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ieee international conference on Fuzzy Systems (FUZZ-ieee)

作者： Acampora, Giovanni Vitiello, Autilia Nottingham Trent Univ Sch Sci & Technol Nottingham NG11 8NS England Univ Salerno Dept Comp Sci I-84084 Salerno Italy

ISBN: (纸本)9781467374286

Inferring Gene Regulatory Networks (GRNs) from expression data is one of the most challenging topic in computational biology. Indeed, the reasoning about GRN behaviours is a crucial biological task useful to provide an significant support for the identification of genetic diseases and the estimation of the effects of medications. Over years, several approaches have been applied to infer GRNs, most of them are based on deterministic and crisp-based algorithms. However, the intrinsic imprecise nature of the gene regulation makes these approaches as inefficient and characterized by a low accuracy. Starting from this consideration, in this work, we propose to use Fuzzy cognitive Maps to model the complex behaviour of GRNs and to learn FCMs models of GRNs by means of an innovative evolutionary algorithm: the Big Bang-Big Crunch algorithm. As shown through a statistical comparison, the proposed approach outperforms other evolutionary learning methods in inferring GRNs representing, as a consequence, a breakthrough approach in this fascinating and challenging domain.

关键词： biology computing diseases evolutionary computation fuzzy set theory genetics learning (artificial intelligence) statistical analysis GRN big bang-big crunch algorithm computational biology crisp-based algorithms deterministic algorithms evolutionary learning methods fuzzy cognitive maps learning gene regulation gene regulatory networks genetic diseases statistical comparison Computational modeling Fuzzy cognitive maps Gene expression Proteins Sociology Time series analysis

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Knowledge Mining for cognitive Agents Through Path based Forward Checking 16

Knowledge Mining for Cognitive Agents Through Path based For...

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16th ieee/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed computing (SNPD)

作者： Atahary, Tanvir Taha, Tarek Webber, Fredrick Douglass, Scott Univ Dayton Elect & Comp Engn Dayton OH 45469 USA Air Force Res Lab Human Effectiveness Directorate Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9781479986767

The cognitively Enhanced complex Event Processing (CECEP) architecture is an autonomous decision support tool that reasons and learns like humans and enables enhanced agent-based decision making. This architecture has applications in both military and civilian domains, including operations research and data mining. One of the most computationally challenging aspects of CECEP is mining domain knowledge captured in cognitive domain ontologies (CDOs). This requires massively linked knowledge databases to be searched based on a large set of constraints to generate intelligent decisions. The solution search for CDOs is a kind of Constraint Satisfaction Problem (CSP). Due to the unique nature of the CDO-to-CSP mapping, generic constraint solvers are inefficient. We introduce a novel high performance path based forward checking CSP algorithm to solve CDOs and compare it to a commonly utilized CSP solving application. Additionally our approach enables a very compact and efficient representation of the entire solution space to allow fast processing and give agents key ideas on how to further reduce the solution space. The proposed algorithm provided a speedup of about 10-25 times for generating the first solution and about half a million times for all the solutions over a Choco based conventional CSP approach.

关键词： Knowledge Mining Accelerate Constraint Satisfaction problem Forward Checking cognitive Agents

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Watson and the era of cognitive computing

Watson and the era of cognitive computing

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ieee international conference on Pervasive computing and Communications (PerCom)

作者： Guruduth S. Banavar Cognitive Computing IBM Research

Summary form only given. In the last decade, the availability of massive amounts of new data, and the development of new machine learning technologies, have augmented reasoning systems to give rise to a new class of computing systems. These cognitive Systems learn from data, reason from models, and interact naturally with us, to perform complex tasks better than either humans or machines can do by themselves. In essence, cognitive systems help us perform like the best in each domain by penetrating the complexity of big data and leveraging the power of models. O ne of the first cognitive systems, Watson, demonstrated through a Jeopardy! exhibition match, that it was capable of answering complex factoid questions as effectively as the worlds champions. Follow-on cognitive systems perform other tasks, such as discovery, reasoning, and multi-modal understanding in a variety of domains, such as healthcare, insurance, and education. We believe such cognitive systems will transform every profession, industry, and our everyday life for the better. In this talk, I will give an overview of the applications and key capabilities of cognitive systems, and highlight the role pervasive computing will play in such systems.

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Develop Fuzzy cognitive Maps based on recorded data and information

Develop Fuzzy Cognitive Maps based on recorded data and info...

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ieee international conference on Fuzzy Systems

作者： Chrysostomos Stylios Voula C. Georgopoulos Knowledge and Intelligent Computing Laboratory Computer Engineering Depart. Technological Educational Institute of Epirus INTERACT Lab School of Health & Welfare Professions Technological Educational Institute of Western Greece

ISBN: (纸本)9781467374293

This work presents a novel integrated approach on how to develop Fuzzy cognitive Maps combining human expert knowledge with existing recorded information and historical data. The proposed approach aims to extract information from unstructured data and to transform it into knowledge in the form of a FCM. The proposed approach still is dependent on experts but providing them with more information and supportive data, in the form of particular evidence-based information available in the literature in order to better justify their selections. The proposed approach is inherit to the FCM and its structure the extracted knowledge and it can be used to model a complex system such as the Medical Decision Support Systems.

关键词： Fuzzy cognitive Maps Knowledge extraction Historical data Case based Soft computing

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Information flow and complex event processing of the sensor network communication

Information flow and complex event processing of the sensor ...

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international conference on cognitive Infocommunications (CogInfoCom)

作者： Zoltán Gál Hunor Sándor Béla Genge University of Debrecen Center for High Performance Computing Debrecen Hungary Department of Computer Science Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Informatics Petru Maior University of Tg. Mures Tg. Mures Romania

ISBN: (纸本)9781467381307

Research institutes and companies are focusing intensively on complex Event Processing, Event Stream Processing, Information Flow Processing and Surprise Event Detection methods and algorithms. This phenomenon is intensified by the rapid evolution and spreading in practice of the Internet of Things services. A huge amount of data is created continuously by the physical and logical sensors embedded into various equipment and aimed to monitor the state of physical processes. Time critical query-response mechanisms of the QoS based systems are more and more penetrating in the low bandwidth wireless sensor environment, as well. The behavior of the wireless sensor network requires special evaluation of the state information sent to and processed by the sink node. The items of the status information flow are affected by the low energy and low bandwidth characteristics of sensor networks. Despite of uncertainty of the data transmission in wireless sensor networks the energy constraint permits rarely retransmission of data affected by error. To mitigate the aforementioned issues, cognitive infocommunication algorithms may prove to be an effective solutions. Consequently, this paper presents a method to detect special events and surprises in time processes of the sensor network communication. The proposed method is applied to ZigBee sensor network (based on ieee 802.15.4 standard) in different congestion scenarios.

关键词： Monitoring Companies Focusing Zigbee Artificial neural networks Internet

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Knowledge mining for cognitive agents through path based forward checking

Knowledge mining for cognitive agents through path based for...

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ACIS international conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing (SNPD)

作者： Tanvir Atahary Tarek Taha Fredrick Webber Scott Douglass Electrical and Computer Engineering University of Dayton Dayton OH USA Human Effectiveness Directorate Air Force Research Laboratory OH USA

关键词： II-VI semiconductor materials Cadmium compounds Algorithm design and analysis Clouds Knowledge engineering Atmospheric modeling data mining

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Towards a Social Interaction-based Cognition Model: An Analysis of Spatial data Infrastructure 13

Towards a Social Interaction-based Cognition Model: An Analy...

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13th ieee international conference on cognitive Informatics and cognitive computing (ICCI*CC)

作者： Reynoso, Luis Grosclaude, Eduardo Sanchez, Laura Alvarez, Mabel Univ Comahue Fac Informat RA-1400 Buenos Aires DF Argentina Univ Patagonia San Juan Bosco RA-9100 Trelew Chubut Argentina

ISBN: (纸本)9781479960811

Distributed cognition is a psychological theory which assumes that knowledge lies not only within the individual but also in the individual's social and physical environment. Today, we tend to achieve cognitive results by means of a sequence of complex and subtly interwoven interactions, using technological devices, and with the help of other, more knowledgeable people. As dwellers of a new century, we are agents of a novel technological assembly where knowledge is socially produced, and nurtured by the various sources of many communities of practice (CoP). In this paper we propose a social interaction-based cognition model which applies distributed cognition and interoperability between different actors of CoP in a web environment. The core components of the model are Authenticity and Coupling, Assemblage and Shared Meanings. We also present the main findings of qualitative research in a case of study to Spatial data Infraestructure (SDI) and CoP around this technological assemblies.

关键词： Social Interaction Distributed Cognition Communities of Practice Interoperability

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HCN Production Process Hybrid Intelligence Based on Artificial Neural Networks and Genetic Algorithm 13

HCN Production Process Hybrid Intelligence Based on Artifici...

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13th ieee international conference on cognitive Informatics and cognitive computing (ICCI*CC)

作者： Yi, Jun Zhang, Rui Huang, Di Li, Taifu Peng, Jun Su, Yingying Chongqing Univ Sci & Technol Coll Elect & Informat Engn Chongqing Peoples R China

ISBN: (纸本)9781479960811

complex process modeling and optimization system is a hot area of research. A system model is proposed between process parameters and performance index by using the BP neural network for hydrogen cyanide (HCN) production process. In proposed method, the optimal process parameters would be searched by using genetic algorithm and these optimal parameters could be entered into BP neural network to predict the conversion rate of ammonia. The table about HCN production and process parameters can be produced as optimal results to increase the conversion rate of ammonia. The test result provides that proposed modeling method is a new and effective way for solving optimization problems of multi-dimensional nonlinear system.

关键词： process modeling data preprocessing BP neural network Genetic Algorithm HCN

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Symbol recognition: cognitive approach

Symbol recognition: Cognitive approach

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international conference on Electronic Systems, Signal Processing, and computing Technologies, ICESC 2014

作者： Bashir, Rumaan Giri, Kaiser J. Department of Computer Science Islamic University of Science and Technnology Awantipora India

ISBN: (纸本)9781479921027

The field of Computer Science has been solving issues related to the domains of data, information, knowledge and intelligence, obviously in a chronological manner. Among these the issue of Symbol Recognition has received lot of attention. The procedure of analyzing and recognizing symbols involves various stages. A number of algorithms have been devised and implemented for the purpose of symbol recognition but usually focus on complex features and properties. In this paper, we propose a cognitive model for the recognition of offline machine drawn symbols which uses minimal amount of data. The algorithm proposed is independent of the size/slant of the symbol. © 2014 ieee.

关键词： Byte Code cognitive Feature Extraction Pixel Based Approach Recognition Symbol

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Applying cognitive situation awareness to collision avoidance for harbour last-mile area safety

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED computing 2014年第5期5卷 741-745页

作者： Clemente, Susanna Loia, Vincenzo Veniero, Mario Univ Salerno Dept Informat I-84100 Salerno Italy CORISA Consorzio Ric Sistemi Ad Agenti Salerno Italy

Maneuvering ships in harbour areas is recognized as one of the most complex activity to be carried out Le (An automatic control system for ship harbour maneuvers using decoupling control. In: ieee international conference on Robotics and Automation, 2001. Proceedings 2001 ICRA 2: 2108-2113, 2001) as a consequence of all information needs related to safety maintenance during guidance and control activities. By taking advantage of existing results, in this work we argue how situation awareness could be a leading and valuable technology to support decision making activities in this application. In particular, we propose the usage of a decentralized, autonomous, agent-based cognitive situation awareness framework, yet successfully experimented for airport safety monitoring and specifically modified to be applied to the maritime domain. The proposed framework exploits sensor network acquired streamed data management activities, together with semantic technologies and uncertainty management methods. The resulting architecture is aimed at monitoring ongoing situations and forecasting potential collisions, identifying involved entities and relations in order to improve the ability of maneuvering operators in assessing the current situations and their possible evolutions. Results and performances will be verified at the Port of Salerno, in order to show that information supporting inferred situations comply with real needs of decision making activities to prevent collisions during daily operations.

关键词： Agents cognitive systems Ontology Sensor networks Situation awareness Ubiquitous computing

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