This document proposes a cognitive-inspired model for self-organizing networks. It begins with motivation for developing self-organizing overlay networks that can optimize their structure without global information. It then describes a scenario where nodes in a connected network want to retrieve items from each other using a limited number of links. The document goes on to present the cognitive-inspired hub detection algorithm, which uses concepts like diffusion, competitive interaction, and cognitive dissonance to identify hub nodes. It evaluates the algorithm through numerical simulations that aim to maximize the number of reachable items or minimize the energy used. The results show the cognitive approach outperforms a randomized algorithm.
Graded Patterns in Attractor Networks explores how noise can exist in large neural networks like the brain. The study introduces graded firing patterns, where neuron firing rates vary across populations, rather than being uniform. Simulations found graded patterns decreased reaction times and increased variability compared to uniform patterns. This suggests graded firing represents increased noise but may play a functional role in neural processing like memory retrieval.
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.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document summarizes a research paper on using steganography techniques to hide encrypted messages within images while also providing data integrity. It discusses embedding encrypted message bits using the LSB (least significant bit) technique and a modulus 4 bit technique. It also uses MD5 hash algorithms to provide data integrity by sending a message digest along with the encrypted data. The analysis shows that the LSB technique improves the PSNR (peak signal-to-noise ratio) over the modulus 4 bit technique, indicating less image degradation. Using the hash algorithm ensures the data was not altered during transmission.
The document summarizes a mathematical algorithm for quickly identifying steganographic signatures in images. It defines key concepts used in the algorithm such as the definition of an image, pixel neighborhood, pixel aberration, etc. The algorithm analyzes any given image and generates a "concentrating suspicion value" (Γ) which is a numerical value indicating how likely the image contains hidden information embedded using concentrating steganographic algorithms. Images with higher Γ values are more likely to contain stego information. The algorithm provides a fast way to filter images for more thorough interrogation.
This document summarizes a research paper that proposes using an improved harmony search algorithm for automatic clustering. The improved harmony search algorithm uses variable parameters like pitch adjustment rate and bandwidth to evolve candidate cluster centers and determine the appropriate number of clusters. The algorithm aims to minimize within-cluster variance and maximize between-cluster variance. It was tested on several datasets and found to be able to accurately determine the number of clusters and locations of cluster centers.
This document lists various products and ideas for dealing with monsters under the bed or other childhood fears, including:
1) Lights, music, and other devices that use light, sound, or motion sensors to detect monsters.
2) Protective accessories like wristbands, badges, and anti-monster sprays.
3) Tactics for deterring or escaping monsters like slippery surfaces, traps, guards, or an escape route.
4) Activities to distract from fears like reading, games, or spending time with family.
This document summarizes a research paper that proposes a new algorithm for identifying steganographic signatures in digital images. The algorithm analyzes any image and assigns it a "suspicion value" based on the likelihood that it contains hidden information. Images with higher suspicion values would require more thorough analysis, while those with lower values are less likely to contain steganography. The algorithm is intended to quickly filter images flowing online to identify possible stego images for further investigation, without requiring extensive computation. It focuses specifically on "distributing" steganographic algorithms that hide data in the least significant bits of many pixels. The paper evaluates the suspicion values produced for various cover and stego-images generated by three such steganographic algorithms.
This document provides an overview of neural networks. It discusses that neural networks are composed of interconnected processing units similar to neurons in the brain. Neural networks can learn patterns from examples through training and are well-suited for problems that are difficult to solve with traditional algorithms. The document outlines common neural network architectures like feedforward and feedback networks. It also discusses neural network learning methods and applications.
Graded Patterns in Attractor Networks explores how noise can exist in large neural networks like the brain. The study introduces graded firing patterns, where neuron firing rates vary across populations, rather than being uniform. Simulations found graded patterns decreased reaction times and increased variability compared to uniform patterns. This suggests graded firing represents increased noise but may play a functional role in neural processing like memory retrieval.
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.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
The document summarizes a research paper on using steganography techniques to hide encrypted messages within images while also providing data integrity. It discusses embedding encrypted message bits using the LSB (least significant bit) technique and a modulus 4 bit technique. It also uses MD5 hash algorithms to provide data integrity by sending a message digest along with the encrypted data. The analysis shows that the LSB technique improves the PSNR (peak signal-to-noise ratio) over the modulus 4 bit technique, indicating less image degradation. Using the hash algorithm ensures the data was not altered during transmission.
The document summarizes a mathematical algorithm for quickly identifying steganographic signatures in images. It defines key concepts used in the algorithm such as the definition of an image, pixel neighborhood, pixel aberration, etc. The algorithm analyzes any given image and generates a "concentrating suspicion value" (Γ) which is a numerical value indicating how likely the image contains hidden information embedded using concentrating steganographic algorithms. Images with higher Γ values are more likely to contain stego information. The algorithm provides a fast way to filter images for more thorough interrogation.
This document summarizes a research paper that proposes using an improved harmony search algorithm for automatic clustering. The improved harmony search algorithm uses variable parameters like pitch adjustment rate and bandwidth to evolve candidate cluster centers and determine the appropriate number of clusters. The algorithm aims to minimize within-cluster variance and maximize between-cluster variance. It was tested on several datasets and found to be able to accurately determine the number of clusters and locations of cluster centers.
This document lists various products and ideas for dealing with monsters under the bed or other childhood fears, including:
1) Lights, music, and other devices that use light, sound, or motion sensors to detect monsters.
2) Protective accessories like wristbands, badges, and anti-monster sprays.
3) Tactics for deterring or escaping monsters like slippery surfaces, traps, guards, or an escape route.
4) Activities to distract from fears like reading, games, or spending time with family.
This document summarizes a research paper that proposes a new algorithm for identifying steganographic signatures in digital images. The algorithm analyzes any image and assigns it a "suspicion value" based on the likelihood that it contains hidden information. Images with higher suspicion values would require more thorough analysis, while those with lower values are less likely to contain steganography. The algorithm is intended to quickly filter images flowing online to identify possible stego images for further investigation, without requiring extensive computation. It focuses specifically on "distributing" steganographic algorithms that hide data in the least significant bits of many pixels. The paper evaluates the suspicion values produced for various cover and stego-images generated by three such steganographic algorithms.
This document provides an overview of neural networks. It discusses that neural networks are composed of interconnected processing units similar to neurons in the brain. Neural networks can learn patterns from examples through training and are well-suited for problems that are difficult to solve with traditional algorithms. The document outlines common neural network architectures like feedforward and feedback networks. It also discusses neural network learning methods and applications.
- The document outlines regulations for fishing in Ireland and Northern Ireland including bag limits, seasons, licenses required, catch and release rules, and prohibited fishing methods. It discusses the government agencies that oversee fisheries management - Inland Fisheries Ireland, the Central Fisheries Board, Department of Culture, Arts and Leisure, and the Loughs Agency. It provides specific details on regulations for different species like salmon, trout, pike, and bass.
The document discusses various tourism bodies in Ireland including Fáilte Ireland, Tourism Ireland, and regional tourism offices. It provides information on their roles in supporting the tourism industry through practical business support, marketing Ireland as a destination, and developing the visitor economy. It also discusses the Northern Ireland Tourism Board and its responsibilities in marketing Northern Ireland as a tourist destination.
The years from 1865-1895 saw many important developments in the United States, including the Bessemer process which made steel production more efficient, the rise of social Darwinism and its influence on business, and the establishment of the Buffalo Soldiers regiment in 1866. Key events also included the Homestead Act which offered free land, the completion of the transcontinental railroad in 1869, and the massacre of Cheyenne at Sand Creek in 1864. Inventors and businessmen like Thomas Edison, Alexander Graham Bell, Andrew Carnegie, and John D. Rockefeller also rose to prominence during this period, helping to industrialize the nation.
Malcolm Fraser founded the Stuttering Foundation of America in 1947 after struggling with stuttering since childhood and receiving therapy. He had a successful career with his brother at their company, NAPA-Genuine Parts. Fraser generously supported the Foundation over time, with endowment income now covering over 50% of operating costs. He received awards for his commitment to helping people who stutter, including the Charles Van Riper award from the American Speech-Language-Hearing Association. Fraser worked to increase awareness of stuttering and help people constructively address it.
The document is a collection of observations about different body parts, describing features like eye and hair color, the shape of noses, cleanliness of ears, uses of hands, dancing abilities, and tattoos. Many of the sentences refer to specific people and body parts without larger context or meaning.
This document contains personal information about Diana Alejandro Marín Rodríguez. It provides her place of living, age, marital status, phone number, family members, occupation, favorite sport, and favorite singer. It also includes pictures and descriptions of the rooms in her house, her daily routine, and activities she likes doing alone, with family or friends such as shopping, walking, laughing, and going to movies.
The document outlines the organization chart for Cardique, a public corporation created by Law 99 in 1993 to manage and conserve the environment and natural resources in Colombia. The chart shows that Cardique has subdepartments for environmental management, planning, protocols, general secretariat, administrative and financial, and an environmental quality laboratory. The subdepartments are responsible for monitoring natural resources, territorial management planning, disseminating corporate actions, legal matters, financial management and staffing, and providing analytical services for water, soil and air samples.
The document discusses RFID technology, including how it works, common applications, and survey results on possible uses. RFID uses radio frequencies to electronically identify objects. Survey respondents thought RFID could be applied to library management, logistics/supply chain management, and medical/pharmaceutical industries.
Hitler realized that gradual psychological changes were needed to shift the German people's views to accept his agenda of using force and violence. He systematically utilized propaganda through radio, the press, films, and mass meetings to educate Germans and reinforce National Socialist ideas. The film "Triumph of the Will" documented one of Hitler's mass rallies and demonstrated the power of film to promote his message.
The document summarizes a study analyzing the impacts of accelerated agricultural growth in Mozambique. The study uses an economic model to compare a baseline growth scenario to a "CAADP scenario" where agriculture grows at 7% annually by focusing on high-potential regions. The model finds the CAADP scenario would significantly reduce poverty and food insecurity compared to the baseline. However, the document notes policies should target all regions to ensure equal outcomes and discusses interactions between agriculture and other development strategies.
The Elavia group is a family-owned, professionally managed business established in 1915 that specializes in lifts and international trading. It aims to be a leader in manufacturing, installing, and modernizing lifts, as well as trading niche food and beverage products globally. Through its Excel Lifts and Excel Cenomundus divisions, the group works to provide safe and convenient lift transportation while assisting foreign companies establish in India's diverse markets.
What is SPF record good for? | Part 7#17Eyal Doron
What is SPF record good for? | Part 7#17
http://o365info.com/what-is-spf-record-good-for-part-7-17
The purpose of the SPF record and the relation to for our mail infrastructure. How does the SPF record enable us to prevent a scenario in which hostile elements could send E-mail on our behalf.
Eyal Doron | o365info.com
This document contains basic math equations that equal 4. It shows that 2 + 2, 3 + 2, 9 - 8, 6 - 4, 2 x 3, 10 x 2, and 4 / 2 all equal 4, while 6 / 6 equals 1.
This document discusses different alert services available through legal research databases. It describes how to set up search alerts, Shepard's alerts, publication alerts, docket alerts, and more on Lexis Advance and WestlawNext. It also mentions alert options on Bloomberg Law, CCH Intelliconnect, Bloomberg BNA, and some other databases. The document provides examples and links for additional information on using the various alert tools. It concludes by discussing legal blogs and ways to follow blogs through RSS readers or Twitter.
This document summarizes a study of deep learning models and Bayesian statistics. It discusses the history of artificial intelligence and machine learning before introducing restricted Boltzmann machines, deep belief networks, and Bayesian statistics. It describes experiments applying restricted Boltzmann machines to classify movies and generate images, and using a deep belief network to classify images from multiple datasets with 100% accuracy. The conclusion states that deep learning has advanced artificial intelligence by allowing algorithms to perform multiple tasks and taken us closer to the original goal of general artificial intelligence.
Invited Tutorial - Cognitive Design for Artificial Minds AI*IA 2022Antonio Lieto
This document provides an overview of cognitive design for artificial minds. It discusses how cognitive artificial systems are inspired by human and natural cognition. The key points made are:
- Cognitive artificial systems are inspired by human and natural cognition to be more general and versatile than standard AI systems.
- Examples of cognitively inspired AI systems include ACT-R, Soar, and systems developed using the subsumption architecture.
- Cognitively inspired systems differ from standard AI in that they aim to have explanatory power for human cognition through structural models of cognitive processes and representations.
- Such systems can be used to test cognitive theories, provide human-like capabilities, and potentially lead to more general artificial intelligence.
- The document outlines regulations for fishing in Ireland and Northern Ireland including bag limits, seasons, licenses required, catch and release rules, and prohibited fishing methods. It discusses the government agencies that oversee fisheries management - Inland Fisheries Ireland, the Central Fisheries Board, Department of Culture, Arts and Leisure, and the Loughs Agency. It provides specific details on regulations for different species like salmon, trout, pike, and bass.
The document discusses various tourism bodies in Ireland including Fáilte Ireland, Tourism Ireland, and regional tourism offices. It provides information on their roles in supporting the tourism industry through practical business support, marketing Ireland as a destination, and developing the visitor economy. It also discusses the Northern Ireland Tourism Board and its responsibilities in marketing Northern Ireland as a tourist destination.
The years from 1865-1895 saw many important developments in the United States, including the Bessemer process which made steel production more efficient, the rise of social Darwinism and its influence on business, and the establishment of the Buffalo Soldiers regiment in 1866. Key events also included the Homestead Act which offered free land, the completion of the transcontinental railroad in 1869, and the massacre of Cheyenne at Sand Creek in 1864. Inventors and businessmen like Thomas Edison, Alexander Graham Bell, Andrew Carnegie, and John D. Rockefeller also rose to prominence during this period, helping to industrialize the nation.
Malcolm Fraser founded the Stuttering Foundation of America in 1947 after struggling with stuttering since childhood and receiving therapy. He had a successful career with his brother at their company, NAPA-Genuine Parts. Fraser generously supported the Foundation over time, with endowment income now covering over 50% of operating costs. He received awards for his commitment to helping people who stutter, including the Charles Van Riper award from the American Speech-Language-Hearing Association. Fraser worked to increase awareness of stuttering and help people constructively address it.
The document is a collection of observations about different body parts, describing features like eye and hair color, the shape of noses, cleanliness of ears, uses of hands, dancing abilities, and tattoos. Many of the sentences refer to specific people and body parts without larger context or meaning.
This document contains personal information about Diana Alejandro Marín Rodríguez. It provides her place of living, age, marital status, phone number, family members, occupation, favorite sport, and favorite singer. It also includes pictures and descriptions of the rooms in her house, her daily routine, and activities she likes doing alone, with family or friends such as shopping, walking, laughing, and going to movies.
The document outlines the organization chart for Cardique, a public corporation created by Law 99 in 1993 to manage and conserve the environment and natural resources in Colombia. The chart shows that Cardique has subdepartments for environmental management, planning, protocols, general secretariat, administrative and financial, and an environmental quality laboratory. The subdepartments are responsible for monitoring natural resources, territorial management planning, disseminating corporate actions, legal matters, financial management and staffing, and providing analytical services for water, soil and air samples.
The document discusses RFID technology, including how it works, common applications, and survey results on possible uses. RFID uses radio frequencies to electronically identify objects. Survey respondents thought RFID could be applied to library management, logistics/supply chain management, and medical/pharmaceutical industries.
Hitler realized that gradual psychological changes were needed to shift the German people's views to accept his agenda of using force and violence. He systematically utilized propaganda through radio, the press, films, and mass meetings to educate Germans and reinforce National Socialist ideas. The film "Triumph of the Will" documented one of Hitler's mass rallies and demonstrated the power of film to promote his message.
The document summarizes a study analyzing the impacts of accelerated agricultural growth in Mozambique. The study uses an economic model to compare a baseline growth scenario to a "CAADP scenario" where agriculture grows at 7% annually by focusing on high-potential regions. The model finds the CAADP scenario would significantly reduce poverty and food insecurity compared to the baseline. However, the document notes policies should target all regions to ensure equal outcomes and discusses interactions between agriculture and other development strategies.
The Elavia group is a family-owned, professionally managed business established in 1915 that specializes in lifts and international trading. It aims to be a leader in manufacturing, installing, and modernizing lifts, as well as trading niche food and beverage products globally. Through its Excel Lifts and Excel Cenomundus divisions, the group works to provide safe and convenient lift transportation while assisting foreign companies establish in India's diverse markets.
What is SPF record good for? | Part 7#17Eyal Doron
What is SPF record good for? | Part 7#17
http://o365info.com/what-is-spf-record-good-for-part-7-17
The purpose of the SPF record and the relation to for our mail infrastructure. How does the SPF record enable us to prevent a scenario in which hostile elements could send E-mail on our behalf.
Eyal Doron | o365info.com
This document contains basic math equations that equal 4. It shows that 2 + 2, 3 + 2, 9 - 8, 6 - 4, 2 x 3, 10 x 2, and 4 / 2 all equal 4, while 6 / 6 equals 1.
This document discusses different alert services available through legal research databases. It describes how to set up search alerts, Shepard's alerts, publication alerts, docket alerts, and more on Lexis Advance and WestlawNext. It also mentions alert options on Bloomberg Law, CCH Intelliconnect, Bloomberg BNA, and some other databases. The document provides examples and links for additional information on using the various alert tools. It concludes by discussing legal blogs and ways to follow blogs through RSS readers or Twitter.
This document summarizes a study of deep learning models and Bayesian statistics. It discusses the history of artificial intelligence and machine learning before introducing restricted Boltzmann machines, deep belief networks, and Bayesian statistics. It describes experiments applying restricted Boltzmann machines to classify movies and generate images, and using a deep belief network to classify images from multiple datasets with 100% accuracy. The conclusion states that deep learning has advanced artificial intelligence by allowing algorithms to perform multiple tasks and taken us closer to the original goal of general artificial intelligence.
Invited Tutorial - Cognitive Design for Artificial Minds AI*IA 2022Antonio Lieto
This document provides an overview of cognitive design for artificial minds. It discusses how cognitive artificial systems are inspired by human and natural cognition. The key points made are:
- Cognitive artificial systems are inspired by human and natural cognition to be more general and versatile than standard AI systems.
- Examples of cognitively inspired AI systems include ACT-R, Soar, and systems developed using the subsumption architecture.
- Cognitively inspired systems differ from standard AI in that they aim to have explanatory power for human cognition through structural models of cognitive processes and representations.
- Such systems can be used to test cognitive theories, provide human-like capabilities, and potentially lead to more general artificial intelligence.
This is the talk given at the Faculty of Information Technology, Monash University on 19/08/2020. It covers our recent research on the topics of learning to reason, including dual-process theory, visual reasoning and neural memories.
This document provides an overview of unsupervised machine learning techniques for clustering. It discusses different types of clustering including flat partitions, hierarchical trees, and hard vs soft memberships. Specific clustering algorithms are covered like K-means, hierarchical agglomerative clustering (HAC), DBSCAN, and graph-based clustering. Distance functions and linkage methods for HAC are also summarized. The document concludes with examples of applications for different clustering techniques.
ANNs have been widely used in various domains for: Pattern recognition Funct...vijaym148
The document discusses artificial neural networks (ANNs), which are computational models inspired by the human brain. ANNs consist of interconnected nodes that mimic neurons in the brain. Knowledge is stored in the synaptic connections between neurons. ANNs can be used for pattern recognition, function approximation, and associative memory. Backpropagation is an important algorithm for training multilayer ANNs by adjusting the synaptic weights based on examples. ANNs have been applied to problems like image classification, speech recognition, and financial prediction.
This document provides an overview of artificial neural networks (ANNs). It discusses how ANNs are inspired by biological neural networks and are composed of interconnected nodes that mimic neurons. ANNs use a learning process to update synaptic connection weights between nodes based on training data to perform tasks like pattern recognition. The document outlines the history of ANNs and covers popular applications. It also describes common ANN properties, architectures, and the backpropagation algorithm used for training multilayer networks.
This document provides an overview of artificial neural networks (ANNs). It discusses how ANNs are inspired by biological neural networks and are composed of interconnected nodes that mimic neurons. ANNs use a learning process to update synaptic connection weights between nodes based on training data to perform tasks like pattern recognition. The document outlines the history of ANNs and covers popular applications. It also describes common ANN properties, architectures, and the backpropagation algorithm used for training multilayer networks.
This thesis examines self-organization and polychronization in liquid state machines (LSMs). LSMs are a type of recurrent neural network inspired by the brain. The thesis introduces machine learning concepts and neural network models. It discusses how self-organized recurrent neural networks can develop input separation and perform tasks through spike-timing dependent plasticity and other mechanisms. Polychronization, where groups of neurons fire together in precise patterns, is also examined. The thesis hypothesizes that an LSM incorporating both self-organization and polychronization could have improved information processing abilities compared to models without these features.
Face recognition using artificial neural networkSumeet Kakani
This document provides an overview of a face recognition system that uses artificial neural networks. It describes the structure and processing of artificial neural networks, including convolutional networks. It discusses how the system works, including local image sampling, the self-organizing map, and the convolutional network. It then provides details about the implementation and applications of the system for face recognition, and concludes by discussing the benefits of the system.
Community detection aims to identify groups of nodes in a network that are more densely connected internally than to the rest of the network. It can reveal properties of networks without privacy risks. While similar to clustering, community detection methods consider graph properties directly due to challenges from network data. Two recent methods are discussed - one based on shortest path betweenness to iteratively remove inter-community edges, and another based on optimizing modularity, a measure of community structure quality. Modularity can be computed using the eigenvectors of the modularity matrix.
soft computing BTU MCA 3rd SEM unit 1 .pptxnaveen356604
This document discusses hard computing and soft computing. Hard computing uses deterministic algorithms and mathematical models to produce accurate and predictable results, while soft computing can handle imprecision, uncertainty, and ambiguity. Soft computing techniques include fuzzy logic, neural networks, genetic algorithms, probabilistic reasoning, and evolutionary computation. These techniques aim to mimic human-like reasoning by tolerating uncertainty, learning and adapting, and integrating multiple methods. Examples of evolutionary computation algorithms provided are genetic algorithms, genetic programming, evolutionary strategies, differential evolution, and particle swarm optimization. Neural networks, ant colony optimization, and fuzzy logic are also summarized.
Describing latest research in visual reasoning, in particular visual question answering. Covering both images and videos. Dual-process theories approach. Relational memory.
This paper introduces auto-encoding variational Bayes, a generative modeling technique that allows for efficient and scalable approximate inference. The method utilizes variational inference within the framework of autoencoders to learn the posterior distribution over latent variables. It approximates the intractable true posterior using a recognition model conditioned on the observations. The parameters are estimated by maximizing a evidence lower bound derived using Jensen's inequality. This allows for backpropagation to efficiently learn the generative and inference models jointly. The technique was demonstrated on density estimation tasks with MNIST data.
The project aims at development of efficient segmentation method for the CBIR system. Mean-shift segmentation generates a list of potential objects which are meaningful and then these objects are clustered according to a predefined similarity measure. The method was tested on benchmark data and F-Score of .30 was achieved.
This document discusses self-awareness in extremely distributed wireless sensor networks. It describes how such networks can utilize duty-cycled communication to save energy while maintaining synchronization. At the system level, algorithms are proposed for cluster merging and synchronization. Gossip-based data dissemination is discussed as a building block for application-level awareness, allowing local decision making. Remaining challenges are noted around ensuring information dissemination in crowded network conditions.
This document summarizes a paper on multimodal emotion recognition from speech, text, and video data. It discusses how combining multiple modalities can provide richer information than single modalities alone. It presents the IEMOCAP and CMU-MOSEI datasets and compares their modalities. Techniques for fusing modalities include early and late fusion. The paper proposes a solution that filters ineffective data, regenerates proxy features, and uses multiplicative fusion to boost stronger modalities. It evaluates the approach on the CMU-MOSEI dataset using speech, text, and video features and discusses limitations in distinguishing some emotions.
This document provides an overview of a presentation on deep learning given by Melanie Swan. The key points are:
1) Melanie Swan is a technology theorist who gave a presentation on deep learning and smart networks at a conference in Indianapolis.
2) She discussed the definition and technical details of deep learning, including how it is inspired by concepts from statistical mechanics and physics. Deep learning uses neural networks of processing units to model high-level abstractions in data.
3) Deep learning has many applications including image recognition, speech recognition, and question answering. It is seen as important due to the large worldwide spending on AI and the growth of data science jobs.
This document provides an overview of a Machine Learning course, including:
- The course is taught by Max Welling and includes homework, a project, quizzes, and a final exam.
- Topics covered include classification, neural networks, clustering, reinforcement learning, Bayesian methods, and more.
- Machine learning involves computers learning from data to improve performance and make predictions. It is a subfield of artificial intelligence.
The document describes an experiment on small group dynamics using a virtual minority voting game. It discusses Lewin's field theory of group dynamics and uses an online framework to study how 150 subjects in 15 groups interacted under different conditions: blank (no task), topic-based (discussing animal experimentation), and voting-based (trying to be in the second largest cluster). The results show significant differences in communication and centrality measures between conditions, suggesting the tasks influenced group interactions and strategies.
This document summarizes an experiment on small group dynamics using a virtual interaction environment. It included three conditions: a minority voting game with no consensus strategy, a blank interaction with no task, and a majority voting game. The experiment aimed to characterize how communication networks and affinities form in small groups. It used an interface dividing interaction between public chat and private messages, and public/private radar spaces to manipulate positions. Order parameters like activity, centrality degree, and probability matrices were used to analyze communication structure and relationships over time. The results were intended to capture fundamental aspects of individual behavior in small group virtual dynamics.
7 summer solstice2012-a cognitive heuristic model of epidemicsAle Cignetti
The document proposes a cognitive heuristic model for modeling epidemics that accounts for psychological and cognitive effects. It discusses limitations of traditional models and the need to consider adaptive cognitive strategies of agents. A tri-partite cognitive agent model is introduced containing modules for unconscious processes, reasoning, and learning. Finally, a recipe is outlined for an epidemics model incorporating a weighted network environment, viral features, economic factors, bounded agent cognition, and multiple timescales.
The document discusses dynamics of online social networks. It summarizes previous models for network growth and introduces a new model that incorporates the impact of "locality" through an exploration and elaboration phase. The model is able to generate realistic scale-free networks with community structure and short average path lengths similar to real-world social networks like political blogs and friendships. Results show the model fits real network data better than previous models.
4 a cognitive heuristic model of epidemicsAle Cignetti
- The document proposes a cognitive heuristic model for modeling epidemics that accounts for human cognitive and behavioral factors.
- It describes three key aspects of the cognitive model: 1) representing the network as multilayered rather than homogeneous to capture adaptive human behavior, 2) modeling agents as "smart and adapting" rather than rigid, and 3) accounting for multiple timescales in epidemics, including virus spread, human learning and behavior change, and network evolution.
- The model uses a tripartite structure to represent cognitive modules of unconscious knowledge, reasoning, and learning. It provides an algorithm for simulating epidemics that incorporates the cognitive heuristics of agents interacting on a dynamic network over multiple timescales.
3 a cognitive heuristic model of community recognition finalAle Cignetti
- The document proposes a cognitive heuristic model for recognizing local communities.
- It describes the ambiguous concept of community and notes communities can be described as a clustering spectrum.
- The model is inspired by human cognitive skills and heuristics for effective community detection. It uses a tri-partite model involving unconscious knowledge, reasoning, and learning modules.
- The paper outlines a simple cognitive algorithm for community detection based on knowledge discovery, learning, inference, and evaluation phases that aims to be inherently local and scalable.
The document describes a tri-partite model of cognitive heuristics. It is composed of three modules:
Module I processes external information using schemes and a relevance heuristic to extract context. Module II performs reasoning, goal-setting, recognition, and problem-solving using heuristics. Module III provides learning and evaluation feedback to improve the system over time. Each module contains schemes that interface with a shared knowledge context to complete their functions.
The document describes a tri-partite model of computational knowledge. It proposes modeling human cognition using three modules that process information at different timescales and cognitive costs based on evolutionary features. Module I deals with unconscious knowledge like perception and attention. Module II involves conscious reasoning processes. Module III focuses on learning and development over various timescales. The model aims to quantitatively represent cognitive processes below rational reasoning to enable more human-like artificial intelligence.
1. Motivation Scenario Algorithm Evaluation
A Cognitive-Inspired Model for Self-Organizing
Networks
ASENSIS 2012
Daniel Borkmann0 Andrea Guazzini12 Emanuele Massaro3
Stefan Rudolph4
0
Communication Systems Group, ETH Zurich, Switzerland
1
Institute for Informatics and Telematics, National Research Council, Pisa, Italy
2
Department of Psychology, University of Florence, Italy
3
Department of Informatics and Systems, University of Florence, Italy
4
Organic Computing Group, University of Augsburg, Germany
10th September, 2012
Borkmann, Guazzini, Massaro, Rudolph Self-Organizing Networks 1 / 19
3. Motivation Scenario Algorithm Evaluation
Motivation
Large Scale Networks emerge
Internet
Pervasive Computing
Often used: Overlay networks
Problems of overlay networks
Structured: Hard without global information
Unstructured: No optimization of network structure
Idea
Self-optimization of an overlay network
Through a cognitive-inspired model
Borkmann, Guazzini, Massaro, Rudolph Self-Organizing Networks 3 / 19
4. Motivation Scenario Algorithm Evaluation
Scenario
Connected network of n nodes
Static, nodes don’t disappear or appear
Each holdes one item (e.g. a service or data)
Each wants to retrieve items with respect to its energy
Each has a limited number of links from 1 . . . m
Each node can change its links
Optimization problems: change links in order to
Retrieve all items with the minimum number of hops
Maximize the number of items with a fixed amount of hops
Borkmann, Guazzini, Massaro, Rudolph Self-Organizing Networks 4 / 19
5. Motivation Scenario Algorithm Evaluation
Cognitive-Inspired Hub Detection
Diffusion and Competitive Interaction
At start
A is the adjacency matrix
Every node i has a state vector Si (short term memory)
(k )
Si is the probability that node i belongs to community k
Every node belongs to its own community
Update of the state vectors
1
S (t + 2 ) = mSik (t ) + (1 − m) ∑j Aij Sjk (t )
α 1
Sik (t + 2 )
S (t + 1) =
∑j Sij (t + 1 )
α
2
Borkmann, Guazzini, Massaro, Rudolph Self-Organizing Networks 5 / 19
6. Motivation Scenario Algorithm Evaluation
Cognitive-Inspired Hub Detection
Diffusion and Competitive Interaction
Entropy
Ei = − ∑(Sj · log (Sj ))
Plateaus show sub-clusters
When curvature changes sign, save information in temporary
memory box
Shannon entropy of information
6.00
5.00
4.00
Entropy
3.00
2.00
1.00
0.00
0 5 10 15 20 25 30 35 40
Time
Borkmann, Guazzini, Massaro, Rudolph Self-Organizing Networks 6 / 19
7. Motivation Scenario Algorithm Evaluation
Cognitive-Inspired Hub Detection
Cognitive Dissonance
Cognitive concept found by social psychologists
Reduces conflicting cognitions
Creates consistent belief system
∑k |Sik −Sjk |
Here: Dij := 2
Interesting for adaption of α :
Eit −1 +Dit −1 Eit +Dit
If Ki
− Ki
< ε for more than τ ∗ times
Set αi = 1.5|η (0,σ ) | + 1
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8. Motivation Scenario Algorithm Evaluation
Cognitive-Inspired Hub Detection
Long Term Memory
Store potential hubs in the Long Term Memory
Find B 1 time positions by sorting with respect to first derivative
Sort the remaining vectors with respect to the entropy
Find the potential hubs in the state vectors
Use Long Term Buffer of size B 2
The last B 2 sets of size B 1 are stored (bounded rationality)
This creates a (B 1 , B 2 ) matrix
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9. Motivation Scenario Algorithm Evaluation
Rewiring
With help of this Long Term Memory, we can can create a “hub
list" for each node
Rewiring steps:
1. Find the weakest X % of the nodes
2. Choose Y % of the nodes at random
3. Each of these nodes closes a connection to a non-hub
4. Each of these nodes opens a new connection to a potential hub
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15. Motivation Scenario Algorithm Evaluation
Numerical Simulation
Scenarios
1. Maximization of the reachable items of the nodes
The energy (hops) is limited
Weakest nodes: Minimum number of items
2. Minimization of used energy
All item will be reached in every step
Weakest nodes: Maximum number of energy
Randomized Algorithm
For comparison
Does not use hub list
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16. Motivation Scenario Algorithm Evaluation
Numerical Simulation
Parameters
Number of nodes n
Mean connectivity
Mean extra connectivity
Number of unique items I
Number of items to retrieve Imax
Hub detection: m, α
Rewiring
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18. Motivation Scenario Algorithm Evaluation
Evaluation
Results for the minimization of energy
Topology Optimization
166.00
164.00
162.00
160.00
Mean energy
158.00
156.00
154.00
152.00
150.00
148.00
0 100 200 300 400 500 600 700 800 900 1000
Round
Rewiring, cognitive approach Rewiring, randomzied approach
Setting: Mean over 50 runs, n = 200, mean_conn= 4, extra_conn= 4, I = 50, Imax = 45, rw_weak= 0.09, rw_rand= 0.03
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19. Motivation Scenario Algorithm Evaluation
Conclusion
Contributions
Development of a cognitive model for community detection
Application of information for self-optimization of a network
Comparison with a randomized algorithm
Future Work
(i) Evaluate the algorithm on a wide range of large scale network
topologies
(ii) Localize the decision making of a node when to rewire or not
(iii) Introduce more dynamics into items and nodes
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