Privacy-preserving protocols for secure and reliable data aggregation in IoT-enabled Smart Metering systems

Extracting knowledge from databases is a procedure which interest has increased in a wide variety of areas like stock market, medicine or census data, to name a few. A compact representation of this knowledge is given by rules. Formal concept analysis plays an important role in this area. This paper introduces a new kind of attribute implications considering the fuzzy notions of support and confidence and is also focused on the particular case in which the set of attributes are intensions. Moreover, an application to clustering for size reduction of concept lattices is included.

Generating Fuzzy Attribute Rules Via Fuzzy Formal Concept Analysis

Land consolidation of small-scale farms in preparation for a cane harvester

Understanding graph algorithms for beginners is the biggest nightmare for them. To conquer that fear we have decided to build a website which will help them to understand graph algorithms in a fun and easy way. It is a visualizer website for Graph Algorithms, where you can see a detailed explanation and animations of important algorithm runtime and build intuition. Graph Algorithm Visualizer allows you to easily construct graphs and step-by-step observe execution of algorithms on them. It visualizes different types of graph algorithms such as Prim’s Algorithm, Kruskal Algorithm, DFS etc. Our aim is to build a project which will work for a teaching and learning tool. In learning mode, we are providing a detailed visualization of graph-based algorithms, such as Kruskal, Prim’s algorithm as well as each step will be verified against the algorithm and results will be provided at a time. We have confidence that our project will help many students to understand graph-based algorithms at a deeper level and improve their knowledge of graph algorithms. This model is especially built to help faculty to teach graph algorithms in a creative and fun way for students. 

Artificial Intelligence Based Dynamic Approach to Visualize the Graphs

OF THE DISSERTATION PRIVACY-PRESERVING PROTOCOLS FOR IEEE 802.11S-BASED SMART GRID ADVANCED METERING INFRASTRUCTURE NETWORKS by Samet Tonyali Florida International University, 2018 Miami, Florida Professor Kemal Akkaya, Major Professor The ongoing Smart Grid (SG) initiative proposes several modifications to the existing power grid in order to better manage power demands, reduce CO2 emissions and ensure reliability through several new applications. One part of the SG initiative that is currently being implemented is the Advanced Metering Infrastructure (AMI) which provides two-way communication between the utility company and the consumers’ smart meters (SMs). The AMI can be built by using a wireless mesh network which enables multi-hop communication of SMs. The AMI network enables collection of fine-grained power consumption data at frequent intervals. Such a fine-grained level poses several privacy concerns for the consumers. Eavesdroppers can capture data packets and analyze them by means of load monitoring techniques to make inferences about household activities. To prevent this, in this dissertation, we proposed several privacy-preserving protocols for the IEEE 802.11s-based AMI network, which are based on data obfuscation, fully homomorphic encryption and secure multiparty computation. Simulation results have shown that the performance of the protocols degrades as the network grows. To overcome this problem, we presented a scalable simulation framework for the evaluation of IEEE 802.11s-based AMI applications. We proposed several modifications and parameter adjustments for the network protocols being used. In addition,

/pdf/privacy-preserving-protocols-for-ieee-802-11s-based-smart-35saljzcik.pdf

Privacy-Preserving Protocols for IEEE 802.11s-based Smart Grid Advanced Metering Infrastructure Networks

This paper proposed a new algorithm to find a minimum spanning tree of an undirected weighted graph graph This new algorithm provides a fresh approach to produce a minimum spanning tree A minimum spanning tree is a sub graph of any undirected weighted graph that gives the minimal cost valued edges to reach every node of any graph The proposed algorithm is named as RAY algorithm for determining the minimum spanning tree We named this new algorithm as RAY, as it gives a new ray of hope in the field of graphs that can be used as a better option for finding the minimum spanning tree of any undirected weighted graph with less duration of time as well as with an easy approach RAY has less complexity with respect to time for finding the minimum spanning tree of any graph in comparison to other algorithms like prim's algorithm and Kruskal's algorithm which are mostly used to find a minimum spanning tree of the graph RAY algorithm select any one node of the given graph as a root node and then it joins every edge connected to that node, which do not form any cycle in the graph This process is repeated until we traverse each node of the graph and the edges those forms cycle during this process are stored separately Now only these separately stored edges are traversed and we check in the graph for maximum weighted edge from the edges that are coming in the cycle which is formed due that particular separately stored edge If there is any edge in the cycle which is greater in weigh than that of separately stored edge then we discarded maximum weighted edge and the new edge which we stored separately is taken into the minimum spanning tree This same procedure is repeated for each edge that we stored separately At the end of this procedure we get a tree which is the minimum spanning tree of the given graph by using RAY algorithm

Determining minimum spanning tree in an undirected weighted graph

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Determining minimum spanning tree in an undirected weighted graph