems
  • Engineering Graphics and Drawing
  • Fourier Series, Partial Differential Equations and Its Applications
  • Fundamentals of Solid State Engineering
  • Immunology
  • Industrial Nanotechnology
  • Intelligent Manufacturing Technology
  • Knowledge Management Systems
  • Micro and Nanofabrication
  • Modelling Tools and Techniques for Micro, Nano Systems
  • Nanobiotechnology
  • Nanochemistry
  • Nanoelectronics
  • Nanophotonics
  • Numerical Methods and Its Application
  • Polymer and Nanocomposites
  • Principles of Engineering Metallurgy
  • Probability and Random Process
  • Programming Using Matlab
  • Quantum Mechanics
  • Statistical Mechanics and Thermodynamics of Small Systems
  • Synthesis and Characterization of Nanomaterials
  • Advanced Drug Delivery Systems
  • Atomistic Modelling
  • Carbon Nanotechnology
  • Green Nanotechnology
  • Introduction To Scientific Research
  • Lithography Techniques and Fabrication
  • MEMS and NEMS
  • Micro and Nanofluidics
  • Microelectronics and VLSI
  • Molecular Spectroscopy and Its Applications
  • Nano and Micro Emulsions
  • Nano-computing
  • Nano-medicine
  • Nanomagnetism
  • Supramolecular Systems
  • Robotics Engineering
  • Nanotechnology for Energy Systems
  • Nanotechnology in Agriculture and Food Processing
  • Nanotechnology In Cosmetics
  • Nanotechnology in Textiles
  • Nanotechnology in Tissue Engineering
  • Smart Sensor Systems
  • Nanotribology
  • Photovoltaic Technology
  • Surface and interfaces
  • Physics of Solid State Devices
  • Polymer Engineering
  • Advanced Calculus and Complex Analysis
  • Calculus and Solid
  • Chemistry
  • Elements Of Nanoscience and Nanotechnology
  • Geometry
  • Materials Science
  • Physics
  • Principles of Environmental Science
  • Sanfoundry is looking for Interns who are passionate about their field of study and like core subjects in Nano Technology Engineering. Every intern contributes to Sanfoundry’s Global learning project during their internship and is Mentored and Guided by our Founder and CTO. If you are interested to contribute and apply, here’s full detail of Sanfoundry’s Internship Program.

     
    Sanfoundry Global Education & Learning Series – Nano Technology Engineering Internships!




    Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @
    LinkedIn | Facebook | Twitter



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    Internships in Automobile Engineering



    Bangalore Internships - Automobile Engineering

    Sanfoundry located at Bangalore offers internships to deserving B.Tech/M.Tech Students in Automobile Engineering Branch. In Automobile Engineering internships offered by Sanfoundry, shortlisted interns will be working towards the creation of useful artifacts like questions and answers, tutorials, articles, real-world problems and solutions on Automobile Engineering. Moreover, every intern working on Automobile Engineering internship will focus on one specific subject under the Automobile branch. This will help the intern to develop an in-depth understanding of that particular subject in their branch.

    Here’s the list of topics for Internship in “Automobile Engineering”.

  • Applied Thermodynamics
  • Two Phase flow and Heat Transfer
  • Air Conditioning and Ventilation
  • Air Pollution Control and Design of Equipment
  • Automotive Chassis, Suspension and Components Design
  • Automotive chassis & Suspension
  • Hybrid Vehicle Technology
  • Advance Strength of Materials
  • Auxiliary Systems of Automotive Engines
  • Automotive Fuels, Lubricants and Combustion
  • Automotive Pollution and Control
  • Automotive Transmission
  • Vehicle Maintenance
  • Statistics and Numerical Methods
  • Chemical Engineering Thermodynamics
  • CAD/CAM/CAE
  • Computer Aided Machine Drawing
  • Control Engineering
  • Design of Machine Elements
  • Kinematics and Dynamics of Machines
  • Applied Electronics and Microprocessors
  • Engine and Vehicle Management System
  • Design and Metallurgy of Welded Joints
  • Advance Engineering Thermodynamics
  • Mechanics of Materials
  • Modeling and Finite Element Analysis
  • Fluid Mechanics
  • Fluid Mechanics and Machinery
  • Rail Vehicle Dynamics
  • Convective Heat and Mass Transfer
  • Nontradtional Machining
  • Machine Shop and Tool Design
  • Manufacturing Processes
  • Advance Manufacturing Process Simulation and Management
  • Computer Science and Operation Research
  • Mechanical Measurements and Metallurgy
  • Flight Vehicle Design
  • Advance Theory of IC Engines
  • Automobile Engineering
  • Alternative Fuels and Energy Systems
  • Artificial Intelligence
  • Automotive Electrical and Electronics Systems
  • Automotive Aerodynamics
  • Refrigeration and Air conditioning
  • Automotive Safety
  • Design of Composite Materials
  • Computer Graphics
  • Computer Integrated Manufacturing and Automation
  • Programming Language DBMS
  • Automotive Engine Components Design and Auxiliary Systems
  • Design of Experiments and Sample Survey Methods
  • Design of Jigs, Fixtures and Press Tools
  • Disaster Resistant Building and Management
  • Earth Moving Equipments and Tractors
  • Engine Auxiliary Systems
  • Estimation, Costing and Specifications
  • Engineering System Design
  • Entrepreneurship Development, Management and Apparel Entrepreneurship
  • Advance Foundry Technology
  • Advance Gas Dynamics
  • Applied Tribology
  • Air Transport Management
  • Hydraulics and Pneumatics
  • Metrology and Instrumentation
  • Fundamentals and Applications of Nanotechnology
  • Vibration Analysis
  • off Road Vehicles
  • Industrial Engineering and Operations Research
  • Robotics
  • Smart Materials and Structures
  • Theory of Plasticity and Fracture Mechanics
  • New Total Quality Management
  • Basic Electrical Engineering
  • Basic Electronics Engineering
  • Partial Differential Equations and Transform Theorems
  • Computer Aided Engineering Drawing
  • Differential and Difference Equations
  • Elements of Civil Engineering and Engineering Mechanics
  • Elements of Mechanical Engineering
  • Engineering Chemistry
  • Engineering Mathematics
  • Advance Engineering Mathematics
  • Engineering Physics
  • Environmental Science and Engineering
  • Multivariable Calculus and Differential Equations
  • Probability and Statistics
  • Algorithms and Data Structures
  • Applications of Differential and Difference Equations
  • Sanfoundry is looking for Interns who are passionate about their field of study and like core subjects in Automobile Engineering. Every intern contributes to Sanfoundry’s Global learning project during their internship and is Mentored and Guided by our Founder and CTO. If you are interested to contribute and apply, here’s full detail of Sanfoundry’s Internship Program.

     
    Sanfoundry Global Education & Learning Series – Automobile Engineering Internships!




    Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @
    LinkedIn | Facebook | Twitter



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    Co-ordinate Compression Multiple Choice Questions and Answers (MCQs)


    This set of Data Structures & Algorithms Multiple Choice Questions & Answers (MCQs) focuses on “Co-ordinate Compression”.

    1. What is co-ordinate compression?
    a) process of reassigning co-ordinates to remove gaps
    b) inserting gaps in a co-ordinate system
    c) removing redundant co-ordinates
    d) adding extra gaps
    View Answer

    Answer: a
    Explanation: Co-ordinate compression is the process of reassigning co-ordinates in order to remove gaps. This helps in improving efficiency of a solution.

    2. What is the need for co-ordinate compression?
    a) for improving time complexity
    b) for improving space complexity
    c) for improving both time and space complexity
    d) for making code simpler
    View Answer

    Answer: c
    Explanation:Co-ordinate compression is the process of reassigning co-ordinates in order to remove gaps. This helps in improving both time and space complexity of a solution.

    3. What is the output for the following code?

    #include <bits/stdc++.h> 
    using namespace std;  
    void convert(int a[], int n) 
    { 	
    	vector <pair<int, int> > vec;	
    	for (int i = 0; i < n; i++) 
    		vec.push_back(make_pair(a[i], i)); 
    	sort(vec.begin(), vec.end()); 	
    	for (int i=0; i<n; i++) 
    		a[vec[i].second] = i; 
    } 
    void printArr(int a[], int n) 
    { 
    	for (int i=0; i<n; i++) 
    		cout << a[i] << " "; 
    } 
    int main() 
    { 
    	int arr[] = {10,8,2,5,7}; 
    	int n = sizeof(arr)/sizeof(arr[0]);  
    	convert(arr , n); 
       	printArr(arr, n); 
    	return 0; 
    }

    a) 4 3 0 1 2
    b) 1 2 3 4 5
    c) 5 4 1 2 3
    d) 0 1 2 3 4
    View Answer

    Answer: a
    Explanation: The given code converts the elements of the input array. They are replaced with their respective position number in the sorted array.

    4. What will be the time complexity of given code?

    #include <bits/stdc++.h> 
    using namespace std;  
    void convert(int a[], int n) 
    { 	
    	vector <pair<int, int> > vec; 	
    	for (int i = 0; i < n; i++) 
    		vec.push_back(make_pair(a[i], i)); 	
    	sort(vec.begin(), vec.end()); 	
    	for (int i=0; i<n; i++) 
    		a[vec[i].second] = i; 
    } 
    void printArr(int a[], int n) 
    { 
    	for (int i=0; i<n; i++) 
    		cout << a[i] << " "; 
    } 
    int main() 
    { 
    	int arr[] = {10,8,2,5,7}; 
    	int n = sizeof(arr)/sizeof(arr[0]); 	
    	convert(arr , n); 
       	printArr(arr, n); 
    	return 0; 
    }

    a) O(n)
    b) O(n log n)
    c) O(n2)
    d) O(log n)
    View Answer

    Answer: b
    Explanation: The time complexity of the given code will be governed by the time complexity of the sorting algorithm used. As this code uses in built sorting of C++ so it will take O(n log n) time.

    5. What is the auxiliary space complexity of the given code?

    #include <bits/stdc++.h> 
    using namespace std;  
    void convert(int a[], int n) 
    { 	
    	vector <pair<int, int> > vec; 	
    	for (int i = 0; i < n; i++) 
    		vec.push_back(make_pair(a[i], i)); 	
    	sort(vec.begin(), vec.end()); 
    	for (int i=0; i<n; i++) 
    		a[vec[i].second] = i; 
    } 
    void printArr(int a[], int n) 
    { 
    	for (int i=0; i<n; i++) 
    		cout << a[i] << " "; 
    } 
    int main() 
    { 
    	int arr[] = {10,8,2,5,7}; 
    	int n = sizeof(arr)/sizeof(arr[0]);  
    	convert(arr , n); 
       	printArr(arr, n); 
    	return 0; 
    }

    a) O(1)
    b) O(n)
    c) O(log n)
    d) O(n log n)
    View Answer

    Answer: b
    Explanation: The given code uses an auxiliary space of O(n). It is used by a vector which pairs each element of the array with their respective index number of the original array.

    6. What will be the output of the following code?

    #include <bits/stdc++.h> 
    using namespace std; 
    void convert(int arr[], int n) 
    { 
    	int temp[n]; 
    	memcpy(temp, arr, n*sizeof(int)); 
    	sort(temp, temp + n); 	
            unordered_map<int, int> map; 	
    	int sort_index = 0; 
    	for (int i = 0; i < n; i++) 
    		map[temp[i]] = sort_index++; 	
    	for (int i = 0; i < n; i++) 
    		arr[i] = map[arr[i]]; 
    } 
    void printArr(int arr[], int n) 
    { 
    	for (int i=0; i<n; i++) 
    		cout << arr[i] << " "; 
    } 
    int main() 
    { 
    	int arr[] = {3,5,2,4}; 
    	int n = sizeof(arr)/sizeof(arr[0]); 
    	convert(arr , n); 	
    	printArr(arr, n); 
    	return 0; 
    }

    a) 0 2 3 4
    b) 1 3 0 2
    c) 2 4 1 3
    d) 1 2 3 4
    View Answer

    Answer: b
    Explanation: The given code converts the elements of input array. They are replaced with their respective position number in the sorted array.

    7. What is the time complexity of the following code?

    #include <bits/stdc++.h> 
    using namespace std; 
    void convert(int arr[], int n) 
    { 	
    	int temp[n]; 
    	memcpy(temp, arr, n*sizeof(int)); 
    	sort(temp, temp + n); 	
            unordered_map<int, int> map; 	
    	int sort_index = 0; 
    	for (int i = 0; i < n; i++) 
    		map[temp[i]] = sort_index++; 	
    	for (int i = 0; i < n; i++) 
    		arr[i] = map[arr[i]]; 
    } 
    void printArr(int arr[], int n) 
    { 
    	for (int i=0; i<n; i++) 
    		cout << arr[i] << " "; 
    } 
    int main() 
    { 
    	int arr[] = {10, 20, 15, 12, 11, 50}; 
    	int n = sizeof(arr)/sizeof(arr[0]); 
    	convert(arr , n); 	
    	printArr(arr, n); 
    	return 0; 
    }

    a) O(n)
    b) O(1)
    c) O(n log n)
    d) O(n2)
    View Answer

    Answer: c
    Explanation: The time complexity of the given code will be governed by the time complexity of the sorting algorithm used. As this code uses inbuilt sorting of C++ so it will take O(n log n) time.

    8. What will be the auxiliary space complexity of the following code?
    a) O(n)
    b) O(1)
    c) O(log n)
    d) O(n log n)
    View Answer

    Answer: a
    Explanation: The given code uses an auxiliary space of O(n). It is used by a vector which pairs each element of the array with their respective index number of the original array.

    9. Co-ordinate compression reduces the number of squares in a graph.
    a) true
    b) false
    View Answer

    Answer: a
    Explanation: The idea behind co-ordinate compression is to reduce the number of squares in a graph by converting them into rectangles of viable size. This reduces the time complexity of traversal.

    10. Co-ordinate compression can only be applied in a co-ordinate system problem
    a) true
    b) false
    View Answer

    Answer: b
    Explanation: Co-ordinate compression technique can be applied where such optimization is suitable. It does not require to co-ordinate system problem only.

    Sanfoundry Global Education & Learning Series – Data Structures & Algorithms.

    To practice all areas of Data Structures & Algorithms, here is complete set of 1000+ Multiple Choice Questions and Answers.



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    Square Root Decomposition Multiple Choice Questions and Answers (MCQs)


    This set of Data Structures & Algorithms Multiple Choice Questions & Answers (MCQs) focuses on “Square Root Decomposition”.

    1. What is the purpose of using square root decomposition?
    a) to reduce the time complexity of a code
    b) to increase the space complexity of a code
    c) to reduce the space complexity of a code
    d) to reduce the space and time complexity of a code
    View Answer

    Answer: a
    Explanation: Square decomposition is mainly used in competitive programming to optimize code. It reduces the time complexity by a factor of √n.

    2. By what factor time complexity is reduced when we apply square root decomposition to a code?
    a) n
    b) √n
    c) n2
    d) n-1/2
    View Answer

    Answer: b
    Explanation: In square root decomposition a given array is decomposed into small parts each of size √n. This reduces the time complexity of the code by a factor of √n.

    3. What will be the worst case time complexity of finding the sum of elements in a given range of (l,r) in an array of size n?
    a) O(n)
    b) O(l+r)
    c) O(l-r)
    d) O(r-l)
    View Answer

    Answer: a
    Explanation: For a given array of size n we have to traverse all n elements in the worst case. In such a case l=0, r=n-1 so the time complexity will be O(n).

    4. What will be the worst case time complexity of finding the sum of elements in a given range of (l,r) in an array of size n when we use square root optimization?
    a) O(n)
    b) O(l+r)
    c) O(√n)
    d) O(r-l)
    View Answer

    Answer: c
    Explanation: When we use square root optimization we decompose the given array into √n chunks each of size √n. So after calculating the sum of each chunk individually, we require to iterate only 3*√n times to calculate the sum in the worst case.

    5. Total how many iterations are required to find the sum of elements in a given range of (l,r) in an array of size n when we use square root optimization?
    a) √n
    b) 2*√n
    c) 3*√n
    d) n*√n
    View Answer

    Answer: c
    Explanation: After calculating the sum of each chunk individually we require to iterate only 3*√n times to calculate the sum in the worst case. It is because two of the √n factors consider the worst case time complexity of summing elements in the first and last block. Whereas the third √n considers the factor of summing the √n chunks.

    6. What will be the time complexity of update query operation in an array of size n when we use square root optimization?
    a) O(√n)
    b) O(n)
    c) O(1)
    d) O(n2)
    View Answer

    Answer:c
    Explanation: The time complexity of query operation remains the same in both square root optimized code and non optimized code. We simply find the chunk in which the update requires to be performed and then add the new updated value at the desired index.

    7. Square root decomposition technique is only applicable when the number of indices in an array is a perfect square.
    a) true
    b) false
    View Answer

    Answer: b
    Explanation: Square root decomposition technique can be applied to an array with any number of indices. It does not require this number to be a perfect square.

    8. What will be the worst case time complexity of code to find sum in given query range (l,r) in an array of size n with q number of such queries?
    a) O(n)
    b) O(q)
    c) O(n*q)
    d) O(n+q)
    View Answer

    Answer: c
    Explanation: For finding the result of one query the worst case time complexity will be n. So for q queries the time complexity will be O(q*n). This can be reduced by using square root optimization.

    9. What will be the worst case time complexity of code to find sum in given query range (l,r) in an array of size n with q number of such queries when we apply MO’s algorithm?
    a) O(n*q)
    b) O(n)
    c) O((q+n)√n)
    d) O(q*√n)
    View Answer

    Answer: c
    Explanation: Mo’s algorithm requires O(q*√n) + O(n*√n) time for processing all the queries. It is better than the naive solution where O(n*q) time is required.

    10. Mo’s algorithm can only be used for problems where the query can be calculated from the result of the previous query.
    a) true
    b) false
    View Answer

    Answer: a
    Explanation: Mo’s algorithm uses the result of the previous query in order to compute the result of the given query. It cannot be implemented where such a scenario is not possible.

    11. What will be the time complexity of the code to find a minimum element from an array of size n and uses square root decomposition(exclude pre processing time)?
    a) O(√n)
    b) O(n)
    c) O(1)
    d) O(n2)
    View Answer

    Answer: a
    Explanation: For finding the minimum element in a given array of size n using square root decomposition we first divide the array into √n chunks and calculate the result for them individually. So for a given query, the result of middle blocks has to be calculated along with the extreme elements. This takes O(√n) time in the worst case.

    Sanfoundry Global Education & Learning Series – Data Structures & Algorithms.

    To practice all areas of Data Structures & Algorithms, here is complete set of 1000+ Multiple Choice Questions and Answers.



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    Machine Drawing Questions and Answers – Thread Profile


    This set of Machine Drawing Multiple Choice Questions & Answers (MCQs) focuses on “Thread Profile”.

    1. If a screw thread advances in the nut when turned in a clockwise direction, it is called _________
    a) left hand helix
    b) right hand helix
    c) clockwise helix
    d) anticlockwise helix
    View Answer

    Answer: b
    Explanation: Right hand helix has the thread that advances in the nut when turned in a clockwise direction. When thread advances in the nut when turned in an anticlockwise direction then it is termed as left hand helix thread.

    2. Threads are classified into V thread, Acme thread, Knuckle thread, etc. on the basis of _________
    a) start of threads
    b) hand of helix
    c) profile of the groove
    d) surface
    View Answer

    Answer: c
    Explanation: On the basis of the profile of the groove, threads are classified as V thread, Acme thread, Knuckle thread, Buttress thread, Square thread, etc. On the basis of start of threads, threads are classified as single start, double start, triple start, etc.

    3. Pitch of the profile depends on the ______
    a) nominal diameter
    b) internal diameter
    c) external diameter
    d) mean diameter
    View Answer

    Answer: a
    Explanation: Threads are specified according to their pitch of profile. Pitch of the profile depends on the nominal diameter of the thread. The proportions of the profile are calculated in terms of the pitch.

    4. Metric threads are not termed as ___________
    a) BSW thread
    b) V thread
    c) American thread
    d) Unified thread
    View Answer

    Answer: a
    Explanation: A practical modification of V thread is called a metric thread. It is also called an American thread or Unified thread. All these have the included angle of 600. But in BSW thread included angle is 550 and hence it is different.

    5. Depth of thread is ______ times of pitch in case of British Standard Whitworth Thread.
    a) 0.75
    b) 0.64
    c) 0.55
    d) 0.80
    View Answer

    Answer: b
    Explanation: BSW threads are similar to the V threads, but the included angle is 55o. The depth of thread in case of BSW thread is 0.64 times of pitch of the thread. Radii at root and crest are 0.14 times that of pitch.

    6. Vice used for carpentry work has ______ thread.
    a) square
    b) buttress
    c) acme
    d) square
    View Answer

    Answer: b
    Explanation: Buttress threads are used where power is to be transmitted in a single direction only. Hence it is used in applications like vice used for carpentry work. It has efficiency as good as square thread and strength as much as V thread.

    7. Which of the following option do not specify a knuckle thread?
    a) Semi-circular profile of radius 1/4th of pitch
    b) Suitably formed by molding or rolling
    c) Used in sheet metal covers for jars
    d) Transmits power in one direction only
    View Answer

    Answer: d
    Explanation: Knuckle thread has a semi-circular profile of radius 1/4th of the pitch. Knuckle threads are suitably formed by molding as well as rolling and can be used in sheet metal covers for jars. But thread which can transmit power in one direction only is Buttress thread.

    8. Coarse pitches are used for ____________
    a) rough application
    b) general application
    c) precision application
    d) special application
    View Answer

    Answer: a
    Explanation: Pitch for the same diameter thread varies depending upon the application. Coarse pitch is used for rough application, medium pitch for general application and fine pitch is used for precision work.

    9. Square threads are used for ________
    a) power transmission
    b) clamping devices
    c) easy operation of engagement and disengagement
    d) fastening purpose
    View Answer

    Answer: a
    Explanation: Square thread is the simple and strong type of thread profile. It is used for power transmission. Its width and depth are equal to the half of the pitch.

    10. __________ is the slight improvement over square thread.
    a) Buttress thread
    b) Knuckle thread
    c) Acme thread
    d) BSW thread
    View Answer

    Answer: c
    Explanation: An acme thread is a slight improvement over square thread. Sides of the acme thread are inclined at 14.50. Square thread is difficult to cut because a parallel surface of both flanks and hence acme thread are used instead at some places.

    Sanfoundry Global Education & Learning Series – Machine Drawing.

    To practice all areas of Machine Drawing, here is complete set of 1000+ Multiple Choice Questions and Answers.



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