K tree
•Download as PPTX, PDF•
0 likes•282 views
K-D trees are binary search trees for organizing points in a k-dimensional space. This document describes a 2D K-D tree, where each node contains an (x,y) point and levels alternate between using the x-coordinate and y-coordinate for sorting. K-D trees provide efficient lookup of nearest neighbors and range queries, with insertion and retrieval taking O(log N) time on average for a balanced tree of N points.
Report
Share
Report
Share
Recommended
Biconnected components (13024116056)
This document discusses bi-connected components in graphs. It defines an articulation point as a vertex in a connected graph whose removal would disconnect the graph. A bi-connected component is a maximal subgraph that contains no articulation points. The document presents algorithms for identifying articulation points and bi-connected components in a graph using depth-first search (DFS). It introduces the concepts of tree edges, back edges, forward edges and cross edges in a DFS tree and explains how to use these edge types to determine if a vertex is an articulation point based on the minimum discovery time of its descendant vertices.
Input-Buffering
Algorithm for Buffer Pairs, Algorithm for Sentinels,
Working of Buffer Pairs and Sentinels with example
MASTER SLAVE JK FLIP FLOP & T FLIP FLOP
Sequential logic circuits use a clock signal to control the timing of state changes in memory elements like flip-flops. A master-slave JK flip-flop allows both the J and K inputs to be simultaneously 1, toggling the output. When this occurs, the master section is reset if the clock is 1, and set if the clock is 0, preventing unstable oscillations between circuits.
2.3 sequantial logic circuit
This document discusses sequential logic circuits and flip-flops. It begins by defining sequential logic and differentiating it from combinational logic. It then describes flip-flops as the basic building blocks of sequential logic that provide memory. It identifies four common types of flip-flops - SR, JK, D and T - and describes their operation, truth tables and implementation using logic gates. The document provides details on each type of flip-flop to help understand their functionality and applications in sequential logic circuits.
Spanning trees & applications
This document discusses minimum spanning trees. It defines a minimum spanning tree as a spanning tree of a connected, undirected graph that has a minimum total cost among all spanning trees of that graph. The document provides properties of minimum spanning trees, including that they are acyclic, connect all vertices, and have n-1 edges for a graph with n vertices. Applications of minimum spanning trees mentioned include communication networks, power grids, and laying telephone wires to minimize total length.
Parsing LL(1), SLR, LR(1)
This document discusses parsing and different parsing techniques. It defines parsing as the process of verifying that tokens generated by a lexical analyzer follow the syntactic rules of a language. Parsers can be top-down or bottom-up. Top-down parsers build the parse tree from the root to leaves by following leftmost derivations, while bottom-up parsers start from the leaves and work upwards. The document also discusses LL(1), SLR, and LR(1) parsing techniques, including how to construct parsing tables and handle conflicts. LR(1) parsers are more restrictive than SLR(1) parsers in where they allow reduce operations.
JK flip flops
JK flip-flops have two outputs, Q and Q', and four modes of operation: hold, set, reset, toggle. The primary output is Q. There are two stable states that can store state information. JK flip-flops are used for data storage in registers, counting in counters, and frequency division. They can divide the frequency of a periodic waveform in half by toggling on each input clock pulse.
Recommended
Biconnected components (13024116056)
This document discusses bi-connected components in graphs. It defines an articulation point as a vertex in a connected graph whose removal would disconnect the graph. A bi-connected component is a maximal subgraph that contains no articulation points. The document presents algorithms for identifying articulation points and bi-connected components in a graph using depth-first search (DFS). It introduces the concepts of tree edges, back edges, forward edges and cross edges in a DFS tree and explains how to use these edge types to determine if a vertex is an articulation point based on the minimum discovery time of its descendant vertices.
Input-Buffering
Algorithm for Buffer Pairs, Algorithm for Sentinels,
Working of Buffer Pairs and Sentinels with example
MASTER SLAVE JK FLIP FLOP & T FLIP FLOP
Sequential logic circuits use a clock signal to control the timing of state changes in memory elements like flip-flops. A master-slave JK flip-flop allows both the J and K inputs to be simultaneously 1, toggling the output. When this occurs, the master section is reset if the clock is 1, and set if the clock is 0, preventing unstable oscillations between circuits.
2.3 sequantial logic circuit
This document discusses sequential logic circuits and flip-flops. It begins by defining sequential logic and differentiating it from combinational logic. It then describes flip-flops as the basic building blocks of sequential logic that provide memory. It identifies four common types of flip-flops - SR, JK, D and T - and describes their operation, truth tables and implementation using logic gates. The document provides details on each type of flip-flop to help understand their functionality and applications in sequential logic circuits.
Spanning trees & applications
This document discusses minimum spanning trees. It defines a minimum spanning tree as a spanning tree of a connected, undirected graph that has a minimum total cost among all spanning trees of that graph. The document provides properties of minimum spanning trees, including that they are acyclic, connect all vertices, and have n-1 edges for a graph with n vertices. Applications of minimum spanning trees mentioned include communication networks, power grids, and laying telephone wires to minimize total length.
Parsing LL(1), SLR, LR(1)
This document discusses parsing and different parsing techniques. It defines parsing as the process of verifying that tokens generated by a lexical analyzer follow the syntactic rules of a language. Parsers can be top-down or bottom-up. Top-down parsers build the parse tree from the root to leaves by following leftmost derivations, while bottom-up parsers start from the leaves and work upwards. The document also discusses LL(1), SLR, and LR(1) parsing techniques, including how to construct parsing tables and handle conflicts. LR(1) parsers are more restrictive than SLR(1) parsers in where they allow reduce operations.
JK flip flops
JK flip-flops have two outputs, Q and Q', and four modes of operation: hold, set, reset, toggle. The primary output is Q. There are two stable states that can store state information. JK flip-flops are used for data storage in registers, counting in counters, and frequency division. They can divide the frequency of a periodic waveform in half by toggling on each input clock pulse.
Stressen's matrix multiplication
Strassen's algorithm improves on the basic matrix multiplication algorithm which runs in O(N3) time. It achieves this by dividing the matrices into sub-matrices and performing 7 multiplications and 18 additions on the sub-matrices, rather than the 8 multiplications of the basic algorithm. This results in a runtime of O(N2.81) using divide and conquer, providing an asymptotic improvement over the basic O(N3) algorithm.
8.flip flops and registers
Flip flops are basic memory elements that store one bit of information as a 1 or 0. Common types include RS, D, JK, T, and master-slave JK flip flops. Flip flops have two stable states and two complementary outputs. They are used as registers for storage, in frequency dividers, and digital counters. Registers consist of groups of flip flops that hold information, while shift registers can shift data in one or both directions using cascaded flip flops and clock pulses. Flip flops have applications in interfacing digital systems, as delay circuits, and for converting between serial and parallel data.
Race around and master slave flip flop
The Reason Why we use master slave JK flip flop instead of simple level triggered flip flop is Racing condition which can be successfully avoided using two SR latches fed with inverted clocks.
Sequential Circuit
This document discusses various types of flip-flops including RS, D, JK, T flip-flops. It describes their characteristic tables and excitation tables. It also covers sequential circuits, state tables, state diagrams, state equations, and the design of counters using flip-flops. Key topics include the use of flip-flops as memory elements, master-slave configurations to prevent race-around conditions, and how to analyze and design sequential circuits and counters.
80486 microprocessor
The 80486 microprocessor features an integrated math coprocessor that is 3 times faster than the 80386/387 combination. It has an 8KB internal code and data cache and uses a 168-pin PGA package. New signals support burst mode memory access and bus sharing. The 80486 includes parity checking/generation and additional page table entry bits control internal caching.
AVL Tree
An AVL tree is a self-balancing binary search tree that guarantees search, insertion, and deletion operations will take O(log n) time on average. It achieves this by ensuring the heights of the left and right subtrees of every node differ by at most one. When an insertion or deletion causes a height imbalance of two, rotations are performed to rebalance the tree.
Registers and counters
Registers are groups of flip-flops that store binary data. An n-bit register contains n flip-flops and can store 2^n different states. Registers are used to store and provide digital data to logic circuits. There are different types of registers including shift registers. Shift registers can transfer data in serial-in serial-out, serial-in parallel-out, parallel-in serial-out, and parallel-in parallel-out modes. Counters are registers that increment their stored value on each clock pulse and are used to count events.
Unit 4 clocked_flip_flops
The document discusses different types of flip-flops including RS NAND and NOR flip-flops, and covers the basics of sequential logic circuits. It defines level-triggered and edge-triggered clock inputs for flip-flops and compares asynchronous and synchronous clocked flip-flops. The timing diagrams show how positive and negative edge triggering determines when the output of a flip-flop changes state in response to clock pulses and input signals.
KNN
The document discusses the K-nearest neighbors (KNN) algorithm, a supervised machine learning classification method. KNN classifies new data based on the labels of the k nearest training samples in feature space. It can be used for both classification and regression problems, though it is mainly used for classification. The algorithm works by finding the k closest samples in the training data to the new sample and predicting the label based on a majority vote of the k neighbors' labels.
Spanning trees
PPT of Spanning trees
BY Shareb Ismaeel
DEPT. OF INFORMATION TECHNOLOGY
CENTRAL UNIVERSITY OF KASHMIR
Moore and mealy machines
Moore and Mealy machines are two types of finite state machines. A Mealy machine's output depends on the current state and input, and its output size equals its input size. A Moore machine's output depends only on the current state, and its output size is one larger than its input size. Mealy machines are defined as tuples including states, inputs, outputs, transitions, and an output function. Moore machines are similarly defined except the output function maps states to outputs rather than states and inputs. Examples of Moore and Mealy machine applications include elevators, compilers, SRAM, and vending machines.
strassen matrix multiplication algorithm
Strassen's algorithm improves upon the standard matrix multiplication algorithm by using divide and conquer and only requiring 7 recursive multiplications to multiply 2x2 submatrices rather than 8. This results in a running time of O(n^2.81) rather than O(n^3) for large matrix sizes. The algorithm divides the matrices into submatrices, recursively multiplies the submatrices using 7 intermediate terms rather than relying on the commutativity of multiplication, and combines the results. While the improvement may seem small, the reduced exponent means Strassen's algorithm performs better than the standard algorithm for matrices larger than about 32x32 due to the impact of the exponent on runtime.
COMPILER DESIGN- Syntax Directed Translation
COMPILER DESIGN- Syntax Directed TranslationJyothishmathi Institute of Technology and Science Karimnagar
Syntax-Directed Translation: Syntax-Directed Definitions, Evaluation Orders for SDD's, Applications of Syntax-Directed Translation, Syntax-Directed Translation Schemes, and Implementing L-Attributed SDD's. Intermediate-Code Generation: Variants of Syntax Trees, Three-Address Code, Types and Declarations, Type Checking, Control Flow, Back patching, Switch-StatementsTopological Sorting
It is related to Analysis and Design Of Algorithms Subject.Basically it describe basic of topological sorting, it's algorithm and step by step process to solve the example of topological sort.
Combinational circuit
Combinational circuit, Half Adder,Full Adder, Half Subtractor, Full Subtractor, Multiplexers , Demultiplexer , Decoder , Encoder
Binomial Heap
A binomial heap is a collection of binomial trees where each node has a key, trees are heap-ordered with minimum keys at the root, and trees have different sizes. Binomial heaps support creation, finding minimum keys, merging, insertion, removal of minimum keys, decreasing keys, and removal through keeping degree, child, sibling, and parent pointers at each node and combining trees of different sizes.
Data encoding
Data encoding converts data into a signal form for transmission. There are different encoding methods for digital-to-digital, digital-to-analog, analog-to-analog, and analog-to-digital conversion. Common digital encoding techniques include unipolar, bipolar, and polar encoding, which represent binary data using single or multiple voltage levels. Non-return-to-zero and return-to-zero are examples that represent bits through the signal remaining at a level or returning to zero between bits. Manchester encoding and differential Manchester encoding are biphase techniques that provide clocking through signal transitions.
BFS and DFS
BFS and DFS are algorithms for traversing or searching graph data structures. BFS uses a queue to visit nodes level by level, making it slower but able to find the shortest path. DFS uses a stack to visit nodes depth-wise, making it faster but unable to find the shortest path. Both BFS and DFS have a time complexity of O(V+E) where V is the number of vertices and E is the number of edges.
Properties of Regular Expressions
The document describes the properties of regular languages and proves that regular languages are closed under various operations including concatenation, union, intersection, complement, reversal, and Kleene star. It provides examples of constructing non-deterministic finite automata (NFAs) and deterministic finite automata (DFAs) to represent languages that are the result of applying these operations to regular languages. Key steps involved in the constructions of NFAs and DFAs for each operation are outlined.
And or search
AND-OR search graphs are used to represent problem solving and decomposition. The nodes represent states or goals, and successors are labeled as either AND or OR branches. AND branches indicate subgoals that must all be achieved, while OR branches represent alternative subgoals that could achieve the parent goal. AO* is an AND-OR graph algorithm that can find multiple solutions by combining AND and OR branches, but does not always find an optimal solution as it may not explore all possibilities once a solution is found. In contrast, A* is an OR graph algorithm that finds a single optimal solution by guaranteeing to explore all possibilities.
Case study
The GINA team at EMC applied the data analytics lifecycle to analyze innovation data from their global innovation network. They gathered structured and unstructured data from multiple sources to track research and ideas. Through data preparation, modeling, and analysis using techniques like NLP and social network analysis, they identified key innovators and hubs of activity. This helped EMC cultivate new intellectual property and partnerships. While successful, the team noted areas for improving data quality and making the insights more actionable over time.
Sampling and its type
Information about Sampling which is small part of big data on that data sampling we perform operations
More Related Content
What's hot
Stressen's matrix multiplication
Strassen's algorithm improves on the basic matrix multiplication algorithm which runs in O(N3) time. It achieves this by dividing the matrices into sub-matrices and performing 7 multiplications and 18 additions on the sub-matrices, rather than the 8 multiplications of the basic algorithm. This results in a runtime of O(N2.81) using divide and conquer, providing an asymptotic improvement over the basic O(N3) algorithm.
8.flip flops and registers
Flip flops are basic memory elements that store one bit of information as a 1 or 0. Common types include RS, D, JK, T, and master-slave JK flip flops. Flip flops have two stable states and two complementary outputs. They are used as registers for storage, in frequency dividers, and digital counters. Registers consist of groups of flip flops that hold information, while shift registers can shift data in one or both directions using cascaded flip flops and clock pulses. Flip flops have applications in interfacing digital systems, as delay circuits, and for converting between serial and parallel data.
Race around and master slave flip flop
The Reason Why we use master slave JK flip flop instead of simple level triggered flip flop is Racing condition which can be successfully avoided using two SR latches fed with inverted clocks.
Sequential Circuit
This document discusses various types of flip-flops including RS, D, JK, T flip-flops. It describes their characteristic tables and excitation tables. It also covers sequential circuits, state tables, state diagrams, state equations, and the design of counters using flip-flops. Key topics include the use of flip-flops as memory elements, master-slave configurations to prevent race-around conditions, and how to analyze and design sequential circuits and counters.
80486 microprocessor
The 80486 microprocessor features an integrated math coprocessor that is 3 times faster than the 80386/387 combination. It has an 8KB internal code and data cache and uses a 168-pin PGA package. New signals support burst mode memory access and bus sharing. The 80486 includes parity checking/generation and additional page table entry bits control internal caching.
AVL Tree
An AVL tree is a self-balancing binary search tree that guarantees search, insertion, and deletion operations will take O(log n) time on average. It achieves this by ensuring the heights of the left and right subtrees of every node differ by at most one. When an insertion or deletion causes a height imbalance of two, rotations are performed to rebalance the tree.
Registers and counters
Registers are groups of flip-flops that store binary data. An n-bit register contains n flip-flops and can store 2^n different states. Registers are used to store and provide digital data to logic circuits. There are different types of registers including shift registers. Shift registers can transfer data in serial-in serial-out, serial-in parallel-out, parallel-in serial-out, and parallel-in parallel-out modes. Counters are registers that increment their stored value on each clock pulse and are used to count events.
Unit 4 clocked_flip_flops
The document discusses different types of flip-flops including RS NAND and NOR flip-flops, and covers the basics of sequential logic circuits. It defines level-triggered and edge-triggered clock inputs for flip-flops and compares asynchronous and synchronous clocked flip-flops. The timing diagrams show how positive and negative edge triggering determines when the output of a flip-flop changes state in response to clock pulses and input signals.
KNN
The document discusses the K-nearest neighbors (KNN) algorithm, a supervised machine learning classification method. KNN classifies new data based on the labels of the k nearest training samples in feature space. It can be used for both classification and regression problems, though it is mainly used for classification. The algorithm works by finding the k closest samples in the training data to the new sample and predicting the label based on a majority vote of the k neighbors' labels.
Spanning trees
PPT of Spanning trees
BY Shareb Ismaeel
DEPT. OF INFORMATION TECHNOLOGY
CENTRAL UNIVERSITY OF KASHMIR
Moore and mealy machines
Moore and Mealy machines are two types of finite state machines. A Mealy machine's output depends on the current state and input, and its output size equals its input size. A Moore machine's output depends only on the current state, and its output size is one larger than its input size. Mealy machines are defined as tuples including states, inputs, outputs, transitions, and an output function. Moore machines are similarly defined except the output function maps states to outputs rather than states and inputs. Examples of Moore and Mealy machine applications include elevators, compilers, SRAM, and vending machines.
strassen matrix multiplication algorithm
Strassen's algorithm improves upon the standard matrix multiplication algorithm by using divide and conquer and only requiring 7 recursive multiplications to multiply 2x2 submatrices rather than 8. This results in a running time of O(n^2.81) rather than O(n^3) for large matrix sizes. The algorithm divides the matrices into submatrices, recursively multiplies the submatrices using 7 intermediate terms rather than relying on the commutativity of multiplication, and combines the results. While the improvement may seem small, the reduced exponent means Strassen's algorithm performs better than the standard algorithm for matrices larger than about 32x32 due to the impact of the exponent on runtime.
COMPILER DESIGN- Syntax Directed Translation
COMPILER DESIGN- Syntax Directed TranslationJyothishmathi Institute of Technology and Science Karimnagar
Syntax-Directed Translation: Syntax-Directed Definitions, Evaluation Orders for SDD's, Applications of Syntax-Directed Translation, Syntax-Directed Translation Schemes, and Implementing L-Attributed SDD's. Intermediate-Code Generation: Variants of Syntax Trees, Three-Address Code, Types and Declarations, Type Checking, Control Flow, Back patching, Switch-StatementsTopological Sorting
It is related to Analysis and Design Of Algorithms Subject.Basically it describe basic of topological sorting, it's algorithm and step by step process to solve the example of topological sort.
Combinational circuit
Combinational circuit, Half Adder,Full Adder, Half Subtractor, Full Subtractor, Multiplexers , Demultiplexer , Decoder , Encoder
Binomial Heap
A binomial heap is a collection of binomial trees where each node has a key, trees are heap-ordered with minimum keys at the root, and trees have different sizes. Binomial heaps support creation, finding minimum keys, merging, insertion, removal of minimum keys, decreasing keys, and removal through keeping degree, child, sibling, and parent pointers at each node and combining trees of different sizes.
Data encoding
Data encoding converts data into a signal form for transmission. There are different encoding methods for digital-to-digital, digital-to-analog, analog-to-analog, and analog-to-digital conversion. Common digital encoding techniques include unipolar, bipolar, and polar encoding, which represent binary data using single or multiple voltage levels. Non-return-to-zero and return-to-zero are examples that represent bits through the signal remaining at a level or returning to zero between bits. Manchester encoding and differential Manchester encoding are biphase techniques that provide clocking through signal transitions.
BFS and DFS
BFS and DFS are algorithms for traversing or searching graph data structures. BFS uses a queue to visit nodes level by level, making it slower but able to find the shortest path. DFS uses a stack to visit nodes depth-wise, making it faster but unable to find the shortest path. Both BFS and DFS have a time complexity of O(V+E) where V is the number of vertices and E is the number of edges.
Properties of Regular Expressions
The document describes the properties of regular languages and proves that regular languages are closed under various operations including concatenation, union, intersection, complement, reversal, and Kleene star. It provides examples of constructing non-deterministic finite automata (NFAs) and deterministic finite automata (DFAs) to represent languages that are the result of applying these operations to regular languages. Key steps involved in the constructions of NFAs and DFAs for each operation are outlined.
And or search
AND-OR search graphs are used to represent problem solving and decomposition. The nodes represent states or goals, and successors are labeled as either AND or OR branches. AND branches indicate subgoals that must all be achieved, while OR branches represent alternative subgoals that could achieve the parent goal. AO* is an AND-OR graph algorithm that can find multiple solutions by combining AND and OR branches, but does not always find an optimal solution as it may not explore all possibilities once a solution is found. In contrast, A* is an OR graph algorithm that finds a single optimal solution by guaranteeing to explore all possibilities.
What's hot (20)
More from Suraksha Sanghavi
Case study
The GINA team at EMC applied the data analytics lifecycle to analyze innovation data from their global innovation network. They gathered structured and unstructured data from multiple sources to track research and ideas. Through data preparation, modeling, and analysis using techniques like NLP and social network analysis, they identified key innovators and hubs of activity. This helped EMC cultivate new intellectual property and partnerships. While successful, the team noted areas for improving data quality and making the insights more actionable over time.
Sampling and its type
Information about Sampling which is small part of big data on that data sampling we perform operations
Air pollution monitoring system
This document describes an air pollution monitoring system that uses sensors interfaced with a monitoring shield to detect pollutants like dust, smoke, carbon monoxide, and carbon dioxide. The sensor data is transmitted wirelessly to a web server and cloud database. Users can monitor real-time data streams online. Data analytics are performed periodically to analyze trends and generate alert messages when pollution levels exceed thresholds. The system was deployed to monitor indoor and outdoor air quality.
An eye with an atm
This document proposes enhancing ATM security through iris recognition. It begins with an introduction to ATMs and discusses limitations of current security methods like PINs and fingerprints. Iris recognition is presented as an alternative biometric for identification. The document outlines how iris recognition works, its advantages of being accurate, stable and difficult to forge. Potential disadvantages like cost and small iris target are noted. It concludes iris recognition could provide more reliable security for ATM use by allowing quick, permanent identification without PINs or cards.
Smart water tank
This document describes a smart water tank project that uses an ultrasonic sensor and Arduino to automatically control a motor based on water level. When the water level drops below a certain point, the ultrasonic sensor detects this and turns the motor on to refill the tank. When the water reaches a full level, the sensor turns the motor off. An intermediate level triggers a text message on a mobile phone via GSM modem to notify the tank is at 50% capacity. The system is designed to automatically regulate water levels in applications like hotels, factories and homes to efficiently control water pumps.
Case study of goggle map
Google Maps is a web mapping service developed by Google that offers satellite imagery, street maps, 360° panoramic Street View, real-time traffic conditions, and route planning capabilities. It was originally a desktop program created in 2004 and later acquired and converted into a web application by Google. Google Maps allows maps to be embedded on third party websites and offers business locators worldwide. It is one of the most popular smartphone apps, used by over half of global smartphone owners.
Case Study Of Webgraph
The document discusses web graphs, where nodes represent web pages and edges represent hyperlinks. Web graphs are highly dynamic as pages and links are constantly added and removed. They also have properties like being sparse, with most pages having a constant number of links, and having small world characteristics, with the diameter being small relative to the graph's size. Analyzing web graphs can provide statistics about their structure and properties.
More from Suraksha Sanghavi (7)
Recently uploaded
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering PROJECT REPORT ON SUMMER VOCATIONAL TRAINING
AT MBB AIRPORT
22CYT12-Unit-V-E Waste and its Management.ppt
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
BRAIN TUMOR DETECTION for seminar ppt.pdf
BRAIN TUMOR DETECTION
AND CLASSIFICATION USING
ARTIFICIAL INTELLIGENCE
Advanced control scheme of doubly fed induction generator for wind turbine us...
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Data Driven Maintenance | UReason Webinar
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Rainfall intensity duration frequency curve statistical analysis and modeling...
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
原版制作(Humboldt毕业证书)柏林大学毕业证学位证一模一样
原件一模一样【微信：bwp0011】《(Humboldt毕业证书)柏林大学毕业证学位证》【微信：bwp0011】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问微bwp0011
【主营项目】
一.毕业证【微bwp0011】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【微bwp0011】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Slides for the 4th Presentation on LLM Fine-Tuning with QLoRA Presented by Anant, featuring DataStax Astra
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Recently uploaded (20)
Mechanical Engineering on AAI Summer Training Report-003.pdf
Mechanical Engineering on AAI Summer Training Report-003.pdf
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
Rainfall intensity duration frequency curve statistical analysis and modeling...
Rainfall intensity duration frequency curve statistical analysis and modeling...
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
IEEE Aerospace and Electronic Systems Society as a Graduate Student Member
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
K tree
- 1. Prepared by:- Suraksha Sanghavi
- 2. • Invented in 1970s by Jon Bentley • It is a binary tree • K-tree is also known as KD tree (k-diamensional) Where D=1,2,3…… • But we have in study is 2D Tree • Each level has a “cutting dimension” • Each node contains a point P = (x,y)
- 3. Complexity Insert: Average and balanced trees: O(log N) Worst case: O(N) Print: Range query: for M matches Perfectly balanced tree: K-D trees: O(M + kN (1-1/k) ) 2-D trees: O(M + N)
- 4. • Its left side with space known as left subtree • Its right side with points known as right subtree • Its first node is root (Grand parent) • While inserting its child (parent) it checks with x-cordinate • While inserting next node at next level it checks with y-co-dinate
- 5. • It is reprsenting in two way • 1)Tree 2)Graph • 0 level - x-alinged (vertical line)-compare with x-co-ordinate. • 1-level – y-alinged (horizontal line –it depend on child on which side) – compare with y-co- ordinate. • 2-level – x-alinged-compare x-cordinate. • 3-level – y alinged-compare y –corinate.
- 7. 1.Nearest neighbour Search 2.Database Queries