Top PDF Optimized Proposed Algorithm for Graph Traversal

Optimized Proposed Algorithm for Graph Traversal

Optimized Proposed Algorithm for Graph Traversal

Step 2: After going to A, it’s neighboring unvisited nodes B,D gets visited and thus the adjacent edge count for A,B, and D will be 0.So the adjacency matrix will be:.. Step 4: As all th[r]

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Recursive contraction algorithm: a novel and efficient graph traversal method for scanning all minimal cut sets

Recursive contraction algorithm: a novel and efficient graph traversal method for scanning all minimal cut sets

The RCA_MC algorithm is a modification of Tsukiyama’s algorithm in [14]. Both algorithms are recursive methods that examine the connectivity of subgraphs obtained by deleting edge cutsets. Besides, they both exhaustively scan all connected subgraphs. However, they are different in their scanning methods; where in Tsukiyama’s algorithm the notion of 1-point extensions are used for this purpose, as compared to our proposed scheme which uses BFS ordering of vertices adjacent to a contracted node. This difference enables us to develop the ERCA_MC algorithm, which skips over those subgraphs that do not contribute to the list of minimal cutsets. As finding cutsets is a recursive process, significant reductions in the processing time can be achieved. In cases where no subgraph can be skipped, both the RCA_MC and the ERCA_MC algorithms have the same number of recursions. We use simulations to provide empirical evidence that the complexity of the ERCA_MC algorithm is linear per edge cutset.
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Obstacle-Avoiding Rectilinear Steiner Minimum Tree: A Survey

Obstacle-Avoiding Rectilinear Steiner Minimum Tree: A Survey

Table based wirelength Estimation (OA_FLUTE) in order to generate OARSTs and then recombine them. To make the initial connected graph, FOARS uses OASG.FLUTE is a very robust and speed tool get the RSMT and is widely used in academic global routers but FLUTE is not built for handling obstacles. To create OARSMT the SRT generated using FLUTE is applied with obstacles, local optimization is done and later all the locally optimized trees are combined to get the final solution. But since there is no global view taken into consideration, this scheme fails to support large number of points or complexly placed obstacles. To overcome this issue partitioning algorithm is proposed which provides a global view for the problem at higher level and partition problem into smaller ones. This algorithm is divided into five stages. OASG generation-connectivity graph is generated novel octant OASG generation algorithm. Obstacle Penalized MST (OPMST) generation- MTST is generated from OASG and OPMST is generated from MTST.OAST generation- Based on OPMST, partitioning is done and the partitioned are processed under OA_FLUTE.OARST generation – Rectilinearization is done and later V-shape refinement is done to reduce the wire length.Run time complexity of FOARS algorithm is O(n log n).
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Test Case Generation for UML Behavioral Diagram by Traversal Algorithm

Test Case Generation for UML Behavioral Diagram by Traversal Algorithm

Rajiv mall et al. [4] presented a process to produce test cases by applying combination of use case and sequence diagram. They transform diagrams into their respective graphs. Then graphs are merged together to make the system graph. But, it was not clearly shown that how graphs are merged together. The optimization is not done for generated test cases. Abinash Tripathy et al. [3] give an idea to produce test cases. They amalgamate UML AD and SD for card validation . Ranjita Kumari Swain et al. [5] have produced the test cases using AD. In their method, activity diagram is initially transformed into ADG. The depth first traversal technique is used for traversing the paths. All activity paths are produced by using proposed algorithm. Finally, path coverage criterion is used for TCG. Swagatika Dalai et al. [9] described a method to produce test cases for object oriented systems using integrated UML Models. Then traversing is completed to produce test cases. But optimization of test cases is still not completed.
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Efficient Mining Web Navigation Pattern using an Efficient Graph Traverse Algorithm

Efficient Mining Web Navigation Pattern using an Efficient Graph Traverse Algorithm

Abstract— In the modern world navigational behaviour of website visitor is an important role. In this paper implemented the web navigational pattern for college websites. Traditional method of web usage mining approach gives inefficient result for their web navigational pattern. So to overcome this, in this paper proposed an algortihm through-surfing pattern (TSP) from incremental database for college websites. The term TSP are well known to display the next visited Web pages in a browsing session. To record the information about navigation path of college website visitors by introducing path traversal graph and also applied the proposed efficient graph traverse algorithm depend on the proposed number of maximal references of path traversal pattern to discover the TSPS. The experimental results show the proposed mining method of TSP for college websites is provide high efficient and effective precision and recall based on minimum support compared to other approaches.
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Evaluation of Proposed Algorithm with Preceding GMT for Fraudulence Diagnosis

Evaluation of Proposed Algorithm with Preceding GMT for Fraudulence Diagnosis

CONCLUSION & FUTURE SCOPE In spite of the fact that the present algorithm as of now performs entirely well, it can be implemented on a regular basis frameworks to follow the pattern of Fraud ascent and fall in the offer financial sector and we can look at the present graph of financial changes with the pattern present in graph database, so that on the off chance that it finds any similarity in the pattern it can force a security check over that specific transaction and foresee the future progress .This could be helpful in arranging the avoidance of a few wrongdoings which can add to the general population who gets influenced because of fraud. graph mining is a right now exceptionally dynamic research industry. The application zones of graph mining are across the board expanding from science and technology to web applications.
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Keyword Mining and Co-Word Construction by Proposed Tagging, Statistical and Graph Based (TSG) Algorithm

Keyword Mining and Co-Word Construction by Proposed Tagging, Statistical and Graph Based (TSG) Algorithm

TF-ISF statistical approach is applied on property group terms and raw group terms only, because title group terms are never presented in sentences. This method is inverse function method. Because of this inverse nature, this approach eliminates the words, even though having more frequencies but not much contributed to find out the concept of the document. For example, word appears more number of times in a single sentence is not an important keyword. By comparing the top ranked high frequency words with the top ranked TS-ISF words, the common words of both property group and raw group terms are identified and labelled as property group keywords and raw group keyword. After applying the statistical approaches to our three group terms, first part of our proposed algorithm derives the ranked keyword set for title group, property group and raw group. The second part of the proposed algorithm constructs the co-words from the derived keywords. Co-words are constructed by identifying the binding or linkages or strength among the derived keywords. The proposed algorithm finds the linkage strength between the words by three different approaches. First approach is co-occurrence statistical information (CSI), which is statistical approach. Second method is graph based co-word construction approach and the last approach is co-occurrence matrix approach. The following Algorithm 3 explains the co-word construction process using co-occurrence statistical information (CSI) and graph based method.
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A novel FPGA segmentation method based on the improved ant colony optimization

A novel FPGA segmentation method based on the improved ant colony optimization

Since the above has analyzed the construction of m -partite weighted graph, the discussion here mainly focuses on how to find a forest in a m -partite weighted graph satisfying the following constraints: The weighted sum is maximal, and any two vertexes of any tree do not belong to one part simultaneously. The detailed implementation process is shown as below (relevant mathematical procedures will be shown in appendixes).

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Task Time Optimization of a Robot Manipulator using Artificial Neural Network and Genetic Algorithm

Task Time Optimization of a Robot Manipulator using Artificial Neural Network and Genetic Algorithm

In this paper we have proposed an evolutionary method to optimize the task time of robot manipulators. Tasks can be planned in joint space with respect to robot joints or in Cartesian space with respect to robot end effector under kinodynamic constraints. Genetic algorithm is implemented to optimize the parameters associated with the selected motion trajectory profile. These optimized results were then taken as the training data to train an artificial neural network which is used to obtain task time, velocity, accelerations and torques required by each motor to perform a given task. The method adopted in this study can be applied to any serial redundant or non-redundant manipulator that has rigid links and known kinematic and dynamic models with free motions or motions along specified paths with obstacle avoidance. The robot kinematic and dynamic models and the optimization method are developed in MATLAB.
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An Optimized BP Algorithm Based on PLS

An Optimized BP Algorithm Based on PLS

Using neural network processing singular sample, which with many characteristic variables and few samples, in the characteristic variables set may be exist a high degree of correlation between the variables, may cause data redundancy, take up storage space, and computing time; while the relatively few samples may lead to network training is not complete. Aim at these deficiencies of singular sample, in this paper, based on PLS algorithm, combined with BP neural network algorithm, and proposed and optimized BP neural network algorithm based on PLS algorithm (PLS-BP algorithm).
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Trust based Secure Graph Detection Algorithm with Routing Graph Modelling in Wireless AdHoc Network

Trust based Secure Graph Detection Algorithm with Routing Graph Modelling in Wireless AdHoc Network

The trust based Secure Routing Protocol (TSR) was the first Hybrid routing protocol. It was proposed to reduce the control overhead of Proactive routing protocol and to decrease the latency of Reactive routing protocol. It is suitable for the networks with large span and diverse mobility patterns. For each node a routing zone is defined separately. Within the routing zone, routes are available immediately but for outside the zone, TSR employs route discovery procedure. For each node, a separate routing zone is defined. The routing zones of neighbouring nodes overlap with each other’s zone. Each routing zone has a radius ρ expressed in hops. The zone includes the nodes whose distance from the source node is at most ρ hops.
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An Improved Algorithm for Inducing Classifica...

An Improved Algorithm for Inducing Classifica...

In this present scenario, gradually the world develop into more earliest at the equivalent time more and more difficult and spirited so that decision making must be taken in an optimal approach for enhanced outcome in a quicker mode. As a result optimization is very significant and regarding act of acquiring the best result below given circumstances. This is the explanation following why optimization has been an admired research topic for decades. Ant colony algorithm may generate unnecessary conditions in the graph; it‘s enhanced to reduce such graphs to improve the actions of the introduced scheme. By moving, each ant incrementally creates an explanation to the predicament.
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Clustering 1-dimensional periodic network using betweenness centrality

Clustering 1-dimensional periodic network using betweenness centrality

Because of the applications discussed in the previous paragraph, there are many works that proposed algorithms for the graph. Those works include a work by Orlin, who proposes algorithms to determine weakly connected components [7], strongly con- nected components [7], Eulerian paths [7], minimum cost spanning trees [7], maximum flows [8], and minimum cost flows [9]. Later, Cohen and Megiddo propose algorithms to test bipartiteness [10] and detect cycles [11] in the periodic graphs. Besides that, an algorithm to test a planarity of a given periodic graph is proposed by Iwano and Steiglitz in [12], and an algorithm to find a shortest path for an arbitrary periodic graph is pro- posed by Höfting and Wanke in [13]. In [14], Fu proposes the shortest path algorithm for a special class of planar periodic graphs. The result shows that planarity can help in speeding up the computation of the previous shortest path algorithm.
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Ontology modularization: principles and practice

Ontology modularization: principles and practice

Seidenberg and Rector [115] developed a technique specifically for extracting an ontol- ogy module from the GALEN 6,7 medical ontology. However, the core of the technique is generic and can be applied to other ontologies. The technique takes one or more classes of the ontology as input, the Sig(M ), and anything that participates, even indi- rectly, to the definition of an included class is added to the ontology module too. The algorithm can be broken down as follows, assume we have a Sig(M ) = {A}. Firstly the hierarchy is upwardly traversed (analogous to Upper Cotopy defined in [93], which calculates the set of super-concepts of a concept), so all of the A’s superclasses are included. Next the hierarchy is downwardly traversed so that all the A’s subclasses are included. It should be noted that the sibling classes of A are not included, they could be included by explicitly adding them to the Sig(M). The restrictions, intersection, union and equivalent classes of the already included classes can now be added to the module. Lastly, properties across the hierarchy from the previously included classes are traversed; the target of these links are only upwardly traversed.
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A Novel Content-Based Image Retrieval Technique Using Tree Matching

A Novel Content-Based Image Retrieval Technique Using Tree Matching

As image region features may have different ranges (one region with very small value and one region with very huge value), therefore a normalization method should be applied on each of them. We employed min/max algorithm [2] as shown in the following formula to achieve a weighted normalized similarity factor between two features I and I', where ω is an initial weight:

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High-Throughput Finite Field Multipliers Using Redundant Basis for FPGA and ASIC Implementations

High-Throughput Finite Field Multipliers Using Redundant Basis for FPGA and ASIC Implementations

evolved as a mainstream dedicated computing platform. FPGAs however do not have abundant number of registers to be used in the multiplier. Therefore, we have modified the proposed algorithm and architecture for reduction of register- complexity particularly for the implementation of RB multipliers on FPGA platform. Apart from these we also present a low critical-path digit-serial RB multiplier for very high throughput applications. 2 LITERATURE SURVEY

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Small-Size Broadband Coding Metasurface for RCS Reduction Based on Particle Swarm Optimization Algorithm

Small-Size Broadband Coding Metasurface for RCS Reduction Based on Particle Swarm Optimization Algorithm

The population used in the PSO module is set to 100, and the number of iterations N iter is set to 500. The initial phase value of the unit cell structure is 0 or π, which is simplified to 0 or 1 in the design of the algorithm. The fitness function curve obtained by numerical optimization in MATLAB is shown in Fig. 3(a). It can be seen that the curve decreases rapidly in the initial stage and then tends to be a stable value. The final result of coding sequence optimization is shown in Fig. 3(b).

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A Novel Design For Generating Dynamic Length Message Digest To Ensure Integrity Using Block Cipher Approach

A Novel Design For Generating Dynamic Length Message Digest To Ensure Integrity Using Block Cipher Approach

Internal designing of the proposed algorithm is totally different from the existing SHA or MD algorithms. It is designed on a principal of cryptographic block cipher chaining mode. It has broken an earlier fashion of generating a fixed size digest; it generates a variable size digest. Also, proposed algorithm works on a pseudo – random number which gives the proposed algorithm strength and stand against various attacks. Steps to design the hash using proposed algorithm is as follows:

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An Efficient Stack Based Graph Traversal Method for Network Configuration

An Efficient Stack Based Graph Traversal Method for Network Configuration

Vijayalakshmi M K, Mysuru, Karnataka. Completed B.Ed in theyear 2018 from Amrita School of Education,AmritaVishwaVidyapeetham, Mysuru.Studied M.Sc Mathematics in the year 2015 from JSS College ofArts, Commerce and Sciences, Ooty road Mysuru. Have done fourmonths of teaching internship in Vishwaprajna School, Mysuru while doing B.Ed.Attended ‘One day National Conference on Recent Advances in Mathematics’ , organized by Department of Mathematics, JSS College of Arts, Commerce and Science,, Mysuru.Attended ‘International Conference on Mathematics- Yesterday and Today’ at JSS College of Arts, Commerce and Science, Mysuru.Participated in ‘One Day National Seminar – SUJNANA Education for Excellence’ at RIMSE, Mysuru.Project on ‘Data Integrity Proof in Cloud Storage’.Project on ‘Leaf Chromatography’.Presented a paper in National Conference “Structural,Institutional and Financial sector changes in the new Millennium and theroad ahead” on the topic “Perspective of Teacher Educators on two yearB.Ed course suggested by NCTE and assessing their TeachingCompetencies in imparting it”. Published an article “Perspective of Teacher Educators on two year B.Ed course suggested by NCTE and assessing their Teaching Competencies in imparting it” in an IOSR JOURNAL.Presented a paper in Two Day National Conference “Recent Innovations in Computing, Communication and Intelligent Systems (RICCIS’19) on the topic “An Efficient Stack Based Graph Traversal Method
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Reference Scan Algorithm for Path Traversal Patterns

Reference Scan Algorithm for Path Traversal Patterns

As it has been told before that World Wide Web is made up of incredible amount of information which is in a hierarchical structure where the pages are considered as nodes and they are linked with each other via hyperlinks represented using arrows and the users can move forward and backward with the help of hyperlinks and icons rendered to them. Some pages may be visited again by the user because of the location of the web page than its content, say for example to visit a sibling node the user usually uses the backward icon and then forward icon instead of going straight to the URL. So finally to get useful traversal patterns of the user from the server data the need is to prune the effect of these backward visits and extract the useful patterns of importance. In this paper it is being assumed that the backward traversals are just for the ease of moving to the previous page and the main concentration is on the discovery of meaningful forward user access patterns. A backward reference is basically for accessing the previously visited page by the same user. When a previous access is made by the user the path user was moving on terminates. This gives us a forward reference path which we term as maximal forward reference. After obtaining the maximal forward reference it starts again from the starting point from where we started to obtain the forward reference path and then resume in obtaining a new user traversed path. Also if a null source node appears termination should be made and a new path should be found again.
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