'Node 4' presentation slideshows

Artificial Neural Networks

Artificial Neural Networks. Introduction. Artificial Neural Networks (ANN) Information processing paradigm inspired by biological nervous systems ANN is composed of a system of neurons connected by synapses ANN learn by example Adjust synaptic connections between neurons. History.

1.07k views • 75 slides

Artificial Neural Networks

Artificial Neural Networks. Introduction. Artificial Neural Networks (ANN) Information processing paradigm inspired by biological nervous systems ANN is composed of a system of neurons connected by synapses ANN learn by example Adjust synaptic connections between neurons. History.

1.17k views • 75 slides

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509 views • 41 slides

PRSim : Sublinear Time SimRank Computation on Large Power-Law Graphs.

PRSim : Sublinear Time SimRank Computation on Large Power-Law Graphs. Zhewei Wei, Xiaodong He, Xiaokui Xiao, Sibo Wang, Yu Liu, Xiaoyong Du, and Ji-Rong Wen. Zhewei Wei Renmin University of China. Problems and Motivations. SimRank [KDD 02]. Professor A. Student A. University.

313 views • 31 slides

Spatial Reuse Ring Networks

Spatial Reuse Ring Networks. Chun-Hung Chen Department of Computer Science and Information Engineering National Taipei University of Technology 2003.10.24. Outlines. Ring Networks Spatial Reuse Spatial Reuse Protocol Resilient Packet Ring. Ring Networks.

513 views • 29 slides

Statements and Expressions

392 views • 29 slides

Spatial Reuse Ring Networks

Spatial Reuse Ring Networks. Chun-Hung Chen Department of Computer Science and Information Engineering National Taipei University of Technology 2003.10.24. Outlines. Ring Networks Spatial Reuse Spatial Reuse Protocol Resilient Packet Ring. Ring Networks.

314 views • 29 slides

EMIS 8374 Solving Max Flow Problems with Non-Zero Lower Bounds Updated 18 March 2008

EMIS 8374 Solving Max Flow Problems with Non-Zero Lower Bounds Updated 18 March 2008. Not Always Feasible. 2. (3,5). 1. s. (0,2). 3. ( ? , u ). t. Example Max Flow Problem. ( ? , u ). (0,2). 2. 4. (0,4). (0,5). 1. 6. (3,6). (5,6). t. s. (0,5). (0,6). 3. 5. (0,7).

272 views • 27 slides

MAC Reliable Broadcast in Ad Hoc Networks Ken Tang, Mario Gerla

MAC Reliable Broadcast in Ad Hoc Networks Ken Tang, Mario Gerla University of California, Los Angeles (ktang, gerla@cs.ucla.edu). Overview. Ad hoc network introduction Medium access control (MAC) protocol Broadcast limitation Broadcast Medium Window (BMW) protocol

311 views • 20 slides

MAC Reliable Broadcast in Ad Hoc Networks Ken Tang, Mario Gerla

MAC Reliable Broadcast in Ad Hoc Networks Ken Tang, Mario Gerla University of California, Los Angeles (ktang, gerla@cs.ucla.edu). Overview. Ad hoc network introduction Medium access control (MAC) protocol Broadcast limitation Broadcast Medium Window (BMW) protocol

202 views • 20 slides

On the Nash Equilibria of Graphical Games for Channel Access in Multihop Wireless Networks

On the Nash Equilibria of Graphical Games for Channel Access in Multihop Wireless Networks. Vaggelis G. Douros Stavros Toumpis George C. Polyzos. WWRF-WCNC @ Istanbul, 06 .0 4 .2014. Motivation (1). New communication paradigms will arise. Motivation (2).

238 views • 15 slides

Mikko Vapa, research student P2P Computing Group Department of Mathematical Information Technology

Optimal Resource Discovery Paths of Gnutella2 The IEEE 22nd International Conference on Advanced Information Networking and Applications (AINA 2008) 27.3.2008. Mikko Vapa, research student P2P Computing Group Department of Mathematical Information Technology www.mit.jyu.fi/ cheesefactory.

276 views • 13 slides

A P2P On-Demand Video Streaming System with Multiple Description Coding

A P2P On-Demand Video Streaming System with Multiple Description Coding. Yanming Shen, Xiaofeng Xu, Shivendra Panwar, Keith Ross, Yao Wang Polytechnic University. Introduction. Media content forms a significant fraction of Internet traffic.

133 views • 13 slides

How to Construct a Data Collection Tree

1. 2. 3. 4. 5. How to Construct a Data Collection Tree. 1. 2. 3. How to Construct a Data Collection Tree. 1. 2. 3. 4. How to Construct a Data Collection Tree. If node 4 receives the tree construction message from node 2 first, node 4 may select node 2 as its parent. 1. 2. 3. 4.

57 views • 5 slides

EXPLOITING VALUE LOCALITY FOR SECURE-ENERGY AWARE COMMUNICATION

EXPLOITING VALUE LOCALITY FOR SECURE-ENERGY AWARE COMMUNICATION. H. Saputra, N. Vijaykrishnan, M. Kandemir, R. Brooks, and M.J. Irwin Computer Science and Engineering Applied Research Lab The Pennsylvania State University. Node 1. Node 2. Node 1. Node 2. 2. B,2. A. A. A. A. Ptr_2.

113 views • 3 slides

NODE 0 mRS 0: 13.6% (n=551) mRS 1: 19.4% (n=785) mRS 2: 14.7% (n=597) mRS 3: 16.5% (n=668)

DAY-90 mRS. NODE 0 mRS 0: 13.6% (n=551) mRS 1: 19.4% (n=785) mRS 2: 14.7% (n=597) mRS 3: 16.5% (n=668) mRS 4: 21.1% (n=855) mRS 5: 7.0% (n=324) mRS 6: 6.7% (n=271). Day-30 mRS > 3. Day-30 mRS ? 3. NODE 2 mRS 0: 0.1% (n=2) mRS 1: 1.8% (n=32) mRS 2: 4.2% (n=76)

203 views • 1 slides

UNIVERSITY OF IBADAN NETWORK DIAGRAM

Cisco 3600. SERIES. 0. 1. 2. 4. ACTIVE. READY. 1. COM. AUX. SYSTEM. RPS. 0. PCMCIA. Internet. Router. Cisco. 3600. Public Switch. Mail Server. MicroTik (Firewall, Bandwidth shaper, Traffic logger , Web proxy, NAT, Installed and connect every node to the network).

188 views • 1 slides