To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
This document discusses a proposed system for improving social-based routing in delay tolerant networks. The proposed system takes into account both the frequency and duration of contacts to generate a higher quality social graph. It also studies community evolution to dynamically detect overlapping communities and bridge nodes in social networks. Simulation results show the proposed routing algorithm outperforms existing strategies significantly.
This document discusses enabling efficient data queries in Mobile Ad-hoc SOcial Networks (MASONs). MASONs allow users with shared interests to connect via Bluetooth or WiFi to query localized data from each other's devices. The challenges of opportunistic connectivity, distributed storage, and unknown expertise are addressed. A centralized optimization model is proposed to minimize communication costs while supporting query rates within delay budgets. A distributed query protocol uses "reachable expertise" routing and controlled redundancy to improve query delivery rates. The protocol's feasibility and efficiency are evaluated through a testbed and simulations.
This document discusses predicting new friendships in social networks using temporal information. It describes research on predicting new links in social networks over time using supervised learning models trained on temporal features from past network interactions. The researchers used anonymized Facebook data over 28 months to train decision tree and neural network classifiers to predict new relationships, finding models using temporal information performed better than those without it.
Graph theory concepts like centrality, clustering, and node-edge diagrams are used to analyze social networks. Visualization techniques include matrix representations and node-link diagrams, each with advantages. Hybrid representations combine these to leverage their strengths. MatrixExplorer allows interactive exploration of social networks using both matrix and node-link views.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
This document provides an overview of social network analysis, including key concepts, analytic techniques, and examples of classic studies. It discusses the basic components of social networks like actors, ties, and relationships. It also describes different types of networks and measures used in social network analysis, such as degree centrality and betweenness centrality. Finally, it highlights some influential early social network analysis studies and resources for further information.
This document discusses social network analysis (SNA), a tool used to analyze social relationships and networks. SNA elicits, analyzes, and visualizes how actors interact and resources move through a network. It represents actors as nodes and their relationships as ties. The document provides examples of SNA's application in education, health, and agriculture. It outlines the process of conducting SNA through workshops or surveys to collect node attribute and tie/link data, which is then analyzed using software to visualize the network. The document suggests opportunities to further develop SNA, such as presenting networks back to communities and measuring social capital.
An updated look at social network extraction system a personal data analysis ...eSAT Publishing House
This document summarizes a study on analyzing personal social network data over time. The study extracted data from Facebook, calculated social network analysis metrics like degree distribution and betweenness centrality, and analyzed how the network changed dynamically over time. Key findings included identifying influential and non-influential users, detecting communities that formed within the network, and identifying the celebrity or most influential user within one person's local network. Analyzing how social networks and interactions change dynamically provides insights useful for applications like marketing and recommendations.
This document discusses a proposed system for improving social-based routing in delay tolerant networks. The proposed system takes into account both the frequency and duration of contacts to generate a higher quality social graph. It also studies community evolution to dynamically detect overlapping communities and bridge nodes in social networks. Simulation results show the proposed routing algorithm outperforms existing strategies significantly.
This document discusses enabling efficient data queries in Mobile Ad-hoc SOcial Networks (MASONs). MASONs allow users with shared interests to connect via Bluetooth or WiFi to query localized data from each other's devices. The challenges of opportunistic connectivity, distributed storage, and unknown expertise are addressed. A centralized optimization model is proposed to minimize communication costs while supporting query rates within delay budgets. A distributed query protocol uses "reachable expertise" routing and controlled redundancy to improve query delivery rates. The protocol's feasibility and efficiency are evaluated through a testbed and simulations.
This document discusses predicting new friendships in social networks using temporal information. It describes research on predicting new links in social networks over time using supervised learning models trained on temporal features from past network interactions. The researchers used anonymized Facebook data over 28 months to train decision tree and neural network classifiers to predict new relationships, finding models using temporal information performed better than those without it.
Graph theory concepts like centrality, clustering, and node-edge diagrams are used to analyze social networks. Visualization techniques include matrix representations and node-link diagrams, each with advantages. Hybrid representations combine these to leverage their strengths. MatrixExplorer allows interactive exploration of social networks using both matrix and node-link views.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
This document provides an overview of social network analysis, including key concepts, analytic techniques, and examples of classic studies. It discusses the basic components of social networks like actors, ties, and relationships. It also describes different types of networks and measures used in social network analysis, such as degree centrality and betweenness centrality. Finally, it highlights some influential early social network analysis studies and resources for further information.
This document discusses social network analysis (SNA), a tool used to analyze social relationships and networks. SNA elicits, analyzes, and visualizes how actors interact and resources move through a network. It represents actors as nodes and their relationships as ties. The document provides examples of SNA's application in education, health, and agriculture. It outlines the process of conducting SNA through workshops or surveys to collect node attribute and tie/link data, which is then analyzed using software to visualize the network. The document suggests opportunities to further develop SNA, such as presenting networks back to communities and measuring social capital.
An updated look at social network extraction system a personal data analysis ...eSAT Publishing House
This document summarizes a study on analyzing personal social network data over time. The study extracted data from Facebook, calculated social network analysis metrics like degree distribution and betweenness centrality, and analyzed how the network changed dynamically over time. Key findings included identifying influential and non-influential users, detecting communities that formed within the network, and identifying the celebrity or most influential user within one person's local network. Analyzing how social networks and interactions change dynamically provides insights useful for applications like marketing and recommendations.
Community Detection in Social Networks: A Brief OverviewSatyaki Sikdar
The document provides an overview of community detection in social networks. It discusses that networks are found everywhere where there are interactions between actors. It then motivates the importance of detecting communities by explaining that communities are groups of nodes that likely share properties and roles. Detecting communities has applications like improving recommendation systems and parallel computing. It also justifies the existence of communities in real networks using the concept of homophily where similar actors tend to connect. The document then discusses different approaches to detecting communities including Girvan-Newman algorithm based on edge betweenness and Louvain method which uses greedy modularity optimization.
1. The document discusses the history and modeling of social networks, from early concepts like "six degrees of separation" to current models like scale-free networks.
2. It describes different models that have been used to represent social networks mathematically, including random graphs, small-world networks, and scale-free networks which have highly connected hubs.
3. Current research focuses on characterizing network topology, understanding dynamic processes on networks, and how networks respond to failures or attacks.
The Mathematics of Social Network Analysis: Metrics for Academic Social NetworksEditor IJCATR
Social network analysis plays an important role in analyzing social relations and patterns of interaction among actors in a
social network. Such networks can be casual, like those on social media sites, or formal, like academic social networks. Each of these
networks is characterised by underlying data which defines various features of the network. Keeping in view the size and diversity of
these networks it may not be possible to dissect entire network with conventional means. Social network visualization can be used to
graphically represent these networks in a concise and easy to understand manner. Social network visualization tools rely heavily on
quantitative features to numerically define various attributes of the network. These features also referred to as social network metrics
used everyday mathematics as their foundations. In this paper we provide an overview of various social network analysis metrics that
are commonly used to analyse social networks. Explanation of these metrics and their relevance for academic social networks is also
outlined
This document provides an overview of social network analysis (SNA). It defines social networks as sets of nodes (individuals) connected by links, with SNA having roots in sociology, economics, physics and mathematics emerging in the 1930s. The document discusses software used to perform SNA, and how networks can be analyzed by their shapes, types, and measures at the node and network levels. It provides examples of how SNA can be used across sectors and industries, and for organizations in Cambodia specifically. A case study example is also presented.
An introduction in the world of Social Network Analysis and a view on how this may help learning networks. History, data collection and several analysis techniques are shown.
1. Basics of Social Networks
2. Real-world problem
3. How to construct graph from real-world problem?
4. What graph theory problem getting from real-world problem?
5. Graph type of Social Networks
6. Special properties in social graph
7. How to find communities and groups in social networks? (Algorithms)
8. How to interpret graph solution back to real-world problem?
Community detection algorithms are used to identify densely connected groups of nodes in networks. Modularity optimization is commonly used, which detects communities as groups of nodes with more connections within groups than expected by chance. Parameters like resolution affect results. Multilayer networks model systems with multiple network layers over nodes. Multilayer modularity generalizes modularity to multilayer networks. Community detection in multilayer networks provides insights into structures across data types and applications.
FAST AND ACCURATE MINING THE COMMUNITY STRUCTURE: INTEGRATING CENTER LOCATING...Nexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
This document summarizes two presentations about community detection in social media networks. The first presentation discusses using edge content, like image tags, to help identify communities in networks. The second focuses on leveraging interaction intensities on Twitter to detect communities that form around certain events over time. Both aim to improve on traditional methods that only consider network structure.
Hybrid sentiment and network analysis of social opinion polarization icoictAndry Alamsyah
The rapid growth of social media and user generated contents (UGC) has provided a rich source of potentially relevant data. The problems arise on how to summarize those data to understand and transforming it into information. Twitter as one of the most popular social networking and micro-blogging service can be analyzed in terms of content produced with sentiment analysis. On the other hand, some types of networks can also be constructed to analyze the social network structure and network properties. This research intended to combine those content and structural approaches into hybrid approach for identifies social opinion polarization, this is in the form of conversation network. Sentiment analysis used to determine public sentiment, and social network analysis used to analyze the structure of the network, detecting communities and influential actors in the network. Using this hybrid approach, we have comprehensive understanding about social opinion polarization. As case study, we present real social opinion polarization about reclamation issue in Indonesia.
The document discusses social networks and their applications. It provides an overview of social network properties like diameter, degree distributions, clustering, and small world models. It then discusses how e-markets can enable trading of information and provides examples like stock markets and price posting markets. It proposes a model of a social network where economic agents are connected based on trust and a seller can use the network to sell products by approaching recommenders and their friends. The system would update trustworthiness and connections based on purchase decisions.
The document discusses network diffusion and peer influence. It begins by defining diffusion and compartment models used to model disease spread. It then discusses how network structure, including topology, timing of connections, and structural transmission, can impact diffusion. Simulation is proposed to test how network features like distance, clustering, redundancy, and high-degree nodes influence spread. The relationships between contact networks, exposure networks based on timing, and actual transmission networks are also introduced.
This document provides an overview of social network analysis (SNA) including concepts, methods, and applications. It begins with background on how SNA originated from social science and network analysis/graph theory. Key concepts discussed include representing social networks as graphs, identifying strong and weak ties, central nodes, and network cohesion. Practical applications of SNA are also outlined, such as in business, law enforcement, and social media sites. The document concludes by recommending when and why to use SNA.
A comparative study of social network analysis toolsDavid Combe
This document compares several social network analysis tools based on their functionalities and benchmarks them using sample datasets. It finds that Pajek, Gephi, igraph, and NetworkX are mature tools that handle network representation, visualization, characterization with indicators, and community detection well. Gephi is interactive but community detection is experimental. NetworkX is attribute-friendly and handles large networks but lacks visualization. Igraph is optimized for clustering but not custom attributes. The best tool depends on the specific analysis needs.
Graph and language embeddings were used to analyze user data from Reddit to predict whether authors would post in the SuicideWatch subreddit. Metapath2vec was used to generate graph embeddings from subreddit and author relationships. Doc2vec was used to generate document embeddings based on language similarity between submissions and subreddits. Combining the graph and document embeddings in a logistic regression achieved 90% accuracy in predicting SuicideWatch posters, reducing both false positives and false negatives compared to using the embeddings separately. Next steps proposed using the embeddings to better understand similarities between related subreddits and predict risk factors in posts.
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS Signature searching in a netwo...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS A scientometric analysis of cloud c...IEEEMEMTECHSTUDENTPROJECTS
This document discusses a proposed system for improving the process of clustering and displaying search results from literature on cloud computing. The existing system has problems with only displaying results from registered candidates, poor data display, and lack of security. The proposed system aims to display the highest ranking search keywords based on user and publisher rankings to make the process more secure. It uses clustering to automatically organize documents by topic to improve information retrieval. The system would have administrative, publisher, search, and user modules and use ASP.Net and SQL Server software.
IEEE 2014 DOTNET DATA MINING PROJECTS Product aspect-ranking-and--its-applica...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET DATA MINING PROJECTS Trusted db a-trusted-hardware-based-dat...IEEEMEMTECHSTUDENTPROJECTS
The document describes TrustedDB, a database system that uses trusted hardware to enable private queries on outsourced data. TrustedDB allows clients to execute SQL queries while preserving privacy and regulatory compliance by leveraging tamper-proof trusted hardware for sensitive query processing stages. This removes limitations of software-only encryption approaches. The system partitions queries into public and private components, executing the latter on secure hardware for better performance and lower costs than solely cryptographic approaches. Evaluation shows TrustedDB can support full-fledged databases on trusted hardware more cost-effectively than existing techniques.
Community Detection in Social Networks: A Brief OverviewSatyaki Sikdar
The document provides an overview of community detection in social networks. It discusses that networks are found everywhere where there are interactions between actors. It then motivates the importance of detecting communities by explaining that communities are groups of nodes that likely share properties and roles. Detecting communities has applications like improving recommendation systems and parallel computing. It also justifies the existence of communities in real networks using the concept of homophily where similar actors tend to connect. The document then discusses different approaches to detecting communities including Girvan-Newman algorithm based on edge betweenness and Louvain method which uses greedy modularity optimization.
1. The document discusses the history and modeling of social networks, from early concepts like "six degrees of separation" to current models like scale-free networks.
2. It describes different models that have been used to represent social networks mathematically, including random graphs, small-world networks, and scale-free networks which have highly connected hubs.
3. Current research focuses on characterizing network topology, understanding dynamic processes on networks, and how networks respond to failures or attacks.
The Mathematics of Social Network Analysis: Metrics for Academic Social NetworksEditor IJCATR
Social network analysis plays an important role in analyzing social relations and patterns of interaction among actors in a
social network. Such networks can be casual, like those on social media sites, or formal, like academic social networks. Each of these
networks is characterised by underlying data which defines various features of the network. Keeping in view the size and diversity of
these networks it may not be possible to dissect entire network with conventional means. Social network visualization can be used to
graphically represent these networks in a concise and easy to understand manner. Social network visualization tools rely heavily on
quantitative features to numerically define various attributes of the network. These features also referred to as social network metrics
used everyday mathematics as their foundations. In this paper we provide an overview of various social network analysis metrics that
are commonly used to analyse social networks. Explanation of these metrics and their relevance for academic social networks is also
outlined
This document provides an overview of social network analysis (SNA). It defines social networks as sets of nodes (individuals) connected by links, with SNA having roots in sociology, economics, physics and mathematics emerging in the 1930s. The document discusses software used to perform SNA, and how networks can be analyzed by their shapes, types, and measures at the node and network levels. It provides examples of how SNA can be used across sectors and industries, and for organizations in Cambodia specifically. A case study example is also presented.
An introduction in the world of Social Network Analysis and a view on how this may help learning networks. History, data collection and several analysis techniques are shown.
1. Basics of Social Networks
2. Real-world problem
3. How to construct graph from real-world problem?
4. What graph theory problem getting from real-world problem?
5. Graph type of Social Networks
6. Special properties in social graph
7. How to find communities and groups in social networks? (Algorithms)
8. How to interpret graph solution back to real-world problem?
Community detection algorithms are used to identify densely connected groups of nodes in networks. Modularity optimization is commonly used, which detects communities as groups of nodes with more connections within groups than expected by chance. Parameters like resolution affect results. Multilayer networks model systems with multiple network layers over nodes. Multilayer modularity generalizes modularity to multilayer networks. Community detection in multilayer networks provides insights into structures across data types and applications.
FAST AND ACCURATE MINING THE COMMUNITY STRUCTURE: INTEGRATING CENTER LOCATING...Nexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
This document summarizes two presentations about community detection in social media networks. The first presentation discusses using edge content, like image tags, to help identify communities in networks. The second focuses on leveraging interaction intensities on Twitter to detect communities that form around certain events over time. Both aim to improve on traditional methods that only consider network structure.
Hybrid sentiment and network analysis of social opinion polarization icoictAndry Alamsyah
The rapid growth of social media and user generated contents (UGC) has provided a rich source of potentially relevant data. The problems arise on how to summarize those data to understand and transforming it into information. Twitter as one of the most popular social networking and micro-blogging service can be analyzed in terms of content produced with sentiment analysis. On the other hand, some types of networks can also be constructed to analyze the social network structure and network properties. This research intended to combine those content and structural approaches into hybrid approach for identifies social opinion polarization, this is in the form of conversation network. Sentiment analysis used to determine public sentiment, and social network analysis used to analyze the structure of the network, detecting communities and influential actors in the network. Using this hybrid approach, we have comprehensive understanding about social opinion polarization. As case study, we present real social opinion polarization about reclamation issue in Indonesia.
The document discusses social networks and their applications. It provides an overview of social network properties like diameter, degree distributions, clustering, and small world models. It then discusses how e-markets can enable trading of information and provides examples like stock markets and price posting markets. It proposes a model of a social network where economic agents are connected based on trust and a seller can use the network to sell products by approaching recommenders and their friends. The system would update trustworthiness and connections based on purchase decisions.
The document discusses network diffusion and peer influence. It begins by defining diffusion and compartment models used to model disease spread. It then discusses how network structure, including topology, timing of connections, and structural transmission, can impact diffusion. Simulation is proposed to test how network features like distance, clustering, redundancy, and high-degree nodes influence spread. The relationships between contact networks, exposure networks based on timing, and actual transmission networks are also introduced.
This document provides an overview of social network analysis (SNA) including concepts, methods, and applications. It begins with background on how SNA originated from social science and network analysis/graph theory. Key concepts discussed include representing social networks as graphs, identifying strong and weak ties, central nodes, and network cohesion. Practical applications of SNA are also outlined, such as in business, law enforcement, and social media sites. The document concludes by recommending when and why to use SNA.
A comparative study of social network analysis toolsDavid Combe
This document compares several social network analysis tools based on their functionalities and benchmarks them using sample datasets. It finds that Pajek, Gephi, igraph, and NetworkX are mature tools that handle network representation, visualization, characterization with indicators, and community detection well. Gephi is interactive but community detection is experimental. NetworkX is attribute-friendly and handles large networks but lacks visualization. Igraph is optimized for clustering but not custom attributes. The best tool depends on the specific analysis needs.
Graph and language embeddings were used to analyze user data from Reddit to predict whether authors would post in the SuicideWatch subreddit. Metapath2vec was used to generate graph embeddings from subreddit and author relationships. Doc2vec was used to generate document embeddings based on language similarity between submissions and subreddits. Combining the graph and document embeddings in a logistic regression achieved 90% accuracy in predicting SuicideWatch posters, reducing both false positives and false negatives compared to using the embeddings separately. Next steps proposed using the embeddings to better understand similarities between related subreddits and predict risk factors in posts.
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS Signature searching in a netwo...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS A scientometric analysis of cloud c...IEEEMEMTECHSTUDENTPROJECTS
This document discusses a proposed system for improving the process of clustering and displaying search results from literature on cloud computing. The existing system has problems with only displaying results from registered candidates, poor data display, and lack of security. The proposed system aims to display the highest ranking search keywords based on user and publisher rankings to make the process more secure. It uses clustering to automatically organize documents by topic to improve information retrieval. The system would have administrative, publisher, search, and user modules and use ASP.Net and SQL Server software.
IEEE 2014 DOTNET DATA MINING PROJECTS Product aspect-ranking-and--its-applica...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET DATA MINING PROJECTS Trusted db a-trusted-hardware-based-dat...IEEEMEMTECHSTUDENTPROJECTS
The document describes TrustedDB, a database system that uses trusted hardware to enable private queries on outsourced data. TrustedDB allows clients to execute SQL queries while preserving privacy and regulatory compliance by leveraging tamper-proof trusted hardware for sensitive query processing stages. This removes limitations of software-only encryption approaches. The system partitions queries into public and private components, executing the latter on secure hardware for better performance and lower costs than solely cryptographic approaches. Evaluation shows TrustedDB can support full-fledged databases on trusted hardware more cost-effectively than existing techniques.
IEEE 2014 DOTNET DATA MINING PROJECTS Anonymous query processing in road netw...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET NETWORKING PROJECTS A proximity aware interest-clustered p2p...IEEEMEMTECHSTUDENTPROJECTS
This document describes a proposed proximity-aware and interest-clustered peer-to-peer (P2P) file sharing system (PAIS) that forms physically close nodes into clusters and further groups nodes with common interests into subclusters. It aims to improve file searching efficiency by creating replicas of frequently requested files within subclusters. The system analyzes user interests and file sharing behaviors to construct the network topology and uses an intelligent file replication algorithm. The experimental results show this approach improves file searching performance compared to existing P2P systems.
IEEE 2014 DOTNET DATA MINING PROJECTS Mining statistically significant co loc...IEEEMEMTECHSTUDENTPROJECTS
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IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS Secure and efficient data tran...IEEEMEMTECHSTUDENTPROJECTS
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DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
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JAVA 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone based ...IEEEGLOBALSOFTTECHNOLOGIES
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IRJET- Predicting Social Network Communities Structure Changes and Detection ...IRJET Journal
This document discusses predicting changes in community structures of social networks and detecting spam bots. It proposes using digital DNA behavioral modeling to predict crucial events in how social network communities expand, shrink, or combine over time. Digital DNA reflects a user's unique pattern of interactions and can be used for social fingerprinting to efficiently distinguish real users from spam bots. The document reviews several related works and approaches for tracking community changes, predicting critical events, and modeling community evolution over time. It concludes that critical community changes can be predicted using digital DNA and that the proposed approach using social fingerprinting may effectively detect spam bots.
Service usage classification with encrypted internet traffic in mobile messag...Finalyearprojects Toall
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efficient data query in intermittently-connected mobile ad hoc social networksswathi78
This document discusses efficient data query in intermittently connected mobile ad hoc social networks (MASONs). It proposes a centralized optimization model and distributed data query protocol to address challenges like opportunistic connectivity and unknown data providers. A testbed experiment using 25 tablets for 15 days demonstrated feasibility and efficiency. Simulations under various network settings provided additional performance insights not possible through lab experiments alone. The goal is to determine an optimal transmission strategy that supports the desired query rate within a delay budget while minimizing communication costs.
Internet ttraffic monitering anomalous behiviour detectionGyan Prakash
This document discusses a methodology for monitoring internet traffic and detecting anomalous behavior. It begins by noting the challenges of understanding vast quantities of internet traffic data due to the diversity of applications and services. Recent cyber attacks have made it important to develop techniques to analyze communication patterns in traffic data for network security purposes.
The proposed methodology uses data mining and entropy-based techniques to build behavior profiles of internet backbone traffic. It involves clustering traffic based on communication patterns, automatically classifying behaviors, and modeling structures for analysis. The methodology is validated using data sets from internet core links. It aims to automatically discover significant behaviors, provide interpretations, and quickly identify anomalous events like scanning or denial of service attacks.
The document proposes a framework called MultiComm to identify communities in multi-dimensional networks. MultiComm evaluates the affinity between items in the same or different dimensions to generate communities from seed items. It calculates visit probabilities for each item in each dimension and compares the values. Experiments on synthetic and real-world data suggest MultiComm can effectively find communities in multi-dimensional networks and outperforms other algorithms in accuracy. The framework is intended to discover related groups of users, authors, or other entities interacting across multiple network dimensions like tags, photos, and comments.
Stochastic load balancing for virtual resource management in datacentersFinalyearprojects Toall
To get IEEE 2015-2017 Project for above title in .Net or Java
mail to finalyearprojects2all@gmail.com or contact +91 8870791415
IEEE 2015-2016 Project Videos: https://www.youtube.com/channel/UCyK6peTIU3wPIJxXD0MbNvA
Geo community-based broadcasting for data dissemination in mobile social netw...IEEEFINALYEARPROJECTS
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Automatic Generation Of Communication ArchitecturesCynthia Velynne
This document describes an automatic approach for generating communication architectures from an abstract model. It involves these key steps:
1. Mapping abstract message passing channels onto shared communication buses through techniques like channel grouping and protocol selection.
2. Instantiating bus functional models for components and inserting necessary communication elements like arbiters.
3. Synthesizing synchronization between components through interrupts or polling.
4. Connecting all components through generated bus wires to produce the final communication model.
Experimental results on applications like JPEG encoding and MP3 decoding demonstrate the effectiveness of the automatic approach.
This document contains summaries of several academic papers related to various technical topics such as data center optimization, content delivery in opportunistic networks, Petri net analysis, usability testing of health inspection software, cognitive cellular networks, multimedia transmission over cognitive radio networks, load balancing in cloud computing, ship speed prediction, collaborative manufacturing strategies, and green cellular networks.
Trend-Based Networking Driven by Big Data Telemetry for Sdn and Traditional N...josephjonse
Organizations face a challenge of accurately analyzing network data and providing automated action based on the observed trend. This trend-based analytics is beneficial to minimize the downtime and improve the performance of the network services, but organizations use different network management tools to understand and visualize the network traffic with limited abilities to dynamically optimize the network. This research focuses on the development of an intelligent system that leverages big data telemetry analysis in Platform for Network Data Analytics (PNDA) to enable comprehensive trendbased networking decisions. The results include a graphical user interface (GUI) done via a web application for effortless management of all subsystems, and the system and application developed in this research demonstrate the true potential for a scalable system capable of effectively benchmarking the network to set the expected behavior for comparison and trend analysis. Moreover, this research provides a proof of concept of how trend analysis results are actioned in both a traditional network and a software-defined network (SDN) to achieve dynamic, automated load balancing
Trend-Based Networking Driven by Big Data Telemetry for Sdn and Traditional N...josephjonse
This summarizes a research paper on developing an intelligent system that leverages big data telemetry analysis to enable trend-based networking decisions. The system collects data from traditional and SDN networks using SNMP and OpenFlow. Logstash filters the data and sends it to PNDA's Kafka interface. A Jupyter notebook streams the data to OpenTSDB. Benchmarking identifies trends, and the system takes automated action like load balancing across the networks when trends are detected. A GUI provides centralized management. The system demonstrates using big data analytics to monitor networks and make proactive, automated decisions based on observed trends.
TREND-BASED NETWORKING DRIVEN BY BIG DATA TELEMETRY FOR SDN AND TRADITIONAL N...ijngnjournal
Organizations face a challenge of accurately analyzing network data and providing automated action
based on the observed trend. This trend-based analytics is beneficial to minimize the downtime and
improve the performance of the network services, but organizations use different network management
tools to understand and visualize the network traffic with limited abilities to dynamically optimize the
network. This research focuses on the development of an intelligent system that leverages big data
telemetry analysis in Platform for Network Data Analytics (PNDA) to enable comprehensive trendbased networking decisions. The results include a graphical user interface (GUI) done via a web
application for effortless management of all subsystems, and the system and application developed in
this research demonstrate the true potential for a scalable system capable of effectively benchmarking
the network to set the expected behavior for comparison and trend analysis. Moreover, this research
provides a proof of concept of how trend analysis results are actioned in both a traditional network and
a software-defined network (SDN) to achieve dynamic, automated load balancing.
Automatic Layer-Based Generation Of System-On-Chip Bus Communication ModelsKaren Gomez
This document summarizes an approach for automatically generating system-on-chip (SoC) bus communication models through layered refinement from an abstract specification. It presents a two-stage design flow for communication synthesis: 1) network design to generate a customized heterogeneous bus network model, and 2) link design to refine the network model into a linked implementation. The approach targets architectures consisting of processing elements connected by a network of shared buses, with buses connected by communication elements. It generates models at different abstraction levels to enable early design space exploration while balancing simulation speed and accuracy.
Similar to IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS On social delay tolerant networking aggregation, tie detection, and routing (20)
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS Web image re ranking using query-sp...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
This document describes a proposed system for enabling effective yet privacy-preserving fuzzy keyword search in cloud computing. It formalizes the problem of fuzzy keyword search over encrypted cloud data for the first time. The system uses edit distance to quantify keyword similarity and develops two techniques - wildcard-based and gram-based - to construct efficient fuzzy keyword sets. It then proposes a symbol-based trie-traverse searching scheme to match keywords and retrieve files. Security analysis shows the solution preserves privacy while allowing fuzzy searches.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS Automatic scaling of internet appli...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS A mechanism design approach to reso...IEEEMEMTECHSTUDENTPROJECTS
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IEEE 2014 DOTNET MOBILE COMPUTING PROJECTS Smart dc mobility prediction based...IEEEMEMTECHSTUDENTPROJECTS
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IEEE 2014 DOTNET MOBILE COMPUTING PROJECTS Preserving location-privacy-in-geo...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
IEEE 2014 DOTNET MOBILE COMPUTING PROJECTS A qos-oriented-distributed-routing...IEEEMEMTECHSTUDENTPROJECTS
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IEEE 2014 DOTNET MOBILE COMPUTING PROJECTS An active resource orchestration f...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
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IEEE 2014 DOTNET NETWORKING PROJECTS Pricing under constraints_in_access_netw...IEEEMEMTECHSTUDENTPROJECTS
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Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.
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.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
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Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS On social delay tolerant networking aggregation, tie detection, and routing
1. GLOBALSOFT TECHNOLOGIES
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On Social Delay-Tolerant Networking Aggregation, Tie
Detection, and Routing
Abstract
Social-based routing protocols have shown their promising capability to improve the message delivery
efficiency in Delay Tolerant Networks (DTNs). The efficiency greatly relies on the quality of the
aggregated social graph that is determined by the metrics used to measure the strength of social
connections. In this paper, we propose an improved metrics that leads to high-quality social graph by
taking both frequency and duration of contacts into consideration. Furthermore, to improve the
performance of social-based message transmission, we systematically study the community evolution
problem that has been little investigated in the literation. Distributed algorithms based on the obtained
social graph are developed such that the overlapping communities and bridge nodes (i.e., connecting
nodes between communities) can be dynamically detected in an evolutionary social network. Finally, we
take all the results above into our social-based routing design. Extensive trace-driven simulation results
show that our routing algorithm outperforms existing social-based forwarding strategies significantly.
Existing system
Social-based routing protocols have shown their promising capability to improve the message delivery
efficiency in Delay Tolerant Networks (DTNs). The efficiency greatly relies on the quality of the
2. aggregated social graph that is determined by the metrics used to measure the strength of social
connections.
Proposed system
In this paper, we propose an improved metrics that leads to high-quality social graph by taking both
frequency and duration of contacts into consideration. Furthermore, to improve the performance of
social-based message transmission, we systematically study the community evolution problem that has
been little investigated in the literation. Distributed algorithms based on the obtained social graph are
developed such that the overlapping communities and bridge nodes (i.e., connecting nodes between
communities) can be dynamically detected in an evolutionary social network. Finally, we take all the
results above into our social-based routing design. Extensive trace-driven simulation results show that
our routing algorithm outperforms existing social-based forwarding strategies significantly.
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 256 MB(min)
Hard Disk - 20 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
SOFTWARE CONFIGURATION:-
Operating System : Windows XP
Programming Language : JAVA