This document presents a study comparing different graph search algorithms for solving mazes represented as images. The paper implements bidirectional versions of breadth-first search (BFS) and A* search and compares their performance on 8x8 and 16x16 mazes to the traditional unidirectional algorithms. For smaller 8x8 mazes, BFS performed best but for larger 16x16 mazes, bidirectional BFS was most efficient at finding the shortest path. Bidirectional search improves results but uses more space. The key aspect is finding the meeting point where the two searches meet, guaranteeing a solution if one exists.
Breadth first algorithm for solving Image based maze problemNavin Kumar
The project includes maze solving using the breadth-first search algorithm. The maze given is of predefined dimensions so that the image processing can be done easily.
The Implementation can be found at http://navin.live/maze
The Project is submitted in partial fulfillment of the requirements for the award of the degree of master of technology for the following Subjects
1) PROJECT MTCS-308
2) SEMINAR MTCS-307
at I.K.GUJRAL PUNJAB TECHNICAL UNIVERSITY
KAPURTHALA
By
Navin Kumar
Roll No. 1710965
Bidirectional graph search techniques for finding shortest path in image base...Navin Kumar
The intriguing problem of solving a maze comes
under the territory of algorithms and artificial intelligence.
The maze solving using computers is quite of interest for many
researchers, hence, there had been many previous attempts to
come up with a solution which is optimum in terms of time and
space. Some of the best performing algorithms suitable for the
problem are breadth-first search, A* algorithm, best-first
search and many others which ultimately are the
enhancement of these basic algorithms. The images are
converted into graph data structures after which an algorithm
is applied eventually pointing the trace of the solution on the
maze image. This paper is an attempt to do the same by
implementing the bidirectional version of these well-known
algorithms and study their performance with the former. The
bidirectional approach is indeed capable of providing
improved results at an expense of space. The vital part of the
approach is to find the meeting point of the two bidirectional
searches which will be guaranteed to meet if there exists any
solution.
Example of iterative deepening search & bidirectional searchAbhijeet Agarwal
There are the some examples of Iterative deepening search & Bidirectional Search with some definitions and some theory related to the both searches. If you have any query please ask in comment or mail i will be happy to help you
ICDE-2015 Shortest Path Traversal Optimization and Analysis for Large Graph C...Waqas Nawaz
Waqas Nawaz Khokhar presented research on optimizing shortest path traversal and analysis for large graph clustering. The presentation outlined challenges with traditional graph clustering approaches for big real-world graphs. It proposed four optimizations: 1) a collaborative similarity measure to reduce complexity from O(n3) to O(n2logn); 2) identifying overlapping shortest path regions to avoid redundant traversals; 3) confining traversals within clusters to limit unnecessary graph regions; and 4) allowing parallel shortest path queries to reduce latency. Experimental results on real and synthetic graphs showed the approaches improved efficiency by 40% in time and an order of magnitude in space while maintaining clustering quality. Future work aims to address intermediate data explosion
A Survey on Block Matching Algorithms for Video Coding Yayah Zakaria
Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades,
hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality.
This document discusses object removal from digital photographs through exemplar-based inpainting. It describes Criminisi's algorithm which combines texture synthesis and inpainting to remove objects while preserving linear structures and avoiding blurring. The algorithm works by assigning priority values to pixels based on proximity to linear structures, and then propagates texture patterns from surrounding regions into the removed object area. Experimental results show Criminisi's approach produces better outcomes than either texture synthesis or inpainting alone. Future work areas include improving curved structure propagation and applying the method to video.
The document discusses clustering techniques and provides details about the k-means clustering algorithm. It begins with an introduction to clustering and lists different clustering techniques. It then describes the k-means algorithm in detail, including how it works, the steps involved, and provides an example illustration. Finally, it discusses comments on the k-means algorithm, focusing on aspects like choosing the value of k, initializing cluster centroids, and different distance measurement methods.
Square transposition: an approach to the transposition process in block cipherjournalBEEI
The transposition process is needed in cryptography to create a diffusion effect on data encryption standard (DES) and advanced encryption standard (AES) algorithms as standard information security algorithms by the National Institute of Standards and Technology. The problem with DES and AES algorithms is that their transposition index values form patterns and do not form random values. This condition will certainly make it easier for a cryptanalyst to look for a relationship between ciphertexts because some processes are predictable. This research designs a transposition algorithm called square transposition. Each process uses square 8 × 8 as a place to insert and retrieve 64-bits. The determination of the pairing of the input scheme and the retrieval scheme that have unequal flow is an important factor in producing a good transposition. The square transposition can generate random and non-pattern indices so that transposition can be done better than DES and AES.
Breadth first algorithm for solving Image based maze problemNavin Kumar
The project includes maze solving using the breadth-first search algorithm. The maze given is of predefined dimensions so that the image processing can be done easily.
The Implementation can be found at http://navin.live/maze
The Project is submitted in partial fulfillment of the requirements for the award of the degree of master of technology for the following Subjects
1) PROJECT MTCS-308
2) SEMINAR MTCS-307
at I.K.GUJRAL PUNJAB TECHNICAL UNIVERSITY
KAPURTHALA
By
Navin Kumar
Roll No. 1710965
Bidirectional graph search techniques for finding shortest path in image base...Navin Kumar
The intriguing problem of solving a maze comes
under the territory of algorithms and artificial intelligence.
The maze solving using computers is quite of interest for many
researchers, hence, there had been many previous attempts to
come up with a solution which is optimum in terms of time and
space. Some of the best performing algorithms suitable for the
problem are breadth-first search, A* algorithm, best-first
search and many others which ultimately are the
enhancement of these basic algorithms. The images are
converted into graph data structures after which an algorithm
is applied eventually pointing the trace of the solution on the
maze image. This paper is an attempt to do the same by
implementing the bidirectional version of these well-known
algorithms and study their performance with the former. The
bidirectional approach is indeed capable of providing
improved results at an expense of space. The vital part of the
approach is to find the meeting point of the two bidirectional
searches which will be guaranteed to meet if there exists any
solution.
Example of iterative deepening search & bidirectional searchAbhijeet Agarwal
There are the some examples of Iterative deepening search & Bidirectional Search with some definitions and some theory related to the both searches. If you have any query please ask in comment or mail i will be happy to help you
ICDE-2015 Shortest Path Traversal Optimization and Analysis for Large Graph C...Waqas Nawaz
Waqas Nawaz Khokhar presented research on optimizing shortest path traversal and analysis for large graph clustering. The presentation outlined challenges with traditional graph clustering approaches for big real-world graphs. It proposed four optimizations: 1) a collaborative similarity measure to reduce complexity from O(n3) to O(n2logn); 2) identifying overlapping shortest path regions to avoid redundant traversals; 3) confining traversals within clusters to limit unnecessary graph regions; and 4) allowing parallel shortest path queries to reduce latency. Experimental results on real and synthetic graphs showed the approaches improved efficiency by 40% in time and an order of magnitude in space while maintaining clustering quality. Future work aims to address intermediate data explosion
A Survey on Block Matching Algorithms for Video Coding Yayah Zakaria
Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades,
hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality.
This document discusses object removal from digital photographs through exemplar-based inpainting. It describes Criminisi's algorithm which combines texture synthesis and inpainting to remove objects while preserving linear structures and avoiding blurring. The algorithm works by assigning priority values to pixels based on proximity to linear structures, and then propagates texture patterns from surrounding regions into the removed object area. Experimental results show Criminisi's approach produces better outcomes than either texture synthesis or inpainting alone. Future work areas include improving curved structure propagation and applying the method to video.
The document discusses clustering techniques and provides details about the k-means clustering algorithm. It begins with an introduction to clustering and lists different clustering techniques. It then describes the k-means algorithm in detail, including how it works, the steps involved, and provides an example illustration. Finally, it discusses comments on the k-means algorithm, focusing on aspects like choosing the value of k, initializing cluster centroids, and different distance measurement methods.
Square transposition: an approach to the transposition process in block cipherjournalBEEI
The transposition process is needed in cryptography to create a diffusion effect on data encryption standard (DES) and advanced encryption standard (AES) algorithms as standard information security algorithms by the National Institute of Standards and Technology. The problem with DES and AES algorithms is that their transposition index values form patterns and do not form random values. This condition will certainly make it easier for a cryptanalyst to look for a relationship between ciphertexts because some processes are predictable. This research designs a transposition algorithm called square transposition. Each process uses square 8 × 8 as a place to insert and retrieve 64-bits. The determination of the pairing of the input scheme and the retrieval scheme that have unequal flow is an important factor in producing a good transposition. The square transposition can generate random and non-pattern indices so that transposition can be done better than DES and AES.
- Linear algebra is important for image recognition and other fields like physics, economics, and politics. It allows analyzing relationships between multiple variables without calculus.
- Python is a good platform for linear algebra due to libraries like NumPy that allow fast processing of multi-dimensional data like matrices. It also has simple syntax without semicolons.
- Key concepts discussed include vectors, matrices, linear transformations, abstraction, and how linear algebra solves problems in fields like quantum mechanics. Comprehensions provide a concise way to generate sets, lists, and arrays in Python.
This document provides an overview of brute force and divide-and-conquer algorithms. It discusses various brute force algorithms like computing an, string matching, closest pair problem, convex hull problems, and exhaustive search algorithms like the traveling salesman problem and knapsack problem. It also analyzes the time efficiency of these brute force algorithms. The document then discusses the divide-and-conquer approach and provides examples like merge sort, quicksort, and matrix multiplication. It provides pseudocode and analysis for mergesort. In summary, the document covers brute force and divide-and-conquer techniques for solving algorithmic problems.
This document proposes an optimized version of the AO* algorithm called OAO* that improves upon AO* in two ways:
1) It performs a depth-limited search on nodes before assigning heuristic values, allowing previously underestimated nodes to become promising.
2) It handles interacting subproblems, where the optimal solution to one subproblem depends on the solution to another. This provides a more realistic solution.
The OAO* algorithm is shown to always provide an optimal or better solution than AO* by re-evaluating nodes and accounting for interactions between subproblems. It also explores fewer nodes overall through the use of an explored list to avoid re-exploring known nodes.
- The document discusses one-dimensional and two-dimensional arrays in C. It defines arrays, provides examples of declaring and initializing arrays, and describes common array operations like insertion, deletion, modification, and traversal. It also discusses two-dimensional arrays and provides an example program to add two matrices using a 2D array. The key topics covered are the basic concepts of arrays, declaring and initializing single and multi-dimensional arrays, and common operations performed on arrays.
Backtracking based integer factorisation, primality testing and square root c...csandit
Breaking a big integer into two factors is a famous problem in the field of Mathematics and
Cryptography for years. Many crypto-systems use such a big number as their key or part of a
key with the assumption - it is too big that the fastest factorisation algorithms running on the
fastest computers would take impractically long period of time to factorise. Hence, many efforts
have been provided to break those crypto-systems by finding two factors of an integer for
decades. In this paper, a new factorisation technique is proposed which is based on the concept
of backtracking. Binary bit by bit operations are performed to find two factors of a given
integer. This proposed solution can be applied in computing square root, primality test, finding
prime factors of integer numbers etc. If the proposed solution is proven to be efficient enough, it
may break the security of many crypto-systems. Implementation and performance comparison of
the technique is kept for future research.
Design and analysis of algorithms - Abstract ViewWaqas Nawaz
This document discusses the design and analysis of algorithms. It introduces algorithms and defines them as sets of rules to solve computational problems. It emphasizes the importance of both designing algorithms through techniques like divide-and-conquer as well as analyzing their performance through complexity analysis. The document provides examples of analyzing worst-case, best-case, and average-case runtime and uses an example algorithm to find the largest number in an array to demonstrate space and time analysis methods.
The document summarizes the ORB (Oriented FAST and Rotated BRIEF) feature detection and description algorithm. It begins by explaining how ORB improves on SIFT and SURF by combining the FAST keypoint detector with BRIEF descriptors to provide a method that is faster and has rotation invariance. It then describes the FAST detector, BRIEF descriptors, and how ORB adds orientation to BRIEF to achieve rotational invariance. Finally, it provides an overview of the full ORB algorithm and demonstrates its applications in areas like image matching, object recognition, and robot vision.
1) The document describes a vehicle routing project that uses a multi-commodity network flow formulation to explore sub-optimal solutions for object classification with noisy sensors on a 2D grid.
2) It formulates the problem as assigning tasks to vehicles (commodities) that must flow through the graph in 4 directions while being constrained by boundaries and returning to base.
3) The algorithm uses a look-ahead window to consider future moves and a rollout step using linear programming to approximate costs farther in time and decide optimal vehicle movements.
I am Danny G . I am an Electrical Engineering Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. Matlab, Schiller International University, USA. I have been helping students with their homework for the past 9 years. I solve assignments related to Electrical Engineering.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Electrical Engineering Assignments.
The document describes three different searching techniques: linear search, binary search, and DN search. Linear search has a worst case time complexity of O(n) as it searches through each element sequentially. Binary search has a worst case time complexity of O(log n) but requires the list to be sorted. DN search also has a worst case time complexity of O(log n) and can be applied to both sorted and unsorted lists, making it more powerful than the other techniques.
This document discusses using genetic algorithms to cryptanalyze the RSA cryptosystem. It first provides an overview of the RSA algorithm and how it works. It then discusses the Karatsuba algorithm, which can be used to efficiently multiply very large numbers. The document goes on to explain the basic concepts behind genetic algorithms, including representation, selection, crossover, and mutation operators. The authors propose applying genetic algorithms to generate new number pairs p and q that could be used to factor the RSA modulus N and break the cryptosystem. Specifically, they suggest using genetic algorithm operators to generate a new population of p and q values to use in cryptanalyzing RSA.
The document discusses graph-based clustering methods. It describes how graphs can be used to represent real-world networks from domains like biology, technology, social networks, and economics. It introduces the idea of using minimal spanning trees and hierarchical clustering to identify clusters in graph data. Two common algorithms for finding minimal spanning trees are described: Prim's algorithm and Kruskal's algorithm. Different strategies for iteratively deleting branches from the minimal spanning tree are also summarized to form clusters, such as deleting the branch with the maximum weight or inconsistent branches based on a reference value.
The branch-and-bound method is used to solve optimization problems by traversing a state space tree. It computes a bound at each node to determine if the node is promising. Better approaches traverse nodes breadth-first and choose the most promising node using a bounding heuristic. The traveling salesperson problem is solved using branch-and-bound by finding an initial tour, defining a bounding heuristic as the actual cost plus minimum remaining cost, and expanding promising nodes in best-first order until finding the minimal tour.
I am Kennedy L. I am a Digital Signal Processing Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. in Matlab, Monash University, Australia. I have been helping students with their homework for the past 6 years. I solve assignments related to Digital Signal Processing.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Digital Signal Processing Assignments.
FUAT – A Fuzzy Clustering Analysis ToolSelman Bozkır
This document summarizes fuzzy c-means clustering (FCM) and introduces a software tool called FUAT that aims to address some of the difficulties with FCM. FCM is a soft clustering method that allows data elements to belong to more than one cluster. It is based on fuzzy set theory and combines c-means clustering with handling fuzziness in data. FUAT stands for Fuzzy Unsupervised Analysis Tool and provides features like automatic cluster number detection, interactive viewers for insights into results, and connectivity to R for further analysis. It aims to make fuzzy clustering more transparent and help with challenges like selecting initial centroids and evaluating clusters.
This document discusses lower bounds and limitations of algorithms. It begins by defining lower bounds and providing examples of problems where tight lower bounds have been established, such as sorting requiring Ω(nlogn) comparisons. It then discusses methods for establishing lower bounds, including trivial bounds, decision trees, adversary arguments, and problem reduction. The document explores different classes of problems based on complexity, such as P, NP, and NP-complete problems. It concludes by examining approaches for tackling difficult combinatorial problems that are NP-hard, such as using exact algorithms, approximation algorithms, and local search heuristics.
Manifold learning with application to object recognitionzukun
This document discusses manifold learning techniques for dimensionality reduction that can uncover the intrinsic structure of high-dimensional data. It introduces Isomap and Locally Linear Embedding (LLE) as two popular manifold learning algorithms. Isomap uses graph-based distances to preserve global structure, while LLE aims to preserve local linear relationships between neighbors. Both techniques find low-dimensional embeddings that best represent the high-dimensional data. Manifold learning provides data compression and enables techniques like object recognition by discovering the underlying manifold structure.
Structure and Motion - 3D Reconstruction of Cameras and StructureGiovanni Murru
The document discusses structure from motion reconstruction from multiple images. It provides an overview of the steps to:
1. Estimate camera motion and 3D structure from a sequence of images using a stratified approach, starting with projective reconstruction and refining to affine and metric reconstruction.
2. Reconstruct structure and motion for two datasets - a public dataset and a personal dataset acquired by the student.
3. The key steps are feature detection, matching, estimating the fundamental matrix, triangulating 3D points, identifying the plane at infinity to upgrade from projective to affine reconstruction, and further refinement to metric reconstruction if possible.
This document compares three popular path planning algorithms: A*, greedy best first search, and jump point search. It implements the algorithms in MATLAB using grid-based maps with random start/goal points and static obstacles. The algorithms are evaluated based on computational complexity, time complexity, and space complexity. Jump point search generally has the best performance out of the three algorithms as it can make long jumps along straight lines in the grid, exploring fewer nodes than A*.
Fault diagnosis using genetic algorithms and principal curveseSAT Journals
Abstract Several applications of nonlinear principal component analysis (NPCA) have appeared recently in process monitoring and fault diagnosis. In this paper a new approach is proposed for fault detection based on principal curves and genetic algorithms. The principal curve is a generation of linear principal component (PCA) introduced by Hastie as a parametric curve passes satisfactorily through the middle of data. The existing principal curves algorithms employ the first component of the data as an initial estimation of principal curve. However the dependence on initial line leads to a lack of flexibility and the final curve is only satisfactory for specific problems. In this paper we extend this work in two ways. First, we propose a new method based on genetic algorithms to find the principal curve. Here, lines are fitted and connected to form polygonal lines (PL). Second, potential application of principal curves is discussed. An example is used to illustrate fault diagnosis of nonlinear process using the proposed approach. Index Terms: Principal curve, Genetic Algorithm, Nonlinear principal component analysis, Fault detection.
Optimized Robot Path Planning Using Parallel Genetic Algorithm Based on Visib...IJERA Editor
An analysis is made for optimized path planning for mobile robot by using parallel genetic algorithm. The
parallel genetic algorithm (PGA) is applied on the visible midpoint approach to find shortest path for mobile
robot. The hybrid ofthese two algorithms provides a better optimized solution for smooth and shortest path for
mobile robot. In this problem, the visible midpoint approach is used to make the effectiveness for avoiding
local minima. It gives the optimum paths which are always consisting on free trajectories. But the
proposedhybrid parallel genetic algorithm converges very fast to obtain the shortest route from source to
destination due to the sharing of population. The total population is partitioned into a number subgroups to
perform the parallel GA. The master thread is the center of information exchange and making selection with
fitness evaluation.The cell to cell crossover makes the algorithm significantly good. The problem converges
quickly with in a less number of iteration.
- Linear algebra is important for image recognition and other fields like physics, economics, and politics. It allows analyzing relationships between multiple variables without calculus.
- Python is a good platform for linear algebra due to libraries like NumPy that allow fast processing of multi-dimensional data like matrices. It also has simple syntax without semicolons.
- Key concepts discussed include vectors, matrices, linear transformations, abstraction, and how linear algebra solves problems in fields like quantum mechanics. Comprehensions provide a concise way to generate sets, lists, and arrays in Python.
This document provides an overview of brute force and divide-and-conquer algorithms. It discusses various brute force algorithms like computing an, string matching, closest pair problem, convex hull problems, and exhaustive search algorithms like the traveling salesman problem and knapsack problem. It also analyzes the time efficiency of these brute force algorithms. The document then discusses the divide-and-conquer approach and provides examples like merge sort, quicksort, and matrix multiplication. It provides pseudocode and analysis for mergesort. In summary, the document covers brute force and divide-and-conquer techniques for solving algorithmic problems.
This document proposes an optimized version of the AO* algorithm called OAO* that improves upon AO* in two ways:
1) It performs a depth-limited search on nodes before assigning heuristic values, allowing previously underestimated nodes to become promising.
2) It handles interacting subproblems, where the optimal solution to one subproblem depends on the solution to another. This provides a more realistic solution.
The OAO* algorithm is shown to always provide an optimal or better solution than AO* by re-evaluating nodes and accounting for interactions between subproblems. It also explores fewer nodes overall through the use of an explored list to avoid re-exploring known nodes.
- The document discusses one-dimensional and two-dimensional arrays in C. It defines arrays, provides examples of declaring and initializing arrays, and describes common array operations like insertion, deletion, modification, and traversal. It also discusses two-dimensional arrays and provides an example program to add two matrices using a 2D array. The key topics covered are the basic concepts of arrays, declaring and initializing single and multi-dimensional arrays, and common operations performed on arrays.
Backtracking based integer factorisation, primality testing and square root c...csandit
Breaking a big integer into two factors is a famous problem in the field of Mathematics and
Cryptography for years. Many crypto-systems use such a big number as their key or part of a
key with the assumption - it is too big that the fastest factorisation algorithms running on the
fastest computers would take impractically long period of time to factorise. Hence, many efforts
have been provided to break those crypto-systems by finding two factors of an integer for
decades. In this paper, a new factorisation technique is proposed which is based on the concept
of backtracking. Binary bit by bit operations are performed to find two factors of a given
integer. This proposed solution can be applied in computing square root, primality test, finding
prime factors of integer numbers etc. If the proposed solution is proven to be efficient enough, it
may break the security of many crypto-systems. Implementation and performance comparison of
the technique is kept for future research.
Design and analysis of algorithms - Abstract ViewWaqas Nawaz
This document discusses the design and analysis of algorithms. It introduces algorithms and defines them as sets of rules to solve computational problems. It emphasizes the importance of both designing algorithms through techniques like divide-and-conquer as well as analyzing their performance through complexity analysis. The document provides examples of analyzing worst-case, best-case, and average-case runtime and uses an example algorithm to find the largest number in an array to demonstrate space and time analysis methods.
The document summarizes the ORB (Oriented FAST and Rotated BRIEF) feature detection and description algorithm. It begins by explaining how ORB improves on SIFT and SURF by combining the FAST keypoint detector with BRIEF descriptors to provide a method that is faster and has rotation invariance. It then describes the FAST detector, BRIEF descriptors, and how ORB adds orientation to BRIEF to achieve rotational invariance. Finally, it provides an overview of the full ORB algorithm and demonstrates its applications in areas like image matching, object recognition, and robot vision.
1) The document describes a vehicle routing project that uses a multi-commodity network flow formulation to explore sub-optimal solutions for object classification with noisy sensors on a 2D grid.
2) It formulates the problem as assigning tasks to vehicles (commodities) that must flow through the graph in 4 directions while being constrained by boundaries and returning to base.
3) The algorithm uses a look-ahead window to consider future moves and a rollout step using linear programming to approximate costs farther in time and decide optimal vehicle movements.
I am Danny G . I am an Electrical Engineering Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. Matlab, Schiller International University, USA. I have been helping students with their homework for the past 9 years. I solve assignments related to Electrical Engineering.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Electrical Engineering Assignments.
The document describes three different searching techniques: linear search, binary search, and DN search. Linear search has a worst case time complexity of O(n) as it searches through each element sequentially. Binary search has a worst case time complexity of O(log n) but requires the list to be sorted. DN search also has a worst case time complexity of O(log n) and can be applied to both sorted and unsorted lists, making it more powerful than the other techniques.
This document discusses using genetic algorithms to cryptanalyze the RSA cryptosystem. It first provides an overview of the RSA algorithm and how it works. It then discusses the Karatsuba algorithm, which can be used to efficiently multiply very large numbers. The document goes on to explain the basic concepts behind genetic algorithms, including representation, selection, crossover, and mutation operators. The authors propose applying genetic algorithms to generate new number pairs p and q that could be used to factor the RSA modulus N and break the cryptosystem. Specifically, they suggest using genetic algorithm operators to generate a new population of p and q values to use in cryptanalyzing RSA.
The document discusses graph-based clustering methods. It describes how graphs can be used to represent real-world networks from domains like biology, technology, social networks, and economics. It introduces the idea of using minimal spanning trees and hierarchical clustering to identify clusters in graph data. Two common algorithms for finding minimal spanning trees are described: Prim's algorithm and Kruskal's algorithm. Different strategies for iteratively deleting branches from the minimal spanning tree are also summarized to form clusters, such as deleting the branch with the maximum weight or inconsistent branches based on a reference value.
The branch-and-bound method is used to solve optimization problems by traversing a state space tree. It computes a bound at each node to determine if the node is promising. Better approaches traverse nodes breadth-first and choose the most promising node using a bounding heuristic. The traveling salesperson problem is solved using branch-and-bound by finding an initial tour, defining a bounding heuristic as the actual cost plus minimum remaining cost, and expanding promising nodes in best-first order until finding the minimal tour.
I am Kennedy L. I am a Digital Signal Processing Assignment Expert at matlabassignmentexperts.com. I hold a Ph.D. in Matlab, Monash University, Australia. I have been helping students with their homework for the past 6 years. I solve assignments related to Digital Signal Processing.
Visit matlabassignmentexperts.com or email info@matlabassignmentexperts.com.
You can also call on +1 678 648 4277 for any assistance with Digital Signal Processing Assignments.
FUAT – A Fuzzy Clustering Analysis ToolSelman Bozkır
This document summarizes fuzzy c-means clustering (FCM) and introduces a software tool called FUAT that aims to address some of the difficulties with FCM. FCM is a soft clustering method that allows data elements to belong to more than one cluster. It is based on fuzzy set theory and combines c-means clustering with handling fuzziness in data. FUAT stands for Fuzzy Unsupervised Analysis Tool and provides features like automatic cluster number detection, interactive viewers for insights into results, and connectivity to R for further analysis. It aims to make fuzzy clustering more transparent and help with challenges like selecting initial centroids and evaluating clusters.
This document discusses lower bounds and limitations of algorithms. It begins by defining lower bounds and providing examples of problems where tight lower bounds have been established, such as sorting requiring Ω(nlogn) comparisons. It then discusses methods for establishing lower bounds, including trivial bounds, decision trees, adversary arguments, and problem reduction. The document explores different classes of problems based on complexity, such as P, NP, and NP-complete problems. It concludes by examining approaches for tackling difficult combinatorial problems that are NP-hard, such as using exact algorithms, approximation algorithms, and local search heuristics.
Manifold learning with application to object recognitionzukun
This document discusses manifold learning techniques for dimensionality reduction that can uncover the intrinsic structure of high-dimensional data. It introduces Isomap and Locally Linear Embedding (LLE) as two popular manifold learning algorithms. Isomap uses graph-based distances to preserve global structure, while LLE aims to preserve local linear relationships between neighbors. Both techniques find low-dimensional embeddings that best represent the high-dimensional data. Manifold learning provides data compression and enables techniques like object recognition by discovering the underlying manifold structure.
Structure and Motion - 3D Reconstruction of Cameras and StructureGiovanni Murru
The document discusses structure from motion reconstruction from multiple images. It provides an overview of the steps to:
1. Estimate camera motion and 3D structure from a sequence of images using a stratified approach, starting with projective reconstruction and refining to affine and metric reconstruction.
2. Reconstruct structure and motion for two datasets - a public dataset and a personal dataset acquired by the student.
3. The key steps are feature detection, matching, estimating the fundamental matrix, triangulating 3D points, identifying the plane at infinity to upgrade from projective to affine reconstruction, and further refinement to metric reconstruction if possible.
This document compares three popular path planning algorithms: A*, greedy best first search, and jump point search. It implements the algorithms in MATLAB using grid-based maps with random start/goal points and static obstacles. The algorithms are evaluated based on computational complexity, time complexity, and space complexity. Jump point search generally has the best performance out of the three algorithms as it can make long jumps along straight lines in the grid, exploring fewer nodes than A*.
Fault diagnosis using genetic algorithms and principal curveseSAT Journals
Abstract Several applications of nonlinear principal component analysis (NPCA) have appeared recently in process monitoring and fault diagnosis. In this paper a new approach is proposed for fault detection based on principal curves and genetic algorithms. The principal curve is a generation of linear principal component (PCA) introduced by Hastie as a parametric curve passes satisfactorily through the middle of data. The existing principal curves algorithms employ the first component of the data as an initial estimation of principal curve. However the dependence on initial line leads to a lack of flexibility and the final curve is only satisfactory for specific problems. In this paper we extend this work in two ways. First, we propose a new method based on genetic algorithms to find the principal curve. Here, lines are fitted and connected to form polygonal lines (PL). Second, potential application of principal curves is discussed. An example is used to illustrate fault diagnosis of nonlinear process using the proposed approach. Index Terms: Principal curve, Genetic Algorithm, Nonlinear principal component analysis, Fault detection.
Optimized Robot Path Planning Using Parallel Genetic Algorithm Based on Visib...IJERA Editor
An analysis is made for optimized path planning for mobile robot by using parallel genetic algorithm. The
parallel genetic algorithm (PGA) is applied on the visible midpoint approach to find shortest path for mobile
robot. The hybrid ofthese two algorithms provides a better optimized solution for smooth and shortest path for
mobile robot. In this problem, the visible midpoint approach is used to make the effectiveness for avoiding
local minima. It gives the optimum paths which are always consisting on free trajectories. But the
proposedhybrid parallel genetic algorithm converges very fast to obtain the shortest route from source to
destination due to the sharing of population. The total population is partitioned into a number subgroups to
perform the parallel GA. The master thread is the center of information exchange and making selection with
fitness evaluation.The cell to cell crossover makes the algorithm significantly good. The problem converges
quickly with in a less number of iteration.
PATH FINDING SOLUTIONS FOR GRID BASED GRAPHacijjournal
Any path finding will work as long as there are no obstacles on distractions along the way. A genetic A*
algorithm has been used for more advanced environments in graph. Implementation of the path finding
algorithm for grid based graph with or without obstacles.
This document discusses parallelizing graph algorithms on GPUs for optimization. It summarizes previous work on parallel Breadth-First Search (BFS), All Pair Shortest Path (APSP), and Traveling Salesman Problem (TSP) algorithms. It then proposes implementing BFS, APSP, and TSP on GPUs using optimization techniques like reducing data transfers between CPU and GPU and modifying the algorithms to maximize GPU computing power and memory usage. The paper claims this will improve performance and speedup over CPU implementations. It focuses on optimizing graph algorithms for parallel GPU processing to accelerate applications involving large graph analysis and optimization problems.
Fast Computational Four-Neighborhood Search Algorithm For Block matching Moti...IJERA Editor
The Motion estimation is an effective method for removing temporal redundancyfound in video sequence compression. Block Matching algorithm has been widely used in motion estimation and a number of fast algorithms have proposed to reduce the computational complexity of BMA. In this paper we propose a new search strategy for fast block matching based on Four-Neighborhood Search (FNS) and fast computational strategy, this new algorithm can significantly speed up the computation of the block matching by reducing the number of checked points and the time computational. Results have been shown that 89% to 93% of operations can be saved while maintaining the quality of video relative to full search algorithm.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
GRAPH MATCHING ALGORITHM FOR TASK ASSIGNMENT PROBLEMIJCSEA Journal
Task assignment is one of the most challenging problems in distributed computing environment. An optimal task assignment guarantees minimum turnaround time for a given architecture. Several approaches of optimal task assignment have been proposed by various researchers ranging from graph partitioning based tools to heuristic graph matching. Using heuristic graph matching, it is often impossible to get optimal task assignment for practical test cases within an acceptable time limit. In this paper, we have parallelized the basic heuristic graph-matching algorithm of task assignment which is suitable only for cases where processors and inter processor links are homogeneous. This proposal is a derivative of the basic task assignment methodology using heuristic graph matching. The results show that near optimal assignments are obtained much faster than the sequential program in all the cases with reasonable speed-up.
An efficient hardware logarithm generator with modified quasi-symmetrical app...IJECEIAES
This paper presents a low-error, low-area FPGA-based hardware logarithm generator for digital signal processing systems which require high-speed, real time logarithm operations. The proposed logarithm generator employs the modified quasi-symmetrical approach for an efficient hardware implementation. The error analysis and implementation results are also presented and discussed. The achieved results show that the proposed approach can reduce the approximation error and hardware area compared with traditional methods.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining ApproachMangaiK4
This document summarizes a research paper that proposes a new algorithm called BugLoc for detecting bugs in multi-threaded software applications via graph mining. The algorithm uses an object template to store graph data from a sample dataset in order to reduce complexity. It then calculates threshold values and identifies frequent subgraphs to detect the exact location of software bugs. The experimental results showed that the BugLoc algorithm is efficient, accurate and scalable for large graph datasets in bug localization.
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining ApproachMangaiK4
Abstract - Detection of software bugs and its occurrences, repudiation and its root cause is a very difficult process in large multi threaded applications. It is a must for a software developer or software organization to identify bugs in their applications and to remove or overcome them. The application should be protected from malfunctioning. Many of the compilers and Integrated Development Environments are effectively identifying errors and bugs in applications while running or compiling, but they fail in detecting actual cause for the bugs in the running applications. The developer has to reframe or recreate the package with the new one without bugs. It is time consuming and effort is wasted in Software Development Life Cycle. There is a possibility to use graph mining techniques in detecting software bugs. But there are many problems in using graph mining techniques. Managing large graph data, processing nodes with links and processing subgraphs are the problems to be faced in graph mining approach. This paper presents a novel algorithm named BugLoc which is capable of detecting bugs from the multi threaded software application. The BugLoc uses object template to store graph data which reduces graph management complexities. It also uses substring analysis method in detecting frequent subgraphs. The BugLoc then analyses frequent subgraphs to detect exact location of the software bugs. The experimental results show that the algorithm is very efficient, accurate and scalable for large graph data set.
Node Path Visualizer Using Shortest Path AlgorithmsIRJET Journal
This document describes a tool for visualizing shortest path algorithms. The tool allows users to create and save graph structures and visualize the step-by-step execution of algorithms like Dijkstra's algorithm. It is intended to supplement classroom instruction or be used as a complete e-learning application. The tool implements grid-based graphs and allows selection of different pathfinding algorithms to find the shortest path between two nodes. Algorithms can be unweighted or weighted based on node values. The tool aims to help students better understand shortest path algorithms through interactive visualization.
M ESH S IMPLIFICATION V IA A V OLUME C OST M EASUREijcga
We develop a polygonal mesh simplification algorithm based on a novel analysis of the mesh
geometry.
Particularly, we propose first a characterization of vertices as hyperbolic or non
-
hyperbolic depend
-
ing
upon their discrete local geometry. Subsequently, the simplification process computes a volume cost for
each non
-
hyperbolic vertex, in anal
-
ogy with spherical volume, to capture the loss of fidelity if that vertex
is decimated. Vertices of least volume cost are then successively deleted and the resulting holes re
-
triangulated using a method based on a novel heuristic. Preliminary experiments i
ndicate a performance
comparable to that of the best known mesh simplification algorithms
IRJET- Object Detection using Hausdorff DistanceIRJET Journal
This document proposes a new object recognition system using Hausdorff distance. The system aims to improve on existing methods like YOLO that struggle with small objects and can capture garbage data. The document outlines preprocessing steps like noise cancellation, representing shapes as point sets, and extracting features. It then describes using Hausdorff distance and shape context to find the best match between input and reference shapes. Testing on datasets showed encouraging results for recognizing handwritten digits.
IRJET - Object Detection using Hausdorff DistanceIRJET Journal
This document proposes using Hausdorff distance for object detection as it can better handle noise compared to other methods like Euclidean distance. The document discusses preprocessing images using Gaussian filtering for noise cancellation. It then represents shapes as point sets for feature extraction before using Hausdorff distance to match shapes between reference and test images for object recognition. Encouraging results were obtained when testing on MNIST, COIL and private handwritten digit datasets.
A PROJECT REPORT ON REMOVAL OF UNNECESSARY OBJECTS FROM PHOTOS USING MASKINGIRJET Journal
This document presents a project report on removing unnecessary objects from photos using masking techniques. It discusses using algorithms like Fast Marching and Navier-Stokes to fill in missing image data and maintain continuity across boundaries. The Fast Marching method begins at region boundaries and works inward, prioritizing completion of boundary pixels first. Navier-Stokes uses fluid dynamics equations to continue intensity value functions and ensure they remain continuous at boundaries. Color filtering can also be used to segment specific colored objects or regions. The project aims to implement these techniques to remove unwanted objects from images and fill the resulting gaps seamlessly.
1) The document discusses algorithms for finding optimal bus routes between locations, including Dijkstra's algorithm and improvements made to address its limitations.
2) It analyzes shortest path algorithms based on graph theory, least transfers, and station matrices. An improved Dijkstra's algorithm is proposed to find shortest paths between any two nodes.
3) The results show the improved algorithm can determine the shortest distance and transfer routes between any four bus stations, demonstrating its accuracy and feasibility for route planning applications.
IRJET- Survey on Implementation of Graph Theory in Routing Protocols of Wired...IRJET Journal
This document discusses how graph theory and shortest path algorithms are used in routing protocols for wired computer networks. It provides an overview of different routing protocols (RIP, OSPF, EIGRP) and the shortest path algorithms they use (Bellman-Ford, Dijkstra's) to determine the best route between nodes. The author analyzes the efficiency of these routing protocols and algorithms based on how quickly they can calculate the shortest path, especially as network sizes increase. The focus is on analyzing undirected graphs to model computer networks where traffic can flow bidirectionally.
Similar to IRJET- Bidirectional Graph Search Techniques for Finding Shortest Path in Image based Maze Problem (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
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.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
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.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
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.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
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.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.