WorldWideScience

Sample records for methods providing intelligent

  1. Intelligent methods for cyber warfare

    CERN Document Server

    Reformat, Marek; Alajlan, Naif

    2015-01-01

    Cyberwarfare has become an important concern for governmental agencies as well businesses of various types.  This timely volume, with contributions from some of the internationally recognized, leaders in the field, gives readers a glimpse of the new and emerging ways that Computational Intelligence and Machine Learning methods can be applied to address problems related to cyberwarfare. The book includes a number of chapters that can be conceptually divided into three topics: chapters describing different data analysis methodologies with their applications to cyberwarfare, chapters presenting a number of intrusion detection approaches, and chapters dedicated to analysis of possible cyber attacks and their impact. The book provides the readers with a variety of methods and techniques, based on computational intelligence, which can be applied to the broad domain of cyberwarfare.

  2. Providing an efficient intelligent transportation system through ...

    Indian Academy of Sciences (India)

    present view point, analysis of traffic signs are first considered via intelligence based ... colour information has been only used in segmentation, once detection .... Because number of road sign shapes is more than two classes, multi-class ...

  3. A Lead Provided by Bookmarks - Intelligent Browsers

    Directory of Open Access Journals (Sweden)

    Dan Balanescu

    2015-05-01

    Full Text Available Browsers are applications that allow Internet access. A defining characteristic is their unidirectionality: Navigator-> Internet. The purpose of this article is to support the idea of Intelligent Browsers that is defined by bidirectional: Navigator-> Internet and Internet-> Navigator. The fundamental idea is that the Internet contains huge resources of knowledge, but they are “passive”. The purpose of this article is to propose the “activation” of this knowledge so that they, through “Intelligent Browsers”, to become from Sitting Ducks to Active Mentors. Following this idea, the present article proposes changes to Bookmarks function, from the current status of Favorites to Recommendations. The article presents an analysis of the utility of this function (by presenting a research of web browsing behaviors and in particular finds that the significance of this utility has decreased lately (to the point of becoming almost useless, as will be shown, in terms data-information-knowledge. Finally, it presents the idea of a project which aims to be an applied approach that anticipates the findings of this study and the concept of Intelligent Browsers (or Active Browsers required in the context of the Big Data concept.

  4. COMPETITIVE INTELLIGENCE ANALYSIS - SCENARIOS METHOD

    Directory of Open Access Journals (Sweden)

    Ivan Valeriu

    2014-07-01

    Full Text Available Keeping a company in the top performing players in the relevant market depends not only on its ability to develop continually, sustainably and balanced, to the standards set by the customer and competition, but also on the ability to protect its strategic information and to know in advance the strategic information of the competition. In addition, given that economic markets, regardless of their profile, enable interconnection not only among domestic companies, but also between domestic companies and foreign companies, the issue of economic competition moves from the national economies to the field of interest of regional and international economic organizations. The stakes for each economic player is to keep ahead of the competition and to be always prepared to face market challenges. Therefore, it needs to know as early as possible, how to react to others’ strategy in terms of research, production and sales. If a competitor is planning to produce more and cheaper, then it must be prepared to counteract quickly this movement. Competitive intelligence helps to evaluate the capabilities of competitors in the market, legally and ethically, and to develop response strategies. One of the main goals of the competitive intelligence is to acknowledge the role of early warning and prevention of surprises that could have a major impact on the market share, reputation, turnover and profitability in the medium and long term of a company. This paper presents some aspects of competitive intelligence, mainly in terms of information analysis and intelligence generation. Presentation is theoretical and addresses a structured method of information analysis - scenarios method – in a version that combines several types of analysis in order to reveal some interconnecting aspects of the factors governing the activity of a company.

  5. Constructing an Intelligent Patent Network Analysis Method

    Directory of Open Access Journals (Sweden)

    Chao-Chan Wu

    2012-11-01

    Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

  6. National Water Model: Providing the Nation with Actionable Water Intelligence

    Science.gov (United States)

    Aggett, G. R.; Bates, B.

    2017-12-01

    The National Water Model (NWM) provides national, street-level detail of water movement through time and space. Operating hourly, this flood of information offers enormous benefits in the form of water resource management, natural disaster preparedness, and the protection of life and property. The Geo-Intelligence Division at the NOAA National Water Center supplies forecasters and decision-makers with timely, actionable water intelligence through the processing of billions of NWM data points every hour. These datasets include current streamflow estimates, short and medium range streamflow forecasts, and many other ancillary datasets. The sheer amount of NWM data produced yields a dataset too large to allow for direct human comprehension. As such, it is necessary to undergo model data post-processing, filtering, and data ingestion by visualization web apps that make use of cartographic techniques to bring attention to the areas of highest urgency. This poster illustrates NWM output post-processing and cartographic visualization techniques being developed and employed by the Geo-Intelligence Division at the NOAA National Water Center to provide national actionable water intelligence.

  7. Intelligent structural optimization: Concept, Model and Methods

    International Nuclear Information System (INIS)

    Lu, Dagang; Wang, Guangyuan; Peng, Zhang

    2002-01-01

    Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

  8. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

    Dourgnon-Hanoune, A.; Porcheron, M.; Ricard, B.

    1996-01-01

    To assist in diagnosis of its nuclear power plants, the Research and Development Division of Electricite de France has been developing skills in Artificial Intelligence for about a decade. Different diagnostic expert systems have been designed. Among them, SILEX for control rods cabinet troubleshooting, DIVA for turbine generator diagnosis, DIAPO for reactor coolant pump diagnosis. This know how in expert knowledge modeling and acquisition is direct result of experience gained during developments and of a more general reflection on knowledge based system development. We have been able to reuse this results for other developments such as a guide for auxiliary rotating machines diagnosis. (authors)

  9. Computing Nash equilibria through computational intelligence methods

    Science.gov (United States)

    Pavlidis, N. G.; Parsopoulos, K. E.; Vrahatis, M. N.

    2005-03-01

    Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.

  10. Incentives and provider payment methods.

    Science.gov (United States)

    Barnum, H; Kutzin, J; Saxenian, H

    1995-01-01

    The mode of payment creates powerful incentives affecting provider behavior and the efficiency, equity and quality outcomes of health finance reforms. This article examines provider incentives as well as administrative costs, and institutional conditions for successful implementation associated with provider payment alternatives. The alternatives considered are budget reforms, capitation, fee-for-service, and case-based reimbursement. We conclude that competition, whether through a regulated private sector or within a public system, has the potential to improve the performance of any payment method. All methods generate both adverse and beneficial incentives. Systems with mixed forms of provider payment can provide tradeoffs to offset the disadvantages of individual modes. Low-income countries should avoid complex payment systems requiring higher levels of institutional development.

  11. 3rd Workshop on "Combinations of Intelligent Methods and Applications"

    CERN Document Server

    Palade, Vasile

    2013-01-01

    The combination of different intelligent methods is a very active research area in Artificial Intelligence (AI). The aim is to create integrated or hybrid methods that benefit from each of their components.  The 3rd Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2012) was intended to become a forum for exchanging experience and ideas among researchers and practitioners who are dealing with combining intelligent methods either based on first principles or in the context of specific applications. CIMA 2012 was held in conjunction with the 22nd European Conference on Artificial Intelligence (ECAI 2012).This volume includes revised versions of the papers presented at CIMA 2012.  .

  12. Classification of Children Intelligence with Fuzzy Logic Method

    Science.gov (United States)

    Syahminan; ika Hidayati, Permata

    2018-04-01

    Intelligence of children s An Important Thing To Know The Parents Early on. Typing Can be done With a Child’s intelligence Grouping Dominant Characteristics Of each Type of Intelligence. To Make it easier for Parents in Determining The type of Children’s intelligence And How to Overcome them, for It Created A Classification System Intelligence Grouping Children By Using Fuzzy logic method For determination Of a Child’s degree of intelligence type. From the analysis We concluded that The presence of Intelligence Classification systems Pendulum Children With Fuzzy Logic Method Of determining The type of The Child’s intelligence Can be Done in a way That is easier And The results More accurate Conclusions Than Manual tests.

  13. Hybrid intelligent optimization methods for engineering problems

    Science.gov (United States)

    Pehlivanoglu, Yasin Volkan

    quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles.

  14. The Multiple Intelligences Teaching Method and Mathematics ...

    African Journals Online (AJOL)

    The Multiple Intelligences teaching approach has evolved and been embraced widely especially in the United States. The approach has been found to be very effective in changing situations for the better, in the teaching and learning of any subject especially mathematics. Multiple Intelligences teaching approach proposes ...

  15. Delamination detection using methods of computational intelligence

    Science.gov (United States)

    Ihesiulor, Obinna K.; Shankar, Krishna; Zhang, Zhifang; Ray, Tapabrata

    2012-11-01

    Abstract Reliable delamination prediction scheme is indispensable in order to prevent potential risks of catastrophic failures in composite structures. The existence of delaminations changes the vibration characteristics of composite laminates and hence such indicators can be used to quantify the health characteristics of laminates. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using numerical models of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used via inverse modeling to determine the position, size and location of delaminations using changes in measured natural frequencies. The results clearly highlight the efficiency and the robustness of the approach.

  16. 4th Workshop on Combinations of Intelligent Methods and Applications

    CERN Document Server

    Palade, Vasile; Prentzas, Jim

    2016-01-01

    This volume includes extended and revised versions of the papers presented at the 4th Workshop on “Combinations of Intelligent Methods and Applications” (CIMA 2014) which was intended to become a forum for exchanging experience and ideas among researchers and practitioners dealing with combinations of different intelligent methods in Artificial Intelligence. The aim is to create integrated or hybrid methods that benefit from each of their components. Some of the existing presented efforts combine soft computing methods (fuzzy logic, neural networks and genetic algorithms). Another stream of efforts integrates case-based reasoning or machine learning with soft-computing methods. Some of the combinations have been more widely explored, like neuro-symbolic methods, neuro-fuzzy methods and methods combining rule-based and case-based reasoning. CIMA 2014 was held in conjunction with the 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014). .

  17. Subspace methods for pattern recognition in intelligent environment

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.

  18. Applying intelligent statistical methods on biometric systems

    OpenAIRE

    Betschart, Willie

    2005-01-01

    This master’s thesis work was performed at Optimum Biometric Labs, OBL, located in Karlskrona, Sweden. Optimum Biometric Labs perform independent scenario evaluations to companies who develop biometric devices. The company has a product Optimum preConTM which is surveillance and diagnosis tool for biometric systems. This thesis work’s objective was to develop a conceptual model and implement it as an additional layer above the biometric layer with intelligence about the biometric users. The l...

  19. Intelligent methods for data retrieval in fusion databases

    International Nuclear Information System (INIS)

    Vega, J.

    2008-01-01

    The plasma behaviour is identified through the recognition of patterns inside signals. The search for patterns is usually a manual and tedious procedure in which signals need to be examined individually. A breakthrough in data retrieval for fusion databases is the development of intelligent methods to search for patterns. A pattern (in the broadest sense) could be a single segment of a waveform, a set of pixels within an image or even a heterogeneous set of features made up of waveforms, images and any kind of experimental data. Intelligent methods will allow searching for data according to technical, scientific and structural criteria instead of an identifiable time interval or pulse number. Such search algorithms should be intelligent enough to avoid passing over the entire database. Benefits of such access methods are discussed and several available techniques are reviewed. In addition, the applicability of the methods from general purpose searching systems to ad hoc developments is covered

  20. ORTHO IMAGE AND DTM GENERATION WITH INTELLIGENT METHODS

    Directory of Open Access Journals (Sweden)

    H. Bagheri

    2013-10-01

    Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

  1. Ortho Image and DTM Generation with Intelligent Methods

    Science.gov (United States)

    Bagheri, H.; Sadeghian, S.

    2013-10-01

    Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse

  2. Short-term electric load forecasting using computational intelligence methods

    OpenAIRE

    Jurado, Sergio; Peralta, J.; Nebot, Àngela; Mugica, Francisco; Cortez, Paulo

    2013-01-01

    Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, Evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out...

  3. On construction method of shipborne and airborne radar intelligence and related equipment knowledge graph

    Science.gov (United States)

    Hao, Ruizhe; Huang, Jian

    2017-08-01

    Knowledge graph construction in military intelligence domain is sprouting but technically immature. This paper presents a method to construct the heterogeneous knowledge graph in the field of shipborne and airborne radar and equipment. Based on the expert knowledge and the up-to-date Internet open source information, we construct the knowledge graph of radar characteristic information and the equipment respectively, and establish relationships between two graphs, providing the pipeline and method for the intelligence organization and management in the context of the crowding battlefields big data.

  4. [Development and effects of emotional intelligence program for undergraduate nursing students: mixed methods research].

    Science.gov (United States)

    Lee, Oi Sun; Gu, Mee Ock

    2014-12-01

    This study was conducted to develop and test the effects of an emotional intelligence program for undergraduate nursing students. The study design was a mixed method research. Participants were 36 nursing students (intervention group: 17, control group: 19). The emotional intelligence program was provided for 4 weeks (8 sessions, 20 hours). Data were collected between August 6 and October 4, 2013. Quantitative data were analyzed using Chi-square, Fisher's exact test, t-test, repeated measure ANOVA, and paired t-test with SPSS/WIN 18.0. Qualitative data were analyzed using content analysis. Quantitative results showed that emotional intelligence, communication skills, resilience, stress coping strategy, and clinical competence were significantly better in the experimental group compared to the control group. According to the qualitative results, the nursing students experienced improvement in emotional intelligence, interpersonal relationships, and empowerment, as well as a reduction in clinical practice stress after participation in the emotional intelligence program. Study findings indicate that the emotional intelligence program for undergraduate nursing students is effective and can be recommended as an intervention for improving the clinical competence of undergraduate students in a nursing curriculum.

  5. Artificial neural network intelligent method for prediction

    Science.gov (United States)

    Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

    2017-09-01

    Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

  6. Intelligent numerical methods applications to fractional calculus

    CERN Document Server

    Anastassiou, George A

    2016-01-01

    In this monograph the authors present Newton-type, Newton-like and other numerical methods, which involve fractional derivatives and fractional integral operators, for the first time studied in the literature. All for the purpose to solve numerically equations whose associated functions can be also non-differentiable in the ordinary sense. That is among others extending the classical Newton method theory which requires usual differentiability of function. Chapters are self-contained and can be read independently and several advanced courses can be taught out of this book. An extensive list of references is given per chapter. The book’s results are expected to find applications in many areas of applied mathematics, stochastics, computer science and engineering. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also to be in all science and engineering libraries.

  7. Comparison of methods for estimating premorbid intelligence

    OpenAIRE

    Bright, Peter; van der Linde, Ian

    2018-01-01

    To evaluate impact of neurological injury on cognitive performance it is typically necessary to derive a baseline (or ‘premorbid’) estimate of a patient’s general cognitive ability prior to the onset of impairment. In this paper, we consider a range of common methods for producing this estimate, including those based on current best performance, embedded ‘hold/no hold’ tests, demographic information, and word reading ability. Ninety-two neurologically healthy adult participants were assessed ...

  8. Method of dynamic fuzzy symptom vector in intelligent diagnosis

    International Nuclear Information System (INIS)

    Sun Hongyan; Jiang Xuefeng

    2010-01-01

    Aiming at the requirement of diagnostic symptom real-time updating brought from diagnostic knowledge accumulation and great gap in unit and value of diagnostic symptom in multi parameters intelligent diagnosis, the method of dynamic fuzzy symptom vector is proposed. The concept of dynamic fuzzy symptom vector is defined. Ontology is used to specify the vector elements, and the vector transmission method based on ontology is built. The changing law of symptom value is analyzed and fuzzy normalization method based on fuzzy membership functions is built. An instance proved method of dynamic fussy symptom vector is efficient to solve the problems of symptom updating and unify of symptom value and unit. (authors)

  9. Providing Evidence-Based, Intelligent Support for Flood Resilient Planning and Policy: The PEARL Knowledge Base

    Directory of Open Access Journals (Sweden)

    George Karavokiros

    2016-09-01

    Full Text Available While flood risk is evolving as one of the most imminent natural hazards and the shift from a reactive decision environment to a proactive one sets the basis of the latest thinking in flood management, the need to equip decision makers with necessary tools to think about and intelligently select options and strategies for flood management is becoming ever more pressing. Within this context, the Preparing for Extreme and Rare Events in Coastal Regions (PEARL intelligent knowledge-base (PEARL KB of resilience strategies is presented here as an environment that allows end-users to navigate from their observed problem to a selection of possible options and interventions worth considering within an intuitive visual web interface assisting advanced interactivity. Incorporation of real case studies within the PEARL KB enables the extraction of (evidence-based lessons from all over the word, while the KB’s collection of methods and tools directly supports the optimal selection of suitable interventions. The Knowledge-Base also gives access to the PEARL KB Flood Resilience Index (FRI tool, which is an online tool for resilience assessment at a city level available to authorities and citizens. We argue that the PEARL KB equips authorities with tangible and operational tools that can improve strategic and operational flood risk management by assessing and eventually increasing resilience, while building towards the strengthening of risk governance. The online tools that the PEARL KB gives access to were demonstrated and tested in the city of Rethymno, Greece.

  10. A Survey of Formal Methods for Intelligent Swarms

    Science.gov (United States)

    Truszkowski, Walt; Rash, James; Hinchey, Mike; Rouff, Chrustopher A.

    2004-01-01

    Swarms of intelligent autonomous spacecraft, involving complex behaviors and interactions, are being proposed for future space exploration missions. Such missions provide greater flexibility and offer the possibility of gathering more science data than traditional single spacecraft missions. The emergent properties of swarms make these missions powerful, but simultaneously far more difficult to design, and to assure that the proper behaviors will emerge. These missions are also considerably more complex than previous types of missions, and NASA, like other organizations, has little experience in developing or in verifying and validating these types of missions. A significant challenge when verifying and validating swarms of intelligent interacting agents is how to determine that the possible exponential interactions and emergent behaviors are producing the desired results. Assuring correct behavior and interactions of swarms will be critical to mission success. The Autonomous Nano Technology Swarm (ANTS) mission is an example of one of the swarm types of missions NASA is considering. The ANTS mission will use a swarm of picospacecraft that will fly from Earth orbit to the Asteroid Belt. Using an insect colony analogy, ANTS will be composed of specialized workers for asteroid exploration. Exploration would consist of cataloguing the mass, density, morphology, and chemical composition of the asteroids, including any anomalous concentrations of specific minerals. To perform this task, ANTS would carry miniaturized instruments, such as imagers, spectrometers, and detectors. Since ANTS and other similar missions are going to consist of autonomous spacecraft that may be out of contact with the earth for extended periods of time, and have low bandwidths due to weight constraints, it will be difficult to observe improper behavior and to correct any errors after launch. Providing V&V (verification and validation) for this type of mission is new to NASA, and represents the

  11. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  12. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  13. Continuous surveillance of transformers using artificial intelligence methods; Surveillance continue des transformateurs: application des methodes d'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Schenk, A.; Germond, A. [Ecole Polytechnique Federale de Lausanne, Lausanne (Switzerland); Boss, P.; Lorin, P. [ABB Secheron SA, Geneve (Switzerland)

    2000-07-01

    The article describes a new method for the continuous surveillance of power transformers based on the application of artificial intelligence (AI) techniques. An experimental pilot project on a specially equipped, strategically important power transformer is described. Traditional surveillance methods and the use of mathematical models for the prediction of faults are described. The article describes the monitoring equipment used in the pilot project and the AI principles such as self-organising maps that are applied. The results obtained from the pilot project and methods for their graphical representation are discussed.

  14. Recommendations for the ethical use and design of artificial intelligent care providers.

    Science.gov (United States)

    Luxton, David D

    2014-09-01

    This paper identifies and reviews ethical issues associated with artificial intelligent care providers (AICPs) in mental health care and other helping professions. Specific recommendations are made for the development of ethical codes, guidelines, and the design of AICPs. Current developments in the application of AICPs and associated technologies are reviewed and a foundational overview of applicable ethical principles in mental health care is provided. Emerging ethical issues regarding the use of AICPs are then reviewed in detail. Recommendations for ethical codes and guidelines as well as for the development of semi-autonomous and autonomous AICP systems are described. The benefits of AICPs and implications for the helping professions are discussed in order to weigh the pros and cons of their use. Existing ethics codes and practice guidelines do not presently consider the current or the future use of interactive artificial intelligent agents to assist and to potentially replace mental health care professionals. AICPs present new ethical issues that will have significant ramifications for the mental health care and other helping professions. Primary issues involve the therapeutic relationship, competence, liability, trust, privacy, and patient safety. Many of the same ethical and philosophical considerations are applicable to use and design of AICPs in medicine, nursing, social work, education, and ministry. The ethical and moral aspects regarding the use of AICP systems must be well thought-out today as this will help to guide the use and development of these systems in the future. Topics presented are relevant to end users, AI developers, and researchers, as well as policy makers and regulatory boards. Published by Elsevier B.V.

  15. Towards a New Approach of the Economic Intelligence Process: Basic Concepts, Analysis Methods and Informational Tools

    Directory of Open Access Journals (Sweden)

    Sorin Briciu

    2009-04-01

    Full Text Available One of the obvious trends in current business environment is the increased competition. In this context, organizations are becoming more and more aware of the importance of knowledge as a key factor in obtaining competitive advantage. A possible solution in knowledge management is Economic Intelligence (EI that involves the collection, evaluation, processing, analysis, and dissemination of economic data (about products, clients, competitors, etc. inside organizations. The availability of massive quantities of data correlated with advances in information and communication technology allowing for the filtering and processing of these data provide new tools for the production of economic intelligence.The research is focused on innovative aspects of economic intelligence process (models of analysis, activities, methods and informational tools and is providing practical guidelines for initiating this process. In this paper, we try: (a to contribute to a coherent view on economic intelligence process (approaches, stages, fields of application; b to describe the most important models of analysis related to this process; c to analyze the activities, methods and tools associated with each stage of an EI process.

  16. Reasoning methods in medical consultation systems: artificial intelligence approaches.

    Science.gov (United States)

    Shortliffe, E H

    1984-01-01

    It has been argued that the problem of medical diagnosis is fundamentally ill-structured, particularly during the early stages when the number of possible explanations for presenting complaints can be immense. This paper discusses the process of clinical hypothesis evocation, contrasts it with the structured decision making approaches used in traditional computer-based diagnostic systems, and briefly surveys the more open-ended reasoning methods that have been used in medical artificial intelligence (AI) programs. The additional complexity introduced when an advice system is designed to suggest management instead of (or in addition to) diagnosis is also emphasized. Example systems are discussed to illustrate the key concepts.

  17. SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    V. Panteleev Andrei

    2017-01-01

    Full Text Available An important stage in problem solving process for aerospace and aerostructures designing is calculating their main charac- teristics optimization. The results of the four constrained optimization problems related to the design of various technical systems: such as determining the best parameters of welded beams, pressure vessel, gear, spring are presented. The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. That is why using classical approach for extremum seeking is not efficient. Here comes the necessity of using such methods of optimization that allow to find a near optimal solution in acceptable amount of time with the minimum waste of computer power. Such methods include the methods of Swarm Intelligence: spiral dy- namics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. The Swarm Intelligence methods are designed in such a way that a swarm consisting of agents carries out the search for extremum. In search for the point of extremum, the parti- cles exchange information and consider their experience as well as the experience of population leader and the neighbors in some area. To solve the listed problems there has been designed a program complex, which efficiency is illustrated by the solutions of four applied problems. Each of the considered applied optimization problems is solved with all the three chosen methods. The ob- tained numerical results can be compared with the ones found in a swarm with a particle method. The author gives recommenda- tions on how to choose methods parameters and penalty function value, which consider inequality constraints.

  18. AVID Students' Perceptions of Intelligence: A Mixed Methods Study

    Science.gov (United States)

    Becker, John Darrell

    2012-01-01

    Students' perceptions of intelligence have been shown to have an effect on learning. Students who see intelligence as something that can be developed, those with a growth mindset, often experience academic success, while those who perceive intelligence to be a fixed entity are typically less likely to take on challenging learning experiences and…

  19. Estimation of mechanical properties of nanomaterials using artificial intelligence methods

    Science.gov (United States)

    Vijayaraghavan, V.; Garg, A.; Wong, C. H.; Tai, K.

    2014-09-01

    Computational modeling tools such as molecular dynamics (MD), ab initio, finite element modeling or continuum mechanics models have been extensively applied to study the properties of carbon nanotubes (CNTs) based on given input variables such as temperature, geometry and defects. Artificial intelligence techniques can be used to further complement the application of numerical methods in characterizing the properties of CNTs. In this paper, we have introduced the application of multi-gene genetic programming (MGGP) and support vector regression to formulate the mathematical relationship between the compressive strength of CNTs and input variables such as temperature and diameter. The predictions of compressive strength of CNTs made by these models are compared to those generated using MD simulations. The results indicate that MGGP method can be deployed as a powerful method for predicting the compressive strength of the carbon nanotubes.

  20. Artificial intelligence and immediacy: designing health communication to personally engage consumers and providers.

    Science.gov (United States)

    Kreps, Gary L; Neuhauser, Linda

    2013-08-01

    We describe how ehealth communication programs can be improved by using artificial intelligence (AI) to increase immediacy. We analyzed major deficiencies in ehealth communication programs, illustrating how programs often fail to fully engage audiences and can even have negative consequences by undermining the effective delivery of information intended to guide health decision-making and influence adoption of health-promoting behaviors. We examined the use of AI in ehealth practices to promote immediacy and provided examples from the ChronologyMD project. Strategic use of AI is shown to help enhance immediacy in ehealth programs by making health communication more engaging, relevant, exciting, and actionable. AI can enhance the "immediacy" of ehealth by humanizing health promotion efforts, promoting physical and emotional closeness, increasing authenticity and enthusiasm in health promotion efforts, supporting personal involvement in communication interactions, increasing exposure to relevant messages, reducing demands on healthcare staff, improving program efficiency, and minimizing costs. User-centered AI approaches, such as the use of personally involving verbal and nonverbal cues, natural language translation, virtual coaches, and comfortable human-computer interfaces can promote active information processing and adoption of new ideas. Immediacy can improve information access, trust, sharing, motivation, and behavior changes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  1. Advances in intelligent diagnosis methods for pulmonary ground-glass opacity nodules.

    Science.gov (United States)

    Yang, Jing; Wang, Hailin; Geng, Chen; Dai, Yakang; Ji, Jiansong

    2018-02-07

    Pulmonary nodule is one of the important lesions of lung cancer, mainly divided into two categories of solid nodules and ground glass nodules. The improvement of diagnosis of lung cancer has significant clinical significance, which could be realized by machine learning techniques. At present, there have been a lot of researches focusing on solid nodules. But the research on ground glass nodules started late, and lacked research results. This paper summarizes the research progress of the method of intelligent diagnosis for pulmonary nodules since 2014. It is described in details from four aspects: nodular signs, data analysis methods, prediction models and system evaluation. This paper aims to provide the research material for researchers of the clinical diagnosis and intelligent analysis of lung cancer, and further improve the precision of pulmonary ground glass nodule diagnosis.

  2. Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers

    Directory of Open Access Journals (Sweden)

    Bogdan-Andrei IONESCU

    2014-09-01

    Full Text Available The aim of this paper is to synthesize the concepts behind Business Intelligence, by studying the solutions available on the market provided by the main players. We will present the software solutions already provided by them emphasizing the main advantages and benefits of each of them, but also as a comparative analysis, designed to reveal the area in which each provider is more remarkable than the others.

  3. Using a Combined Platform of Swarm Intelligence Algorithms and GIS to Provide Land Suitability Maps for Locating Cardiac Rehabilitation Defibrillators

    Science.gov (United States)

    KAFFASH-CHARANDABI, Neda; SADEGHI-NIARAKI, Abolghasem; PARK, Dong-Kyun

    2015-01-01

    Background: Cardiac arrest is a condition in which the heart is completely stopped and is not pumping any blood. Although most cardiac arrest cases are reported from homes or hospitals, about 20% occur in public areas. Therefore, these areas need to be investigated in terms of cardiac arrest incidence so that places of high incidence can be identified and cardiac rehabilitation defibrillators installed there. Methods: In order to investigate a study area in Petersburg, Pennsylvania State, and to determine appropriate places for installing defibrillators with 5-year period data, swarm intelligence algorithms were used. Moreover, the location of the defibrillators was determined based on the following five evaluation criteria: land use, altitude of the area, economic conditions, distance from hospitals and approximate areas of reported cases of cardiac arrest for public places that were created in geospatial information system (GIS). Results: The A-P HADEL algorithm results were more precise about 27.36%. The validation results indicated a wider coverage of real values and the verification results confirmed the faster and more exact optimization of the cost function in the PSO method. Conclusion: The study findings emphasize the necessity of applying optimal optimization methods along with GIS and precise selection of criteria in the selection of optimal locations for installing medical facilities because the selected algorithm and criteria dramatically affect the final responses. Meanwhile, providing land suitability maps for installing facilities across hot and risky spots has the potential to save many lives. PMID:26587471

  4. Application of Evolutionary Mechanisms of Enhancers for Development Effective Artificial Intelligence Systems for Providing Data Security

    Directory of Open Access Journals (Sweden)

    M. L. Garanina

    2010-06-01

    Full Text Available This article describes the base approaches of the methods of evolutionary mechanisms (special type of genes — enhancers for parameterizations of AI systems genotype. This method can help in increasing adaptability of AI systems for providing data security.

  5. Cyclotron operating mode determination based on intelligent methods

    International Nuclear Information System (INIS)

    Ouda, M.M.E.M.

    2011-01-01

    Particle accelerators are generators that produce beams of charged particles with energies depending on the accelerator type. The MGC-20 cyclotron is a cyclic particle accelerator used for accelerating protons, deuterons, alpha particles, and helium-3 to different energies. Main applications are isotopes production, nuclear reactions studies, and mass spectroscopy studies and other industrial applications. The cyclotron is a complicated machine depends on using a strong magnetic field and high frequency-high voltage electric field together to accelerate and bend charged particles inside the accelerating chamber. It consists of the following main parts, the radio frequency system, the main magnet with the auxiliary concentric and harmonic coils, the electrostatic deflector, and the ion source, the beam transport system, and high precision and high stability DC power supplies.To accelerate a particle to certain energy, one has to adjust the cyclotron operating parameters to be suitable to accelerate this particle to that energy. If the cyclotron operating parameters together are adjusted to accelerate a charged particle to certain energy, then these parameters together are named the operating mode to accelerate this particle to that energy. For example the operating mode to accelerate protons to 18 MeV is named the (18 MeV protons operating mode). The operating mode includes many parameters that must be adjusted together to be successful to accelerate, extract, focus, steer a particle from the ion source to the experiment. Due to the big number of parameters in the operating modes, 19 parameters have been selected in this thesis to be used in an intelligent system based on feed forward back propagation neural network to determine the parameters for new operating modes. The new intelligent system depends on the available information about the currently used operating modes.The classic way to determine a new operating mode was depending on trial and error method to

  6. Noosphere: Does the Internet Provide an Evolutionary Leap to a Higher Level of Collective Intelligence?

    Directory of Open Access Journals (Sweden)

    Tatjana Milivojević

    2015-09-01

    Full Text Available The neologism noosphere signifies global human consciousness. According to T. de Chardin, it is the third stage in the development of the earth, after the geosphere and the biosphere. As well as the emergence of life has fundamentally changed the geosphere, the emergence of human consciousness has fundamentally changed the biosphere. De Chardin envisioned the “planetarization” of mankind, which is equivalent to the current globalization by information technology. From an anthropological point of view, internet is not a technology or media as others: it has the potential to revolutionize the current civilizational paradigm. With the advent of the internet the idea of the noosphere has been reactualized and related to the concept of collective intelligence. The article questions the hypothesis of an evolutionary leap in a greater collective intelligence or higher level of collective consciousness presenting pros and cons.

  7. Space Environment Modelling with the Use of Artificial Intelligence Methods

    Science.gov (United States)

    Lundstedt, H.; Wintoft, P.; Wu, J.-G.; Gleisner, H.; Dovheden, V.

    1996-12-01

    Space based technological systems are affected by the space weather in many ways. Several severe failures of satellites have been reported at times of space storms. Our society also increasingly depends on satellites for communication, navigation, exploration, and research. Predictions of the conditions in the satellite environment have therefore become very important. We will here present predictions made with the use of artificial intelligence (AI) techniques, such as artificial neural networks (ANN) and hybrids of AT methods. We are developing a space weather model based on intelligence hybrid systems (IHS). The model consists of different forecast modules, each module predicts the space weather on a specific time-scale. The time-scales range from minutes to months with the fundamental time-scale of 1-5 minutes, 1-3 hours, 1-3 days, and 27 days. Solar and solar wind data are used as input data. From solar magnetic field measurements, either made on the ground at Wilcox Solar Observatory (WSO) at Stanford, or made from space by the satellite SOHO, solar wind parameters can be predicted and modelled with ANN and MHD models. Magnetograms from WSO are available on a daily basis. However, from SOHO magnetograms will be available every 90 minutes. SOHO magnetograms as input to ANNs will therefore make it possible to even predict solar transient events. Geomagnetic storm activity can today be predicted with very high accuracy by means of ANN methods using solar wind input data. However, at present real-time solar wind data are only available during part of the day from the satellite WIND. With the launch of ACE in 1997, solar wind data will on the other hand be available during 24 hours per day. The conditions of the satellite environment are not only disturbed at times of geomagnetic storms but also at times of intense solar radiation and highly energetic particles. These events are associated with increased solar activity. Predictions of these events are therefore

  8. Intelligent Continuous Double Auction method For Service Allocation in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Nima Farajian

    2013-10-01

    Full Text Available Market-oriented approach is an effective method for resource management because of its regulation of supply and demand and is suitable for cloud environment where the computing resources, either software or hardware, are virtualized and allocated as services from providers to users. In this paper a continuous double auction method for efficient cloud service allocation is presented in which i enables consumers to order various resources (services for workflows and coallocation, ii consumers and providers make bid and request prices based on deadline and workload time and in addition providers can tradeoff between utilization time and price of bids, iii auctioneers can intelligently find optimum matching by sharing and merging resources which result more trades. Experimental results show that proposed method is efficient in terms of successful allocation rate and resource utilization.

  9. An Integral Model to Provide Reactive and Proactive Services in an Academic CSIRT Based on Business Intelligence

    OpenAIRE

    Walter Fuertes; Francisco Reyes; Paúl Valladares; Freddy Tapia; Theofilos Toulkeridis; Ernesto Pérez

    2017-01-01

    Cyber-attacks have increased in severity and complexity. That requires, that the CERT/CSIRT research and develops new security tools. Therefore, our study focuses on the design of an integral model based on Business Intelligence (BI), which provides reactive and proactive services in a CSIRT, in order to alert and reduce any suspicious or malicious activity on information systems and data networks. To achieve this purpose, a solution has been assembled, that generates information stores, bein...

  10. Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.

    Science.gov (United States)

    Elkin, Peter L; Schlegel, Daniel R; Anderson, Michael; Komm, Jordan; Ficheur, Gregoire; Bisson, Leslie

    2018-04-01

    Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with self-diagnosis of knee problems and to thereby facilitate referral to the right orthopedic subspecialist. They had two independent sports medicine physicians review 469 cases. A board-certified orthopedic sports medicine practitioner, L.B., reviewed any disagreements until a gold standard diagnosis was reached. For each case, the patients entered 126 potential answers to 26 questions into a Web interface. These were modeled by an expert sports medicine physician and the answers were reviewed by L.B. For each finding, the clinician specified the sensitivity (term frequency) and both specificity (Sp) and the heuristic evoking strength (ES). Heuristics are methods of reasoning with only partial evidence. An expert system was constructed that reflected the posttest odds of disease-ranked list for each case. We compare the accuracy of using Sp to that of using ES (original model, p  < 0.0008; term importance * disease importance [DItimesTI] model, p  < 0.0001: Wilcoxon ranked sum test). For patient referral assignment, Sp in the DItimesTI model was superior to the use of ES. By the fifth diagnosis, the advantage was lost and so there is no difference between the techniques when serving as a reminder system. Schattauer GmbH Stuttgart.

  11. Using artificial intelligence methods to design new conducting polymers

    Directory of Open Access Journals (Sweden)

    Ronaldo Giro

    2003-12-01

    Full Text Available In the last years the possibility of creating new conducting polymers exploring the concept of copolymerization (different structural monomeric units has attracted much attention from experimental and theoretical points of view. Due to the rich carbon reactivity an almost infinite number of new structures is possible and the procedure of trial and error has been the rule. In this work we have used a methodology able of generating new structures with pre-specified properties. It combines the use of negative factor counting (NFC technique with artificial intelligence methods (genetic algorithms - GAs. We present the results for a case study for poly(phenylenesulfide phenyleneamine (PPSA, a copolymer formed by combination of homopolymers: polyaniline (PANI and polyphenylenesulfide (PPS. The methodology was successfully applied to the problem of obtaining binary up to quinternary disordered polymeric alloys with a pre-specific gap value or exhibiting metallic properties. It is completely general and can be in principle adapted to the design of new classes of materials with pre-specified properties.

  12. A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

    Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

  13. Operation Iraqi Freedom 04 - 06: Opportunities to Apply Quantitative Methods to Intelligence Analysis

    National Research Council Canada - National Science Library

    Hansen, Eric C

    2005-01-01

    The purpose of this presentation is to illustrate the need for a quantitative analytical capability within organizations and staffs that provide intelligence analysis to Army, Joint, and Coalition Force headquarters...

  14. An Intelligent Method of Product Scheme Design Based on Product Gene

    Directory of Open Access Journals (Sweden)

    Qing Song Ai

    2013-01-01

    Full Text Available Nowadays, in order to have some featured products, many customers tend to buy customized products instead of buying common ones in supermarket. The manufacturing enterprises, with the purpose of improving their competitiveness, are focusing on providing customized products with high quality and low cost as well. At present, how to produce customized products rapidly and cheaply has been the key challenge to manufacturing enterprises. In this paper, an intelligent modeling approach applied to supporting the modeling of customized products is proposed, which may improve the efficiency during the product design process. Specifically, the product gene (PG method, which is an analogy of biological evolution in engineering area, is employed to model products in a new way. Based on product gene, we focus on the intelligent modeling method to generate product schemes rapidly and automatically. The process of our research includes three steps: (1 develop a product gene model for customized products; (2 find the obtainment and storage method for product gene; and (3 propose a specific genetic algorithm used for calculating the solution of customized product and generating new product schemes. Finally, a case study is applied to test the usefulness of our study.

  15. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  16. Risk assessment for pipelines with active defects based on artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Anghel, Calin I. [Department of Chemical Engineering, Faculty of Chemistry and Chemical Engineering, University ' Babes-Bolyai' , Cluj-Napoca (Romania)], E-mail: canghel@chem.ubbcluj.ro

    2009-07-15

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  17. Risk assessment for pipelines with active defects based on artificial intelligence methods

    International Nuclear Information System (INIS)

    Anghel, Calin I.

    2009-01-01

    The paper provides another insight into the pipeline risk assessment for in-service pressure piping containing defects. Beside of the traditional analytical approximation methods or sampling-based methods safety index and failure probability of pressure piping containing defects will be obtained based on a novel type of support vector machine developed in a minimax manner. The safety index or failure probability is carried out based on a binary classification approach. The procedure named classification reliability procedure, involving a link between artificial intelligence and reliability methods was developed as a user-friendly computer program in MATLAB language. To reveal the capacity of the proposed procedure two comparative numerical examples replicating a previous related work and predicting the failure probabilities of pressured pipeline with defects were presented.

  18. Intelligent Learning System using cognitive science theory and artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Cristensen, D.L.

    1986-01-01

    This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.

  19. Intelligent methods for the process parameter determination of plastic injection molding

    Science.gov (United States)

    Gao, Huang; Zhang, Yun; Zhou, Xundao; Li, Dequn

    2018-03-01

    Injection molding is one of the most widely used material processing methods in producing plastic products with complex geometries and high precision. The determination of process parameters is important in obtaining qualified products and maintaining product quality. This article reviews the recent studies and developments of the intelligent methods applied in the process parameter determination of injection molding. These intelligent methods are classified into three categories: Case-based reasoning methods, expert system- based methods, and data fitting and optimization methods. A framework of process parameter determination is proposed after comprehensive discussions. Finally, the conclusions and future research topics are discussed.

  20. Classical methods for interpreting objective function minimization as intelligent inference

    Energy Technology Data Exchange (ETDEWEB)

    Golden, R.M. [Univ. of Texas, Dallas, TX (United States)

    1996-12-31

    Most recognition algorithms and neural networks can be formally viewed as seeking a minimum value of an appropriate objective function during either classification or learning phases. The goal of this paper is to argue that in order to show a recognition algorithm is making intelligent inferences, it is not sufficient to show that the recognition algorithm is computing (or trying to compute) the global minimum of some objective function. One must explicitly define a {open_quotes}relational system{close_quotes} for the recognition algorithm or neural network which identifies the: (i) sample space, (ii) the relevant sigmafield of events generated by the sample space, and (iii) the {open_quotes}relation{close_quotes} for that relational system. Only when such a {open_quotes}relational system{close_quotes} is properly defined, is it possible to formally establish the sense in which computing the global minimum of an objective function is an intelligent, inference.

  1. Research on intelligent machine self-perception method based on LSTM

    Science.gov (United States)

    Wang, Qiang; Cheng, Tao

    2018-05-01

    In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.

  2. Advances in intelligent process-aware information systems concepts, methods, and technologies

    CERN Document Server

    Oberhauser, Roy; Reichert, Manfred

    2017-01-01

    This book provides a state-of-the-art perspective on intelligent process-aware information systems and presents chapters on specific facets and approaches applicable to such systems. Further, it highlights novel advances and developments in various aspects of intelligent process-aware information systems and business process management systems. Intelligence capabilities are increasingly being integrated into or created in many of today’s software products and services. Process-aware information systems provide critical computing infrastructure to support the various processes involved in the creation and delivery of business products and services. Yet the integration of intelligence capabilities into process-aware information systems is a non-trivial yet necessary evolution of these complex systems. The book’s individual chapters address adaptive process management, case management processes, autonomically-capable processes, process-oriented information logistics, process recommendations, reasoning over ...

  3. Prediction of 5-year overall survival in cervical cancer patients treated with radical hysterectomy using computational intelligence methods.

    Science.gov (United States)

    Obrzut, Bogdan; Kusy, Maciej; Semczuk, Andrzej; Obrzut, Marzanna; Kluska, Jacek

    2017-12-12

    Computational intelligence methods, including non-linear classification algorithms, can be used in medical research and practice as a decision making tool. This study aimed to evaluate the usefulness of artificial intelligence models for 5-year overall survival prediction in patients with cervical cancer treated by radical hysterectomy. The data set was collected from 102 patients with cervical cancer FIGO stage IA2-IIB, that underwent primary surgical treatment. Twenty-three demographic, tumor-related parameters and selected perioperative data of each patient were collected. The simulations involved six computational intelligence methods: the probabilistic neural network (PNN), multilayer perceptron network, gene expression programming classifier, support vector machines algorithm, radial basis function neural network and k-Means algorithm. The prediction ability of the models was determined based on the accuracy, sensitivity, specificity, as well as the area under the receiver operating characteristic curve. The results of the computational intelligence methods were compared with the results of linear regression analysis as a reference model. The best results were obtained by the PNN model. This neural network provided very high prediction ability with an accuracy of 0.892 and sensitivity of 0.975. The area under the receiver operating characteristics curve of PNN was also high, 0.818. The outcomes obtained by other classifiers were markedly worse. The PNN model is an effective tool for predicting 5-year overall survival in cervical cancer patients treated with radical hysterectomy.

  4. Intelligence diagnosis method for roller bearings using features of AE signal

    International Nuclear Information System (INIS)

    Pan, J; Wang, H Q; Wang, F; Yang, J F; Liu, W B

    2012-01-01

    Rolling bearings are important components in rotating machines, which are wildly used in industrial production. The fault diagnosis technology plays a very important role for quality and life of machines. Based on symptom parameters of acoustic emission (AE) signals, this paper presents an intelligent diagnosis method for roller bearings using the principal component analysis, rough sets, and BP neural network to detect faults and distinguish fault types. The principal component analysis and the rough sets algorithm are used to reduce details of time-domain symptom parameters for training the BP neural network. The BP neural network, which is used for condition diagnosis of roller bearings, can obtain good convergence using the symptom parameters acquired by the principal component analysis and the rough sets during learning, and automatically distinguish fault types during diagnosing. Practical examples are provided to verify the efficiency of the proposed method.

  5. Trends in ambient intelligent systems the role of computational intelligence

    CERN Document Server

    Khan, Mohammad; Abraham, Ajith

    2016-01-01

    This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

  6. Intelligent Knowledge Recommendation Methods for R&D Knowledge Portals

    Institute of Scientific and Technical Information of China (English)

    KIM Jongwoo; LEE Hongjoo; PARK Sungjoo

    2004-01-01

    The personalization in knowledge portals and knowledge management systems is mainly performed based on users' explicitly specified categories and keywords. The explicit specification approach requires users' participation to start personalization services, and has limitation to adapt changes of users' preference. This paper suggests two implicit personalization approaches: automatic user category assignment method and automatic keyword profile generation method. The performances of the implicit personalization approaches are compared with traditional personalization approach using an Internet news site experiment. The result of the experiment shows that the suggested personalization approaches provide sufficient recommendation effectiveness with lessening users'unwanted involvement in personalization process.

  7. Methods for providing intermediates in the synthesis of atorvastatin.

    NARCIS (Netherlands)

    Dömling, Alexander Stephan Siegfried

    2016-01-01

    The invention relates to the field of medicinal chemistry, In particular, it relates to methods for providing intermediates in the synthesis of Atorvastatin, a competitive inhibitor of HMG-Co A reductase. Provided is a process for providing a compound having a Formula (I) or a pharmaceutically

  8. Sequential mediating effects of provided and received social support on trait emotional intelligence and subjective happiness: A longitudinal examination in Hong Kong Chinese university students.

    Science.gov (United States)

    Ye, Jiawen; Yeung, Dannii Y; Liu, Elaine S C; Rochelle, Tina L

    2018-04-03

    Past research has often focused on the effects of emotional intelligence and received social support on subjective well-being yet paid limited attention to the effects of provided social support. This study adopted a longitudinal design to examine the sequential mediating effects of provided and received social support on the relationship between trait emotional intelligence and subjective happiness. A total of 214 Hong Kong Chinese undergraduates were asked to complete two assessments with a 6-month interval in between. The results of the sequential mediation analysis indicated that the trait emotional intelligence measured in Time 1 indirectly influenced the level of subjective happiness in Time 2 through a sequential pathway of social support provided for others in Time 1 and social support received from others in Time 2. These findings highlight the importance of trait emotional intelligence and the reciprocal exchanges of social support in the subjective well-being of university students. © 2018 International Union of Psychological Science.

  9. Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

    Science.gov (United States)

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2012-01-01

    The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

  10. Comparison of two solution ways of district heating control: Using analysis methods, using artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Balate, J.; Sysala, T. [Technical Univ., Zlin (Czech Republic). Dept. of Automation and Control Technology

    1997-12-31

    The District Heating Systems - DHS (Centralized Heat Supply Systems - CHSS) are being developed in large cities in accordance with their growth. The systems are formed by enlarging networks of heat distribution to consumers and at the same time they interconnect the heat sources gradually built. The heat is distributed to the consumers through the circular networks, that are supplied by several cooperating heat sources, that means by power and heating plants and heating plants. The complicated process of heat production technology and supply requires the system approach when solving the concept of automatized control. The paper deals with comparison of the solution way using the analysis methods and using the artificial intelligence methods. (orig.)

  11. A comprehensive review of the use of computational intelligence methods in mineral exploration

    Directory of Open Access Journals (Sweden)

    Habibollah Bazdar

    2017-11-01

    Full Text Available Introduction Mineral exploration is a process by which it is decided whether or not continuing explorations at the end of each stage t will be cost-effective or not. This decision is dependent upon many factors including technical factors, economic, social and other related factors. All new methods used in mineral exploration are meant to make this decision making more simplified. In recent years, advanced computational intelligence methods for modeling along with many other disciplines of science, including the science of mineral exploration have been used. Although the results of the application of these methods show a good performance, it is essential to determine the mineral potential in terms of geology, mineralogy, petrology and other factors for a final decision. The purpose of this paper is to provide a comprehensive set of mineral exploration research and different applications of computational intelligence techniques in this respect during the last decades. Materials and methods Artificial neural network and its application in mineral exploration Artificial neural network (ANN is a series of communications between the units or nodes that try to function like neurons of the human brain (Jorjani et al., 2008. The network processing capability of communication between the units and the weights connection originates or comes from learning or are predetermined (Monjezi and Dehghani, 2008. The ANN method has been applied in different branches of mining exploration in the last decades (Brown et al., 2000; Leite and de Souza Filho, 2009; Porwal et al., 2003. Support vector machines (SVM and its application in mineral exploration SVM uses a set of examples with known class of information to build a linear hyperplane separating samples of different classes. This initial dataset is known as a training set and every sample within it is characterized by features upon which the classification is based (Smirnoff et al., 2008. The SVM classifier is a

  12. An Intelligent Virtual Human System For Providing Healthcare Information And Support

    Science.gov (United States)

    2011-01-01

    healthcare system, and also to other SMs and Veterans by way of a variety of social networking tools (e.g., 2nd Life, Facebook, etc.). The user can progress... CyberPsychology and Behavior 8, 3 (2005), 187-211. [2] T. Parsons & A.A. Rizzo, Affective Outcomes of Virtual Reality Exposure Therapy for Anxiety...VH System for Providing Healthcare Information and Support508 [4] G. Riva, Virtual Reality in Psychotherapy: Review, CyberPsychology and Behavior 8

  13. Effectiveness of Agile Implementation Methods in Business Intelligence Projects from an End-user Perspective

    Directory of Open Access Journals (Sweden)

    Anna Maria Misiak

    2016-06-01

    Full Text Available The global Business Intelligence (BI market grew by 10% in 2013 according to the Gartner Report. Today organizations require better use of data and analytics to support their business decisions. Internet power and business trend changes have provided a broad term for data analytics – Big Data. To be able to handle it and leverage a value of having access to Big Data, organizations have no other choice than to get proper systems implemented and working. However traditional methods are not efficient for changing business needs. The long time between project start and go-live causes a gap between initial solution blueprint and actual user requirements in the end of the project. This article presents the latest market trends in BI systems implementation by comparing Agile with traditional methods. It presents a case study provided in a large telecommunications company (20K employees and the results of a pilot research provided in the three large companies: telecommunications, digital, and insurance. Both studies prove that Agile methods might be more effective in BI projects from an end-user perspective and give first results and added value in a much shorter time compared to a traditional approach.

  14. Methods and models for quantative assessment of speech intelligibility in cross-language communication

    NARCIS (Netherlands)

    Wijngaarden, S.J. van; Steeneken, H.J.M.; Houtgast, T.

    2001-01-01

    To deal with the effects of nonnative speech communication on speech intelligibility, one must know the magnitude of these effects. To measure this magnitude, suitable test methods must be available. Many of the methods used in cross-language speech communication research are not very suitable for

  15. Prototype of assignment intelligent adaptive of service providers inside of ESB with data mining

    Directory of Open Access Journals (Sweden)

    Andrés Paolo Castaño

    2009-12-01

    Full Text Available The SOA philosophy can address new business challenges, become more competitive and provide integrated information systems. In addition, technologies such as BPM, BAM and Web Services are essential complements to SOA. This work aims to use several of these technologies integrated into a single application that will allow in a phase of a previously defined business process, to perform the analysis of input suppliers to the company through the generation of a decision tree using embedded code of the free tool Weka for data mining in order to feedback the business process and evaluate these results to improve the process. For the realization of this prototype we worked with the jBPM suite, the API from Weka to get the J48 algorithm, the postgresql database, the format for data exchange JSON and the web service

  16. Artificial Intelligence in Civil Engineering

    OpenAIRE

    Lu, Pengzhen; Chen, Shengyong; Zheng, Yujun

    2012-01-01

    Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applicati...

  17. Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.

    Science.gov (United States)

    Li, Ke; Chen, Peng

    2011-01-01

    Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks.

  18. An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism.

    Science.gov (United States)

    Li, Fengmei; Wei, Yaoguang; Chen, Yingyi; Li, Daoliang; Zhang, Xu

    2015-12-09

    Dissolved oxygen (DO) is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

  19. An Intelligent Optical Dissolved Oxygen Measurement Method Based on a Fluorescent Quenching Mechanism

    Directory of Open Access Journals (Sweden)

    Fengmei Li

    2015-12-01

    Full Text Available Dissolved oxygen (DO is a key factor that influences the healthy growth of fishes in aquaculture. The DO content changes with the aquatic environment and should therefore be monitored online. However, traditional measurement methods, such as iodometry and other chemical analysis methods, are not suitable for online monitoring. The Clark method is not stable enough for extended periods of monitoring. To solve these problems, this paper proposes an intelligent DO measurement method based on the fluorescence quenching mechanism. The measurement system is composed of fluorescent quenching detection, signal conditioning, intelligent processing, and power supply modules. The optical probe adopts the fluorescent quenching mechanism to detect the DO content and solves the problem, whereas traditional chemical methods are easily influenced by the environment. The optical probe contains a thermistor and dual excitation sources to isolate visible parasitic light and execute a compensation strategy. The intelligent processing module adopts the IEEE 1451.2 standard and realizes intelligent compensation. Experimental results show that the optical measurement method is stable, accurate, and suitable for online DO monitoring in aquaculture applications.

  20. Design of Intelligent Hydraulic Excavator Control System Based on PID Method

    Science.gov (United States)

    Zhang, Jun; Jiao, Shengjie; Liao, Xiaoming; Yin, Penglong; Wang, Yulin; Si, Kuimao; Zhang, Yi; Gu, Hairong

    Most of the domestic designed hydraulic excavators adopt the constant power design method and set 85%~90% of engine power as the hydraulic system adoption power, it causes high energy loss due to mismatching of power between the engine and the pump. While the variation of the rotational speed of engine could sense the power shift of the load, it provides a new method to adjust the power matching between engine and pump through engine speed. Based on negative flux hydraulic system, an intelligent hydraulic excavator control system was designed based on rotational speed sensing method to improve energy efficiency. The control system was consisted of engine control module, pump power adjusted module, engine idle module and system fault diagnosis module. Special PLC with CAN bus was used to acquired the sensors and adjusts the pump absorption power according to load variation. Four energy saving control strategies with constant power method were employed to improve the fuel utilization. Three power modes (H, S and L mode) were designed to meet different working status; Auto idle function was employed to save energy through two work status detected pressure switches, 1300rpm was setting as the idle speed according to the engine consumption fuel curve. Transient overload function was designed for deep digging within short time without spending extra fuel. An increasing PID method was employed to realize power matching between engine and pump, the rotational speed's variation was taken as the PID algorithm's input; the current of proportional valve of variable displacement pump was the PID's output. The result indicated that the auto idle could decrease fuel consumption by 33.33% compared to work in maximum speed of H mode, the PID control method could take full use of maximum engine power at each power mode and keep the engine speed at stable range. Application of rotational speed sensing method provides a reliable method to improve the excavator's energy efficiency and

  1. The use of foresight methods in strategic raw materials intelligence - an international review

    Science.gov (United States)

    Konrat Martins, Marco Antonio; Bodo, Balazs; Falck, Eberhard

    2017-04-01

    Foresight methods are systematic attempts to look into the longer term future of science, society, economy and technology. There is a range of tools and techniques that can be used individually or combined, most commonly classified into qualitative, quantitative or semi-quantitative methods, that follow an exploratory or normative approach. These tools can help to identify the longer term visions, orienting policy formulation and decisions, triggering actions, among other objectives. There is an identified lack of European strategic foresight knowledge in the raw materials domain. Since the European Raw Materials Initiative was launched in 2008, the EU has been attempting to overcome challenges related to the future access of non-energy and non-agricultural raw materials. In this context, the ongoing H2020 project, MICA (Mineral Intelligence Capacity Analysis, Grant Agreement No. 689648), has been launched to answer to stakeholders needs by consolidating relevant data, determining relevant methods and tools, and investigating Raw Materials Intelligence options for European mineral policy development, all tailored to fit under the umbrella of a European Raw Materials Intelligence Capacity Platform (EU-RMICP). As part of the MICA activities, an assessment of best practices and benchmarks of international raw materials foresight case studies has been carried out in order to review how EU and non-EU countries have employed foresight. A pool of 30 case studies has been collected and reviewed internationally, one third of which were selected for detailed assessment. These were classified according to their background and goals, in function of methods employed, and to the purpose of each method in the study: a total of 12 different methods were identified in these studies. For longer time frames, qualitative predictive methods such as Scenario Development have been repeatedly observed for mineral raw materials foresight studies. Substantial variations were observed in

  2. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  3. Intelligent Evaluation Method of Tank Bottom Corrosion Status Based on Improved BP Artificial Neural Network

    Science.gov (United States)

    Qiu, Feng; Dai, Guang; Zhang, Ying

    According to the acoustic emission information and the appearance inspection information of tank bottom online testing, the external factors associated with tank bottom corrosion status are confirmed. Applying artificial neural network intelligent evaluation method, three tank bottom corrosion status evaluation models based on appearance inspection information, acoustic emission information, and online testing information are established. Comparing with the result of acoustic emission online testing through the evaluation of test sample, the accuracy of the evaluation model based on online testing information is 94 %. The evaluation model can evaluate tank bottom corrosion accurately and realize acoustic emission online testing intelligent evaluation of tank bottom.

  4. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    Reifman, J.

    1997-01-01

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  5. Selected business intelligence methods for decision-making support in a finance institution

    OpenAIRE

    Mezera, Filip; Křupka, Jiří

    2017-01-01

    This article deals with decision-making support methods’ implementation in a medium size financial company with international operations. The objective of this article is to show the abilities of these methods to precise decision-making of management. At the beginning of this article there is briefly described the existing situation in this business sector in Central Europe. After that part Business Intelligence methods are described as well as the reasons while these methods have been introd...

  6. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2012-01-01

    Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

  7. Modern architectures for intelligent systems: reusable ontologies and problem-solving methods.

    Science.gov (United States)

    Musen, M A

    1998-01-01

    When interest in intelligent systems for clinical medicine soared in the 1970s, workers in medical informatics became particularly attracted to rule-based systems. Although many successful rule-based applications were constructed, development and maintenance of large rule bases remained quite problematic. In the 1980s, an entire industry dedicated to the marketing of tools for creating rule-based systems rose and fell, as workers in medical informatics began to appreciate deeply why knowledge acquisition and maintenance for such systems are difficult problems. During this time period, investigators began to explore alternative programming abstractions that could be used to develop intelligent systems. The notions of "generic tasks" and of reusable problem-solving methods became extremely influential. By the 1990s, academic centers were experimenting with architectures for intelligent systems based on two classes of reusable components: (1) domain-independent problem-solving methods-standard algorithms for automating stereotypical tasks--and (2) domain ontologies that captured the essential concepts (and relationships among those concepts) in particular application areas. This paper will highlight how intelligent systems for diverse tasks can be efficiently automated using these kinds of building blocks. The creation of domain ontologies and problem-solving methods is the fundamental end product of basic research in medical informatics. Consequently, these concepts need more attention by our scientific community.

  8. Method for providing uranium with a protective copper coating

    Science.gov (United States)

    Waldrop, Forrest B.; Jones, Edward

    1981-01-01

    The present invention is directed to a method for providing uranium metal with a protective coating of copper. Uranium metal is subjected to a conventional cleaning operation wherein oxides and other surface contaminants are removed, followed by etching and pickling operations. The copper coating is provided by first electrodepositing a thin and relatively porous flash layer of copper on the uranium in a copper cyanide bath. The resulting copper-layered article is then heated in an air or inert atmosphere to volatilize and drive off the volatile material underlying the copper flash layer. After the heating step an adherent and essentially non-porous layer of copper is electro-deposited on the flash layer of copper to provide an adherent, multi-layer copper coating which is essentially impervious to corrosion by most gases.

  9. System and Method for Providing a Climate Data Persistence Service

    Science.gov (United States)

    Schnase, John L. (Inventor); Ripley, III, William David (Inventor); Duffy, Daniel Q. (Inventor); Thompson, John H. (Inventor); Strong, Savannah L. (Inventor); McInerney, Mark (Inventor); Sinno, Scott (Inventor); Tamkin, Glenn S. (Inventor); Nadeau, Denis (Inventor)

    2018-01-01

    A system, method and computer-readable storage devices for providing a climate data persistence service. A system configured to provide the service can include a climate data server that performs data and metadata storage and management functions for climate data objects, a compute-storage platform that provides the resources needed to support a climate data server, provisioning software that allows climate data server instances to be deployed as virtual climate data servers in a cloud computing environment, and a service interface, wherein persistence service capabilities are invoked by software applications running on a client device. The climate data objects can be in various formats, such as International Organization for Standards (ISO) Open Archival Information System (OAIS) Reference Model Submission Information Packages, Archive Information Packages, and Dissemination Information Packages. The climate data server can enable scalable, federated storage, management, discovery, and access, and can be tailored for particular use cases.

  10. Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment.

    Science.gov (United States)

    Dilsizian, Steven E; Siegel, Eliot L

    2014-01-01

    Although advances in information technology in the past decade have come in quantum leaps in nearly every aspect of our lives, they seem to be coming at a slower pace in the field of medicine. However, the implementation of electronic health records (EHR) in hospitals is increasing rapidly, accelerated by the meaningful use initiatives associated with the Center for Medicare & Medicaid Services EHR Incentive Programs. The transition to electronic medical records and availability of patient data has been associated with increases in the volume and complexity of patient information, as well as an increase in medical alerts, with resulting "alert fatigue" and increased expectations for rapid and accurate diagnosis and treatment. Unfortunately, these increased demands on health care providers create greater risk for diagnostic and therapeutic errors. In the near future, artificial intelligence (AI)/machine learning will likely assist physicians with differential diagnosis of disease, treatment options suggestions, and recommendations, and, in the case of medical imaging, with cues in image interpretation. Mining and advanced analysis of "big data" in health care provide the potential not only to perform "in silico" research but also to provide "real time" diagnostic and (potentially) therapeutic recommendations based on empirical data. "On demand" access to high-performance computing and large health care databases will support and sustain our ability to achieve personalized medicine. The IBM Jeopardy! Challenge, which pitted the best all-time human players against the Watson computer, captured the imagination of millions of people across the world and demonstrated the potential to apply AI approaches to a wide variety of subject matter, including medicine. The combination of AI, big data, and massively parallel computing offers the potential to create a revolutionary way of practicing evidence-based, personalized medicine.

  11. The Professionalization of Intelligence Cooperation

    DEFF Research Database (Denmark)

    Svendsen, Adam David Morgan

    "Providing an in-depth insight into the subject of intelligence cooperation (officially known as liason), this book explores the complexities of this process. Towards facilitating a general understanding of the professionalization of intelligence cooperation, Svendsen's analysis includes risk...... management and encourages the realisation of greater resilience. Svendsen discusses the controversial, mixed and uneven characterisations of the process of the professionalization of intelligence cooperation and argues for a degree of 'fashioning method out of mayhem' through greater operational...

  12. A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders

    Science.gov (United States)

    Shao, Haidong; Jiang, Hongkai; Lin, Ying; Li, Xingqiu

    2018-03-01

    Automatic and accurate identification of rolling bearings fault categories, especially for the fault severities and fault orientations, is still a major challenge in rotating machinery fault diagnosis. In this paper, a novel method called ensemble deep auto-encoders (EDAEs) is proposed for intelligent fault diagnosis of rolling bearings. Firstly, different activation functions are employed as the hidden functions to design a series of auto-encoders (AEs) with different characteristics. Secondly, EDAEs are constructed with various auto-encoders for unsupervised feature learning from the measured vibration signals. Finally, a combination strategy is designed to ensure accurate and stable diagnosis results. The proposed method is applied to analyze the experimental bearing vibration signals. The results confirm that the proposed method can get rid of the dependence on manual feature extraction and overcome the limitations of individual deep learning models, which is more effective than the existing intelligent diagnosis methods.

  13. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    OpenAIRE

    PAVLENKO, Vitaliy; PAVLENKO, Tetiana; MOROZOVA, Olga; KUZNETSOVA, Anna; VOROPAI, Olena

    2017-01-01

    The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have b...

  14. A Reasoning Method of Cyber-Attack Attribution Based on Threat Intelligence

    OpenAIRE

    Li Qiang; Yang Ze-Ming; Liu Bao-Xu; Jiang Zheng-Wei

    2016-01-01

    With the increasing complexity of cyberspace security, the cyber-attack attribution has become an important challenge of the security protection systems. The difficult points of cyber-attack attribution were forced on the problems of huge data handling and key data missing. According to this situation, this paper presented a reasoning method of cyber-attack attribution based on threat intelligence. The method utilizes the intrusion kill chain model and Bayesian network to build attack chain a...

  15. Residential building energy estimation method based on the application of artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, S.; Kajl, S.

    1999-07-01

    The energy requirements of a residential building five to twenty-five stories high can be measured using a newly proposed analytical method based on artificial intelligence. The method is fast and provides a wide range of results such as total energy consumption values, power surges, and heating or cooling consumption values. A series of database were created to take into account the particularities which influence the energy consumption of a building. In this study, DOE-2 software was created for use in 8 apartment models. A total of 27 neural networks were used, 3 for the estimation of energy consumption in the corridor, and 24 for inside the apartments. Three user interfaces were created to facilitate the estimation of energy consumption. These were named the Energy Estimation Assistance System (EEAS) interfaces and are only accessible using MATLAB software. The input parameters for EEAS are: climatic region, exterior wall resistance, roofing resistance, type of windows, infiltration, number of storeys, and corridor ventilation system operating schedule. By changing the parameters, the EEAS can determine annual heating, cooling and basic energy consumption levels for apartments and corridors. 2 tabs., 2 figs.

  16. Development of a method of continuous improvement of services using the Business Intelligence tools

    Directory of Open Access Journals (Sweden)

    Svetlana V. Kulikova

    2018-01-01

    Full Text Available The purpose of the study was to develop a method of continuous improvement of services using the Business Intelligence tools.Materials and methods: the materials are used on the concept of the Deming Cycle, methods and Business Intelligence technologies, Agile methodology and SCRUM.Results: the article considers the problem of continuous improvement of services and offers solutions using methods and technologies of Business Intelligence. In this case, the purpose of this technology is to solve and make the final decision regarding what needs to be improved in the current organization of services. In other words, Business Intelligence helps the product manager to see what is hidden from the “human eye” on the basis of received and processed data. Development of a method based on the concept of the Deming Cycle and Agile methodologies, and SCRUM.The article describes the main stages of development of method based on activity of the enterprise. It is necessary to fully build the Business Intelligence system in the enterprise to identify bottlenecks and justify the need for their elimination and, in general, for continuous improvement of the services. This process is represented in the notation of DFD. The article presents a scheme for the selection of suitable agile methodologies.The proposed concept of the solution of the stated objectives, including methods of identification of problems through Business Intelligence technology, development of the system for troubleshooting and analysis of results of the introduced changes. The technical description of the project is given.Conclusion: following the work of the authors there was formed the concept of the method for the continuous improvement of the services, using the Business Intelligence technology with the specifics of the enterprises, offering SaaS solutions. It was also found that when using this method, the recommended development methodology is SCRUM. The result of this scientific

  17. Method for Providing Semiconductors Having Self-Aligned Ion Implant

    Science.gov (United States)

    Neudeck, Philip G. (Inventor)

    2014-01-01

    A method is disclosed that provides a self-aligned nitrogen-implant particularly suited for a Junction Field Effect Transistor (JFET) semiconductor device preferably comprised of a silicon carbide (SiC). This self-aligned nitrogen-implant allows for the realization of durable and stable electrical functionality of high temperature transistors such as JFETs. The method implements the self-aligned nitrogen-implant having predetermined dimensions, at a particular step in the fabrication process, so that the SiC junction field effect transistors are capable of being electrically operating continuously at 500.degree. C. for over 10,000 hours in an air ambient with less than a 10% change in operational transistor parameters.

  18. Method for providing a low density high strength polyurethane foam

    Science.gov (United States)

    Whinnery, Jr., Leroy L.; Goods, Steven H.; Skala, Dawn M.; Henderson, Craig C.; Keifer, Patrick N.

    2013-06-18

    Disclosed is a method for making a polyurethane closed-cell foam material exhibiting a bulk density below 4 lbs/ft.sup.3 and high strength. The present embodiment uses the reaction product of a modified MDI and a sucrose/glycerine based polyether polyol resin wherein a small measured quantity of the polyol resin is "pre-reacted" with a larger quantity of the isocyanate in a defined ratio such that when the necessary remaining quantity of the polyol resin is added to the "pre-reacted" resin together with a tertiary amine catalyst and water as a blowing agent, the polymerization proceeds slowly enough to provide a stable foam body.

  19. A REVIEW OF VIBRATION MACHINE DIAGNOSTICS BY USING ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Grover Zurita

    2016-09-01

    Full Text Available In the industry, gears and rolling bearings failures are one of the foremost causes of breakdown in rotating machines, reducing availability time of the production and resulting in costly systems downtime. Therefore, there are growing demands for vibration condition based monitoring of gears and bearings, and any method in order to improve the effectiveness, reliability, and accuracy of the bearing faults diagnosis ought to be evaluated. In order to perform machine diagnosis efficiently, researchers have extensively investigated different advanced digital signal processing techniques and artificial intelligence methods to accurately extract fault characteristics from vibration signals. The main goal of this article is to present the state-of-the-art development in vibration analysis for machine diagnosis based on artificial intelligence methods.

  20. Intelligent screening of electrofusion-polyethylene joints based on a thermal NDT method

    Science.gov (United States)

    Doaei, Marjan; Tavallali, M. Sadegh

    2018-05-01

    The combinations of infrared thermal images and artificial intelligence methods have opened new avenues for pushing the boundaries of available testing methods. Hence, in the current study, a novel thermal non-destructive testing method for polyethylene electrofusion joints was combined with k-means clustering algorithms as an intelligent screening tool. The experiments focused on ovality of pipes in the coupler, as well as misalignment of pipes-couplers in 25 mm diameter joints. The temperature responses of each joint to an internal heat pulse were recorded by an IR thermal camera, and further processed to identify the faulty joints. The results represented clustering accuracy of 92%, as well as more than 90% abnormality detection capabilities.

  1. Soft computing in artificial intelligence

    CERN Document Server

    Matson, Eric

    2014-01-01

    This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

  2. Developing energy forecasting model using hybrid artificial intelligence method

    Institute of Scientific and Technical Information of China (English)

    Shahram Mollaiy-Berneti

    2015-01-01

    An important problem in demand planning for energy consumption is developing an accurate energy forecasting model. In fact, it is not possible to allocate the energy resources in an optimal manner without having accurate demand value. A new energy forecasting model was proposed based on the back-propagation (BP) type neural network and imperialist competitive algorithm. The proposed method offers the advantage of local search ability of BP technique and global search ability of imperialist competitive algorithm. Two types of empirical data regarding the energy demand (gross domestic product (GDP), population, import, export and energy demand) in Turkey from 1979 to 2005 and electricity demand (population, GDP, total revenue from exporting industrial products and electricity consumption) in Thailand from 1986 to 2010 were investigated to demonstrate the applicability and merits of the present method. The performance of the proposed model is found to be better than that of conventional back-propagation neural network with low mean absolute error.

  3. Integrating Symbolic and Statistical Methods for Testing Intelligent Systems Applications to Machine Learning and Computer Vision

    Energy Technology Data Exchange (ETDEWEB)

    Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL

    2016-01-01

    Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.

  4. Effects of Cooperative Learning Method Type Stad, Language Aptitude, and Intelligence on the Achievement English Hotel at Medan Tourism Academy

    Directory of Open Access Journals (Sweden)

    Abdul Kadir Ritonga

    2017-01-01

    Full Text Available STAD cooperative learning method which is considered effective in achieving the goal of learning the English language, especially for students majoring in Tourism Academy who are required to master English for Specific Purposes (ESP in accordance with their needs. This study uses factorial design 2x3x3 version of the non-equivalent control group design with ANOVA 3 Ways. The subjects were students MDK III / 5 A and B courses MDK III.5 Rooms Division department Hospitality Academy Year 2015/2016. The samples are saturated samples. Data were collected through a pretest, posttest, and instrument of Language Aptitude and Intelligence parametric statistics analyzed by parametric statistics with significance level of 0.05%. The results showed that: (1 there are differences between method STAD cooperative learning and expository on Hospitality English achievement, (2 there are differences between the students who have high language aptitude and low language aptitude on English achievement, (3 there are differences between students who have high language aptitude and medium on Hospitality English achievement, (4 there are differences between students who have the medium language aptitude and low language aptitude on Hospitality English achievement, (5 there are differences between students who have high intelligence and low intelligence\\ on Hospitality English achievement, (6 there are no differences between who have high intelligence and medium intelligence on Hospitality English achievement, (7 there are differences between students who have the medium intelligence and low intelligence on Hospitality English achievement, (8 there is no interaction between the learning method and language aptitude on Hospitality English achievement, (9 there is an interaction between the learning method and the intelligence on Hospitality English achievement, (10 there is no interaction between intelligence and language aptitude on Hospitality English achievement. (11

  5. An Integral Model to Provide Reactive and Proactive Services in an Academic CSIRT Based on Business Intelligence

    Directory of Open Access Journals (Sweden)

    Walter Fuertes

    2017-11-01

    Full Text Available Cyber-attacks have increased in severity and complexity. That requires, that the CERT/CSIRT research and develops new security tools. Therefore, our study focuses on the design of an integral model based on Business Intelligence (BI, which provides reactive and proactive services in a CSIRT, in order to alert and reduce any suspicious or malicious activity on information systems and data networks. To achieve this purpose, a solution has been assembled, that generates information stores, being compiled from a continuous network transmission of several internal and external sources of an organization. However, it contemplates a data warehouse, which is focused like a correlator of logs, being formed by the information of feeds with diverse formats. Furthermore, it analyzed attack detection and port scanning, obtained from sensors such as Snort and Passive Vulnerability Scanner, which are stored in a database, where the logs have been generated by the systems. With such inputs, we designed and implemented BI systems using the phases of the Ralph Kimball methodology, ETL and OLAP processes. In addition, a software application has been implemented using the SCRUM methodology, which allowed to link the obtained logs to the BI system for visualization in dynamic dashboards, with the purpose of generating early alerts and constructing complex queries using the user interface through objects structures. The results demonstrate, that this solution has generated early warnings based on the level of criticality and level of sensitivity of malware and vulnerabilities as well as monitoring efficiency, increasing the level of security of member institutions.

  6. Control and Driving Methods for LED Based Intelligent Light Sources

    DEFF Research Database (Denmark)

    Beczkowski, Szymon

    of the diode is controlled either by varying the magnitude of the current or by driving the LED with a pulsed current and regulate the width of the pulse. It has been shown previously, that these two methods yield different effects on diode's efficacy and colour point. A hybrid dimming strategy has been...... proposed where two variable quantities control the intensity of the diode. This increases the controllability of the diode giving new optimisation possibilities. It has been shown that it is possible to compensate for temperature drift of white diode's colour point using hybrid dimming strategy. Also...

  7. Artificial Intelligence Methods Applied to Parameter Detection of Atrial Fibrillation

    Science.gov (United States)

    Arotaritei, D.; Rotariu, C.

    2015-09-01

    In this paper we present a novel method to develop an atrial fibrillation (AF) based on statistical descriptors and hybrid neuro-fuzzy and crisp system. The inference of system produce rules of type if-then-else that care extracted to construct a binary decision system: normal of atrial fibrillation. We use TPR (Turning Point Ratio), SE (Shannon Entropy) and RMSSD (Root Mean Square of Successive Differences) along with a new descriptor, Teager- Kaiser energy, in order to improve the accuracy of detection. The descriptors are calculated over a sliding window that produce very large number of vectors (massive dataset) used by classifier. The length of window is a crisp descriptor meanwhile the rest of descriptors are interval-valued type. The parameters of hybrid system are adapted using Genetic Algorithm (GA) algorithm with fitness single objective target: highest values for sensibility and sensitivity. The rules are extracted and they are part of the decision system. The proposed method was tested using the Physionet MIT-BIH Atrial Fibrillation Database and the experimental results revealed a good accuracy of AF detection in terms of sensitivity and specificity (above 90%).

  8. Intelligent automation of high-performance liquid chromatography method development by means of a real-time knowledge-based approach.

    Science.gov (United States)

    I, Ting-Po; Smith, Randy; Guhan, Sam; Taksen, Ken; Vavra, Mark; Myers, Douglas; Hearn, Milton T W

    2002-09-27

    We describe the development, attributes and capabilities of a novel type of artificial intelligence system, called LabExpert, for automation of HPLC method development. Unlike other computerised method development systems, LabExpert operates in real-time, using an artificial intelligence system and design engine to provide experimental decision outcomes relevant to the optimisation of complex separations as well as the control of the instrumentation, column selection, mobile phase choice and other experimental parameters. LabExpert manages every input parameter to a HPLC data station and evaluates each output parameter of the HPLC data station in real-time as part of its decision process. Based on a combination of inherent and user-defined evaluation criteria, the artificial intelligence system programs use a reasoning process, applying chromatographic principles and acquired experimental observations to iteratively provide a regime for a priori development of an acceptable HPLC separation method. Because remote monitoring and control are also functions of LabExpert, the system allows full-time utilisation of analytical instrumentation and associated laboratory resources. Based on our experience with LabExpert with a wide range of analyte mixtures, this artificial intelligence system consistently identified in a similar or faster time-frame preferred sets of analytical conditions that are equal in resolution, efficiency and throughput to those empirically determined by highly experienced chromatographic scientists. An illustrative example, demonstrating the potential of LabExpert in the process of method development of drug substances, is provided.

  9. Aerial robot intelligent control method based on back-stepping

    Science.gov (United States)

    Zhou, Jian; Xue, Qian

    2018-05-01

    The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

  10. An intelligent detection method for high-field asymmetric waveform ion mobility spectrometry.

    Science.gov (United States)

    Li, Yue; Yu, Jianwen; Ruan, Zhiming; Chen, Chilai; Chen, Ran; Wang, Han; Liu, Youjiang; Wang, Xiaozhi; Li, Shan

    2018-04-01

    In conventional high-field asymmetric waveform ion mobility spectrometry signal acquisition, multi-cycle detection is time consuming and limits somewhat the technique's scope for rapid field detection. In this study, a novel intelligent detection approach has been developed in which a threshold was set on the relative error of α parameters, which can eliminate unnecessary time spent on detection. In this method, two full-spectrum scans were made in advance to obtain the estimated compensation voltage at different dispersion voltages, resulting in a narrowing down of the whole scan area to just the peak area(s) of interest. This intelligent detection method can reduce the detection time to 5-10% of that of the original full-spectrum scan in a single cycle.

  11. A Lateral Control Method of Intelligent Vehicle Based on Fuzzy Neural Network

    Directory of Open Access Journals (Sweden)

    Linhui Li

    2015-01-01

    Full Text Available A lateral control method is proposed for intelligent vehicle to track the desired trajectory. Firstly, a lateral control model is established based on the visual preview and dynamic characteristics of intelligent vehicle. Then, the lateral error and orientation error are melded into an integrated error. Considering the system parameter perturbation and the external interference, a sliding model control is introduced in this paper. In order to design a sliding surface, the integrated error is chosen as the parameter of the sliding mode switching function. The sliding mode switching function and its derivative are selected as two inputs of the controller, and the front wheel angle is selected as the output. Next, a fuzzy neural network is established, and the self-learning functions of neural network is utilized to construct the fuzzy rules. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed method.

  12. Condition Monitoring Using Computational Intelligence Methods Applications in Mechanical and Electrical Systems

    CERN Document Server

    Marwala, Tshilidzi

    2012-01-01

    Condition monitoring uses the observed operating characteristics of a machine or structure to diagnose trends in the signal being monitored and to predict the need for maintenance before a breakdown occurs. This reduces the risk, inherent in a fixed maintenance schedule, of performing maintenance needlessly early or of having a machine fail before maintenance is due either of which can be expensive with the latter also posing a risk of serious accident especially in systems like aeroengines in which a catastrophic failure would put lives at risk. The technique also measures responses from the whole of the system under observation so it can detect the effects of faults which might be hidden deep within a system, hidden from traditional methods of inspection. Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, m...

  13. Developing an Intelligent Automatic Appendix Extraction Method from Ultrasonography Based on Fuzzy ART and Image Processing

    Directory of Open Access Journals (Sweden)

    Kwang Baek Kim

    2015-01-01

    Full Text Available Ultrasound examination (US does a key role in the diagnosis and management of the patients with clinically suspected appendicitis which is the most common abdominal surgical emergency. Among the various sonographic findings of appendicitis, outer diameter of the appendix is most important. Therefore, clear delineation of the appendix on US images is essential. In this paper, we propose a new intelligent method to extract appendix automatically from abdominal sonographic images as a basic building block of developing such an intelligent tool for medical practitioners. Knowing that the appendix is located at the lower organ area below the bottom fascia line, we conduct a series of image processing techniques to find the fascia line correctly. And then we apply fuzzy ART learning algorithm to the organ area in order to extract appendix accurately. The experiment verifies that the proposed method is highly accurate (successful in 38 out of 40 cases in extracting appendix.

  14. A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

    Science.gov (United States)

    Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin

    2009-08-01

    SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.

  15. Long Term Solar Radiation Forecast Using Computational Intelligence Methods

    Directory of Open Access Journals (Sweden)

    João Paulo Coelho

    2014-01-01

    Full Text Available The point prediction quality is closely related to the model that explains the dynamic of the observed process. Sometimes the model can be obtained by simple algebraic equations but, in the majority of the physical systems, the relevant reality is too hard to model with simple ordinary differential or difference equations. This is the case of systems with nonlinear or nonstationary behaviour which require more complex models. The discrete time-series problem, obtained by sampling the solar radiation, can be framed in this type of situation. By observing the collected data it is possible to distinguish multiple regimes. Additionally, due to atmospheric disturbances such as clouds, the temporal structure between samples is complex and is best described by nonlinear models. This paper reports the solar radiation prediction by using hybrid model that combines support vector regression paradigm and Markov chains. The hybrid model performance is compared with the one obtained by using other methods like autoregressive (AR filters, Markov AR models, and artificial neural networks. The results obtained suggests an increasing prediction performance of the hybrid model regarding both the prediction error and dynamic behaviour.

  16. Star Power: Providing for the Gifted & Talented. Module 3. Applications of Theories of Intelligence to the Gifted/Talented.

    Science.gov (United States)

    Heinemann, Alison; Mallis, Jackie

    The document presents Module 3, applications of theories of intelligence to the gifted/talented, of the Star Power modules developed for school personnel who have an interest in or a need to explore the area of gifted and talented education. It is explained in an introductory section that the modules can be used for independent study, for small…

  17. Providing Formative Assessment to Students Solving Multipath Engineering Problems with Complex Arrangements of Interacting Parts: An Intelligent Tutor Approach

    Science.gov (United States)

    Steif, Paul S.; Fu, Luoting; Kara, Levent Burak

    2016-01-01

    Problems faced by engineering students involve multiple pathways to solution. Students rarely receive effective formative feedback on handwritten homework. This paper examines the potential for computer-based formative assessment of student solutions to multipath engineering problems. In particular, an intelligent tutor approach is adopted and…

  18. An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

    OpenAIRE

    Bo Sun; Qiang Feng; Songjie Li

    2012-01-01

    According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

  19. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    Science.gov (United States)

    Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH

    2009-09-01

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  20. An Effective Wormhole Attack Defence Method for a Smart Meter Mesh Network in an Intelligent Power Grid

    Directory of Open Access Journals (Sweden)

    Jungtaek Seo

    2012-08-01

    Full Text Available Smart meters are one of the key components of intelligent power grids. Wireless mesh networks based on smart meters could provide customer-oriented information on electricity use to the operational control systems, which monitor power grid status and estimate electric power demand. Using this information, an operational control system could regulate devices within the smart grid in order to provide electricity in a cost-efficient manner. Ensuring the availability of the smart meter mesh network is therefore a critical factor in securing the soundness of an intelligent power system. Wormhole attacks can be one of the most difficult-to-address threats to the availability of mesh networks, and although many methods to nullify wormhole attacks have been tried, these have been limited by high computational resource requirements and unnecessary overhead, as well as by the lack of ability of such methods to respond to attacks. In this paper, an effective defense mechanism that both detects and responds to wormhole attacks is proposed. In the proposed system, each device maintains information on its neighbors, allowing each node to identify replayed packets. The effectiveness and efficiency of the proposed method is analyzed in light of additional computational message and memory complexities.

  1. Integrating GPS, GYRO, vehicle speed sensor, and digital map to provide accurate and real-time position in an intelligent navigation system

    Science.gov (United States)

    Li, Qingquan; Fang, Zhixiang; Li, Hanwu; Xiao, Hui

    2005-10-01

    The global positioning system (GPS) has become the most extensively used positioning and navigation tool in the world. Applications of GPS abound in surveying, mapping, transportation, agriculture, military planning, GIS, and the geosciences. However, the positional and elevation accuracy of any given GPS location is prone to error, due to a number of factors. The applications of Global Positioning System (GPS) positioning is more and more popular, especially the intelligent navigation system which relies on GPS and Dead Reckoning technology is developing quickly for future huge market in China. In this paper a practical combined positioning model of GPS/DR/MM is put forward, which integrates GPS, Gyro, Vehicle Speed Sensor (VSS) and digital navigation maps to provide accurate and real-time position for intelligent navigation system. This model is designed for automotive navigation system making use of Kalman filter to improve position and map matching veracity by means of filtering raw GPS and DR signals, and then map-matching technology is used to provide map coordinates for map displaying. In practical examples, for illustrating the validity of the model, several experiments and their results of integrated GPS/DR positioning in intelligent navigation system will be shown for the conclusion that Kalman Filter based GPS/DR integrating position approach is necessary, feasible and efficient for intelligent navigation application. Certainly, this combined positioning model, similar to other model, can not resolve all situation issues. Finally, some suggestions are given for further improving integrated GPS/DR/MM application.

  2. Comparison of artificial intelligence methods and empirical equations to estimate daily solar radiation

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2016-08-01

    In the present research, three artificial intelligence methods including Gene Expression Programming (GEP), Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) as well as, 48 empirical equations (10, 12 and 26 equations were temperature-based, sunshine-based and meteorological parameters-based, respectively) were used to estimate daily solar radiation in Kerman, Iran in the period of 1992-2009. To develop the GEP, ANN and ANFIS models, depending on the used empirical equations, various combinations of minimum air temperature, maximum air temperature, mean air temperature, extraterrestrial radiation, actual sunshine duration, maximum possible sunshine duration, sunshine duration ratio, relative humidity and precipitation were considered as inputs in the mentioned intelligent methods. To compare the accuracy of empirical equations and intelligent models, root mean square error (RMSE), mean absolute error (MAE), mean absolute relative error (MARE) and determination coefficient (R2) indices were used. The results showed that in general, sunshine-based and meteorological parameters-based scenarios in ANN and ANFIS models presented high accuracy than mentioned empirical equations. Moreover, the most accurate method in the studied region was ANN11 scenario with five inputs. The values of RMSE, MAE, MARE and R2 indices for the mentioned model were 1.850 MJ m-2 day-1, 1.184 MJ m-2 day-1, 9.58% and 0.935, respectively.

  3. A Novel Strain-Based Method to Estimate Tire Conditions Using Fuzzy Logic for Intelligent Tires

    Directory of Open Access Journals (Sweden)

    Daniel Garcia-Pozuelo

    2017-02-01

    Full Text Available The so-called intelligent tires are one of the most promising research fields for automotive engineers. These tires are equipped with sensors which provide information about vehicle dynamics. Up to now, the commercial intelligent tires only provide information about inflation pressure and their contribution to stability control systems is currently very limited. Nowadays one of the major problems for intelligent tire development is how to embed feasible and low cost sensors to obtain reliable information such as inflation pressure, vertical load or rolling speed. These parameters provide key information for vehicle dynamics characterization. In this paper, we propose a novel algorithm based on fuzzy logic to estimate the mentioned parameters by means of a single strain-based system. Experimental tests have been carried out in order to prove the suitability and durability of the proposed on-board strain sensor system, as well as its low cost advantages, and the accuracy of the obtained estimations by means of fuzzy logic.

  4. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

    A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

  5. Artificial Intelligence in Civil Engineering

    Directory of Open Access Journals (Sweden)

    Pengzhen Lu

    2012-01-01

    Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

  6. An intelligent service matching method for mechanical equipment condition monitoring using the fibre Bragg grating sensor network

    Science.gov (United States)

    Zhang, Fan; Zhou, Zude; Liu, Quan; Xu, Wenjun

    2017-02-01

    Due to the advantages of being able to function under harsh environmental conditions and serving as a distributed condition information source in a networked monitoring system, the fibre Bragg grating (FBG) sensor network has attracted considerable attention for equipment online condition monitoring. To provide an overall conditional view of the mechanical equipment operation, a networked service-oriented condition monitoring framework based on FBG sensing is proposed, together with an intelligent matching method for supporting monitoring service management. In the novel framework, three classes of progressive service matching approaches, including service-chain knowledge database service matching, multi-objective constrained service matching and workflow-driven human-interactive service matching, are developed and integrated with an enhanced particle swarm optimisation (PSO) algorithm as well as a workflow-driven mechanism. Moreover, the manufacturing domain ontology, FBG sensor network structure and monitoring object are considered to facilitate the automatic matching of condition monitoring services to overcome the limitations of traditional service processing methods. The experimental results demonstrate that FBG monitoring services can be selected intelligently, and the developed condition monitoring system can be re-built rapidly as new equipment joins the framework. The effectiveness of the service matching method is also verified by implementing a prototype system together with its performance analysis.

  7. IP-MLI: An Independency of Learning Materials from Platforms in a Mobile Learning using Intelligent Method

    Directory of Open Access Journals (Sweden)

    Mohammed Abdallh Otair

    2006-06-01

    Full Text Available Attempting to deliver a monolithic mobile learning system is too inflexible in view of the heterogeneous mixture of hardware and services available and the desirability of facility blended approaches to learning delivery, and how to build learning materials to run on all platforms[1]. This paper proposes a framework of mobile learning system using an intelligent method (IP-MLI . A fuzzy matching method is used to find suitable learning material design. It will provide a best matching for each specific platform type for each learner. The main contribution of the proposed method is to use software layer to insulate learning materials from device-specific features. Consequently, many versions of learning materials can be designed to work on many platform types.

  8. Application of artificial intelligence methods for prediction of steel mechanical properties

    Directory of Open Access Journals (Sweden)

    Z. Jančíková

    2008-10-01

    Full Text Available The target of the contribution is to outline possibilities of applying artificial neural networks for the prediction of mechanical steel properties after heat treatment and to judge their perspective use in this field. The achieved models enable the prediction of final mechanical material properties on the basis of decisive parameters influencing these properties. By applying artificial intelligence methods in combination with mathematic-physical analysis methods it will be possible to create facilities for designing a system of the continuous rationalization of existing and also newly developing industrial technologies.

  9. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Vitaliy PAVLENKO

    2017-06-01

    Full Text Available The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have built a simulation model for component transportation and delivery for manufactured products using the Simulink graphical environment for building models.

  10. Intelligent tuning method of PID parameters based on iterative learning control for atomic force microscopy.

    Science.gov (United States)

    Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang

    2018-01-01

    Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Cognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data

    Directory of Open Access Journals (Sweden)

    Karel Octavianus Bachri

    2017-07-01

    Full Text Available A3S(Arwin-Adang-Aciek-Sembiring is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN. First, the proposed method is tested using the previously published data, and then followed by implementation on maintenance data. Maintenance data are fused to obtain part condition, and part conditions are fused to obtain transformer condition. Result shows proposed method is valid for DGA fault identification with the average accuracy of 91.1%. The proposed method not only can interpret the major fault, it can also identify the minor fault occurring along with the major fault, allowing early warning feature. Result also shows part conditions can be interpreted using information fusion on maintenance data, and the transformer condition can be interpreted using information fusion on part conditions. The future works on this research is to gather more data, to elaborate more factors to be fused, and to design a cognitive processor that can be used to implement this concept of intelligent instrumentation.

  12. Configurable intelligent optimization algorithm design and practice in manufacturing

    CERN Document Server

    Tao, Fei; Laili, Yuanjun

    2014-01-01

    Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorit

  13. Research on Intelligent Avoidance Method of Shipwreck Based on Bigdata Analysis

    Directory of Open Access Journals (Sweden)

    Li Wei

    2017-11-01

    Full Text Available In order to solve the problem that current avoidance method of shipwreck has the problem of low success rate of avoidance, this paper proposes a method of intelligent avoidance of shipwreck based on big data analysis. Firstly,our method used big data analysis to calculate the safe distance of approach of ship under the head-on situation, the crossing situation and the overtaking situation.On this basis, by calculating the risk-degree of collision of ships,our research determined the degree of immediate danger of ships.Finally, we calculated the three kinds of evaluation function of ship navigation, and used genetic algorithm to realize the intelligent avoidance of shipwreck.Experimental result shows that compared the proposed method with the traditional method in two in a recent meeting when the distance to closest point of approach between two ships is 0.13nmile, they can effectively evade.The success rate of avoidance is high.

  14. Handbook of Intelligent Vehicles

    CERN Document Server

    2012-01-01

    The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above.

  15. Artificial Intelligence in Cardiology.

    Science.gov (United States)

    Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

    2018-06-12

    Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  16. Hybrid Intelligent Control Method to Improve the Frequency Support Capability of Wind Energy Conversion Systems

    Directory of Open Access Journals (Sweden)

    Shin Young Heo

    2015-10-01

    Full Text Available This paper presents a hybrid intelligent control method that enables frequency support control for permanent magnet synchronous generators (PMSGs wind turbines. The proposed method for a wind energy conversion system (WECS is designed to have PMSG modeling and full-scale back-to-back insulated-gate bipolar transistor (IGBT converters comprising the machine and grid side. The controller of the machine side converter (MSC and the grid side converter (GSC are designed to achieve maximum power point tracking (MPPT based on an improved hill climb searching (IHCS control algorithm and de-loaded (DL operation to obtain a power margin. Along with this comprehensive control of maximum power tracking mode based on the IHCS, a method for kinetic energy (KE discharge control of the supporting primary frequency control scheme with DL operation is developed to regulate the short-term frequency response and maintain reliable operation of the power system. The effectiveness of the hybrid intelligent control method is verified by a numerical simulation in PSCAD/EMTDC. Simulation results show that the proposed approach can improve the frequency regulation capability in the power system.

  17. Based on Short Motion Paths and Artificial Intelligence Method for Chinese Chess Game

    Directory of Open Access Journals (Sweden)

    Chien-Ming Hung

    2017-08-01

    Full Text Available The article develops the decision rules to win each set of the Chinese chess game using evaluation algorithm and artificial intelligence method, and uses the mobile robot to be instead of the chess, and presents the movement scenarios using the shortest motion paths for mobile robots. Player can play the Chinese chess game according to the game rules with the supervised computer. The supervised computer decides the optimal motion path to win the set using artificial intelligence method, and controls mobile robots according to the programmed motion paths of the assigned chesses moving on the platform via wireless RF interface. We uses enhance A* searching algorithm to solve the shortest path problem of the assigned chess, and solve the collision problems of the motion paths for two mobile robots moving on the platform simultaneously. We implement a famous set to be called lwild horses run in farmr using the proposed method. First we use simulation method to display the motion paths of the assigned chesses for the player and the supervised computer. Then the supervised computer implements the simulation results on the chessboard platform using mobile robots. Mobile robots move on the chessboard platform according to the programmed motion paths and is guided to move on the centre line of the corridor, and avoid the obstacles (chesses, and detect the cross point of the platform using three reflective IR modules.

  18. 32 CFR 199.14 - Provider reimbursement methods.

    Science.gov (United States)

    2010-07-01

    ... physicians. (6) All services provided by nurse anesthetists. (7) All services related to discharges involving... more accurate data became available. (v) No update for inflation. The children's hospital differential... considered lower volume hospitals. (B) Hospitals that subsequently become higher volume hospitals. In any...

  19. Hybrid Modeling and Optimization of Manufacturing Combining Artificial Intelligence and Finite Element Method

    CERN Document Server

    Quiza, Ramón; Davim, J Paulo

    2012-01-01

    Artificial intelligence (AI) techniques and the finite element method (FEM) are both powerful computing tools, which are extensively used for modeling and optimizing manufacturing processes. The combination of these tools has resulted in a new flexible and robust approach as several recent studies have shown. This book aims to review the work already done in this field as well as to expose the new possibilities and foreseen trends. The book is expected to be useful for postgraduate students and researchers, working in the area of modeling and optimization of manufacturing processes.

  20. Intelligent Detection of Structure from Remote Sensing Images Based on Deep Learning Method

    Science.gov (United States)

    Xin, L.

    2018-04-01

    Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.

  1. Methodical Approaches to Communicative Providing of Retailer Branding

    Directory of Open Access Journals (Sweden)

    Andrey Kataev

    2017-07-01

    Full Text Available The thesis is devoted to the rationalization of methodical approaches for provision of branding of retail trade enterprises. The article considers the features of brand perception by retail consumers and clarifies the specifics of customer reviews of stores for the procedures accompanying brand management. It is proved that besides traditional communication mix, the most important tool of communicative influence on buyers is the store itself as a place for comfortable shopping. The shop should have a stimulating effect on all five human senses, including sight, smell, hearing, touch, and taste, which shall help maximize consumer integration into the buying process.

  2. An infrastructure with a unified control plane to integrate IP into optical metro networks to provide flexible and intelligent bandwidth on demand for cloud computing

    Science.gov (United States)

    Yang, Wei; Hall, Trevor

    2012-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users and the nature of the Internet traffic will undertake a fundamental transformation. Consequently, the current Internet will no longer suffice for serving cloud traffic in metro areas. This work proposes an infrastructure with a unified control plane that integrates simple packet aggregation technology with optical express through the interoperation between IP routers and electrical traffic controllers in optical metro networks. The proposed infrastructure provides flexible, intelligent, and eco-friendly bandwidth on demand for cloud computing in metro areas.

  3. Prediction of shear wave velocity using empirical correlations and artificial intelligence methods

    Science.gov (United States)

    Maleki, Shahoo; Moradzadeh, Ali; Riabi, Reza Ghavami; Gholami, Raoof; Sadeghzadeh, Farhad

    2014-06-01

    Good understanding of mechanical properties of rock formations is essential during the development and production phases of a hydrocarbon reservoir. Conventionally, these properties are estimated from the petrophysical logs with compression and shear sonic data being the main input to the correlations. This is while in many cases the shear sonic data are not acquired during well logging, which may be for cost saving purposes. In this case, shear wave velocity is estimated using available empirical correlations or artificial intelligent methods proposed during the last few decades. In this paper, petrophysical logs corresponding to a well drilled in southern part of Iran were used to estimate the shear wave velocity using empirical correlations as well as two robust artificial intelligence methods knows as Support Vector Regression (SVR) and Back-Propagation Neural Network (BPNN). Although the results obtained by SVR seem to be reliable, the estimated values are not very precise and considering the importance of shear sonic data as the input into different models, this study suggests acquiring shear sonic data during well logging. It is important to note that the benefits of having reliable shear sonic data for estimation of rock formation mechanical properties will compensate the possible additional costs for acquiring a shear log.

  4. Methods of Computational Intelligence in the Context of Quality Assurance in Foundry Products

    Directory of Open Access Journals (Sweden)

    Rojek G.

    2016-06-01

    Full Text Available One way to ensure the required technical characteristics of castings is the strict control of production parameters affecting the quality of the finished products. If the production process is improperly configured, the resulting defects in castings lead to huge losses. Therefore, from the point of view of economics, it is advisable to use the methods of computational intelligence in the field of quality assurance and adjustment of parameters of future production. At the same time, the development of knowledge in the field of metallurgy, aimed to raise the technical level and efficiency of the manufacture of foundry products, should be followed by the development of information systems to support production processes in order to improve their effectiveness and compliance with the increasingly more stringent requirements of ergonomics, occupational safety, environmental protection and quality. This article is a presentation of artificial intelligence methods used in practical applications related to quality assurance. The problem of control of the production process involves the use of tools such as the induction of decision trees, fuzzy logic, rough set theory, artificial neural networks or case-based reasoning.

  5. Prediction of shear wave velocity using empirical correlations and artificial intelligence methods

    Directory of Open Access Journals (Sweden)

    Shahoo Maleki

    2014-06-01

    Full Text Available Good understanding of mechanical properties of rock formations is essential during the development and production phases of a hydrocarbon reservoir. Conventionally, these properties are estimated from the petrophysical logs with compression and shear sonic data being the main input to the correlations. This is while in many cases the shear sonic data are not acquired during well logging, which may be for cost saving purposes. In this case, shear wave velocity is estimated using available empirical correlations or artificial intelligent methods proposed during the last few decades. In this paper, petrophysical logs corresponding to a well drilled in southern part of Iran were used to estimate the shear wave velocity using empirical correlations as well as two robust artificial intelligence methods knows as Support Vector Regression (SVR and Back-Propagation Neural Network (BPNN. Although the results obtained by SVR seem to be reliable, the estimated values are not very precise and considering the importance of shear sonic data as the input into different models, this study suggests acquiring shear sonic data during well logging. It is important to note that the benefits of having reliable shear sonic data for estimation of rock formation mechanical properties will compensate the possible additional costs for acquiring a shear log.

  6. 5th International Workshop on Combinations of Intelligent Methods and Applications

    CERN Document Server

    Palade, Vasile; Prentzas, Jim

    2017-01-01

    Complex problems usually cannot be solved by individual methods or techniques and require the synergism of more than one of them to be solved. This book presents a number of current efforts that use combinations of methods or techniques to solve complex problems in the areas of sentiment analysis, search in GIS, graph-based social networking, intelligent e-learning systems, data mining and recommendation systems. Most of them are connected with specific applications, whereas the rest are combinations based on principles. Most of the chapters are extended versions of the corresponding papers presented in CIMA-15 Workshop, which took place in conjunction with IEEE ICTAI-15, in November 2015. The rest are invited papers that responded to special call for papers for the book. The book is addressed to researchers and practitioners from academia or industry, who are interested in using combined methods in solving complex problems in the above areas.

  7. Artificial intelligence methods applied for quantitative analysis of natural radioactive sources

    International Nuclear Information System (INIS)

    Medhat, M.E.

    2012-01-01

    Highlights: ► Basic description of artificial neural networks. ► Natural gamma ray sources and problem of detections. ► Application of neural network for peak detection and activity determination. - Abstract: Artificial neural network (ANN) represents one of artificial intelligence methods in the field of modeling and uncertainty in different applications. The objective of the proposed work was focused to apply ANN to identify isotopes and to predict uncertainties of their activities of some natural radioactive sources. The method was tested for analyzing gamma-ray spectra emitted from natural radionuclides in soil samples detected by a high-resolution gamma-ray spectrometry based on HPGe (high purity germanium). The principle of the suggested method is described, including, relevant input parameters definition, input data scaling and networks training. It is clear that there is satisfactory agreement between obtained and predicted results using neural network.

  8. Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong

    2011-12-01

    Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

  9. Quality control of intelligence research

    International Nuclear Information System (INIS)

    Lu Yan; Xin Pingping; Wu Jian

    2014-01-01

    Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

  10. Methods and Technologies of XML Data Modeling for IP Mode Intelligent Measuring and Controlling System

    International Nuclear Information System (INIS)

    Liu, G X; Hong, X B; Liu, J G

    2006-01-01

    This paper presents the IP mode intelligent measuring and controlling system (IMIMCS). Based on object-oriented modeling technology of UML and XML Schema, the innovative methods and technologies of some key problems for XML data modeling in the IMIMCS were especially discussed, including refinement for systemic business by means of use-case diagram of UML, the confirmation of the content of XML data model and logic relationship of the objects of XML Schema with the aid of class diagram of UML, the mapping rules from the UML object model to XML Schema. Finally, the application of the IMIMCS based on XML for a modern greenhouse was presented. The results show that the modeling methods of the measuring and controlling data in the IMIMCS involving the multi-layer structure and many operating systems process strong reliability and flexibility, guarantee uniformity of complex XML documents and meet the requirement of data communication across platform

  11. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NN ds ) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  12. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  13. EFFECTIVENESS OF AGILE COMPARED TO WATERFALL IMPLEMENTATION METHODS IN IT PROJECTS: ANALYSIS BASED ON BUSINESS INTELLIGENCE PROJECTS

    Directory of Open Access Journals (Sweden)

    Kisielnicki Jerzy

    2017-10-01

    Full Text Available The global Business Intelligence (BI market grew by 7.3% in 2016 according to the Gartner report (2017. Today, organizations require better use of data and analytics to support their business decisions. Internet power and business trend changes have provided a broad term for data analytics - Big Data. To be able to handle it and leverage a value of having access to Big Data, organizations have no other choice than to get proper systems implemented and working. However, traditional methods are not efficient for changing business needs. Long time between project start and go-live causes a gap between initial solution blueprint and actual user requirements at the end of the project. This article presents the latest market trends in BI systems implementation by comparing agile with traditional methods. It presents a case study provided in a large telecommunications company (350 BI users and the results of a pilot research provided in the three large companies: media, digital, and insurance. Both studies prove that agile methods might be more effective in BI projects from an end-user perspective and give first results and added value in a much shorter time compared to a traditional approach.

  14. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  15. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  16. On Intelligent Design and Planning Method of Process Route Based on Gun Breech Machining Process

    Science.gov (United States)

    Hongzhi, Zhao; Jian, Zhang

    2018-03-01

    The paper states an approach of intelligent design and planning of process route based on gun breech machining process, against several problems, such as complex machining process of gun breech, tedious route design and long period of its traditional unmanageable process route. Based on gun breech machining process, intelligent design and planning system of process route are developed by virtue of DEST and VC++. The system includes two functional modules--process route intelligent design and its planning. The process route intelligent design module, through the analysis of gun breech machining process, summarizes breech process knowledge so as to complete the design of knowledge base and inference engine. And then gun breech process route intelligently output. On the basis of intelligent route design module, the final process route is made, edited and managed in the process route planning module.

  17. Position detectors, methods of detecting position, and methods of providing positional detectors

    Science.gov (United States)

    Weinberg, David M.; Harding, L. Dean; Larsen, Eric D.

    2002-01-01

    Position detectors, welding system position detectors, methods of detecting various positions, and methods of providing position detectors are described. In one embodiment, a welding system positional detector includes a base that is configured to engage and be moved along a curved surface of a welding work piece. At least one position detection apparatus is provided and is connected with the base and configured to measure angular position of the detector relative to a reference vector. In another embodiment, a welding system positional detector includes a weld head and at least one inclinometer mounted on the weld head. The one inclinometer is configured to develop positional data relative to a reference vector and the position of the weld head on a non-planar weldable work piece.

  18. Managing Sustainability with the Support of Business Intelligence Methods and Tools

    Science.gov (United States)

    Petrini, Maira; Pozzebon, Marlei

    In this paper we explore the role of business intelligence (BI) in helping to support the management of sustainability in contemporary firms. The concepts of sustainability and corporate social responsibility (CSR) are among the most important themes to have emerged in the last decade at the global level. We suggest that BI methods and tools have an important but not yet well studied role to play in helping organizations implement and monitor sustainable and socially responsible business practices. Using grounded theory, the main contribution of our study is to propose a conceptual model that seeks to support the process of definition and monitoring of socio-environmental indicators and the relationship between their management and business strategy.

  19. An intelligent despeckling method for swept source optical coherence tomography images of skin

    Science.gov (United States)

    Adabi, Saba; Mohebbikarkhoran, Hamed; Mehregan, Darius; Conforto, Silvia; Nasiriavanaki, Mohammadreza

    2017-03-01

    Optical Coherence Optical coherence tomography is a powerful high-resolution imaging method with a broad biomedical application. Nonetheless, OCT images suffer from a multiplicative artefacts so-called speckle, a result of coherent imaging of system. Digital filters become ubiquitous means for speckle reduction. Addressing the fact that there still a room for despeckling in OCT, we proposed an intelligent speckle reduction framework based on OCT tissue morphological, textural and optical features that through a trained network selects the winner filter in which adaptively suppress the speckle noise while preserve structural information of OCT signal. These parameters are calculated for different steps of the procedure to be used in designed Artificial Neural Network decider that select the best denoising technique for each segment of the image. Results of training shows the dominant filter is BM3D from the last category.

  20. An Intelligent Method for Structural Reliability Analysis Based on Response Surface

    Institute of Scientific and Technical Information of China (English)

    桂劲松; 刘红; 康海贵

    2004-01-01

    As water depth increases, the structural safety and reliability of a system become more and more important and challenging. Therefore, the structural reliability method must be applied in ocean engineering design such as offshore platform design. If the performance function is known in structural reliability analysis, the first-order second-moment method is often used. If the performance function could not be definitely expressed, the response surface method is always used because it has a very clear train of thought and simple programming. However, the traditional response surface method fits the response surface of quadratic polynomials where the problem of accuracy could not be solved, because the true limit state surface can be fitted well only in the area near the checking point. In this paper, an intelligent computing method based on the whole response surface is proposed, which can be used for the situation where the performance function could not be definitely expressed in structural reliability analysis. In this method, a response surface of the fuzzy neural network for the whole area should be constructed first, and then the structural reliability can be calculated by the genetic algorithm. In the proposed method, all the sample points for the training network come from the whole area, so the true limit state surface in the whole area can be fitted. Through calculational examples and comparative analysis, it can be known that the proposed method is much better than the traditional response surface method of quadratic polynomials, because, the amount of calculation of finite element analysis is largely reduced, the accuracy of calculation is improved,and the true limit state surface can be fitted very well in the whole area. So, the method proposed in this paper is suitable for engineering application.

  1. The use of artificial intelligence methods for visual analysis of properties of surface layers

    Directory of Open Access Journals (Sweden)

    Tomasz Wójcicki

    2014-12-01

    Full Text Available [b]Abstract[/b]. The article presents a selected area of research on the possibility of automatic prediction of material properties based on the analysis of digital images. Original, holistic model of forecasting properties of surface layers based on a multi-step process that includes the selected methods of processing and analysis of images, inference with the use of a priori knowledge bases and multi-valued fuzzy logic, and simulation with the use of finite element methods is presented. Surface layers characteristics and core technologies of their production processes such as mechanical, thermal, thermo-mechanical, thermo-chemical, electrochemical, physical are discussed. Developed methods used in the model for the classification of images of the surface layers are shown. The objectives of the use of selected methods of processing and analysis of digital images, including techniques for improving the quality of images, segmentation, morphological transformation, pattern recognition and simulation of physical phenomena in the structures of materials are described.[b]Keywords[/b]: image analysis, surface layer, artificial intelligence, fuzzy logic

  2. Study (Prediction of Main Pipes Break Rates in Water Distribution Systems Using Intelligent and Regression Methods

    Directory of Open Access Journals (Sweden)

    Massoud Tabesh

    2011-07-01

    Full Text Available Optimum operation of water distribution networks is one of the priorities of sustainable development of water resources, considering the issues of increasing efficiency and decreasing the water losses. One of the key subjects in optimum operational management of water distribution systems is preparing rehabilitation and replacement schemes, prediction of pipes break rate and evaluation of their reliability. Several approaches have been presented in recent years regarding prediction of pipe failure rates which each one requires especial data sets. Deterministic models based on age and deterministic multi variables and stochastic group modeling are examples of the solutions which relate pipe break rates to parameters like age, material and diameters. In this paper besides the mentioned parameters, more factors such as pipe depth and hydraulic pressures are considered as well. Then using multi variable regression method, intelligent approaches (Artificial neural network and neuro fuzzy models and Evolutionary polynomial Regression method (EPR pipe burst rate are predicted. To evaluate the results of different approaches, a case study is carried out in a part ofMashhadwater distribution network. The results show the capability and advantages of ANN and EPR methods to predict pipe break rates, in comparison with neuro fuzzy and multi-variable regression methods.

  3. Improved Ordinary Measure and Image Entropy Theory based intelligent Copy Detection Method

    Directory of Open Access Journals (Sweden)

    Dengpan Ye

    2011-10-01

    Full Text Available Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.

  4. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.

    2004-01-01

    In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.

  5. Enhancing Context Analysis with Intelligence in Providing e-Health Services: Less Infrastructure Dependency in Supporting Cardio-Vascular Patients

    OpenAIRE

    Verbraeck, A.; Widya, I.A.; Shishkov, Boris; Cordeiro, J.; Ranchordas, A.

    2009-01-01

    In Europe, we observe an increasing number of people with health problems, who could theoretically receive care outside of a hospital when their condition could be properly monitored. Not being able to provide this monitoring leads to an increasing pressure on an already overcrowded hospital system and increased costs. Ubiquitous technology on top of a high-quality IT infra-structure has already proven to be able to provide partial solutions. However, such infrastructure is not available thro...

  6. Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking

    Science.gov (United States)

    Wang, Yajie; Shi, Yunbo; Yu, Xiaoyu; Liu, Yongjie

    2016-01-01

    Currently, tracking in photovoltaic (PV) systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works. PMID:27327657

  7. Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

    Science.gov (United States)

    Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

    2018-05-01

    Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

  8. New evaluation methods for conceptual design selection using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai [University of Electronic Science and Technology of China, Chengdu (China); Xue, Lihua [Higher Education Press, Beijing (China)

    2013-03-15

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  9. New evaluation methods for conceptual design selection using computational intelligence techniques

    International Nuclear Information System (INIS)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai; Xue, Lihua

    2013-01-01

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  10. Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking.

    Directory of Open Access Journals (Sweden)

    Yajie Wang

    Full Text Available Currently, tracking in photovoltaic (PV systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works.

  11. Intelligent Photovoltaic Systems by Combining the Improved Perturbation Method of Observation and Sun Location Tracking.

    Science.gov (United States)

    Wang, Yajie; Shi, Yunbo; Yu, Xiaoyu; Liu, Yongjie

    2016-01-01

    Currently, tracking in photovoltaic (PV) systems suffers from some problems such as high energy consumption, poor anti-interference performance, and large tracking errors. This paper presents a solar PV tracking system on the basis of an improved perturbation and observation method, which maximizes photoelectric conversion efficiency. According to the projection principle, we design a sensor module with a light-intensity-detection module for environmental light-intensity measurement. The effect of environmental factors on the system operation is reduced, and intelligent identification of the weather is realized. This system adopts the discrete-type tracking method to reduce power consumption. A mechanical structure with a level-pitch double-degree-of-freedom is designed, and attitude correction is performed by closed-loop control. A worm-and-gear mechanism is added, and the reliability, stability, and precision of the system are improved. Finally, the perturbation and observation method designed and improved by this study was tested by simulated experiments. The experiments verified that the photoelectric sensor resolution can reach 0.344°, the tracking error is less than 2.5°, the largest improvement in the charge efficiency can reach 44.5%, and the system steadily and reliably works.

  12. Routledge companion to intelligence studies

    CERN Document Server

    Dover, Robert; Hillebrand, Claudia

    2013-01-01

    The Routledge Companion to Intelligence Studies provides a broad overview of the growing field of intelligence studies. The recent growth of interest in intelligence and security studies has led to an increased demand for popular depictions of intelligence and reference works to explain the architecture and underpinnings of intelligence activity. Divided into five comprehensive sections, this Companion provides a strong survey of the cutting-edge research in the field of intelligence studies: Part I: The evolution of intelligence studies; Part II: Abstract approaches to intelligence; Part III: Historical approaches to intelligence; Part IV: Systems of intelligence; Part V: Contemporary challenges. With a broad focus on the origins, practices and nature of intelligence, the book not only addresses classical issues, but also examines topics of recent interest in security studies. The overarching aim is to reveal the rich tapestry of intelligence studies in both a sophisticated and accessible way. This Companion...

  13. Enhancing Context Analysis with Intelligence in Providing e-Health Services: Less Infrastructure Dependency in Supporting Cardio-Vascular Patients

    NARCIS (Netherlands)

    Verbraeck, A.; Widya, I.A.; Shishkov, Boris; Cordeiro, J.; Ranchordas, A.

    2009-01-01

    In Europe, we observe an increasing number of people with health problems, who could theoretically receive care outside of a hospital when their condition could be properly monitored. Not being able to provide this monitoring leads to an increasing pressure on an already overcrowded hospital system

  14. A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

    Science.gov (United States)

    Yang, Wei; Hall, Trevor J.

    2013-12-01

    The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

  15. Monitoring of operation with artificial intelligence methods; Betriebsueberwachung mit Verfahren der Kuenstlichen Intelligenz

    Energy Technology Data Exchange (ETDEWEB)

    Bruenninghaus, H. [DMT-Gesellschaft fuer Forschung und Pruefung mbH, Essen (Germany). Geschaeftsbereich Systemtechnik

    1999-03-11

    Taking the applications `early detection of fires` and `reduction of burst of messages` as an example, the usability of artificial intelligence (AI) methods in the monitoring of operation was checked in a R and D project. The contribution describes the concept, development and evaluation of solutions to the specified problems. A platform, which made it possible to investigate different AI methods (in particular artificial neuronal networks), had to be creaated as a basis for the project. At the same time ventilation data had to be acquired and processed by the networks for the classification. (orig.) [Deutsch] Am Beispiel der Anwendungsfaelle `Brandfrueherkennung` und `Meldungsschauerreduzierung` wurde im Rahmen eines F+E-Vorhabens die Einsetzbarkeit von Kuenstliche-Intelligenz-Methoden (KI) in der Betriebsueberwachung geprueft. Der Beitrag stellt Konzeption, Entwicklung und Bewertung von Loesungsansaetzen fuer die genannten Aufgabenstellungen vor. Als Grundlage fuer das Vorhaben wurden anhand KI-Methoden (speziell: Kuenstliche Neuronale Netze -KNN) auf der Grundlage gewonnener und aufbereiteter Wetterdaten die Beziehungen zwischen den Wettermessstellen im Laufe des Wetterwegs klassifiziert. (orig.)

  16. Computational Intelligence Method for Early Diagnosis Dengue Haemorrhagic Fever Using Fuzzy on Mobile Device

    Directory of Open Access Journals (Sweden)

    Salman Afan

    2014-03-01

    Full Text Available Mortality from Dengue Haemorrhagic Fever (DHF is still increasing in Indonesia particularly in Jakarta. Diagnosis of the dengue shall be made as early as possible so that first aid can be given in expectation of decreasing death risk. The Study will be conducted by developing expert system based on Computational Intelligence Method. On the first year, study will use the Fuzzy Inference System (FIS Method to diagnose Dengue Haemorrhagic Fever particularly in Mobile Device consist of smart phone. Expert system application which particularly using fuzzy system can be applied in mobile device and it is useful to make early diagnosis of Dengue Haemorrhagic Fever that produce outcome faster than laboratory test. The evaluation of this application is conducted by performing accuracy test before and after validation using data of patient who has the Dengue Haemorrhagic Fever. This expert system application is easy, convenient, and practical to use, also capable of making the early diagnosis of Dengue Haemorraghic to avoid mortality in the first stage.

  17. On the Need for Artificial Intelligence and Advanced Test and Evaluation Methods for Space Exploration

    Science.gov (United States)

    Scheidt, D. H.; Hibbitts, C. A.; Chen, M. H.; Paxton, L. J.; Bekker, D. L.

    2017-02-01

    Implementing mature artificial intelligence would create the ability to significantly increase the science return from a mission, while potentially saving costs in mission and instrument operations, and solving currently intractable problems.

  18. Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)

    CSIR Research Space (South Africa)

    Xing, B

    2009-12-01

    Full Text Available This work focuses on the design and control of a novel hybrid manufacturing system: Reconfigurable Cellular Manufacturing System (RCMS) by using Artificial Intelligence (AI) approach. It is hybrid as it combines the advantages of Cellular...

  19. Emotional intelligence among medical students: a mixed methods study from Chennai, India.

    Science.gov (United States)

    Sundararajan, Subashini; Gopichandran, Vijayaprasad

    2018-05-04

    Emotional Intelligence is the ability of a person to understand and respond to one's own and others' emotions and use this understanding to guide one's thoughts and actions. To assess the level of emotional intelligence of medical students in a medical college in Chennai and to explore their understanding of the role of emotions in medical practice. A quantitative, cross sectional, questionnaire based, survey was conducted among 207 medical students in a college in Chennai, India using the Quick Emotional Intelligence Self Assessment Test and some hypothetical emotional clinical vignettes. This was followed by a qualitative moderated fish-bowl discussion to elicit the opinion of medical students on role of emotions in the practice of medicine. The mean score of Emotional Intelligence was 107.58 (SD 16.44) out of a maximum possible score of 160. Students who went to government schools for high school education had greater emotional intelligence than students from private schools (p = 0.044) and women were more emotionally intelligent in their response to emotional vignettes than men (p = 0.056). The fish bowl discussion highlighted several positive and negative impacts of emotions in clinical care. The students concluded at the end of the discussion that emotions are inevitable in the practice of medicine and a good physician should know how to handle them. Medical students, both men and women, had good level of emotional intelligence in the college that was studied. Students from collectivist social settings like government high schools have better emotional intelligence, which may indicate that a collectivist, community oriented medical education can serve the same purpose. Though students have diverse opinions on the role of emotions in clinical care, cognitive reflection exercises can help them understand its importance.

  20. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Weber, W.; Rabaey, J.M.; Aarts, E.

    2005-01-01

    We briefly review the concept of ambient intelligence and discuss its relation with the domain of intelligent algorithms. By means of four examples of ambient intelligent systems, we argue that new computing methods and quantification measures are needed to bridge the gap between the class of

  1. Reflection on robotic intelligence

    NARCIS (Netherlands)

    Bartneck, C.

    2006-01-01

    This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

  2. Advance in study of intelligent diagnostic method for nuclear power plant

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2008-01-01

    The advance of research on the application of three types of intelligent diagnostic approach based on neural network (ANN), fuzzy logic and expert system to the operation status monitoring and fault diagnosis of nuclear power plant (NPP) was reviewed. The research status and characters on status monitoring and fault diagnosis approaches based on neural network, fuzzy logic and expert system for nuclear power plant were analyzed. The development trend of applied research on intelligent diagnostic approaches for nuclear power plant was explored. The analysis results show that the research achievements on intelligent diagnostic approaches based on fuzzy logic and expert system for nuclear power plant are not much relatively. The research of intelligent diagnostic approaches for nuclear power plant concentrate on the aspect of operation status monitoring and fault diagnosis based on neural networks for nuclear power plant. The advancing tendency of intelligent diagnostic approaches for nuclear power plant is the combination of various intelligent diagnostic approaches, the combination of neural network diagnostic approaches and other diagnostic approaches as well as multiple neural network diagnostic approaches. (authors)

  3. Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

    Science.gov (United States)

    Hortos, William S.

    2006-05-01

    A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the

  4. An intelligent fault diagnosis method of rolling bearings based on regularized kernel Marginal Fisher analysis

    International Nuclear Information System (INIS)

    Jiang Li; Shi Tielin; Xuan Jianping

    2012-01-01

    Generally, the vibration signals of fault bearings are non-stationary and highly nonlinear under complicated operating conditions. Thus, it's a big challenge to extract optimal features for improving classification and simultaneously decreasing feature dimension. Kernel Marginal Fisher analysis (KMFA) is a novel supervised manifold learning algorithm for feature extraction and dimensionality reduction. In order to avoid the small sample size problem in KMFA, we propose regularized KMFA (RKMFA). A simple and efficient intelligent fault diagnosis method based on RKMFA is put forward and applied to fault recognition of rolling bearings. So as to directly excavate nonlinear features from the original high-dimensional vibration signals, RKMFA constructs two graphs describing the intra-class compactness and the inter-class separability, by combining traditional manifold learning algorithm with fisher criteria. Therefore, the optimal low-dimensional features are obtained for better classification and finally fed into the simplest K-nearest neighbor (KNN) classifier to recognize different fault categories of bearings. The experimental results demonstrate that the proposed approach improves the fault classification performance and outperforms the other conventional approaches.

  5. Artificial Intelligence Mechanisms on Interactive Modified Simplex Method with Desirability Function for Optimising Surface Lapping Process

    Directory of Open Access Journals (Sweden)

    Pongchanun Luangpaiboon

    2014-01-01

    Full Text Available A study has been made to optimise the influential parameters of surface lapping process. Lapping time, lapping speed, downward pressure, and charging pressure were chosen from the preliminary studies as parameters to determine process performances in terms of material removal, lap width, and clamp force. The desirability functions of the-nominal-the-best were used to compromise multiple responses into the overall desirability function level or D response. The conventional modified simplex or Nelder-Mead simplex method and the interactive desirability function are performed to optimise online the parameter levels in order to maximise the D response. In order to determine the lapping process parameters effectively, this research then applies two powerful artificial intelligence optimisation mechanisms from harmony search and firefly algorithms. The recommended condition of (lapping time, lapping speed, downward pressure, and charging pressure at (33, 35, 6.0, and 5.0 has been verified by performing confirmation experiments. It showed that the D response level increased to 0.96. When compared with the current operating condition, there is a decrease of the material removal and lap width with the improved process performance indices of 2.01 and 1.14, respectively. Similarly, there is an increase of the clamp force with the improved process performance index of 1.58.

  6. Semen parameters can be predicted from environmental factors and lifestyle using artificial intelligence methods.

    Science.gov (United States)

    Girela, Jose L; Gil, David; Johnsson, Magnus; Gomez-Torres, María José; De Juan, Joaquín

    2013-04-01

    Fertility rates have dramatically decreased in the last two decades, especially in men. It has been described that environmental factors as well as life habits may affect semen quality. In this paper we use artificial intelligence techniques in order to predict semen characteristics resulting from environmental factors, life habits, and health status, with these techniques constituting a possible decision support system that can help in the study of male fertility potential. A total of 123 young, healthy volunteers provided a semen sample that was analyzed according to the World Health Organization 2010 criteria. They also were asked to complete a validated questionnaire about life habits and health status. Sperm concentration and percentage of motile sperm were related to sociodemographic data, environmental factors, health status, and life habits in order to determine the predictive accuracy of a multilayer perceptron network, a type of artificial neural network. In conclusion, we have developed an artificial neural network that can predict the results of the semen analysis based on the data collected by the questionnaire. The semen parameter that is best predicted using this methodology is the sperm concentration. Although the accuracy for motility is slightly lower than that for concentration, it is possible to predict it with a significant degree of accuracy. This methodology can be a useful tool in early diagnosis of patients with seminal disorders or in the selection of candidates to become semen donors.

  7. SII-Based Speech Prepocessing for Intelligibility Improvement in Noise

    DEFF Research Database (Denmark)

    Taal, Cees H.; Jensen, Jesper

    2013-01-01

    filter sets certain frequency bands to zero when they do not contribute to intelligibility anymore. Experiments show large intelligibility improvements with the proposed method when used in stationary speech-shaped noise. However, it was also found that the method does not perform well for speech...... corrupted by a competing speaker. This is due to the fact that the SII is not a reliable intelligibility predictor for fluctuating noise sources. MATLAB code is provided....

  8. Cargo flows distribution over the loading sites of enterprises by using methods of artificial intelligence

    Directory of Open Access Journals (Sweden)

    Олександр Павлович Кіркін

    2017-06-01

    Full Text Available Development of information technologies and market requirements in effective control over cargo flows, forces enterprises to look for new ways and methods of automated control over the technological operations. For rail transportation one of the most complicated tasks of automation is the cargo flows distribution over the sites of loading and unloading. In this article the solution with the use of one of the methods of artificial intelligence – a fuzzy inference has been proposed. The analysis of the last publications showed that the fuzzy inference method is effective for the solution of similar tasks, it makes it possible to accumulate experience, it is stable to temporary impacts of the environmental conditions. The existing methods of the cargo flows distribution over the sites of loading and unloading are too simplified and can lead to incorrect decisions. The purpose of the article is to create a distribution model of cargo flows of the enterprises over the sites of loading and unloading, basing on the fuzzy inference method and to automate the control. To achieve the objective a mathematical model of the cargo flows distribution over the sites of loading and unloading has been made using fuzzy logic. The key input parameters of the model are: «number of loading sites», «arrival of the next set of cars», «availability of additional operations». The output parameter is «a variety of set of cars». Application of the fuzzy inference method made it possible to reduce loading time by 15% and to reduce costs for preparatory operations before loading by 20%. Thus this method is an effective means and holds the greatest promise for railway competitiveness increase. Interaction between different types of transportation and their influence on the cargo flows distribution over the sites of loading and unloading hasn’t been considered. These sites may be busy transshipping at that very time which is characteristic of large enterprises

  9. Advanced intelligent systems

    CERN Document Server

    Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

    2014-01-01

    Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

  10. Artificial intelligence in robot control systems

    Science.gov (United States)

    Korikov, A.

    2018-05-01

    This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

  11. Intelligent inversion method for pre-stack seismic big data based on MapReduce

    Science.gov (United States)

    Yan, Xuesong; Zhu, Zhixin; Wu, Qinghua

    2018-01-01

    Seismic exploration is a method of oil exploration that uses seismic information; that is, according to the inversion of seismic information, the useful information of the reservoir parameters can be obtained to carry out exploration effectively. Pre-stack data are characterised by a large amount of data, abundant information, and so on, and according to its inversion, the abundant information of the reservoir parameters can be obtained. Owing to the large amount of pre-stack seismic data, existing single-machine environments have not been able to meet the computational needs of the huge amount of data; thus, the development of a method with a high efficiency and the speed to solve the inversion problem of pre-stack seismic data is urgently needed. The optimisation of the elastic parameters by using a genetic algorithm easily falls into a local optimum, which results in a non-obvious inversion effect, especially for the optimisation effect of the density. Therefore, an intelligent optimisation algorithm is proposed in this paper and used for the elastic parameter inversion of pre-stack seismic data. This algorithm improves the population initialisation strategy by using the Gardner formula and the genetic operation of the algorithm, and the improved algorithm obtains better inversion results when carrying out a model test with logging data. All of the elastic parameters obtained by inversion and the logging curve of theoretical model are fitted well, which effectively improves the inversion precision of the density. This algorithm was implemented with a MapReduce model to solve the seismic big data inversion problem. The experimental results show that the parallel model can effectively reduce the running time of the algorithm.

  12. Intelligent audio analysis

    CERN Document Server

    Schuller, Björn W

    2013-01-01

    This book provides the reader with the knowledge necessary for comprehension of the field of Intelligent Audio Analysis. It firstly introduces standard methods and discusses the typical Intelligent Audio Analysis chain going from audio data to audio features to audio recognition.  Further, an introduction to audio source separation, and enhancement and robustness are given. After the introductory parts, the book shows several applications for the three types of audio: speech, music, and general sound. Each task is shortly introduced, followed by a description of the specific data and methods applied, experiments and results, and a conclusion for this specific task. The books provides benchmark results and standardized test-beds for a broader range of audio analysis tasks. The main focus thereby lies on the parallel advancement of realism in audio analysis, as too often today’s results are overly optimistic owing to idealized testing conditions, and it serves to stimulate synergies arising from transfer of ...

  13. Intelligent Flight Support System (IFSS): A Real-time Intelligent Decision Support Prototype, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The integration of the analysis tools with the advanced visualization capabilities in The Intelligent Flight Support System (IFSS) can provide a unique method for...

  14. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    Science.gov (United States)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-12-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  15. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    International Nuclear Information System (INIS)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-01-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis

  16. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Stoitsis, John [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece)]. E-mail: stoitsis@biosim.ntua.gr; Valavanis, Ioannis [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Mougiakakou, Stavroula G. [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Golemati, Spyretta [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece); Nikita, Alexandra [University of Athens, Medical School 152 28 Athens (Greece); Nikita, Konstantina S. [National Technical University of Athens, School of Electrical and Computer Engineering, Athens 157 71 (Greece)

    2006-12-20

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  17. 16th UK Workshop on Computational Intelligence

    CERN Document Server

    Gegov, Alexander; Jayne, Chrisina; Shen, Qiang

    2017-01-01

    The book is a timely report on advanced methods and applications of computational intelligence systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, evolving systems and machine learning. The individual chapters are based on peer-reviewed contributions presented at the 16th Annual UK Workshop on Computational Intelligence, held on September 7-9, 2016, in Lancaster, UK. The book puts a special emphasis on novels methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.

  18. Computational intelligence techniques in health care

    CERN Document Server

    Zhou, Wengang; Satheesh, P

    2016-01-01

    This book presents research on emerging computational intelligence techniques and tools, with a particular focus on new trends and applications in health care. Healthcare is a multi-faceted domain, which incorporates advanced decision-making, remote monitoring, healthcare logistics, operational excellence and modern information systems. In recent years, the use of computational intelligence methods to address the scale and the complexity of the problems in healthcare has been investigated. This book discusses various computational intelligence methods that are implemented in applications in different areas of healthcare. It includes contributions by practitioners, technology developers and solution providers.

  19. Application of Computational Intelligence Methods to In-Core Fuel Management

    International Nuclear Information System (INIS)

    Erdogan, A.

    2001-01-01

    k e ff higher than reference values were stored as candidate optimum patterns. At the last stage of the work, an alternative loading pattern generator based on genetic algorithm method was developed. In this method, an initial loading pattern is improved by applying the genetic operators to obtain the optimum. The loading patterns obtained from the rule-based and the genetic algorithm methods were compared, and the genetic algorithm was shown to be more successful than the former. It was seen that, it is possible to automate in-core fuel management activities by applying artificial intelligence techniques

  20. A novel method of providing a library of n-mers or biopolymers

    DEFF Research Database (Denmark)

    2012-01-01

    The present invention relates to a method of providing a library of n-mer sequences, wherein the library is composed of an n-mer sequence. Also the invention concerns a method of providing a library of biopolymer sequences having one or more n-mers in common. Further provided are specific primers...

  1. Optimization of DRASTIC method by supervised committee machine artificial intelligence to assess groundwater vulnerability for Maragheh-Bonab plain aquifer, Iran

    Science.gov (United States)

    Fijani, Elham; Nadiri, Ata Allah; Asghari Moghaddam, Asghar; Tsai, Frank T.-C.; Dixon, Barnali

    2013-10-01

    Contamination of wells with nitrate-N (NO3-N) poses various threats to human health. Contamination of groundwater is a complex process and full of uncertainty in regional scale. Development of an integrative vulnerability assessment methodology can be useful to effectively manage (including prioritization of limited resource allocation to monitor high risk areas) and protect this valuable freshwater source. This study introduces a supervised committee machine with artificial intelligence (SCMAI) model to improve the DRASTIC method for groundwater vulnerability assessment for the Maragheh-Bonab plain aquifer in Iran. Four different AI models are considered in the SCMAI model, whose input is the DRASTIC parameters. The SCMAI model improves the committee machine artificial intelligence (CMAI) model by replacing the linear combination in the CMAI with a nonlinear supervised ANN framework. To calibrate the AI models, NO3-N concentration data are divided in two datasets for the training and validation purposes. The target value of the AI models in the training step is the corrected vulnerability indices that relate to the first NO3-N concentration dataset. After model training, the AI models are verified by the second NO3-N concentration dataset. The results show that the four AI models are able to improve the DRASTIC method. Since the best AI model performance is not dominant, the SCMAI model is considered to combine the advantages of individual AI models to achieve the optimal performance. The SCMAI method re-predicts the groundwater vulnerability based on the different AI model prediction values. The results show that the SCMAI outperforms individual AI models and committee machine with artificial intelligence (CMAI) model. The SCMAI model ensures that no water well with high NO3-N levels would be classified as low risk and vice versa. The study concludes that the SCMAI model is an effective model to improve the DRASTIC model and provides a confident estimate of the

  2. Intelligent Search Method Based ACO Techniques for a Multistage Decision Problem EDP/LFP

    Directory of Open Access Journals (Sweden)

    Mostefa RAHLI

    2006-07-01

    Full Text Available The implementation of a numerical library of calculation based optimization in electrical supply networks area is in the centre of the current research orientations, thus, our project in a form given is centred on the development of platform NMSS1. It's a software environment which will preserve many efforts as regards calculations of charge, smoothing curves, losses calculation and economic planning of the generated powers [23].The operational research [17] in a hand and the industrial practice in the other, prove that the means and processes of simulation reached a level of very appreciable reliability and mathematical confidence [4, 5, 14]. It is of this expert observation that many processes make confidence to the results of simulation.The handicaps of this approach or methodology are that it makes base its judgments and handling on simplified assumptions and constraints whose influence was deliberately neglected to be added to the cost to spend [14].By juxtaposing the methods of simulation with artificial intelligence techniques, gathering set of numerical methods acquires an optimal reliability whose assurance can not leave doubt.Software environment NMSS [23] can be a in the field of the rallying techniques of simulation and electric network calculation via a graphic interface. In the same software integrate an AI capability via a module expert system.Our problem is a multistage case where are completely dependant and can't be performed separately.For a multistage problem [21, 22], the results obtained from a credible (large size problem calculation, makes the following question: Could choice of numerical methods set make the calculation of a complete problem using more than two treatments levels, a total error which will be the weakest one possible? It is well-known according to algorithmic policy; each treatment can be characterized by a function called mathematical complexity. This complexity is in fact a coast (a weight overloading

  3. Methods for Model-Based Reasoning within Agent-Based Ambient Intelligence Applications

    NARCIS (Netherlands)

    Bosse, T.; Both, F.; Gerritsen, C.; Hoogendoorn, M.; Treur, J.

    2012-01-01

    Within agent-based Ambient Intelligence applications agents react to humans based on information obtained by sensoring and their knowledge about human functioning. Appropriate types of reactions depend on the extent to which an agent understands the human and is able to interpret the available

  4. Brain anatomical network and intelligence.

    Directory of Open Access Journals (Sweden)

    Yonghui Li

    2009-05-01

    Full Text Available Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence.

  5. Forming of the regional core transport network taking into account the allocation of alternative energy sources based on artificial intelligence methods

    Directory of Open Access Journals (Sweden)

    Marina ZHURAVSKAYA

    2014-12-01

    Full Text Available In the modern world the alternative energy sources, which considerably depend on a region, play more and more significant role. However, the transition of regions to new energy sources lead to the change of transport and logistic network configuration. The formation of optimal core transport network today is a guarantee of the successful economic development of a region tomorrow. The present article studies the issue of advanced core transport network development in a region based on the experience of European and Asian countries and the opportunity to adapt the best foreign experience to Russian conditions. On the basis of artificial intelligence methods for forest industry complex of Sverdlovskaya Oblast the algorithm of problem solution of an optimal logistic infrastructure allocation is offered and some results of a regional transport network are presented. These methods allowed to solve the set task in the conditions of information uncertainty. There are suggestions on the improvement of transport and logistic network in the territory of Sverdlovskaya Oblast. Traditionally the logistics of mineral fuel plays main role in regions development. Actually it is required to develop logistic strategic plans to be able to provide different possibilities of power-supply, flexible enough to change with the population density, transport infrastructure and demographics of different regions. The problem of logistic centers allocation was studied by many authors. The approach, offered by the authors of this paper is to solve the set of tasks by applying artificial intelligence methods, such as fuzzy set theory and genetic algorithms.

  6. Fetal Intelligent Navigation Echocardiography (FINE): a novel method for rapid, simple, and automatic examination of the fetal heart.

    Science.gov (United States)

    Yeo, Lami; Romero, Roberto

    2013-09-01

    To describe a novel method (Fetal Intelligent Navigation Echocardiography (FINE)) for visualization of standard fetal echocardiography views from volume datasets obtained with spatiotemporal image correlation (STIC) and application of 'intelligent navigation' technology. We developed a method to: 1) demonstrate nine cardiac diagnostic planes; and 2) spontaneously navigate the anatomy surrounding each of the nine cardiac diagnostic planes (Virtual Intelligent Sonographer Assistance (VIS-Assistance®)). The method consists of marking seven anatomical structures of the fetal heart. The following echocardiography views are then automatically generated: 1) four chamber; 2) five chamber; 3) left ventricular outflow tract; 4) short-axis view of great vessels/right ventricular outflow tract; 5) three vessels and trachea; 6) abdomen/stomach; 7) ductal arch; 8) aortic arch; and 9) superior and inferior vena cava. The FINE method was tested in a separate set of 50 STIC volumes of normal hearts (18.6-37.2 weeks of gestation), and visualization rates for fetal echocardiography views using diagnostic planes and/or VIS-Assistance® were calculated. To examine the feasibility of identifying abnormal cardiac anatomy, we tested the method in four cases with proven congenital heart defects (coarctation of aorta, tetralogy of Fallot, transposition of great vessels and pulmonary atresia with intact ventricular septum). In normal cases, the FINE method was able to generate nine fetal echocardiography views using: 1) diagnostic planes in 78-100% of cases; 2) VIS-Assistance® in 98-100% of cases; and 3) a combination of diagnostic planes and/or VIS-Assistance® in 98-100% of cases. In all four abnormal cases, the FINE method demonstrated evidence of abnormal fetal cardiac anatomy. The FINE method can be used to visualize nine standard fetal echocardiography views in normal hearts by applying 'intelligent navigation' technology to STIC volume datasets. This method can simplify

  7. Advanced intelligence and mechanism approach

    Institute of Scientific and Technical Information of China (English)

    ZHONG Yixin

    2007-01-01

    Advanced intelligence will feature the intelligence research in next 50 years.An understanding of the concept of advanced intelligence as well as its importance will be provided first,and detailed analysis on an approach,the mechanism approach.suitable to the advanced intelligence research will then be flolowed.And the mutual relationship among mechanism approach,traditional approaches existed in artificial intelligence research,and the cognitive informatics will be discussed.It is interesting to discover that mechanism approach is a good one to the Advanced Intelligence research and a tmified form of the existed approaches to artificial intelligence.

  8. Realization of Personalized Services for Intelligent Residential Space based on User Identification Method using Sequential Walking Footprints

    Directory of Open Access Journals (Sweden)

    Jin-Woo Jung

    2005-04-01

    Full Text Available A new human-friendly assistive home environment, Intelligent Sweet Home (ISH, developed at KAIST, Korea for testing advanced concepts for independent living of the elderly/the physically handicapped. The concept of ISH is to consider the home itself as an intelligent robot. ISH always checks the intention or health status of the resident. Therefore, ISH can do actively the most proper services considering the resident's life-style by the detected intention or emergency information. But, when there are more than two residents, ISH cannot consider the residents' characteristics or tastes if ISH cannot identify who he/she is before. To realize a personalized service system in the intelligent residential space like ISH, we deal with a human-friendly user identification method for ubiquitous computing environment, specially focused on dynamic human footprint recognition. And then, we address some case studies of personalized services that have been experienced by Human-friendly Welfare Robot System research center, KAIST.

  9. Analysis of operator support method based on intelligent dynamic interlock in lead-cooled fast reactor simulator

    International Nuclear Information System (INIS)

    Xu, Peng; Wang, Jianye; Yang, Minghan; Wang, Weitian; Bai, Yunqing; Song, Yong

    2017-01-01

    Highlights: • We development an operator support method based on intelligent dynamic interlock. • We offer an integrated aid system to reduce the working strength of operators. • The method can help operators avoid dangerous, irreversible operation. • This method can be used in the fusion research reactor in the further. - Abstract: In nuclear systems, operators have to carry out corrective actions when abnormal situations occur. However, operators might make mistakes under pressure. In order to avoid serious consequences of the human errors, a new method for operators support based on intelligent dynamic interlock was proposed. The new method based on full digital instrumentation and control system, contains real-time alarm analysis process, decision support process and automatic safety interlock process. Once abnormal conditions occur, necessary safety interlock parameter based on analysis of real-time alarm and decision support process can be loaded into human-machine interfaces and controllers automatically, and avoid human errors effectively. Furthermore, the new method can make recommendations for further use and development of this technique in nuclear power plant or fusion research reactor.

  10. A proposed method to estimate premorbid full scale intelligence quotient (FSIQ) for the Canadian Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) using demographic and combined estimation procedures.

    Science.gov (United States)

    Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H

    2007-11-01

    Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.

  11. Event classification and optimization methods using artificial intelligence and other relevant techniques: Sharing the experiences

    Science.gov (United States)

    Mohamed, Abdul Aziz; Hasan, Abu Bakar; Ghazali, Abu Bakar Mhd.

    2017-01-01

    Classification of large data into respected classes or groups could be carried out with the help of artificial intelligence (AI) tools readily available in the market. To get the optimum or best results, optimization tool could be applied on those data. Classification and optimization have been used by researchers throughout their works, and the outcomes were very encouraging indeed. Here, the authors are trying to share what they have experienced in three different areas of applied research.

  12. Development of a simplified method for intelligent glazed façade design under different control strategies and verified by building simulation tool BSim

    DEFF Research Database (Denmark)

    Liu, Mingzhe; Wittchen, Kim Bjarne; Heiselberg, Per

    2014-01-01

    The research aims to develop a simplified calculation method for intelligent glazed facade under different control conditions (night shutter, solar shading and natural ventilation) to simulate the energy performance and indoor environment of an office room installed with the intelligent facade......, it is possible to calculate the whole year performance of a room or building with intelligent glazed façade, which makes it a less time consuming tool to investigate the performance of the intelligent façade under different control strategies in the design stage with acceptable accuracy. Results showed good....... The method took the angle dependence of the solar characteristic into account, including the simplified hourly building model developed according to EN 13790 to evaluate the influence of the controlled façade on both the indoor environment (indoor air temperature, solar transmittance through the façade...

  13. A multi-agent based intelligent configuration method for aircraft fleet maintenance personnel

    Directory of Open Access Journals (Sweden)

    Feng Qiang

    2014-04-01

    Full Text Available A multi-agent based fleet maintenance personnel configuration method is proposed to solve the mission oriented aircraft fleet maintenance personnel configuration problem. The maintenance process of an aircraft fleet is analyzed first. In the process each aircraft contains multiple parts, and different parts are repaired by personnel with different majors and levels. The factors and their relationship involved in the process of maintenance are analyzed and discussed. Then the whole maintenance process is described as a 3-layer multi-agent system (MAS model. A communication and reasoning strategy among the agents is put forward. A fleet maintenance personnel configuration algorithm is proposed based on contract net protocol (CNP. Finally, a fleet of 10 aircraft is studied for verification purposes. A mission type with 3 waves of continuous dispatch is imaged. Compared with the traditional methods that can just provide configuration results, the proposed method can provide optimal maintenance strategies as well.

  14. Social Intelligence and Top Management Team: An Exploratory Study of External Knowledge Acquisition for Strategic Change in Global IT Service Providers in India

    Science.gov (United States)

    Kong, Eric; Chadee, Doren; Raman, Revti

    2012-01-01

    This paper focuses on the processes by which firms, particularly knowledge intensive firms, can augment their overall knowledge stock by tapping into external sources of knowledge. It is argued that Top Management Teams' (TMTs') social intelligence is a critical learning capability in acquiring external knowledge that leads to strategic change.…

  15. Intelligent Flow Control Valve

    Science.gov (United States)

    Kelley, Anthony R (Inventor)

    2015-01-01

    The present invention is an intelligent flow control valve which may be inserted into the flow coming out of a pipe and activated to provide a method to stop, measure, and meter flow coming from the open or possibly broken pipe. The intelligent flow control valve may be used to stop the flow while repairs are made. Once repairs have been made, the valve may be removed or used as a control valve to meter the amount of flow from inside the pipe. With the addition of instrumentation, the valve may also be used as a variable area flow meter and flow controller programmed based upon flowing conditions. With robotic additions, the valve may be configured to crawl into a desired pipe location, anchor itself, and activate flow control or metering remotely.

  16. Study on intelligence fault diagnosis method for nuclear power plant equipment based on rough set and fuzzy neural network

    International Nuclear Information System (INIS)

    Liu Yongkuo; Xia Hong; Xie Chunli; Chen Zhihui; Chen Hongxia

    2007-01-01

    Rough set theory and fuzzy neural network are combined, to take full advantages of the two of them. Based on the reduction technology to knowledge of Rough set method, and by drawing the simple rule from a large number of initial data, the fuzzy neural network was set up, which was with better topological structure, improved study speed, accurate judgment, strong fault-tolerant ability, and more practical. In order to test the validity of the method, the inverted U-tubes break accident of Steam Generator and etc are used as examples, and many simulation experiments are performed. The test result shows that it is feasible to incorporate the fault intelligence diagnosis method based on rough set and fuzzy neural network in the nuclear power plant equipment, and the method is simple and convenience, with small calculation amount and reliable result. (authors)

  17. Modeling, control, and simulation of grid connected intelligent hybrid battery/photovoltaic system using new hybrid fuzzy-neural method.

    Science.gov (United States)

    Rezvani, Alireza; Khalili, Abbas; Mazareie, Alireza; Gandomkar, Majid

    2016-07-01

    Nowadays, photovoltaic (PV) generation is growing increasingly fast as a renewable energy source. Nevertheless, the drawback of the PV system is its dependence on weather conditions. Therefore, battery energy storage (BES) can be considered to assist for a stable and reliable output from PV generation system for loads and improve the dynamic performance of the whole generation system in grid connected mode. In this paper, a novel topology of intelligent hybrid generation systems with PV and BES in a DC-coupled structure is presented. Each photovoltaic cell has a specific point named maximum power point on its operational curve (i.e. current-voltage or power-voltage curve) in which it can generate maximum power. Irradiance and temperature changes affect these operational curves. Therefore, the nonlinear characteristic of maximum power point to environment has caused to development of different maximum power point tracking techniques. In order to capture the maximum power point (MPP), a hybrid fuzzy-neural maximum power point tracking (MPPT) method is applied in the PV system. Obtained results represent the effectiveness and superiority of the proposed method, and the average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison to the conventional methods. It has the advantages of robustness, fast response and good performance. A detailed mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Secular gains in fluid intelligence: evidence from the Culture-Fair intelligence test.

    Science.gov (United States)

    Colom, Roberto; García-López, Oscar

    2003-01-01

    There is no doubt about the reality of the secular increase in cognitive test scores. However, there is disagreement about a key issue: does the observed increase reflect a genuine upward trend in intelligence? Evidence from the Raven test is clear, although there are some doubts about its adequacy as a fine-grained measure of fluid intelligence. Evidence from the so-called 'method of correlated vectors' is much less clear. When a crystallized battery is considered, the results leave little doubt: the increase does not reflect gains in general intelligence. However, when a fluid battery is analysed, the increase does reflect gains in general intelligence. The present study uses one of the best available measures of fluid intelligence (the Culture-Fair intelligence test) to provide new evidence for the secular increase in fluid intelligence, beyond the findings from the Raven test and the method of correlated vectors. A total of 4498 Spanish high school students and high school graduates were tested within a time interval of 20 and 23 years, respectively. The results show that there is a clear upward trend in intelligence. Moreover, students show an average increase equivalent to 6 IQ points, while graduates show an average increase of 4 IQ points. Therefore, more selected people (graduates) show a smaller increase than less selected people (students). Some implications are discussed.

  19. System and Method for Providing Vertical Profile Measurements of Atmospheric Gases

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A system and method for using an air collection device to collect a continuous air sample as the device descends through the atmosphere are provided. The air...

  20. Interconnection blocks: a method for providing reusable, rapid, multiple, aligned and planar microfluidic interconnections

    DEFF Research Database (Denmark)

    Sabourin, David; Snakenborg, Detlef; Dufva, Hans Martin

    2009-01-01

    In this paper a method is presented for creating 'interconnection blocks' that are re-usable and provide multiple, aligned and planar microfluidic interconnections. Interconnection blocks made from polydimethylsiloxane allow rapid testing of microfluidic chips and unobstructed microfluidic observ...

  1. Intelligent Tutor

    Science.gov (United States)

    1990-01-01

    NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

  2. Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence

    International Nuclear Information System (INIS)

    Fukatsu, Hiroshi; Naganawa, Shinji; Yumura, Shinnichiro

    2008-01-01

    This study was aimed to validate the performance of a novel image compression method using a neural network to achieve a lossless compression. The encoding consists of the following blocks: a prediction block; a residual data calculation block; a transformation and quantization block; an organization and modification block; and an entropy encoding block. The predicted image is divided into four macro-blocks using the original image for teaching; and then redivided into sixteen sub-blocks. The predicted image is compared to the original image to create the residual image. The spatial and frequency data of the residual image are compared and transformed. Chest radiography, computed tomography (CT), magnetic resonance imaging, positron emission tomography, radioisotope mammography, ultrasonography, and digital subtraction angiography images were compressed using the AIC lossless compression method; and the compression rates were calculated. The compression rates were around 15:1 for chest radiography and mammography, 12:1 for CT, and around 6:1 for other images. This method thus enables greater lossless compression than the conventional methods. This novel method should improve the efficiency of handling of the increasing volume of medical imaging data. (author)

  3. Systems and methods for providing power to a load based upon a control strategy

    Science.gov (United States)

    Perisic, Milun; Kajouke, Lateef A; Ransom, Ray M

    2013-12-24

    Systems and methods are provided for an electrical system. The electrical system includes a load, an interface configured to receive a voltage from a voltage source, and a controller configured to receive the voltage from the voltage source through the interface and to provide a voltage and current to the load. Wherein, when the controller is in a constant voltage mode, the controller provides a constant voltage to the load, when the controller is in a constant current mode, the controller provides a constant current to the load, and when the controller is in a constant power mode, the controller provides a constant power to the load.

  4. Firefly as a novel swarm intelligence variable selection method in spectroscopy.

    Science.gov (United States)

    Goodarzi, Mohammad; dos Santos Coelho, Leandro

    2014-12-10

    A critical step in multivariate calibration is wavelength selection, which is used to build models with better prediction performance when applied to spectral data. Up to now, many feature selection techniques have been developed. Among all different types of feature selection techniques, those based on swarm intelligence optimization methodologies are more interesting since they are usually simulated based on animal and insect life behavior to, e.g., find the shortest path between a food source and their nests. This decision is made by a crowd, leading to a more robust model with less falling in local minima during the optimization cycle. This paper represents a novel feature selection approach to the selection of spectroscopic data, leading to more robust calibration models. The performance of the firefly algorithm, a swarm intelligence paradigm, was evaluated and compared with genetic algorithm and particle swarm optimization. All three techniques were coupled with partial least squares (PLS) and applied to three spectroscopic data sets. They demonstrate improved prediction results in comparison to when only a PLS model was built using all wavelengths. Results show that firefly algorithm as a novel swarm paradigm leads to a lower number of selected wavelengths while the prediction performance of built PLS stays the same. Copyright © 2014. Published by Elsevier B.V.

  5. Enhancing the stabilization of aircraft pitch motion control via intelligent and classical method

    Science.gov (United States)

    Lukman, H.; Munawwarah, S.; Azizan, A.; Yakub, F.; Zaki, S. A.; Rasid, Z. A.

    2017-12-01

    The pitching movement of an aircraft is very important to ensure passengers are intrinsically safe and the aircraft achieve its maximum stability. The equations governing the motion of an aircraft are a complex set of six nonlinear coupled differential equations. Under certain assumptions, it can be decoupled and linearized into longitudinal and lateral equations. Pitch control is a longitudinal problem and thus, only the longitudinal dynamics equations are involved in this system. It is a third order nonlinear system, which is linearized about the operating point. The system is also inherently unstable due to the presence of a free integrator. Because of this, a feedback controller is added in order to solve this problem and enhance the system performance. This study uses two approaches in designing controller: a conventional controller and an intelligent controller. The pitch control scheme consists of proportional, integral and derivatives (PID) for conventional controller and fuzzy logic control (FLC) for intelligent controller. Throughout the paper, the performance of the presented controllers are investigated and compared based on the common criteria of step response. Simulation results have been obtained and analysed by using Matlab and Simulink software. The study shows that FLC controller has higher ability to control and stabilize the aircraft's pitch angle as compared to PID controller.

  6. Method and Apparatus Providing Deception and/or Altered Operation in an Information System Operating System

    Science.gov (United States)

    Cohen, Fred; Rogers, Deanna T.; Neagoe, Vicentiu

    2008-10-14

    A method and/or system and/or apparatus providing deception and/or execution alteration in an information system. In specific embodiments, deceptions and/or protections are provided by intercepting and/or modifying operation of one or more system calls of an operating system.

  7. Provider Payment Trends and Methods in the Massachusetts Health Care System

    OpenAIRE

    Allison Barrett; Timothy Lake

    2010-01-01

    This report investigates provider payment methods in Massachusetts. Payments include fee-for-service, the predominant model; global payments, which pay providers a single fee for all or most required services during a contract period; and pay-for-performance models, which layer quality incentives onto payments.

  8. 47 CFR 51.329 - Notice of network changes: Methods for providing notice.

    Science.gov (United States)

    2010-10-01

    ... 47 Telecommunication 3 2010-10-01 2010-10-01 false Notice of network changes: Methods for providing notice. 51.329 Section 51.329 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED...) Filing a public notice with the Commission; or (2) Providing public notice through industry fora...

  9. Determining the Organizational Intelligence Level of Hospitals in Our Region

    Directory of Open Access Journals (Sweden)

    Khayat Moghadam S

    2013-10-01

    Full Text Available Objectives: A new and unique tool for survival of organizations among their competitors is the use of organizational intelligence; Organizational intelligence means having a comprehensive knowledge of all the environmental factors that affect on the organization. This research  is one of the few studies with the aim of determine the organizational intelligence level of hospitals and ranking of organizational intelligence components to enable administrators to provide more accurate identification of strengths and weaknesses and take more effective steps to improve service delivery. Materials and Methods: This is a descriptive-analytical and applicable study performed in the 2012 at 12 General Hospital related to Mashhad University of Medical Sciences. Data collection was performed by Albrecht organizational intelligence questionnaire. The data gathering tool was the questionnaire Albrecht Organizational Intelligence. The collected Data were analyzed using T-test and Smirnov test with SPSS-16 software. The significance level for all tests was considered 0.05. Results: All components of organizational intelligence were in the optimum status. Component of Shared fate gained the first rank and component of knowledge Deployment gained the last rank. Conclusion: Ranking of organizational intelligence components is different in hospitals of the province and the county; representing different features and conditions. Considering the importance of organizational intelligence role in the promotion of organization, hospital managers can take active steps to improve organizational intelligence based on done rankings.

  10. Artificial intelligence in radiology.

    Science.gov (United States)

    Hosny, Ahmed; Parmar, Chintan; Quackenbush, John; Schwartz, Lawrence H; Aerts, Hugo J W L

    2018-05-17

    Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

  11. Intelligent mechatronics; Intelligent mechatronics

    Energy Technology Data Exchange (ETDEWEB)

    Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

    1995-10-01

    Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

  12. Fluid intelligence: A brief history.

    Science.gov (United States)

    Kent, Phillip

    2017-01-01

    The concept of fluid and crystallized intelligence was introduced to the psychological community approximately 75 years ago by Raymond B. Cattell, and it continues to be an area of active research and controversy. The purpose of this paper is to provide a brief overview of the origin of the concept, early efforts to define intelligence and uses of intelligence tests to address pressing social issues, and the ongoing controversies associated with fluid intelligence and the structure of intelligence. The putative neuropsychological underpinnings and neurological substrates of fluid intelligence are discussed.

  13. System and Method for Providing a Climate Data Analytic Services Application Programming Interface Distribution Package

    Science.gov (United States)

    Schnase, John L. (Inventor); Duffy, Daniel Q. (Inventor); Tamkin, Glenn S. (Inventor)

    2016-01-01

    A system, method and computer-readable storage devices for providing a climate data analytic services application programming interface distribution package. The example system can provide various components. The system provides a climate data analytic services application programming interface library that enables software applications running on a client device to invoke the capabilities of a climate data analytic service. The system provides a command-line interface that provides a means of interacting with a climate data analytic service by issuing commands directly to the system's server interface. The system provides sample programs that call on the capabilities of the application programming interface library and can be used as templates for the construction of new client applications. The system can also provide test utilities, build utilities, service integration utilities, and documentation.

  14. AN INTELLIGENT NEURO-FUZZY TERMINAL SLIDING MODE CONTROL METHOD WITH APPLICATION TO ATOMIC FORCE MICROSCOPE

    Directory of Open Access Journals (Sweden)

    Seied Yasser Nikoo

    2016-11-01

    Full Text Available In this paper, a neuro-fuzzy fast terminal sliding mode control method is proposed for controlling a class of nonlinear systems with bounded uncertainties and disturbances. In this method, a nonlinear terminal sliding surface is firstly designed. Then, this sliding surface is considered as input for an adaptive neuro-fuzzy inference system which is the main controller. A proportinal-integral-derivative controller is also used to asist the neuro-fuzzy controller in order to improve the performance of the system at the begining stage of control operation. In addition, bee algorithm is used in this paper to update the weights of neuro-fuzzy system as well as the parameters of the proportinal-integral-derivative controller. The proposed control scheme is simulated for vibration control in a model of atomic force microscope system and the results are compared with conventional sliding mode controllers. The simulation results show that the chattering effect in the proposed controller is decreased in comparison with the sliding mode and the terminal sliding mode controllers. Also, the method provides the advantages of fast convergence and low model dependency compared to the conventional methods.

  15. Multiple intelligences: Can they be measured?

    OpenAIRE

    Kirsi Tirri; Petri Nokelainen; Erkki Komulainen

    2013-01-01

    This paper is about issues relating to the assessment of multiple intelligences. The first section introduces the authors’ work on building measures of multiple intelligences and moral sensitivities. It also provides a conceptual definition of multiple intelligences based on Multiple Intelligences theory by Howard Gardner (1983). The second section discusses the context specificity of intelligences and alternative approaches to measuring multiple intelligences. The third section analyses the ...

  16. How to Improve Artificial Intelligence through Web

    OpenAIRE

    Adrian Lupasc

    2005-01-01

    Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers may make their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced into Web Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logic layer. The Intelligent Wireless Web’s significant potential for ra...

  17. How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods

    Directory of Open Access Journals (Sweden)

    Grossi Enzo

    2006-05-01

    Full Text Available Abstract Background In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years Discussion The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. Summary The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level.

  18. How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods.

    Science.gov (United States)

    Grossi, Enzo

    2006-05-03

    In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level.

  19. Intelligent robot action planning

    Energy Technology Data Exchange (ETDEWEB)

    Vamos, T; Siegler, A

    1982-01-01

    Action planning methods used in intelligent robot control are discussed. Planning is accomplished through environment understanding, environment representation, task understanding and planning, motion analysis and man-machine communication. These fields are analysed in detail. The frames of an intelligent motion planning system are presented. Graphic simulation of the robot's environment and motion is used to support the planning. 14 references.

  20. Applying Multiple Intelligences

    Science.gov (United States)

    Christodoulou, Joanna A.

    2009-01-01

    The ideas of multiple intelligences introduced by Howard Gardner of Harvard University more than 25 years ago have taken form in many ways, both in schools and in other sometimes-surprising settings. The silver anniversary of Gardner's learning theory provides an opportunity to reflect on the ways multiple intelligences theory has taken form and…

  1. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

    We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

  2. Interconnection blocks: a method for providing reusable, rapid, multiple, aligned and planar microfluidic interconnections

    International Nuclear Information System (INIS)

    Sabourin, D; Snakenborg, D; Dufva, M

    2009-01-01

    In this paper a method is presented for creating 'interconnection blocks' that are re-usable and provide multiple, aligned and planar microfluidic interconnections. Interconnection blocks made from polydimethylsiloxane allow rapid testing of microfluidic chips and unobstructed microfluidic observation. The interconnection block method is scalable, flexible and supports high interconnection density. The average pressure limit of the interconnection block was near 5.5 bar and all individual results were well above the 2 bar threshold considered applicable to most microfluidic applications

  3. Configurable memory system and method for providing atomic counting operations in a memory device

    Science.gov (United States)

    Bellofatto, Ralph E.; Gara, Alan G.; Giampapa, Mark E.; Ohmacht, Martin

    2010-09-14

    A memory system and method for providing atomic memory-based counter operations to operating systems and applications that make most efficient use of counter-backing memory and virtual and physical address space, while simplifying operating system memory management, and enabling the counter-backing memory to be used for purposes other than counter-backing storage when desired. The encoding and address decoding enabled by the invention provides all this functionality through a combination of software and hardware.

  4. Method of immobilizing weapons plutonium to provide a durable, disposable waste product

    Science.gov (United States)

    Ewing, Rodney C.; Lutze, Werner; Weber, William J.

    1996-01-01

    A method of atomic scale fixation and immobilization of plutonium to provide a durable waste product. Plutonium is provided in the form of either PuO.sub.2 or Pu(NO.sub.3).sub.4 and is mixed with and SiO.sub.2. The resulting mixture is cold pressed and then heated under pressure to form (Zr,Pu)SiO.sub.4 as the waste product.

  5. Cloud Service Provider Methods for Managing Insider Threats: Analysis Phase 1

    Science.gov (United States)

    2013-11-01

    of Standards and Technology (NIST) Special Publication 800-145 (NIST SP 800-145) defines three types of cloud services : Software as a Service ( SaaS ...among these three models. NIST SP 800-145 describes the three service models as follows: SaaS —The capability provided to the consumer is to use the...Cloud Service Provider Methods for Managing Insider Threats: Analysis Phase I Greg Porter November 2013 TECHNICAL NOTE CMU/SEI-2013-TN-020

  6. Understanding the Globalization of Intelligence

    DEFF Research Database (Denmark)

    Svendsen, Adam David Morgan

    "This book provides an introduction to the complexities of contemporary Western Intelligence and its dynamics during an era of globalization. Towards an understanding of the globalization of intelligence process, Svendsen focuses on the secretive phenomenon of international or foreign intelligence...... cooperation ('liaison'), as it occurs in both theory and practice. Reflecting a complex coexistence plurality of several different and overlapping concepts in action, the challenging process of the globalization of intelligence emerges as essential for complex issue management purposes during a globalized era...

  7. Advances in chaos theory and intelligent control

    CERN Document Server

    Vaidyanathan, Sundarapandian

    2016-01-01

    The book reports on the latest advances in and applications of chaos theory and intelligent control. Written by eminent scientists and active researchers and using a clear, matter-of-fact style, it covers advanced theories, methods, and applications in a variety of research areas, and explains key concepts in modeling, analysis, and control of chaotic and hyperchaotic systems. Topics include fractional chaotic systems, chaos control, chaos synchronization, memristors, jerk circuits, chaotic systems with hidden attractors, mechanical and biological chaos, and circuit realization of chaotic systems. The book further covers fuzzy logic controllers, evolutionary algorithms, swarm intelligence, and petri nets among other topics. Not only does it provide the readers with chaos fundamentals and intelligent control-based algorithms; it also discusses key applications of chaos as well as multidisciplinary solutions developed via intelligent control. The book is a timely and comprehensive reference guide for graduate s...

  8. Social intelligence, human intelligence and niche construction.

    Science.gov (United States)

    Sterelny, Kim

    2007-04-29

    This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

  9. Application of stochastic and artificial intelligence methods for nuclear material identification

    International Nuclear Information System (INIS)

    Pozzi, S.; Segovia, F.J.

    1999-01-01

    Nuclear materials safeguard efforts necessitate the use of non-destructive methods to determine the attributes of fissile samples enclosed in special, non-accessible containers. To this end, a large variety of methods has been developed at the Oak Ridge National Laboratory (ORNL) and elsewhere. Usually, a given set of statistics of the stochastic neutron-photon coupled field, such as source-detector, detector-detector cross correlation functions, and multiplicities are measured over a range of known samples to develop calibration algorithms. In this manner, the attributes of unknown samples can be inferred by the use of the calibration results. The organization of this paper is as follows: Section 2 describes the Monte Carlo simulations of source-detector cross correlation functions for a set of uranium metallic samples interrogated by the neutrons and photons from a 252 Cf source. From this database, a set of features is extracted in Section 3. The use of neural networks (NN) and genertic programming to provide sample mass and enrichment values from the input sets of features is illustrated in Sections 4 and 5, respectivelyl. Section 6 is a comparison of the results, while Section 7 is a brief summary of the work

  10. PERSONALIZED MEDICINE: GENOME, ELECTRONIC HEALTH AND INTELLIGENT SYSTEMS. PART 2. MOLECULAR GENETICS AND METHODS OF INTELLECTUAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    B. A. Kobrinskii

    2017-01-01

    Full Text Available The transition to personalized medicine in practical terms should combine the problems of molecular-genetic predisposition to diseases with transient states in the organism in the direction of possible pathology. Classification and monitoring of the state can be  effectively carried out using artificial intelligence methods. Various intellectual approaches are considered in different conditions for  monitoring patient.

  11. Attitude Determination Method by Fusing Single Antenna GPS and Low Cost MEMS Sensors Using Intelligent Kalman Filter Algorithm

    Directory of Open Access Journals (Sweden)

    Lei Wang

    2017-01-01

    Full Text Available For meeting the demands of cost and size for micronavigation system, a combined attitude determination approach with sensor fusion algorithm and intelligent Kalman filter (IKF on low cost Micro-Electro-Mechanical System (MEMS gyroscope, accelerometer, and magnetometer and single antenna Global Positioning System (GPS is proposed. The effective calibration method is performed to compensate the effect of errors in low cost MEMS Inertial Measurement Unit (IMU. The different control strategies fusing the MEMS multisensors are designed. The yaw angle fusing gyroscope, accelerometer, and magnetometer algorithm is estimated accurately under GPS failure and unavailable sideslip situations. For resolving robust control and characters of the uncertain noise statistics influence, the high gain scale of IKF is adjusted by fuzzy controller in the transition process and steady state to achieve faster convergence and accurate estimation. The experiments comparing different MEMS sensors and fusion algorithms are implemented to verify the validity of the proposed approach.

  12. Intelligent Method for Identifying Driving Risk Based on V2V Multisource Big Data

    Directory of Open Access Journals (Sweden)

    Jinshuan Peng

    2018-01-01

    Full Text Available Risky driving behavior is a major cause of traffic conflicts, which can develop into road traffic accidents, making the timely and accurate identification of such behavior essential to road safety. A platform was therefore established for analyzing the driving behavior of 20 professional drivers in field tests, in which overclose car following and lane departure were used as typical risky driving behaviors. Characterization parameters for identification were screened and used to determine threshold values and an appropriate time window for identification. A neural network-Bayesian filter identification model was established and data samples were selected to identify risky driving behavior and evaluate the identification efficiency of the model. The results obtained indicated a successful identification rate of 83.6% when the neural network model was solely used to identify risky driving behavior, but this could be increased to 92.46% once corrected by the Bayesian filter. This has important theoretical and practical significance in relation to evaluating the efficiency of existing driver assist systems, as well as the development of future intelligent driving systems.

  13. The Impact of Contextual Background Fusion on Perceived Value and Quality of Unclassified Terrorism Intelligence

    National Research Council Canada - National Science Library

    Eaneff, Charles

    2007-01-01

    ...). Simply pushing intelligence products to NTR is not enough, NTR must possess adequate contextual background in order to effectively utilize intelligence provided by the Intelligence Community (IC...

  14. Intelligence analysis in corporate security

    Directory of Open Access Journals (Sweden)

    Manojlović Dragan

    2014-01-01

    Full Text Available Located in the survey indicate that the protection of a corporation, its internal and external interest from the perspective of quality data for intelligence analysis and the need for kroporacije and corporate security. Furthermore, the results indicate that the application is not only practical knowledge of intelligence analysis, but also its scientific knowledge, provides epistemologically oriented critique of traditional techniques undertaken in corporate security in connection with the analysis of the challenges, risks and threats. On the question of whether it can and should be understood only as a form of corporate espionage, any aspect of such a new concept in the theory and practice of corporate security, competitive intelligence activities, as well as an activity or involves a range of different methods and techniques meaningful and expedient activities to be implemented integrally and continuously within corporate security, given the multiple responses to the work. The privatization of intelligence activities as an irreversible process that was decades ago engulfed the western hemisphere, in the first decade of the third millennium has been accepted in Europe, in the sense that corporations at national and multinational levels of system intelligence analysis used not only for your safety but also for the competition, and nothing and less for growth companies and profits. It has become a resource that helps control their managers in corporations to make timely and appropriate decisions. Research has shown that intelligence analysis in corporate security one factor that brings the diversity of the people and give corporations an advantage not only in time, but much more on the market and product.

  15. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

    This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

  16. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  17. Fault detection and analysis in nuclear research facility using artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Ghazali, Abu Bakar, E-mail: Abakar@uniten.edu.my [Department of Electronics & Communication, College of Engineering, Universiti Tenaga Nasional, 43009 Kajang, Selangor (Malaysia); Ibrahim, Maslina Mohd [Instrumentation Program, Malaysian Nuclear Agency, Bangi (Malaysia)

    2016-01-22

    In this article, an online detection of transducer and actuator condition is discussed. A case study is on the reading of area radiation monitor (ARM) installed at the chimney of PUSPATI TRIGA nuclear reactor building, located at Bangi, Malaysia. There are at least five categories of abnormal ARM reading that could happen during the transducer failure, namely either the reading becomes very high, or very low/ zero, or with high fluctuation and noise. Moreover, the reading may be significantly higher or significantly lower as compared to the normal reading. An artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are good methods for modeling this plant dynamics. The failure of equipment is based on ARM reading so it is then to compare with the estimated ARM data from ANN/ ANFIS function. The failure categories in either ‘yes’ or ‘no’ state are obtained from a comparison between the actual online data and the estimated output from ANN/ ANFIS function. It is found that this system design can correctly report the condition of ARM equipment in a simulated environment and later be implemented for online monitoring. This approach can also be extended to other transducers, such as the temperature profile of reactor core and also to include other critical actuator conditions such as the valves and pumps in the reactor facility provided that the failure symptoms are clearly defined.

  18. A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals.

    Science.gov (United States)

    Castañón-Puga, Manuel; Salazar, Abby Stephanie; Aguilar, Leocundo; Gaxiola-Pacheco, Carelia; Licea, Guillermo

    2015-12-02

    The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs). This approach takes advantage of wireless local area networks (WLANs) over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi-Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

  19. A Novel Hybrid Intelligent Indoor Location Method for Mobile Devices by Zones Using Wi-Fi Signals

    Directory of Open Access Journals (Sweden)

    Manuel Castañón–Puga

    2015-12-01

    Full Text Available The increasing use of mobile devices in indoor spaces brings challenges to location methods. This work presents a hybrid intelligent method based on data mining and Type-2 fuzzy logic to locate mobile devices in an indoor space by zones using Wi-Fi signals from selected access points (APs. This approach takes advantage of wireless local area networks (WLANs over other types of architectures and implements the complete method in a mobile application using the developed tools. Besides, the proposed approach is validated by experimental data obtained from case studies and the cross-validation technique. For the purpose of generating the fuzzy rules that conform to the Takagi–Sugeno fuzzy system structure, a semi-supervised data mining technique called subtractive clustering is used. This algorithm finds centers of clusters from the radius map given by the collected signals from APs. Measurements of Wi-Fi signals can be noisy due to several factors mentioned in this work, so this method proposed the use of Type-2 fuzzy logic for modeling and dealing with such uncertain information.

  20. A Study of Security Awareness Information Delivery within the Defense Intelligence Community

    Science.gov (United States)

    Krasley, Paul F.

    2011-01-01

    Due to limited resources and inconsistent guidance from the U.S. Federal Government, Department of Defense, and multiple environments within the intelligence community, the defense intelligence agencies each developed their own methods to deliver security awareness information. These multiple delivery methods may be providing different levels of…

  1. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

    Science.gov (United States)

    Osipov, Gennady

    2013-04-01

    We propose a solution to the problem of exploration of various mineral resource deposits, determination of their forms / classification of types (oil, gas, minerals, gold, etc.) with the help of satellite photography of the region of interest. Images received from satellite are processed and analyzed to reveal the presence of specific signs of deposits of various minerals. Course of data processing and making forecast can be divided into some stages: Pre-processing of images. Normalization of color and luminosity characteristics, determination of the necessary contrast level and integration of a great number of separate photos into a single map of the region are performed. Construction of semantic map image. Recognition of bitmapped image and allocation of objects and primitives known to system are realized. Intelligent analysis. At this stage acquired information is analyzed with the help of a knowledge base, which contain so-called "attention landscapes" of experts. Used methods of recognition and identification of images: a) combined method of image recognition, b)semantic analysis of posterized images, c) reconstruction of three-dimensional objects from bitmapped images, d)cognitive technology of processing and interpretation of images. This stage is fundamentally new and it distinguishes suggested technology from all others. Automatic registration of allocation of experts` attention - registration of so-called "attention landscape" of experts - is the base of the technology. Landscapes of attention are, essentially, highly effective filters that cut off unnecessary information and emphasize exactly the factors used by an expert for making a decision. The technology based on denoted principles involves the next stages, which are implemented in corresponding program agents. Training mode -> Creation of base of ophthalmologic images (OI) -> Processing and making generalized OI (GOI) -> Mode of recognition and interpretation of unknown images. Training mode

  2. THIRD PARTY LOGISTIC SERVICE PROVIDER SELECTION USING FUZZY AHP AND TOPSIS METHOD

    Directory of Open Access Journals (Sweden)

    Golam Kabir

    2012-03-01

    Full Text Available The use of third party logistic(3PL services providers is increasing globally to accomplish the strategic objectives. In the increasingly competitive environment, logistics strategic management requires systematic and structured approach to have cutting edge over the rival. Logistics service provider selection is a complex multi-criteria decision making process; in which, decision makers have to deals with the optimization of conflicting objectives such as quality, cost, and delivery time. In this paper, fuzzy analytic hierarchy process (FAHP approach based on technique for order preference by similarity to ideal solution (TOPSIS method has been proposed for evaluating and selecting an appropriate logistics service provider, where the ratings of each alternative and importance weight of each criterion are expressed in triangular fuzzy numbers.

  3. A method of providing a barrier in a fracture-containing system

    DEFF Research Database (Denmark)

    2014-01-01

    The present invention relates to a method of providing a barrier in a fracture-containing system, comprising: i) Providing a treatment fluid comprising: a) a base fluid; b) an elastomeric material, wherein said elastomeric material comprises at least one polymer capable of crosslinking into an el......The present invention relates to a method of providing a barrier in a fracture-containing system, comprising: i) Providing a treatment fluid comprising: a) a base fluid; b) an elastomeric material, wherein said elastomeric material comprises at least one polymer capable of crosslinking...... into an elastomer, and c) at least one crosslinking agent; ii) Placing the treatment fluid in a fracture-containing system; iii) Allowing the elastomeric material to crosslink with itself to form a barrier in said fracture-containing system; wherein the elastomeric material and/or the crosslinking agent...... are of neutral buoyancy with regard to the base fluid. The invention is contemplated to having utility not only in the oil-drilling industry but also in the plugging of fractures in sewer drains, pipelines etc....

  4. Intelligent Information Systems Institute

    National Research Council Canada - National Science Library

    Gomes, Carla

    2004-01-01

    ...) at Cornell during the first three years of operation. IISI's mandate is threefold: To perform and stimulate research in computational and data-intensive methods for intelligent decision making systems...

  5. Validation of the Child Premorbid Intelligence Estimate method to predict premorbid Wechsler Intelligence Scale for Children-Fourth Edition Full Scale IQ among children with brain injury.

    Science.gov (United States)

    Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H; Suarez, Mariann; Brickell, Tracey A

    2008-12-01

    Determination of neuropsychological impairment involves contrasting obtained performances with a comparison standard, which is often an estimate of premorbid IQ. M. R. Schoenberg, R. T. Lange, T. A. Brickell, and D. H. Saklofske (2007) proposed the Child Premorbid Intelligence Estimate (CPIE) to predict premorbid Full Scale IQ (FSIQ) using the Wechsler Intelligence Scale for Children-4th Edition (WISC-IV; Wechsler, 2003). The CPIE includes 12 algorithms to predict FSIQ, 1 using demographic variables and 11 algorithms combining WISC-IV subtest raw scores with demographic variables. The CPIE was applied to a sample of children with acquired traumatic brain injury (TBI sample; n = 40) and a healthy demographically matched sample (n = 40). Paired-samples t tests found estimated premorbid FSIQ differed from obtained FSIQ when applied to the TBI sample (ps .02). The demographic only algorithm performed well at a group level, but estimates were restricted in range. Algorithms combining single subtest scores with demographics performed adequately. Results support the clinical application of the CPIE algorithms. However, limitations to estimating individual premorbid ability, including statistical and developmental factors, must be considered. (c) 2008 APA, all rights reserved.

  6. Artificial intelligence applications in information and communication technologies

    CERN Document Server

    Bouguila, Nizar

    2015-01-01

    This book presents various recent applications of Artificial Intelligence in Information and Communication Technologies such as Search and Optimization methods, Machine Learning, Data Representation and Ontologies, and Multi-agent Systems. The main aim of this book is to help Information and Communication Technologies (ICT) practitioners in managing efficiently their platforms using AI tools and methods and to provide them with sufficient Artificial Intelligence background to deal with real-life problems.  .

  7. Methods for estimating residential building energy consumption by application of artificial intelligence; Methode d'estimation energetique des batiments d'habitation basee sur l'application de l'intelligence artificielle

    Energy Technology Data Exchange (ETDEWEB)

    Kajl, S.; Roberge, M-A. [Quebec Univ., Ecole de technologie superieure, Montreal, PQ (Canada)

    1999-02-01

    A method for estimating energy requirements in buildings five to twenty-five stories in height using artificial intelligence techniques is proposed. In developing this technique, the pre-requisites specified were rapid execution, the ability to generate a wide range of results, including total energy consumption, power demands, heating and cooling consumption, and accuracy comparable to that of a detailed building energy simulation software. The method proposed encompasses (1) the creation of various databases such as classification of the parameters used in the energy simulation, modelling using the Department of Energy (DOE)-2 software and validation of the DOE-2 models; (2) application of the neural networks inclusive of teaching the neural network and validation of the neural network's learning; (3) designing an energy estimate assessment (EEA) system for residential buildings; and (4) validation of the EEA system. The system has been developed in the MATLAB software environment, specifically for the climate in the Ottawa region. For use under different climatic conditions appropriate adjustments need to be made for the heating and cooling consumption. 12 refs., tabs., figs., 2 appendices.

  8. Intelligence Ethics:

    DEFF Research Database (Denmark)

    Rønn, Kira Vrist

    2016-01-01

    Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

  9. ELV Recycling Service Provider Selection Using the Hybrid MCDM Method: A Case Application in China

    Directory of Open Access Journals (Sweden)

    Fuli Zhou

    2016-05-01

    Full Text Available With the rapid depletion of natural resources and undesired environmental changes globally, more interest has been shown in the research of green supply chain practices, including end-of-life vehicle (ELV recycling. The ELV recycling is mandatory for auto-manufacturers by legislation for the purpose of minimizing potential environmental damages. The purpose of the present research is to determine the best choice of ELV recycling service provider by employing an integrating hybrid multi-criteria decision making (MCDM method. In this research, economic, environmental and social factors are taken into consideration. The linguistic variables and trapezoidal fuzzy numbers (TFNs are applied into this evaluation to deal with the vague and qualitative information. With the combined weight calculation of criteria based on fuzzy aggregation and Shannon Entropy techniques, the normative multi-criteria optimization technique (FVIKOR method is applied to explore the best solution. An application was performed based on the proposed hybrid MCDM method, and sensitivity analysis was conducted on different decision making scenarios. The present study provides a decision-making approach on ELV recycling business selection under sustainability and green philosophy with high robustness and easy implementation.

  10. Moral Issues in Intelligence-led Policing

    DEFF Research Database (Denmark)

    The core baseline of Intelligence-led Policing is the aim of increasing efficiency and quality of police work, with a focus on crime analysis and intelligence methods as tools for informed and objective decisions both when conducting targeted, specialized operations and when setting strategic...... technological measures, increased private partnerships and international cooperation challenging the core nature of police services as the main providers of public safety and security? This book offers new insights by exploring dilemmas, legal issues and questions raised by the use of new policing methods...

  11. System and method of providing quick thermal comfort with reduced energy by using directed spot conditioning

    Science.gov (United States)

    Wang, Mingyu; Kadle, Prasad S.; Ghosh, Debashis; Zima, Mark J.; Wolfe, IV, Edward; Craig, Timothy D

    2016-10-04

    A heating, ventilation, and air conditioning (HVAC) system and a method of controlling a HVAC system that is configured to provide a perceived comfortable ambient environment to an occupant seated in a vehicle cabin. The system includes a nozzle configured to direct an air stream from the HVAC system to the location of a thermally sensitive portion of the body of the occupant. The system also includes a controller configured to determine an air stream temperature and an air stream flow rate necessary to establish the desired heat supply rate for the sensitive portion and provide a comfortable thermal environment by thermally isolating the occupant from the ambient vehicle cabin temperature. The system may include a sensor to determine the location of the sensitive portion. The nozzle may include a thermoelectric device to heat or cool the air stream.

  12. Method of App Selection for Healthcare Providers Based on Consumer Needs.

    Science.gov (United States)

    Lee, Jisan; Kim, Jeongeun

    2018-01-01

    Mobile device applications can be used to manage health. However, healthcare providers hesitate to use them because selection methods that consider the needs of health consumers and identify the most appropriate application are rare. This study aimed to create an effective method of identifying applications that address user needs. Women experiencing dysmenorrhea and premenstrual syndrome were the targeted users. First, we searched for related applications from two major sources of mobile applications. Brainstorming, mind mapping, and persona and scenario techniques were used to create a checklist of relevant criteria, which was used to rate the applications. Of the 2784 applications found, 369 were analyzed quantitatively. Of those, five of the top candidates were evaluated by three groups: application experts, clinical experts, and potential users. All three groups ranked one application the highest; however, the remaining rankings differed. The results of this study suggest that the method created is useful because it considers not only the needs of various users but also the knowledge of application and clinical experts. This study proposes a method for finding and using the best among existing applications and highlights the need for nurses who can understand and combine opinions of users and application and clinical experts.

  13. Discussion of a method for providing general risk information by linking with the nuclear information

    International Nuclear Information System (INIS)

    Shobu, Nobuhiro; Yokomizo, Shirou; Umezawa, Sayaka

    2004-06-01

    'Risk information navigator (http://www.ricotti.jp/risknavi/)', an internet tool for arousing public interest and fostering people's risk literacy, has been developed as the contents for the official website of Techno Community Square 'RICOTTI' (http://www.ricotti.jp) at TOKAI village. In this report we classified the risk information into the fields, Health/Daily Life', 'Society/Crime/Disaster' and Technology/Environment/Energy', for the internet tool contents. According to these categories we discussed a method for providing various risk information on general fields by linking with the information on nuclear field. The web contents are attached to this report with the CD-R media. (author)

  14. Intelligence Naturelle et Intelligence Artificielle

    OpenAIRE

    Dubois, Daniel

    2011-01-01

    Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

  15. An Intelligent Optimization Method for Vortex-Induced Vibration Reducing and Performance Improving in a Large Francis Turbine

    Directory of Open Access Journals (Sweden)

    Xuanlin Peng

    2017-11-01

    Full Text Available In this paper, a new methodology is proposed to reduce the vortex-induced vibration (VIV and improve the performance of the stay vane in a 200-MW Francis turbine. The process can be divided into two parts. Firstly, a diagnosis method for stay vane vibration based on field experiments and a finite element method (FEM is presented. It is found that the resonance between the Kármán vortex and the stay vane is the main cause for the undesired vibration. Then, we focus on establishing an intelligent optimization model of the stay vane’s trailing edge profile. To this end, an approach combining factorial experiments, extreme learning machine (ELM and particle swarm optimization (PSO is implemented. Three kinds of improved profiles of the stay vane are proposed and compared. Finally, the profile with a Donaldson trailing edge is adopted as the best solution for the stay vane, and verifications such as computational fluid dynamics (CFD simulations, structural analysis and fatigue analysis are performed to validate the optimized geometry.

  16. The optimal design support system for shell components of vehicles using the methods of artificial intelligence

    Science.gov (United States)

    Szczepanik, M.; Poteralski, A.

    2016-11-01

    The paper is devoted to an application of the evolutionary methods and the finite element method to the optimization of shell structures. Optimization of thickness of a car wheel (shell) by minimization of stress functional is considered. A car wheel geometry is built from three surfaces of revolution: the central surface with the holes destined for the fastening bolts, the surface of the ring of the wheel and the surface connecting the two mentioned earlier. The last one is subjected to the optimization process. The structures are discretized by triangular finite elements and subjected to the volume constraints. Using proposed method, material properties or thickness of finite elements are changing evolutionally and some of them are eliminated. As a result the optimal shape, topology and material or thickness of the structures are obtained. The numerical examples demonstrate that the method based on evolutionary computation is an effective technique for solving computer aided optimal design.

  17. The intelligence of dual simplex method to solve linear fractional fuzzy transportation problem.

    Science.gov (United States)

    Narayanamoorthy, S; Kalyani, S

    2015-01-01

    An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.

  18. The Intelligence of Dual Simplex Method to Solve Linear Fractional Fuzzy Transportation Problem

    Directory of Open Access Journals (Sweden)

    S. Narayanamoorthy

    2015-01-01

    Full Text Available An approach is presented to solve a fuzzy transportation problem with linear fractional fuzzy objective function. In this proposed approach the fractional fuzzy transportation problem is decomposed into two linear fuzzy transportation problems. The optimal solution of the two linear fuzzy transportations is solved by dual simplex method and the optimal solution of the fractional fuzzy transportation problem is obtained. The proposed method is explained in detail with an example.

  19. A method to provide rapid in situ determination of tip radius in dynamic atomic force microscopy

    International Nuclear Information System (INIS)

    Santos, Sergio; Guang Li; Souier, Tewfik; Gadelrab, Karim; Chiesa, Matteo; Thomson, Neil H.

    2012-01-01

    We provide a method to characterize the tip radius of an atomic force microscopy in situ by monitoring the dynamics of the cantilever in ambient conditions. The key concept is that the value of free amplitude for which transitions from the attractive to repulsive force regimes are observed, strongly depends on the curvature of the tip. In practice, the smaller the value of free amplitude required to observe a transition, the sharper the tip. This general behavior is remarkably independent of the properties of the sample and cantilever characteristics and shows the strong dependence of the transitions on the tip radius. The main advantage of this method is rapid in situ characterization. Rapid in situ characterization enables one to continuously monitor the tip size during experiments. Further, we show how to reproducibly shape the tip from a given initial size to any chosen larger size. This approach combined with the in situ tip size monitoring enables quantitative comparison of materials measurements between samples. These methods are set to allow quantitative data acquisition and make direct data comparison readily available in the community.

  20. Application of Artificial Intelligence Methods for Analysis of Material and Non-material Determinants of Functioning of Young Europeans in Times of Crisis in the Eurozone

    OpenAIRE

    Gawlik, Remigiusz

    2014-01-01

    The study presents an analysis of possible applications of artificial intelligence methods for understanding, structuring and supporting the decision-making processes of European Youth in times of crisis in the Eurozone. Its main purpose is selecting a research method suitable for grasping and explaining the relations between social, economic and psychological premises when taking important life decisions by young Europeans at the beginning of their adult life. The interdisciplinary ap...

  1. Modeling of biological intelligence for SCM system optimization.

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  2. Modeling of Biological Intelligence for SCM System Optimization

    Directory of Open Access Journals (Sweden)

    Shengyong Chen

    2012-01-01

    Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

  3. Modeling of Biological Intelligence for SCM System Optimization

    Science.gov (United States)

    Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

    2012-01-01

    This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

  4. Artificial Intelligence Methods in Analysis of Morphology of Selected Structures in Medical Images

    Directory of Open Access Journals (Sweden)

    Ryszard Tadeusiewicz

    2001-01-01

    Full Text Available The goal of this paper is the presentation of the possibilities of application of syntactic method of computer image analysis for recognition of local stenoscs of coronary arteries lumen and detection of pathological signs in upper parts of ureter ducts and renal calyxes. Analysis of correct morphology of these structures is possible thanks to thc application of sequence and tree methods from the group of syntactic methods of pattern recognition. In the case of analysis of coronary arteries images the main objective is computer-aided early diagnosis of different form of ischemic cardiovascular diseases. Such diseases may reveal in the form of stable or unstable disturbances of heart rhythm or infarction. ln analysis of kidney radiograms the main goal is recognition of local irregularities in ureter lumens and examination of morphology of renal pelvis and calyxes.

  5. On the Application of Formal Methods to Clinical Guidelines, an Artificial Intelligence Perspective

    NARCIS (Netherlands)

    Hommersom, A.J.

    2008-01-01

    In computer science, all kinds of methods and techniques have been developed to study systems, such as simulation of the behaviour of a system. Furthermore, it is possible to study these systems by proving formal formal properties or by searching through all the possible states that a system may be

  6. Relating business intelligence and enterprise architecture - A method for combining operational data with architectural metadata

    NARCIS (Netherlands)

    Veneberg, R.K.M.; Iacob, Maria Eugenia; van Sinderen, Marten J.; Bodenstaff, L.

    Combining enterprise architecture and operational data is complex (especially when considering the actual ‘matching’ of data with enterprise architecture elements), and little has been written on how to do this. In this paper we aim to fill this gap, and propose a method to combine operational data

  7. Simulation embedded artificial intelligence search method for supplier trading portfolio decision

    DEFF Research Database (Denmark)

    Feng, Donghan; Yan, Z.; Østergaard, Jacob

    2010-01-01

    An electric power supplier in the deregulated environment needs to allocate its generation capacities to participate in contract and spot markets. Different trading portfolios will provide suppliers with different future revenue streams of various distributions. The classical mean-variance (MV) m...

  8. Computational Intelligence in Intelligent Data Analysis

    CERN Document Server

    Nürnberger, Andreas

    2013-01-01

    Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

  9. Method for providing slip energy control in permanent magnet electrical machines

    Science.gov (United States)

    Hsu, John S.

    2006-11-14

    An electric machine (40) has a stator (43), a permanent magnet rotor (38) with permanent magnets (39) and a magnetic coupling uncluttered rotor (46) for inducing a slip energy current in secondary coils (47). A dc flux can be produced in the uncluttered rotor when the secondary coils are fed with dc currents. The magnetic coupling uncluttered rotor (46) has magnetic brushes (A, B, C, D) which couple flux in through the rotor (46) to the secondary coils (47c, 47d) without inducing a current in the rotor (46) and without coupling a stator rotational energy component to the secondary coils (47c, 47d). The machine can be operated as a motor or a generator in multi-phase or single-phase embodiments and is applicable to the hybrid electric vehicle. A method of providing a slip energy controller is also disclosed.

  10. A novel method for the production of core-shell microparticles by inverse gelation optimized with artificial intelligent tools.

    Science.gov (United States)

    Rodríguez-Dorado, Rosalia; Landín, Mariana; Altai, Ayça; Russo, Paola; Aquino, Rita P; Del Gaudio, Pasquale

    2018-03-01

    Numerous studies have been focused on hydrophobic compounds encapsulation as oils. In fact, oils can provide numerous health benefits as synergic ingredient combined with other hydrophobic active ingredients. However, stable microparticles for pharmaceutical purposes are difficult to achieve when commonly techniques are used. In this work, sunflower oil was encapsulated in calcium-alginate capsules by prilling technique in co-axial configuration. Core-shell beads were produced by inverse gelation directly at the nozzle using a w/o emulsion containing aqueous calcium chloride solution in sunflower oil pumped through the inner nozzle while an aqueous alginate solution, coming out from the annular nozzle, produced the beads shell. To optimize process parameters artificial intelligence tools were proposed to optimize the numerous prilling process variables. Homogeneous and spherical microcapsules with narrow size distribution and a thin alginate shell were obtained when the parameters as w/o constituents, polymer concentrations, flow rates and frequency of vibration were optimized by two commercial software, FormRules® and INForm®, which implement neurofuzzy logic and Artificial Neural Networks together with genetic algorithms, respectively. This technique constitutes an innovative approach for hydrophobic compounds microencapsulation. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. Dynamic surface-enhanced Raman spectroscopy and Chemometric methods for fast detection and intelligent identification of methamphetamine and 3, 4-Methylenedioxy methamphetamine in human urine

    Science.gov (United States)

    Weng, Shizhuang; Dong, Ronglu; Zhu, Zede; Zhang, Dongyan; Zhao, Jinling; Huang, Linsheng; Liang, Dong

    2018-01-01

    Conventional Surface-Enhanced Raman Spectroscopy (SERS) for fast detection of drugs in urine on the portable Raman spectrometer remains challenges because of low sensitivity and unreliable Raman signal, and spectra process with manual intervention. Here, we develop a novel detection method of drugs in urine using chemometric methods and dynamic SERS (D-SERS) with mPEG-SH coated gold nanorods (GNRs). D-SERS combined with the uniform GNRs can obtain giant enhancement, and the signal is also of high reproducibility. On the basis of the above advantages, we obtained the spectra of urine, urine with methamphetamine (MAMP), urine with 3, 4-Methylenedioxy Methamphetamine (MDMA) using D-SERS. Simultaneously, some chemometric methods were introduced for the intelligent and automatic analysis of spectra. Firstly, the spectra at the critical state were selected through using K-means. Then, the spectra were proposed by random forest (RF) with feature selection and principal component analysis (PCA) to develop the recognition model. And the identification accuracy of model were 100%, 98.7% and 96.7%, respectively. To validate the effect in practical issue further, the drug abusers'urine samples with 0.4, 3, 30 ppm MAMP were detected using D-SERS and identified by the classification model. The high recognition accuracy of > 92.0% can meet the demand of practical application. Additionally, the parameter optimization of RF classification model was simple. Compared with the general laboratory method, the detection process of urine's spectra using D-SERS only need 2 mins and 2 μL samples volume, and the identification of spectra based on chemometric methods can be finish in seconds. It is verified that the proposed approach can provide the accurate, convenient and rapid detection of drugs in urine.

  12. Artificial intelligence in medicine.

    OpenAIRE

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of ...

  13. Intelligent Lighting Control System

    OpenAIRE

    García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

    2014-01-01

    This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

  14. A multi-agent based intelligent configuration method for aircraft fleet maintenance personnel

    OpenAIRE

    Feng, Qiang; Li, Songjie; Sun, Bo

    2014-01-01

    A multi-agent based fleet maintenance personnel configuration method is proposed to solve the mission oriented aircraft fleet maintenance personnel configuration problem. The maintenance process of an aircraft fleet is analyzed first. In the process each aircraft contains multiple parts, and different parts are repaired by personnel with different majors and levels. The factors and their relationship involved in the process of maintenance are analyzed and discussed. Then the whole maintenance...

  15. INNOVATIVE FORMS SUPPORTING SAFE METHODS OF WORK IN SAFETY ENGINEERING FOR THE DEVELOPMENT OF INTELLIGENT SPECIALIZATIONS

    Directory of Open Access Journals (Sweden)

    Anna GEMBALSKA-KWIECIEŃ

    2016-10-01

    Full Text Available The article discusses innovative forms of participation of employees in the work safety system. It also presents the advantages of these forms of employees’ involvement. The aim of empirical studies was the analysis of their behavior and attitude towards health and safety at work. The issues considered in the article have a significant impact on the improvement of methods of prevention related to work safety and aided the creation of a healthy society.

  16. Providing the physical basis of SCS curve number method and its proportionality relationship from Richards' equation

    Science.gov (United States)

    Hooshyar, M.; Wang, D.

    2016-12-01

    The empirical proportionality relationship, which indicates that the ratio of cumulative surface runoff and infiltration to their corresponding potentials are equal, is the basis of the extensively used Soil Conservation Service Curve Number (SCS-CN) method. The objective of this paper is to provide the physical basis of the SCS-CN method and its proportionality hypothesis from the infiltration excess runoff generation perspective. To achieve this purpose, an analytical solution of Richards' equation is derived for ponded infiltration in shallow water table environment under the following boundary conditions: 1) the soil is saturated at the land surface; and 2) there is a no-flux boundary which moves downward. The solution is established based on the assumptions of negligible gravitational effect, constant soil water diffusivity, and hydrostatic soil moisture profile between the no-flux boundary and water table. Based on the derived analytical solution, the proportionality hypothesis is a reasonable approximation for rainfall partitioning at the early stage of ponded infiltration in areas with a shallow water table for coarse textured soils.

  17. Content and Methods used to Train Tobacco Cessation Treatment Providers: An International Survey.

    Science.gov (United States)

    Kruse, Gina R; Rigotti, Nancy A; Raw, Martin; McNeill, Ann; Murray, Rachael; Piné-Abata, Hembadoon; Bitton, Asaf; McEwen, Andy

    2017-12-01

    There are limited existing data describing the training methods used to educate tobacco cessation treatment providers around the world. To measure the prevalence of tobacco cessation treatment content, skills training and teaching methods reported by tobacco treatment training programs across the world. Web-based survey in May-September 2013 among tobacco cessation training experts across six geographic regions and four World Bank income levels. Response rate was 73% (84 of 115 countries contacted). Of 104 individual programs from 84 countries, most reported teaching brief advice (78%) and one-to-one counseling (74%); telephone counseling was uncommon (33%). Overall, teaching of knowledge topics was more commonly reported than skills training. Programs in lower income countries less often reported teaching about medications, behavioral treatments and biomarkers and less often reported skills-based training about interviewing clients, medication management, biomarker measurement, assessing client outcomes, and assisting clients with co-morbidities. Programs reported a median 15 hours of training. Face-to-face training was common (85%); online programs were rare (19%). Almost half (47%) included no learner assessment. Only 35% offered continuing education. Nearly all programs reported teaching evidence-based treatment modalities in a face-to-face format. Few programs delivered training online or offered continuing education. Skills-based training was less common among low- and middle-income countries (LMICs). There is a large unmet need for tobacco treatment training protocols which emphasize practical skills, and which are more rapidly scalable than face-to-face training in LMICs.

  18. A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

    Science.gov (United States)

    Rocha, José Celso; Passalia, Felipe José; Matos, Felipe Delestro; Takahashi, Maria Beatriz; Ciniciato, Diego de Souza; Maserati, Marc Peter; Alves, Mayra Fernanda; de Almeida, Tamie Guibu; Cardoso, Bruna Lopes; Basso, Andrea Cristina; Nogueira, Marcelo Fábio Gouveia

    2017-08-09

    Morphological analysis is the standard method of assessing embryo quality; however, its inherent subjectivity tends to generate discrepancies among evaluators. Using genetic algorithms and artificial neural networks (ANNs), we developed a new method for embryo analysis that is more robust and reliable than standard methods. Bovine blastocysts produced in vitro were classified as grade 1 (excellent or good), 2 (fair), or 3 (poor) by three experienced embryologists according to the International Embryo Technology Society (IETS) standard. The images (n = 482) were subjected to automatic feature extraction, and the results were used as input for a supervised learning process. One part of the dataset (15%) was used for a blind test posterior to the fitting, for which the system had an accuracy of 76.4%. Interestingly, when the same embryologists evaluated a sub-sample (10%) of the dataset, there was only 54.0% agreement with the standard (mode for grades). However, when using the ANN to assess this sub-sample, there was 87.5% agreement with the modal values obtained by the evaluators. The presented methodology is covered by National Institute of Industrial Property (INPI) and World Intellectual Property Organization (WIPO) patents and is currently undergoing a commercial evaluation of its feasibility.

  19. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  20. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Directory of Open Access Journals (Sweden)

    Ke Li

    2016-01-01

    Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  1. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  2. Director of National Intelligence Statutory Authorities: Status and Proposals

    National Research Council Canada - National Science Library

    Best, Jr., Richard A; Cumming, Alfred

    2008-01-01

    ...) to manage the Intelligence Community (IC). Some observers have questioned whether the act provides the DNI the authority necessary to effectively implement Congress's 2004 intelligence reforms...

  3. Information Foraging Theory: A Framework for Intelligence Analysis

    Science.gov (United States)

    2014-11-01

    oceanographic information, human intelligence (HUMINT), open-source intelligence ( OSINT ), and information provided by other governmental departments [1][5...Human Intelligence IFT Information Foraging Theory LSA Latent Semantic Similarity MVT Marginal Value Theorem OFT Optimal Foraging Theory OSINT

  4. FEM-based Printhead Intelligent Adjusting Method for Printing Conduct Material

    Directory of Open Access Journals (Sweden)

    Liang Xiaodan

    2017-01-01

    Full Text Available Ink-jet printing circuit board has some advantage, such as non-contact manufacture, high manufacture accuracy, and low pollution and so on. In order to improve the and printing precision, the finite element technology is adopted to model the piezoelectric print heads, and a new bacteria foraging algorithm with a lifecycle strategy is proposed to optimize the parameters of driving waveforms for getting the desired droplet characteristics. Results of numerical simulation show such algorithm has a good performance. Additionally, the droplet jetting simulation results and measured results confirmed such method precisely gets the desired droplet characteristics.

  5. Development of dose assessment method for high-energy neutrons using intelligent neutron monitor

    International Nuclear Information System (INIS)

    Satoh, Daiki; Sato, Tatsuhiko; Endo, Akira; Yamaguchi, Yasuhiro; Matsufuji, N.; Sato, S.; Takada, M.

    2006-01-01

    Light output of liquid organic scintillator NE213 has been measured for proton, deuteron, triton, 3 He nucleus and alpha particle. A thick graphite target was bombarded with 400-MeV/u C ions to the produce charged particles. Time-of-flight method was adopted to determine the kinetic energy of the charged particles. Light output for proton was also measured using mono-energy beams of 100 and 160 MeV. The experimental results gave a new database of light output. (author)

  6. An Intelligent Information System for forest management: NED/FVS integration

    Science.gov (United States)

    J. Wang; W.D. Potter; D. Nute; F. Maier; H. Michael Rauscher; M.J. Twery; S. Thomasma; P. Knopp

    2002-01-01

    An Intelligent Information System (IIS) is viewed as composed of a unified knowledge base, database, and model base. This allows an IIS to provide responses to user queries regardless of whether the query process involves a data retrieval, an inference, a computational method, a problem solving module, or some combination of these. NED-2 is a full-featured intelligent...

  7. Infrared thermography based on artificial intelligence as a screening method for carpal tunnel syndrome diagnosis.

    Science.gov (United States)

    Jesensek Papez, B; Palfy, M; Mertik, M; Turk, Z

    2009-01-01

    This study further evaluated a computer-based infrared thermography (IRT) system, which employs artificial neural networks for the diagnosis of carpal tunnel syndrome (CTS) using a large database of 502 thermal images of the dorsal and palmar side of 132 healthy and 119 pathological hands. It confirmed the hypothesis that the dorsal side of the hand is of greater importance than the palmar side when diagnosing CTS thermographically. Using this method it was possible correctly to classify 72.2% of all hands (healthy and pathological) based on dorsal images and > 80% of hands when only severely affected and healthy hands were considered. Compared with the gold standard electromyographic diagnosis of CTS, IRT cannot be recommended as an adequate diagnostic tool when exact severity level diagnosis is required, however we conclude that IRT could be used as a screening tool for severe cases in populations with high ergonomic risk factors of CTS.

  8. Intelligent Control and Protection Methods for Modern Power Systems Based on WAMS

    DEFF Research Database (Denmark)

    Liu, Leo

    Continuously growing demand for electricity, driven by deregulated power markets, has forced power systems to operate closer to their security operation limits. Meanwhile, the increasing penetration of large scale renewable energy may impact the operation of power systems by bringing more...... vulnerability indices i.e. structural vulnerability index (SVI), contingency vulnerability index (CVI) and operational vulnerability index (OVI) are proposed to evaluate the impact of distributed generation (DG) on power system vulnerability. The assessment shows that DG units are able to shorten the electrical...... influencing factors to power system transient stability are also evaluated, e.g. power output of generators in central power plants (CPP), load consumption level and the power exchange in high voltage direct current (HVDC) links. Both structural and dynamic vulnerability assessment, aiming at providing...

  9. Novel activity classification and occupancy estimation methods for intelligent HVAC (heating, ventilation and air conditioning) systems

    International Nuclear Information System (INIS)

    Rana, Rajib; Kusy, Brano; Wall, Josh; Hu, Wen

    2015-01-01

    Reductions in HVAC (heating, ventilation and air conditioning) energy consumption can be achieved by limiting heating in the winter or cooling in the summer. However, the resulting low thermal comfort of building occupants may lead to an override of the HVAC control, which revokes its original purpose. This has led to an increased interest in modeling and real-time tracking of location, activity, and thermal comfort of building occupants for HVAC energy management. While thermal comfort is well understood, it is difficult to measure in real-time environments where user context changes dynamically. Encouragingly, plethora of sensors available on smartphone unleashes the opportunity to measure user contexts in real-time. An important contextual information for measuring thermal comfort is Metabolism rate, which changes based on current physical activities. To measure physical activity, we develop an activity classifier, which achieves 10% higher accuracy compared to Support Vector Machine and k-Nearest Neighbor. Office occupancy is another contextual information for energy-efficient HVAC control. Most of the phone based occupancy estimation techniques will fail to determine occupancy when phones are left at desk while sitting or attending meetings. We propose a novel sensor fusion method to detect if a user is near the phone, which achieves more than 90% accuracy. Determining activity and occupancy our proposed algorithms can help maintaining thermal comfort while reducing HVAC energy consumptions. - Highlights: • We propose activity and occupancy detection for efficient HVAC control. • Activity classifier achieves 10% higher accuracy than SVM and kNN. • For occupancy detection we propose a novel sensor fusion method. • Using Weighted Majority Voting we fuse microphone and accelerometer data on phone. • We achieve more than 90% accuracy in detecting occupancy.

  10. Narrowing of the middle cerebral artery: artificial intelligence methods and comparison of transcranial color coded duplex sonography with conventional TCD.

    Science.gov (United States)

    Swiercz, Miroslaw; Swiat, Maciej; Pawlak, Mikolaj; Weigele, John; Tarasewicz, Roman; Sobolewski, Andrzej; Hurst, Robert W; Mariak, Zenon D; Melhem, Elias R; Krejza, Jaroslaw

    2010-01-01

    The goal of the study was to compare performances of transcranial color-coded duplex sonography (TCCS) and transcranial Doppler sonography (TCD) in the diagnosis of the middle cerebral artery (MCA) narrowing in the same population of patients using statistical and nonstatistical intelligent models for data analysis. We prospectively collected data from 179 consecutive routine digital subtraction angiography (DSA) procedures performed in 111 patients (mean age 54.17+/-14.4 years; 59 women, 52 men) who underwent TCD and TCCS examinations simultaneously. Each patient was examined independently using both ultrasound techniques, 267 M1 segments of MCA were assessed and narrowings were classified as 50% lumen reduction. Diagnostic performance was estimated by two statistical and two artificial neural networks (ANN) classification methods. Separate models were constructed for the TCD and TCCS sonographic data, as well as for detection of "any narrowing" and "severe narrowing" of the MCA. Input for each classifier consisted of the peak-systolic, mean and end-diastolic velocities measured with each sonographic method; the output was MCA narrowing. Arterial narrowings less or equal 50% of lumen reduction were found in 55 and >50% narrowings in 26 out of 267 arteries, as indicated by DSA. In the category of "any narrowing" the rate of correct assignment by all models was 82% to 83% for TCCS and 79% to 81% for TCD. In the diagnosis of >50% narrowing the overall classification accuracy remained in the range of 89% to 90% for TCCS data and 90% to 91% for TCD data. For the diagnosis of any narrowing, the sensitivity of the TCCS was significantly higher than that of the TCD, while for diagnosis of >50% MCA narrowing, sensitivity of the TCCS was similar to sensitivity of the TCD. Our study showed that TCCS outperforms conventional TCD in detection of diagnosis of >50% MCA narrowing. (E-mail: jaroslaw.krejza@uphs.upenn.edu).

  11. Study of the Appropriate and Inappropriate Methods of Visual Arts Education in the Primary Schools According to the Types of Multiple Intelligences

    Directory of Open Access Journals (Sweden)

    Atena Salehi Baladehi

    2017-01-01

    Full Text Available In the current changing world, named the era of knowledge explosion, specialists and those involved in education have been attracted finding a response to a question: what should we teach today’s students that to be useful for them in the future life? The main objective of this study is to investigate the appropriate and inappropriate methods of visual arts education in pre-school. According to the types of multiple intelligences, reaching to this goal requires careful planning, proper training and proper content selection along with talent and interests of learners along with the use of appropriate practice training and educational staff training. The research handles descriptive and analytic methods as well as academic literature. The results suggest the importance of understanding the multiple intelligences in the visual arts education.

  12. Smart x-ray beam position monitor system using artificial intelligence methods for the advanced photon source insertion-device beamlines

    International Nuclear Information System (INIS)

    Shu, D.; Ding, H.; Barraza, J.; Kuzay, T.M.; Haeffner, D.; Ramanathan, M.

    1997-09-01

    At the Advanced Photon Source (APS), each insertion device (ID) beamline front-end has two XBPMs to monitor the X-ray beam position for both that vertical and horizontal directions. Performance challenges for a conventional photoemission type X-ray beam position monitor (XBPM) during operations are contamination of the signal from the neighboring bending magnet sources and the sensitivity of the XBPM to the insertion device (ID) gap variations. Problems are exacerbated because users change the ID gap during their operations, and hence the percentage level of the contamination in the front end XBPM signals varies. A smart XBPM system with a high speed digital signal processor has been built at the Advanced Photon Source for the ID beamline front ends. The new version of the software, which uses an artificial intelligence method, provides a self learning and self-calibration capability to the smart XBPM system. The structure of and recent test results with the system are presented in this paper

  13. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  14. Intelligent Design

    DEFF Research Database (Denmark)

    Hjorth, Poul G.

    2005-01-01

    Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig.......Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig....

  15. Semantic Business Intelligence - a New Generation of Business Intelligence

    Directory of Open Access Journals (Sweden)

    Dinu AIRINEI

    2012-01-01

    Full Text Available Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solution, called Semantic Business Intelligence.

  16. Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

    International Nuclear Information System (INIS)

    Turek, M.; Heiden, W.; Riesen, A.; Chhabda, T.A.; Schubert, J.; Zander, W.; Krueger, P.; Keusgen, M.; Schoening, M.J.

    2009-01-01

    The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overlapping sensory signals, fuzzy logic offers a possibility to mathematically model such systems. Current work goes into the direction of mixed heavy metal solutions and the combination of fuzzy logic with heavy metal-sensitive, silicon-based chemical sensors for training scenarios of arbitrary sensor/probe combinations in terms of an electronic tongue. Heavy metals play an important role in environmental analysis. As trace elements as well as water impurities released from industrial processes they occur in the environment. In this work, the development of a new fuzzy logic method based on potentiometric measurements performed with three different miniaturised chalcogenide glass sensors in different heavy metal solutions will be presented. The critical validation of the developed fuzzy logic program will be demonstrated by means of measurements in unknown single- and multi-component heavy metal solutions. Limitations of this program and a comparison between calculated and expected values in terms of analyte composition and heavy metal ion concentration will be shown and discussed.

  17. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Yan, W.; Henry, G.

    1999-01-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  18. Artificial intelligence/fuzzy logic method for analysis of combined signals from heavy metal chemical sensors

    Energy Technology Data Exchange (ETDEWEB)

    Turek, M. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany); Heiden, W.; Riesen, A. [Bonn-Rhein-Sieg University of Applied Sciences, Sankt Augustin (Germany); Chhabda, T.A. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Schubert, J.; Zander, W. [Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany); Krueger, P. [Institute of Biochemistry and Molecular Biology, RWTH Aachen, Aachen (Germany); Keusgen, M. [Institute for Pharmaceutical Chemistry, Philipps-University Marburg, Marburg (Germany); Schoening, M.J. [Institute of Nano- and Biotechnologies (INB), Aachen University of Applied Sciences, Campus Juelich, Juelich (Germany); Institute of Bio- and Nanosystems (IBN), Research Centre Juelich GmbH, Juelich (Germany)], E-mail: m.j.schoening@fz-juelich.de

    2009-10-30

    The cross-sensitivity of chemical sensors for several metal ions resembles in a way the overlapping sensitivity of some biological sensors, like the optical colour receptors of human retinal cone cells. While it is difficult to assign crisp classification values to measurands based on complex overlapping sensory signals, fuzzy logic offers a possibility to mathematically model such systems. Current work goes into the direction of mixed heavy metal solutions and the combination of fuzzy logic with heavy metal-sensitive, silicon-based chemical sensors for training scenarios of arbitrary sensor/probe combinations in terms of an electronic tongue. Heavy metals play an important role in environmental analysis. As trace elements as well as water impurities released from industrial processes they occur in the environment. In this work, the development of a new fuzzy logic method based on potentiometric measurements performed with three different miniaturised chalcogenide glass sensors in different heavy metal solutions will be presented. The critical validation of the developed fuzzy logic program will be demonstrated by means of measurements in unknown single- and multi-component heavy metal solutions. Limitations of this program and a comparison between calculated and expected values in terms of analyte composition and heavy metal ion concentration will be shown and discussed.

  19. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Upadhyaya, B.R.; Yan, W. [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering; Behravesh, M.M. [Electric Power Research Institute, Palo Alto, CA (United States); Henry, G. [EPRI NDE Center, Charlotte, NC (United States)

    1999-09-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  20. Modelling intelligent behavior

    Science.gov (United States)

    Green, H. S.; Triffet, T.

    1993-01-01

    An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

  1. Emotional Intelligence: Requiring Attention

    Directory of Open Access Journals (Sweden)

    Monica Tudor

    2016-01-01

    Full Text Available This article aims to highlight the need for emotional intelligence. Two methods of measurementare presented in this research, in order to better understand the necessity of a correct result. Theresults of research can lead to recommendations for improving levels of emotional intelligence andare useful for obtaining data to better compare past and present result. The papers presented inthis research are significant for future study of this subject. The first paper presents the evolutionof emotional intelligence in the past two years, more specifically its decrease concerning certaincharacteristics. The second one presents a research on the differences between generations. Thethird one shows a difference in emotional intelligence levels of children from rural versus urbanenvironments and the obstacles that they encounter in their own development.

  2. Effectiveness of artificial intelligence methods in applications to burning optimization and coal mills diagnostics on the basis of IASE's experiences in Turow Power Plant

    Energy Technology Data Exchange (ETDEWEB)

    Pollak, J.; Wozniak, A.W.; Dynia, Z.; Lipanowicz, T.

    2004-07-01

    Modern methods referred to as 'artificial intelligence' have been applied to combustion optimization and implementation of selected diagnostic functions for the milling system of a pulverized lignite-fired boiler. The results of combustion optimization have shown significant improvement of efficiency and reduction of NO, emission. Fuzzy logic has been used to develop, among other things, a fan mill overload detection system.

  3. Development of guidance and methodical documents for providing the decommissioning of radiation-hazardous objects

    International Nuclear Information System (INIS)

    Ermakov, A.

    2015-01-01

    Federal Center for Nuclear and Radiation Safety (JSC FCNRS) developed and approbated guidance and methodical documents for providing the facility to radiologically safe status in the course of Building B decommissioning activity at JSC VNIINM (A.A. Bochvar High-Technology Scientific Research Institute for Inorganic Materials). The scope of application of the documents developed is as follows: - preliminary segregation of radwaste into streams during its collection and preparation for removal from facilities/sites under decommissioning; - express assessment of specific activity (activity) of radwaste generated in the course of dismantling and decontamination activities; - radiological survey of premises and building structures following completion of dismantling and decontamination activities; - SRW processing (compaction, reduction in size), packaging, characterisation and containerisation in order to reduce risks of spread of radioactive contamination. Documents that have been developed can be used both at nuclear facilities/ sites similar to the JSC VNIINM Building B in terms of work stages and types of waste to be generated, and other facilities/ sites taking into consideration their peculiarities. (author)

  4. Artificial intelligence approaches in statistics

    International Nuclear Information System (INIS)

    Phelps, R.I.; Musgrove, P.B.

    1986-01-01

    The role of pattern recognition and knowledge representation methods from Artificial Intelligence within statistics is considered. Two areas of potential use are identified and one, data exploration, is used to illustrate the possibilities. A method is presented to identify and separate overlapping groups within cluster analysis, using an AI approach. The potential of such ''intelligent'' approaches is stressed

  5. Intelligent error correction method applied on an active pixel sensor based star tracker

    Science.gov (United States)

    Schmidt, Uwe

    2005-10-01

    Star trackers are opto-electronic sensors used on-board of satellites for the autonomous inertial attitude determination. During the last years star trackers became more and more important in the field of the attitude and orbit control system (AOCS) sensors. High performance star trackers are based up today on charge coupled device (CCD) optical camera heads. The active pixel sensor (APS) technology, introduced in the early 90-ties, allows now the beneficial replacement of CCD detectors by APS detectors with respect to performance, reliability, power, mass and cost. The company's heritage in star tracker design started in the early 80-ties with the launch of the worldwide first fully autonomous star tracker system ASTRO1 to the Russian MIR space station. Jena-Optronik recently developed an active pixel sensor based autonomous star tracker "ASTRO APS" as successor of the CCD based star tracker product series ASTRO1, ASTRO5, ASTRO10 and ASTRO15. Key features of the APS detector technology are, a true xy-address random access, the multiple windowing read out and the on-chip signal processing including the analogue to digital conversion. These features can be used for robust star tracking at high slew rates and under worse conditions like stray light and solar flare induced single event upsets. A special algorithm have been developed to manage the typical APS detector error contributors like fixed pattern noise (FPN), dark signal non-uniformity (DSNU) and white spots. The algorithm works fully autonomous and adapts to e.g. increasing DSNU and up-coming white spots automatically without ground maintenance or re-calibration. In contrast to conventional correction methods the described algorithm does not need calibration data memory like full image sized calibration data sets. The application of the presented algorithm managing the typical APS detector error contributors is a key element for the design of star trackers for long term satellite applications like

  6. Intelligent editor/printer enhancements

    Science.gov (United States)

    Woodfill, M. C.; Pheanis, D. C.

    1983-01-01

    Microprocessor support hardware, software, and cross assemblers relating to the Motorola 6800 and 6809 process systems were developed. Pinter controller and intelligent CRT development are discussed. The user's manual, design specifications for the MC6809 version of the intelligent printer controller card, and a 132-character by 64-line intelligent CRT display system using a Motorola 6809 MPU, and a one-line assembler and disassembler are provided.

  7. The Effect of Health Information Technology on Health Care Provider Communication: A Mixed-Method Protocol.

    Science.gov (United States)

    Manojlovich, Milisa; Adler-Milstein, Julia; Harrod, Molly; Sales, Anne; Hofer, Timothy P; Saint, Sanjay; Krein, Sarah L

    2015-06-11

    Communication failures between physicians and nurses are one of the most common causes of adverse events for hospitalized patients, as well as a major root cause of all sentinel events. Communication technology (ie, the electronic medical record, computerized provider order entry, email, and pagers), which is a component of health information technology (HIT), may help reduce some communication failures but increase others because of an inadequate understanding of how communication technology is used. Increasing use of health information and communication technologies is likely to affect communication between nurses and physicians. The purpose of this study is to describe, in detail, how health information and communication technologies facilitate or hinder communication between nurses and physicians with the ultimate goal of identifying how we can optimize the use of these technologies to support effective communication. Effective communication is the process of developing shared understanding between communicators by establishing, testing, and maintaining relationships. Our theoretical model, based in communication and sociology theories, describes how health information and communication technologies affect communication through communication practices (ie, use of rich media; the location and availability of computers) and work relationships (ie, hierarchies and team stability). Therefore we seek to (1) identify the range of health information and communication technologies used in a national sample of medical-surgical acute care units, (2) describe communication practices and work relationships that may be influenced by health information and communication technologies in these same settings, and (3) explore how differences in health information and communication technologies, communication practices, and work relationships between physicians and nurses influence communication. This 4-year study uses a sequential mixed-methods design, beginning with a

  8. A method for analyzing the business case for provider participation in the National Cancer Institute's Community Clinical Oncology Program and similar federally funded, provider-based research networks.

    Science.gov (United States)

    Reiter, Kristin L; Song, Paula H; Minasian, Lori; Good, Marjorie; Weiner, Bryan J; McAlearney, Ann Scheck

    2012-09-01

    The Community Clinical Oncology Program (CCOP) plays an essential role in the efforts of the National Cancer Institute (NCI) to increase enrollment in clinical trials. Currently, there is little practical guidance in the literature to assist provider organizations in analyzing the return on investment (ROI), or business case, for establishing and operating a provider-based research network (PBRN) such as the CCOP. In this article, the authors present a conceptual model of the business case for PBRN participation, a spreadsheet-based tool and advice for evaluating the business case for provider participation in a CCOP organization. A comparative, case-study approach was used to identify key components of the business case for hospitals attempting to support a CCOP research infrastructure. Semistructured interviews were conducted with providers and administrators. Key themes were identified and used to develop the financial analysis tool. Key components of the business case included CCOP start-up costs, direct revenue from the NCI CCOP grant, direct expenses required to maintain the CCOP research infrastructure, and incidental benefits, most notably downstream revenues from CCOP patients. The authors recognized the value of incidental benefits as an important contributor to the business case for CCOP participation; however, currently, this component is not calculated. The current results indicated that providing a method for documenting the business case for CCOP or other PBRN involvement will contribute to the long-term sustainability and expansion of these programs by improving providers' understanding of the financial implications of participation. Copyright © 2011 American Cancer Society.

  9. Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

    Science.gov (United States)

    Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing

    2018-08-01

    Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

  10. The ADEPT Framework for Intelligent Autonomy

    National Research Council Canada - National Science Library

    Ricard, Michael; Kolitz, Stephan

    2003-01-01

    ...) architecture for intelligent autonomy. Intelligent autonomy is the ability to plan and execute complex activities in a manner that provides rapid, effective response to stochastic and dynamic mission events...

  11. Business Intelligence in Process Control

    Science.gov (United States)

    Kopčeková, Alena; Kopček, Michal; Tanuška, Pavol

    2013-12-01

    The Business Intelligence technology, which represents a strong tool not only for decision making support, but also has a big potential in other fields of application, is discussed in this paper. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for company management. Article is logically divided into five main parts. In the first part, there is the definition of the technology and the list of main advantages. In the second part, an overview of the system architecture with the brief description of separate building blocks is presented. Also, the hierarchical nature of the system architecture is shown. The technology life cycle consisting of four steps, which are mutually interconnected into a ring, is described in the third part. In the fourth part, analytical methods incorporated in the online analytical processing and data mining used within the business intelligence as well as the related data mining methodologies are summarised. Also, some typical applications of the above-mentioned particular methods are introduced. In the final part, a proposal of the knowledge discovery system for hierarchical process control is outlined. The focus of this paper is to provide a comprehensive view and to familiarize the reader with the Business Intelligence technology and its utilisation.

  12. Young Children's Role-Playing for Enhancing Personal Intelligences in Multiple Intelligences Theory

    Science.gov (United States)

    Wee, Su-Jeong; Shin, Hwa-Sik; Kim, Myung-Hee

    2013-01-01

    This article examines young children's role-play in an effort to develop methods with which teachers can enhance children's interpersonal and intrapersonal intelligences. Examining how MI practice is applied in different cultural and social contexts is important because it can provide new insights on enriching and enhancing curricula and…

  13. Cost-effective implementation of intelligent systems

    Science.gov (United States)

    Lum, Henry, Jr.; Heer, Ewald

    1990-01-01

    Significant advances have occurred during the last decade in knowledge-based engineering research and knowledge-based system (KBS) demonstrations and evaluations using integrated intelligent system technologies. Performance and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent system technologies can be realized. In this paper the rationale and potential benefits for typical examples of application projects that demonstrate an increase in productivity through the use of intelligent system technologies are discussed. These demonstration projects have provided an insight into additional technology needs and cultural barriers which are currently impeding the transition of the technology into operational environments. Proposed methods which addresses technology evolution and implementation are also discussed.

  14. A mixed methods study of patient-provider communication about opioid analgesics.

    Science.gov (United States)

    Hughes, Helen Kinsman; Korthuis, Philip Todd; Saha, Somnath; Eggly, Susan; Sharp, Victoria; Cohn, Jonathan; Moore, Richard; Beach, Mary Catherine

    2015-04-01

    To describe patient-provider communication about opioid pain medicine and explore how these discussions affect provider attitudes toward patients. We audio-recorded 45 HIV providers and 423 patients in routine outpatient encounters at four sites across the country. Providers completed post-visit questionnaires assessing their attitudes toward patients. We identified discussions about opioid pain management and analyzed them qualitatively. We used logistic regression to assess the association between opioid discussion and providers' attitudes toward patients. 48 encounters (11% of the total sample) contained substantive discussion of opioid-related pain management. Most conversations were initiated by patients (n=28, 58%) and ended by the providers (n=36, 75%). Twelve encounters (25%) contained dialog suggesting a difference of opinion or conflict. Providers more often agreed than disagreed to give the prescription (50% vs. 23%), sometimes reluctantly; in 27% (n=13) of encounters, no decision was made. Fewer than half of providers (n=20, 42%) acknowledged the patient's experience of pain. Providers had a lower odds of positive regard for the patient (adjusted OR=0.51, 95% CI: 0.27-0.95) when opioids were discussed. Pain management discussions are common in routine outpatient HIV encounters and providers may regard patients less favorably if opioids are discussed during visits. The sometimes-adversarial nature of these discussions may negatively affect provider attitudes toward patients. Empathy and pain acknowledgment are tools that clinicians can use to facilitate productive discussions of pain management. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Artificial intelligence executive summary

    International Nuclear Information System (INIS)

    Wamsley, S.J.; Purvis, E.E. III

    1984-01-01

    Artificial intelligence (AI) is a high technology field that can be used to provide problem solving diagnosis, guidance and for support resolution of problems. It is not a stand alone discipline, but can also be applied to develop data bases for retention of the expertise that is required for its own knowledge base. This provides a way to retain knowledge that otherwise may be lost. Artificial Intelligence Methodology can provide an automated construction management decision support system, thereby restoring the manager's emphasis to project management

  16. A Strain-Based Method to Detect Tires’ Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development

    Directory of Open Access Journals (Sweden)

    Jorge Yunta

    2018-02-01

    Full Text Available Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system. In this paper, tire tread deformation is measured to provide a strong experimental base with different experiments and test results by means of a tire fitted with sensors. Tests under different working conditions such as vertical load or slip angle have been carried out with an indoor tire test rig. The experimental data analysis shows the strong relation that exists between lateral force and the maximum tensile and compressive strain peaks when the tire is not working at the limit of grip. In the last section, an estimation system from experimental data has been developed and implemented in Simulink to show the potential of strain sensors for developing intelligent tire systems, obtaining as major results a signal to detect tire’s loss of grip and estimations of the lateral friction coefficient.

  17. A Strain-Based Method to Detect Tires' Loss of Grip and Estimate Lateral Friction Coefficient from Experimental Data by Fuzzy Logic for Intelligent Tire Development.

    Science.gov (United States)

    Yunta, Jorge; Garcia-Pozuelo, Daniel; Diaz, Vicente; Olatunbosun, Oluremi

    2018-02-06

    Tires are a key sub-system of vehicles that have a big responsibility for comfort, fuel consumption and traffic safety. However, current tires are just passive rubber elements which do not contribute actively to improve the driving experience or vehicle safety. The lack of information from the tire during driving gives cause for developing an intelligent tire. Therefore, the aim of the intelligent tire is to monitor tire working conditions in real-time, providing useful information to other systems and becoming an active system. In this paper, tire tread deformation is measured to provide a strong experimental base with different experiments and test results by means of a tire fitted with sensors. Tests under different working conditions such as vertical load or slip angle have been carried out with an indoor tire test rig. The experimental data analysis shows the strong relation that exists between lateral force and the maximum tensile and compressive strain peaks when the tire is not working at the limit of grip. In the last section, an estimation system from experimental data has been developed and implemented in Simulink to show the potential of strain sensors for developing intelligent tire systems, obtaining as major results a signal to detect tire's loss of grip and estimations of the lateral friction coefficient.

  18. Intelligent playgrounds

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2009-01-01

    This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

  19. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  20. Devices and methods of operation thereof for providing stable flow for centrifugal compressors

    Science.gov (United States)

    Skoch, Gary J. (Inventor); Stevens, Mark A. (Inventor); Jett, Thomas A. (Inventor)

    2008-01-01

    Centrifugal compressor flow stabilizing devices and methods of operation thereof are disclosed that act upon the flow field discharging from the impeller of a centrifugal compressor and modify the flow field ahead of the diffuser vanes such that flow conditions contributing to rotating stall and surge are reduced or even eliminated. In some embodiments, shaped rods and methods of operation thereof are disclosed, whereas in other embodiments reverse-tangent air injection devices and methods are disclosed.

  1. Affective Computing and Intelligent Interaction

    CERN Document Server

    2012-01-01

    2012 International Conference on Affective Computing and Intelligent Interaction (ICACII 2012) was the most comprehensive conference focused on the various aspects of advances in Affective Computing and Intelligent Interaction. The conference provided a rare opportunity to bring together worldwide academic researchers and practitioners for exchanging the latest developments and applications in this field such as Intelligent Computing, Affective Computing, Machine Learning, Business Intelligence and HCI.   This volume is a collection of 119 papers selected from 410 submissions from universities and industries all over the world, based on their quality and relevancy to the conference. All of the papers have been peer-reviewed by selected experts.  

  2. Employing Artificial Intelligence To Minimise Internet Fraud

    Directory of Open Access Journals (Sweden)

    Edward Wong Sek Khin

    2009-12-01

    Full Text Available Internet fraud is increasing on a daily basis with new methods for extracting funds from government, corporations, businesses in general, and persons appearing almost hourly. The increases in on-line purchasing and the constant vigilance of both seller and buyer have meant that the criminal seems to be one-step ahead at all times. To pre-empt or to stop fraud before it can happen occurs in the non-computer based daily transactions of today because of the natural intelligence of the players, both seller and buyer. Currently, even with advances in computing techniques, intelligence is not the current strength of any computing system of today, yet techniques are available which may reduce the occurrences of fraud, and are usually referred to as artificial intelligence systems.This paper provides an overview of the use of current artificial intelligence (AI techniques as a means of combating fraud.Initially the paper describes how artificial intelligence techniques are employed in systems for detecting credit card fraud (online and offline fraud and insider trading.Following this, an attempt is made to propose the using of MonITARS (Monitoring Insider Trading and Regulatory Surveillance Systems framework which use a combination of genetic algorithms, neural nets and statistical analysis in detecting insider dealing. Finally, the paper discusses future research agenda to the role of using MonITARS system.

  3. A Sequential Mixed Methods Study: An Exploration of the Use of Emotional Intelligence by Senior Student Affairs Officers in Managing Critical Incidents

    Science.gov (United States)

    Johnson, Brian

    2013-01-01

    Emotional intelligence is a relatively new academic discipline that began forming in the early 1990s. Currently, emotional intelligence is used in academia and in business as a new intelligence quotient. This research study investigates how Senior Student Affairs Officers' use their emotional intelligence ability during critical incidents. The…

  4. Unsafe abortion in urban and rural Tanzania: method, provider and consequences

    DEFF Research Database (Denmark)

    Rasch, Vibeke; Kipingili, Rose

    2009-01-01

    OBJECTIVE: To describe unsafe abortion methods and associated health consequences in Tanzania, where induced abortion is restricted by law but common and known to account for a disproportionate share of hospital admissions. METHOD: Cross-sectional study of women admitted with alleged miscarriage...

  5. THE CHANGING LANDSCAPE OF COMPETITIVE INTELLIGENCE: TWO CRITICAL ISSUES INVESTIGATED

    OpenAIRE

    John J. McGonagle; Michael Misner-Elias

    2016-01-01

    Competitive intelligence is evolving. Why? It is the evolving needs of businesses and not the method or technology supporting the gathering and analysis of information that force this continuing evolution. Two changes in competitive intelligence are investigated in this paper: 1) the failure of the competitive intelligence system because of reliance on an outdated understanding of the intelligence cycle and the associated concepts of key intelligence topics (KITs) and key intelligence questio...

  6. Intelligent Advertising

    OpenAIRE

    Díaz Pinedo, Edilfredo Eliot

    2012-01-01

    Intelligent Advertisement diseña e implementa un sistema de publicidad para dispositivos móviles en un centro comercial, donde los clientes reciben publicidad de forma pasiva en sus dispositivos mientras están dentro.

  7. Compositions and methods for providing plants with tolerance to abiotic stress conditions

    KAUST Repository

    Hirt, Heribert; De Zelicourt, Axel; Saad, Maged

    2017-01-01

    It has been discovered that the desert endophytic bacterium SA187 SA187 can provide resistance or tolerance to abiotic stress conditions to seeds or plants. Compositions containing SA187 can be used to enhance plant development and yield under

  8. BUSINESS INTELLIGENCE

    OpenAIRE

    Bogdan Mohor Dumitrita

    2011-01-01

    The purpose of this work is to present business intelligence systems. These systems can be extremely complex and important in modern market competition. Its effectiveness also reflects in price, so we have to exlore their financial potential before investment. The systems have 20 years long history and during that time many of such tools have been developed, but they are rarely still in use. Business intelligence system consists of three main areas: Data Warehouse, ETL tools and tools f...

  9. Intelligent indexing

    International Nuclear Information System (INIS)

    Farkas, J.

    1992-01-01

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space ι 2 to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs

  10. Intelligent indexing

    Energy Technology Data Exchange (ETDEWEB)

    Farkas, J

    1993-12-31

    In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space {iota}{sup 2} to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs.

  11. The subject to emotional intelligence training of changes of emotional intelligence research, and adolescence of Japan seen from overseas literature

    OpenAIRE

    中島, 正世; Nakajima, Masayo

    2015-01-01

    In this paper, the author have revealed the transition about the concept of emotional intelligence from overseas literature, and have tried to clarify the subject to the definition of emotional intelligence, the difference from similar concepts, the measuring method of emotional intelligence, the related element of emotional intelligence, and emotional intelligence training for the man-power development to current adolescence. As a result, the base element which constitutes emotional intellig...

  12. Search for extraterrestrial intelligence (SETI)

    International Nuclear Information System (INIS)

    Morrison, P.; Billingham, J.; Wolfe, J.

    1977-01-01

    Findings are presented of a series of workshops on the existence of extraterrestrial intelligent life and ways in which extraterrestrial intelligence might be detected. The coverage includes the cosmic and cultural evolutions, search strategies, detection of other planetary systems, alternate methods of communication, and radio frequency interference. 17 references

  13. Artificial Intelligence and Science Education.

    Science.gov (United States)

    Good, Ron

    1987-01-01

    Defines artificial intelligence (AI) in relation to intelligent computer-assisted instruction (ICAI) and science education. Provides a brief background of AI work, examples of expert systems, examples of ICAI work, and addresses problems facing AI workers that have implications for science education. Proposes a revised model of the Karplus/Renner…

  14. NMR system and method having a permanent magnet providing a rotating magnetic field

    Science.gov (United States)

    Schlueter, Ross D [Berkeley, CA; Budinger, Thomas F [Berkeley, CA

    2009-05-19

    Disclosed herein are systems and methods for generating a rotating magnetic field. The rotating magnetic field can be used to obtain rotating-field NMR spectra, such as magic angle spinning spectra, without having to physically rotate the sample. This result allows magic angle spinning NMR to be conducted on biological samples such as live animals, including humans.

  15. The duty to provide information in the case of neuroradiological examination methods

    International Nuclear Information System (INIS)

    Deutsch, E.

    1987-01-01

    The author gives a survey on the judicial decisions concerning the obligation to give information in the case of neuroradiological examination methods. The scope and content of the medical explanation depends inter alia on the urgency and the necessity of the medical diagnosis and on the understanding of the patient. (WG) [de

  16. Vehicle Tracking System, Vehicle Infrastructure Provided with Vehicle Tracking System and Method for Tracking

    NARCIS (Netherlands)

    Papp, Z.; Doodeman, G.J.N.; Nelisse, M.W.; Sijs, J.; Theeuwes, J.A.C.; Driessen, B.J.F.

    2010-01-01

    A vehicle tracking system is described comprising - a plurality of sensor nodes (10) that each provide a message (D) indicative for an occupancy status of a detection area of an vehicle infrastructure monitored by said sensor node, said sensor nodes (10) being arranged in the vehicle infrastructure

  17. Compositions and methods for providing plants with tolerance to abiotic stress conditions

    KAUST Repository

    Hirt, Heribert

    2017-07-27

    It has been discovered that the desert endophytic bacterium SA187 SA187 can provide resistance or tolerance to abiotic stress conditions to seeds or plants. Compositions containing SA187 can be used to enhance plant development and yield under environmental stress conditions.

  18. Intelligent control systems 1990

    International Nuclear Information System (INIS)

    Shoureshi, R.

    1991-01-01

    The field of artificial intelligence (Al) has generated many useful ideas and techniques that can be integrated into the design of control systems. It is believed and, for special cases, has been demonstrated, that integration of Al into control systems would provide the necessary tools for solving many of the complex problems that present control techniques and Al algorithms are unable to do, individually. However, this integration requires the development of basic understanding and new fundamentals to provide scientific bases for achievement of its potential. This book presents an overview of some of the latest research studies in the area of intelligent control systems. These papers present techniques for formulation of intelligent control, and development of the rule-based control systems. Papers present applications of control systems in nuclear power plants and HVAC systems

  19. A Novel Resource Management Method of Providing Operating System as a Service for Mobile Transparent Computing

    Directory of Open Access Journals (Sweden)

    Yonghua Xiong

    2014-01-01

    Full Text Available This paper presents a framework for mobile transparent computing. It extends the PC transparent computing to mobile terminals. Since resources contain different kinds of operating systems and user data that are stored in a remote server, how to manage the network resources is essential. In this paper, we apply the technologies of quick emulator (QEMU virtualization and mobile agent for mobile transparent computing (MTC to devise a method of managing shared resources and services management (SRSM. It has three layers: a user layer, a manage layer, and a resource layer. A mobile virtual terminal in the user layer and virtual resource management in the manage layer cooperate to maintain the SRSM function accurately according to the user’s requirements. An example of SRSM is used to validate this method. Experiment results show that the strategy is effective and stable.

  20. A novel resource management method of providing operating system as a service for mobile transparent computing.

    Science.gov (United States)

    Xiong, Yonghua; Huang, Suzhen; Wu, Min; Zhang, Yaoxue; She, Jinhua

    2014-01-01

    This paper presents a framework for mobile transparent computing. It extends the PC transparent computing to mobile terminals. Since resources contain different kinds of operating systems and user data that are stored in a remote server, how to manage the network resources is essential. In this paper, we apply the technologies of quick emulator (QEMU) virtualization and mobile agent for mobile transparent computing (MTC) to devise a method of managing shared resources and services management (SRSM). It has three layers: a user layer, a manage layer, and a resource layer. A mobile virtual terminal in the user layer and virtual resource management in the manage layer cooperate to maintain the SRSM function accurately according to the user's requirements. An example of SRSM is used to validate this method. Experiment results show that the strategy is effective and stable.

  1. METHODS OF PROVIDING NOISE IMMUNITY IN AUTOMOBILE ANTI-THEFT SYSTEM CONTROL

    Directory of Open Access Journals (Sweden)

    Frolov, V.

    2013-06-01

    Full Text Available In modern ani-theft systems they use frequency and phase modulation. Since the width of the signal is limited, it is possible to intercept the signal and then switch off the alarm at the right time.To ensure the noise immunity and secrecy manufacturers use more sophisticated codes using the methods of cryptography. Significant increase in noise immunity in modern ani-theft systems is possible using broadband signals.

  2. System and Method for Providing Web-Based Remote Application Service

    OpenAIRE

    Shuen-Tai Wang; Yu-Ching Lin; Hsi-Ya Chang

    2017-01-01

    With the development of virtualization technologies, a new type of service named cloud computing service is produced. Cloud users usually encounter the problem of how to use the virtualized platform easily over the web without requiring the plug-in or installation of special software. The object of this paper is to develop a system and a method enabling process interfacing within an automation scenario for accessing remote application by using the web browser. To meet this challenge, we have ...

  3. Cloud Service Provider Methods for Managing Insider Threats: Analysis Phase 2, Expanded Analysis and Recommendations

    Science.gov (United States)

    2014-01-01

    and software as a service ( SaaS )) for staff’s abnormal behavior that may indicate an insider incident. As mentioned above, combining SIEM data...Mellon Software Engineering Institute, contacted commercial and government cloud service providers (CSPs) to better understand the administrative and...availability services . We have observed a number of scenarios in which a customer leaves a CSP’s IaaS, PaaS, or SaaS , but its data remains online for some

  4. Organization Effectiveness and Business Intelligence Systems. Literature Review

    Directory of Open Access Journals (Sweden)

    Remigiusz Tunowski

    2015-12-01

    Full Text Available Purpose: To better understand the impact of Business Intelligence systems on organizations’ effectiveness. Methodology: Critical and descriptive literature review. Findings: On the basis of numerous case studies described in literature and pertaining to various types of enterprises, different industries and countries, the paper confirms the positive impact of the implementation of Business Intelligence systems on organizations’ effectiveness. Research implications: The paper provides insights that can fuel future in-depth research aimed at the development of objective methods for measuring the impact of the implementation of Business Intelligence systems on organizational effectiveness, as well as further quantitative research. Practical implications: Results of the majority of studies indicate that the implementation of Business Intelligence systems brings tangible benefits to organizations. The implementation should, however, be appropriate and adequate, adjusted to each organization’s resources. Originality: The paper organizes and systematizes knowledge about the impact of BI implementation on organisation’s efficiency.

  5. Evaluation of Two Statistical Methods Provides Insights into the Complex Patterns of Alternative Polyadenylation Site Switching

    Science.gov (United States)

    Li, Jie; Li, Rui; You, Leiming; Xu, Anlong; Fu, Yonggui; Huang, Shengfeng

    2015-01-01

    Switching between different alternative polyadenylation (APA) sites plays an important role in the fine tuning of gene expression. New technologies for the execution of 3’-end enriched RNA-seq allow genome-wide detection of the genes that exhibit significant APA site switching between different samples. Here, we show that the independence test gives better results than the linear trend test in detecting APA site-switching events. Further examination suggests that the discrepancy between these two statistical methods arises from complex APA site-switching events that cannot be represented by a simple change of average 3’-UTR length. In theory, the linear trend test is only effective in detecting these simple changes. We classify the switching events into four switching patterns: two simple patterns (3’-UTR shortening and lengthening) and two complex patterns. By comparing the results of the two statistical methods, we show that complex patterns account for 1/4 of all observed switching events that happen between normal and cancerous human breast cell lines. Because simple and complex switching patterns may convey different biological meanings, they merit separate study. We therefore propose to combine both the independence test and the linear trend test in practice. First, the independence test should be used to detect APA site switching; second, the linear trend test should be invoked to identify simple switching events; and third, those complex switching events that pass independence testing but fail linear trend testing can be identified. PMID:25875641

  6. Physicians' opinions about partner notification methods: case reporting, patient referral, and provider referral.

    Science.gov (United States)

    Hogben, M; St Lawrence, J S; Montaño, D E; Kasprzyk, D; Leichliter, J S; Phillips, W R

    2004-02-01

    The United States has relied upon partner notification strategies to help break the chain of infection and re-infection for sexually transmitted diseases (STD). Physicians are a vital link in the system of STD control, but little is known of physician opinions about partner notification strategies. We collected opinions about partner notification from a national probability sample of physicians in specialties diagnosing STDs. Physicians responded to 17 questions about three relevant forms of STD partner notification: patient based referral, provider based referral, and case reporting. Exploratory factor analyses showed that responses for each form of partner notification could be grouped into four categories: perceived practice norms, infection control, patient relationships, and time/money. Multivariate analyses of the factors showed that physicians endorsed patient based referral most favourably and provider based referral least favourably. Physicians' opinions about partner notification strategies appear to reflect objective reality in some areas, but not in others. Strategies that improve the fit between physicians' opinions and effective notification are needed: some are discussed here.

  7. Providing Language Instructor with Artificial Intelligence Assistant

    OpenAIRE

    K. Pietroszek

    2007-01-01

    Abstract—This paper presents the preliminary results ofdeveloping HAL for CALL, an artificial intelligenceassistant for language instructor. The assistant consists of achatbot, an avatar (a three-dimensional visualization of thechatbot), a voice (text-to-speech engine interface) andinterfaces to external sources of language knowledge. Sometechniques used in adapting freely available chatbot for theneed of a language learning system are presented.Integration of HAL with Second Life virtual wor...

  8. Providing Language Instructor with Artificial Intelligence Assistant

    Directory of Open Access Journals (Sweden)

    K. Pietroszek

    2007-12-01

    Full Text Available Abstract—This paper presents the preliminary results ofdeveloping HAL for CALL, an artificial intelligenceassistant for language instructor. The assistant consists of achatbot, an avatar (a three-dimensional visualization of thechatbot, a voice (text-to-speech engine interface andinterfaces to external sources of language knowledge. Sometechniques used in adapting freely available chatbot for theneed of a language learning system are presented.Integration of HAL with Second Life virtual world isproposed. We will discuss technical challenges and possiblefuture work directions.

  9. Neural interface methods and apparatus to provide artificial sensory capabilities to a subject

    Energy Technology Data Exchange (ETDEWEB)

    Buerger, Stephen P.; Olsson, III, Roy H.; Wojciechowski, Kenneth E.; Novick, David K.; Kholwadwala, Deepesh K.

    2017-01-24

    Embodiments of neural interfaces according to the present invention comprise sensor modules for sensing environmental attributes beyond the natural sensory capability of a subject, and communicating the attributes wirelessly to an external (ex-vivo) portable module attached to the subject. The ex-vivo module encodes and communicates the attributes via a transcutaneous inductively coupled link to an internal (in-vivo) module implanted within the subject. The in-vivo module converts the attribute information into electrical neural stimuli that are delivered to a peripheral nerve bundle within the subject, via an implanted electrode. Methods and apparatus according to the invention incorporate implantable batteries to power the in-vivo module allowing for transcutaneous bidirectional communication of low voltage (e.g. on the order of 5 volts) encoded signals as stimuli commands and neural responses, in a robust, low-error rate, communication channel with minimal effects to the subjects' skin.

  10. Method for providing uranium articles with a corrosion resistant anodized coating

    International Nuclear Information System (INIS)

    Waldrop, F.B.; Washington, C.A.

    1982-01-01

    Uranium articles are provided with anodized oxide coatings in an aqueous solution of an electrolyte selected from the group consisting of potassium phosphate, potassium hydroxide, ammonium hydroxide, and a mixture of potassium tetraborate and boric acid. The uranium articles are anodized at a temperature greater than about 75 degrees C. With a current flow of less than about 0.036 A/cm2 of surface area while the Ph of the solution is maintained in a range of about 2 to 11.5. The Ph values of the aqueous solution and the low current density utilized during the electrolysis prevent excessive dissolution of the uranium and porosity in the film or watering. The relatively high temperature of the electrolyte bath inhibits hydration and the attendant deleterious pitting so as to enhance corrosion resistance of the anodized coating

  11. A Statistical Method for Aggregated Wind Power Plants to Provide Secondary Frequency Control

    DEFF Research Database (Denmark)

    Hu, Junjie; Ziras, Charalampos; Bindner, Henrik W.

    2017-01-01

    curtailment for aggregated wind power plants providing secondary frequency control (SFC) to the power system. By using historical SFC signals and wind speed data, we calculate metrics for the reserve provision error as a function of the scheduled wind power. We show that wind curtailment can be significantly......The increasing penetration of wind power brings significant challenges to power system operators due to the wind’s inherent uncertainty and variability. Traditionally, power plants and more recently demand response have been used to balance the power system. However, the use of wind power...... as a balancing-power source has also been investigated, especially for wind power dominated power systems such as Denmark. The main drawback is that wind power must be curtailed by setting a lower operating point, in order to offer upward regulation. We propose a statistical approach to reduce wind power...

  12. Pediatric primary care providers' perspectives regarding hospital discharge communication: a mixed methods analysis.

    Science.gov (United States)

    Leyenaar, JoAnna K; Bergert, Lora; Mallory, Leah A; Engel, Richard; Rassbach, Caroline; Shen, Mark; Woehrlen, Tess; Cooperberg, David; Coghlin, Daniel

    2015-01-01

    Effective communication between inpatient and outpatient providers may mitigate risks of adverse events associated with hospital discharge. However, there is an absence of pediatric literature defining effective discharge communication strategies at both freestanding children's hospitals and general hospitals. The objectives of this study were to assess associations between pediatric primary care providers' (PCPs) reported receipt of discharge communication and referral hospital type, and to describe PCPs' perspectives regarding effective discharge communication and areas for improvement. We administered a questionnaire to PCPs referring to 16 pediatric hospital medicine programs nationally. Multivariable models were developed to assess associations between referral hospital type and receipt and completeness of discharge communication. Open-ended questions asked respondents to describe effective strategies and areas requiring improvement regarding discharge communication. Conventional qualitative content analysis was performed to identify emergent themes. Responses were received from 201 PCPs, for a response rate of 63%. Although there were no differences between referral hospital type and PCP-reported receipt of discharge communication (relative risk 1.61, 95% confidence interval 0.97-2.67), PCPs referring to general hospitals more frequently reported completeness of discharge communication relative to those referring to freestanding children's hospitals (relative risk 1.78, 95% confidence interval 1.26-2.51). Analysis of free text responses yielded 4 major themes: 1) structured discharge communication, 2) direct personal communication, 3) reliability and timeliness of communication, and 4) communication for effective postdischarge care. This study highlights potential differences in the experiences of PCPs referring to general hospitals and freestanding children's hospitals, and presents valuable contextual data for future quality improvement initiatives

  13. How to Choose Appropriate Experts for Peer Review: An Intelligent Recommendation Method in a Big Data Context

    Directory of Open Access Journals (Sweden)

    Duanduan Liu

    2015-05-01

    Full Text Available The rapid development of the internet has led to the accumulation of massive amounts of data, and thus we find ourselves entering the age of big data. Obtaining useful information from these big data is a crucial issue. The aim of this article is to solve the problem of recommending experts to provide peer reviews for universities and other scientific research institutions. Our proposed recommendation method has two stages. An information filtering method is first offered to identify proper experts as a candidate set. Then, an aggregation model with various constraints is suggested to recommend appropriate experts for each applicant. The proposed method has been implemented in an online research community, and the results exhibit that the proposed method is more effective than existing ones.

  14. SCREENING OF Lr GENES PROVIDING RESISTANCE TO LEAF RUST IN WHEATH USING MULTIPLEX PCR METHOD

    Directory of Open Access Journals (Sweden)

    Mehmet AYBEKE

    2015-12-01

    Full Text Available Leaf rust is a fungal disease in wheat that causes significant decrease in yield around the world. In Turkey, several genes, including leaf rust-resistant (Lr Lr9, Lr19, Lr24 and Lr28, have been found to induce disease resistance. To obtain resistant cultivars during the breeding process, screening of these genes in various specimens is crucial. Thus, we aimed in the present study primarily to improve the multiplex polymerase chain reaction (PCR methodology by which four Lr genes could be simultaneously screened in plant samples carrying these genes. Serial PCR experiments were carried out for determination of optimal PCR conditions for each Lr gene and in all studies nursery lines were used. PCR conditions were determined as follows: 35 cycles of 95°C for denaturation (30 s, 58°C for annealing (30 s and 72°C for elongation (60 s, with an initial 94°C denaturation (3 min and a 72°C extension (30 min. The primers used in the PCR runs were as follows: Lr9F: TCCTTTTATTCCGCACGCCGG, Lr9R: CCACACTACCCCAAAGAGACG; Lr19F: CATCCTTGGGGACCTC, Lr19R: CCAGCTCGCATACATCCA; Lr24F: TCTAGTCTGTACATGGGGGC, Lr24R: TGGCACATGAACTCCATACG; Lr28F: CCCGGCATAAGTCTATGGTT, Lr28R: CAATGAATGAGATACGTGAA. We found that the optimum annealing temperature for all four genes was 61°C and extension temperatures were 62°C or 64°C. Finally, using this new PCR method, we successfully screened these genes in specimens carrying only one single Lr gene. Optimal multiplex PCR conditions were; denaturation at 94°C for 1 min, 35 extension cycles [94°C for 30 s, 57–61ºC (ideal 61°C for 30 s, and 64–68°C for 2 min] and final extension at 72°C for 30 min. In addition, we achieved positive results when running the optimised multiplex PCR tests on Lr19, Lr24 and Lr28. Future studies are planned to expand new wide multiplex PCR method to include all other Lr genes.

  15. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

    As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.

  16. Analysis of methods of providing anonymity in facial photographs; a randomised controlled study.

    LENUS (Irish Health Repository)

    Clover, A J P

    2010-09-01

    Clinical images are invaluable in medical teaching and research publications. In the past efforts to conceal patient identity, if any, were limited to a black bar concealing the eyes. However, there is no consensus on this among major journals and publishing houses. This research analyses the effectiveness of blacking out the eyes in facial photographs and evaluates alternative techniques. 126 questionnaires were completed. The average numbers of correct responses out of 30 was 24.64 (82.13%) in the control group, 20.59 (68.63%) in the eyes, 20.42 (68.07%) in the eyes and nose group, and 17.53 (58.43%) in the T-shaped group (eyes, nose and mouth). The traditional method of covering the eyes does significantly decrease recognition, however it is only as effective as covering the nose and mouth. The more of the face that is covered the less likely it is that the person is recognised. However, there are people who remain identifiable no matter how much of the face is covered. This work highlights the importance of obtaining consent prior to publication as well as attempting to hide identity.

  17. Research of Classical and Intelligent Information System Solutions for Criminal Intelligence Analysis

    OpenAIRE

    Šimović, Vladimir

    2001-01-01

    The objective of this study is to present research on classical and intelligent information system solutions used in criminal intelligence analysis in Croatian security system theory. The study analyses objective and classical methods of information science, including artificial intelligence and other scientific methods. The intelligence and classical software solutions researched, proposed, and presented in this study were used in developing the integrated information system for the Croatian...

  18. Database in Artificial Intelligence.

    Science.gov (United States)

    Wilkinson, Julia

    1986-01-01

    Describes a specialist bibliographic database of literature in the field of artificial intelligence created by the Turing Institute (Glasgow, Scotland) using the BRS/Search information retrieval software. The subscription method for end-users--i.e., annual fee entitles user to unlimited access to database, document provision, and printed awareness…

  19. Splunk operational intelligence cookbook

    CERN Document Server

    Diakun, Josh; Mock, Derek

    2014-01-01

    This book is intended for users of all levels who are looking to leverage the Splunk Enterprise platform as a valuable operational intelligence tool. The recipes provided in this book will appeal to individuals from all facets of a business - IT, Security, Product, Marketing, and many more!

  20. Gamma Knife radiosurgery of olfactory groove meningiomas provides a method to preserve subjective olfactory function.

    Science.gov (United States)

    Gande, Abhiram; Kano, Hideyuki; Bowden, Gregory; Mousavi, Seyed H; Niranjan, Ajay; Flickinger, John C; Lunsford, L Dade

    2014-02-01

    Anosmia is a common outcome after resection of olfactory groove meningioma(s) (OGM) and for some patients represents a significant disability. To evaluate long term tumor control rates and preservation of subjective olfaction after Gamma Knife (GK) stereotactic radiosurgery (SRS) of OGM. We performed a retrospective chart review and telephone assessments of 41 patients who underwent GK SRS between 1987 and 2008. Clinical outcomes were stratified by full, partial or no subjective olfaction, whereas tumor control was assessed by changes in volume greater or lesser than 25%. The median clinical and imaging follow-up were 76 and 65 months, respectively. Prior to SRS, 19 (46%) patients had surgical resections and two (5%) had received fractionated radiation therapy. Twenty four patients (59%) reported a normal sense of smell, 12 (29%) reported a reduced sense of smell and five (12%) had complete anosmia. The median tumor volume was 8.5 cm(3) (range 0.6-56.1), the mean radiation dose at the tumor margin was 13 Gy (range 10-20) and the median estimated dose to the olfactory nerve was 5.1 Gy (range 1.1-18.1). At follow-up, 27 patients (66%) reported intact olfaction (three (7%) described return to a normal sense of smell), nine (22%) described partial anosmia, and five (12%) had complete anosmia. No patient reported deterioration in olfaction after SRS. Thirteen patients (32%) showed significant tumor regression, 26 (63%) had no further growth and two (5%) had progressed. The progression free tumor control rates were 97% at 1 year and 95% at 2, 10 and 20 years. Symptomatic adverse radiation effects occurred in three (7%) patients. Stereotactic radiosurgery provided both long term tumor control and preservation of olfaction.

  1. Intelligent systems

    CERN Document Server

    Irwin, J David

    2011-01-01

    Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

  2. Intelligent Universe

    Energy Technology Data Exchange (ETDEWEB)

    Hoyle, F

    1983-01-01

    The subject is covered in chapters, entitled: chance and the universe (synthesis of proteins; the primordial soup); the gospel according to Darwin (discussion of Darwin theory of evolution); life did not originate on earth (fossils from space; life in space); the interstellar connection (living dust between the stars; bacteria in space falling to the earth; interplanetary dust); evolution by cosmic control (microorganisms; genetics); why aren't the others here (a cosmic origin of life); after the big bang (big bang and steady state); the information rich universe; what is intelligence up to; the intelligent universe.

  3. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

    A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of artificial intelligence and related themes. This was reflected in the second international workshop on 'Software Engineering, Artificial Intelligence and Expert Systems in High Energy and Nuclear Physics' which took place from 13-18 January at France Telecom's Agelonde site at La Londe des Maures, Provence. It was the second in a series, the first having been held at Lyon in 1990

  4. Artificial Intelligence and Moral intelligence

    Directory of Open Access Journals (Sweden)

    Laura Pana

    2008-07-01

    Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

  5. Intelligent computer-aided training and tutoring

    Science.gov (United States)

    Loftin, R. Bowen; Savely, Robert T.

    1991-01-01

    Specific autonomous training systems based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground-based support personnel that demonstrate an alternative to current training systems are described. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer-Aided Training (ICAT) systems would provide, for the trainee, much of the same experience that could be gained from the best on-the-job training. By integrating domain expertise with a knowledge of appropriate training methods, an ICAT session should duplicate, as closely as possible, the trainee undergoing on-the-job training in the task environment, benefitting from the full attention of a task expert who is also an expert trainer. Thus, the philosophy of the ICAT system is to emulate the behavior of an experienced individual devoting his full time and attention to the training of a novice - proposing challenging training scenarios, monitoring and evaluating the actions of the trainee, providing meaningful comments in response to trainee errors, responding to trainee requests for information, giving hints (if appropriate), and remembering the strengths and weaknesses displayed by the trainee so that appropriate future exercises can be designed.

  6. Towards a universal competitive intelligence process model

    Directory of Open Access Journals (Sweden)

    Rene Pellissier

    2013-08-01

    Full Text Available Background: Competitive intelligence (CI provides actionable intelligence, which provides a competitive edge in enterprises. However, without proper process, it is difficult to develop actionable intelligence. There are disagreements about how the CI process should be structured. For CI professionals to focus on producing actionable intelligence, and to do so with simplicity, they need a common CI process model.Objectives: The purpose of this research is to review the current literature on CI, to look at the aims of identifying and analysing CI process models, and finally to propose a universal CI process model.Method: The study was qualitative in nature and content analysis was conducted on all identified sources establishing and analysing CI process models. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability, only peer-reviewed articles were used.Results: The findings reveal that the majority of scholars view the CI process as a cycle of interrelated phases. The output of one phase is the input of the next phase.Conclusion: The CI process is a cycle of interrelated phases. The output of one phase is the input of the next phase. These phases are influenced by the following factors: decision makers, process and structure, organisational awareness and culture, and feedback.

  7. Detection and intelligent systems for homeland security

    CERN Document Server

    Voeller, John G

    2014-01-01

    Detection and Intelligent Systems for Homeland Security features articles from the Wiley Handbook of Science and Technology for Homeland Security covering advanced technology for image and video interpretation systems used for surveillance, which help in solving such problems as identifying faces from live streaming or stored videos. Biometrics for human identification, including eye retinas and irises, and facial patterns are also presented. The book then provides information on sensors for detection of explosive and radioactive materials and methods for sensing chemical

  8. Experiments on Printed Intelligence and Its Applications

    OpenAIRE

    Barbonelova, Angelina

    2015-01-01

    Printed intelligence technology refers to products and systems that are produced using traditional printing methods and that are able to communicate or react with the user, environment or other products and systems. The technology provides the foundations of innovative products such as printed OLEDs (organic light emitting device), electroluminescent displays, organic photovoltaics, thin film batteries and disposable sensors. This study presents research on different printing techniques i...

  9. Private providers' knowledge, attitudes and misconceptions related to long-acting and permanent contraceptive methods: a case study in Bangladesh.

    Science.gov (United States)

    Ugaz, Jorge; Banke, Kathryn; Rahaim, Stephen; Chowdhury, Wahiduzzaman; Williams, Julie

    2016-11-01

    In Bangladesh, use of long-acting and permanent methods of contraception (LAPMs) remains stagnant. Providers' limited knowledge and biases may be a factor. We assessed private providers' knowledge, misconceptions and general attitudes towards LAPM in two urban areas. The ultimate goal is to shape programs and interventions to overcome these obstacles and improve full method choice in Bangladesh. Trained data collectors interviewed a convenience sample of 235 female doctors (obstetricians-gynecologists and general practitioners) and 150 female nurses from 194 commercial (for-profit) health care facilities in Chittagong City Corporation and Dhaka district. Data were collected on the nature of the practice, training received, knowledge about modern contraceptives and attitudes towards LAPM [including intrauterine device (IUDs), implants, female and male sterilization]. All providers, and especially doctors, lacked adequate knowledge regarding side effects for all LAPMs, particularly female and male sterilization. Providers had misconceptions about the effectiveness and convenience of LAPMs compared to short-acting contraceptive methods. Implants and IUDs were generally perceived more negatively than other methods. The majority of providers believed that husbands favor short-acting methods rather than LAPMs and that women should not use a method that their husbands do not approve of. Our findings document knowledge and attitudinal barriers among private for-profit providers in urban areas affecting their provision of accurate information about LAPM choices. Practitioners should be offered the necessary tools to provide women full access to all modern methods, especially LAPMs, in order to contribute to decreasing unmet need and improving full method choice in Bangladesh. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Hasnain, S.B.

    1992-01-01

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  11. Computational Intelligence for Engineering Systems

    CERN Document Server

    Madureira, A; Vale, Zita

    2011-01-01

    "Computational Intelligence for Engineering Systems" provides an overview and original analysis of new developments and advances in several areas of computational intelligence. Computational Intelligence have become the road-map for engineers to develop and analyze novel techniques to solve problems in basic sciences (such as physics, chemistry and biology) and engineering, environmental, life and social sciences. The contributions are written by international experts, who provide up-to-date aspects of the topics discussed and present recent, original insights into their own experien

  12. Plant intelligence

    Science.gov (United States)

    Lipavská, Helena; Žárský, Viktor

    2009-01-01

    The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

  13. Speech Intelligibility

    Science.gov (United States)

    Brand, Thomas

    Speech intelligibility (SI) is important for different fields of research, engineering and diagnostics in order to quantify very different phenomena like the quality of recordings, communication and playback devices, the reverberation of auditoria, characteristics of hearing impairment, benefit using hearing aids or combinations of these things.

  14. Smithtown: An Intelligent Tutoring System.

    Science.gov (United States)

    Raghavan, Kalyani; Katz, Arnold

    1989-01-01

    Described is an instructional aid that employs artificial intelligence methods to assist students in beginning economics courses to improve their problem-solving skills. Discussed are the rationale, structure, and evaluation of this program. (CW)

  15. Intelligent Transportation Systems : critical standards

    Science.gov (United States)

    1999-06-01

    Intelligent Transportation Systems (ITS) standards are industry-consensus standards that provide the details about how different systems interconnect and communicate information to deliver the ITS user services described in the National ITS Architect...

  16. Business intelligence for insurance companies

    OpenAIRE

    IGNATIUK A.

    2016-01-01

    The current state and future trends for the world and domestic insurance markets are analyzed. The description of business intelligence methodology, tools and their practical implication for insurance companies are provided.

  17. BUSINESS INTELLIGENCE FOR INSURANCE COMPANIES

    Directory of Open Access Journals (Sweden)

    A. Ignatiuk

    2016-06-01

    Full Text Available The current state and future trends for the world and domestic insurance markets are analyzed. The description of business intelligence methodology, tools and their practical implication for insurance companies are provided.

  18. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  19. Dynamic vulnerability assessment and intelligent control for sustainable power systems

    CERN Document Server

    Gonzalez-Longatt, Francisco

    2018-01-01

    Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

  20. Cooperation and the evolution of intelligence.

    Science.gov (United States)

    McNally, Luke; Brown, Sam P; Jackson, Andrew L

    2012-08-07

    The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the 'social intelligence hypothesis'), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.

  1. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  2. Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

    Directory of Open Access Journals (Sweden)

    Moteaal Asadi Shirzi

    2007-03-01

    Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

  3. ECONOMIC INTELLIGENCE - THEORETICAL AND PRACTICAL ASPECTS

    Directory of Open Access Journals (Sweden)

    VIRGIL - ION POPOVICI

    2014-12-01

    Full Text Available Economic Intelligence (EI may be a solution in knowledge management as involves collecting, evaluating, processing, analysis and dissemination of economic data within organizations. The ultimate goal of economic intelligence (EI is to take advantage of this opportunity to develop and improve methods for identifying relevant information sources, analysis of information collected and manipulation, to give the user all the necessary decisions. Scope of the Economic Intelligence focused on information available outside the organization, covering wide areas from technology to market or legal issues. Economic Intelligence (EI is closely related to other approaches to information management, and knowledge management and business intelligence, excelling in the use of software tools.

  4. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  5. Reliability and Validity of the New Tanaka B Intelligence Scale Scores: A Group Intelligence Test

    OpenAIRE

    Uno, Yota; Mizukami, Hitomi; Ando, Masahiko; Yukihiro, Ryoji; Iwasaki, Yoko; Ozaki, Norio

    2014-01-01

    OBJECTIVE: The present study evaluated the reliability and concurrent validity of the new Tanaka B Intelligence Scale, which is an intelligence test that can be administered on groups within a short period of time. METHODS: The new Tanaka B Intelligence Scale and Wechsler Intelligence Scale for Children-Third Edition were administered to 81 subjects (mean age ± SD 15.2 ± 0.7 years) residing in a juvenile detention home; reliability was assessed using Cronbach's alpha coefficient, and concurre...

  6. Predictive Estimates of Employees’ Intelligence at Workplace with Special Reference to Emotional and Spiritual Intelligence

    OpenAIRE

    B. K. Punia; Priyanka Yadav

    2015-01-01

    The piece of writing investigates the relationship between employees’ emotional and Spiritual intelligence. A conversation of spirituality and emotions within the workplace can be an unthinkable topic. However, emotional intelligence and spiritual intelligence are, at present, more widely acknowledged. Drawing a research connected with these construct we suggest that emotional intelligence within the employees in organisations may provide employees with a medium to better understand and mix s...

  7. The Cyber Intelligence Challenge of Asyngnotic Networks

    Directory of Open Access Journals (Sweden)

    Edward M. Roche

    2015-09-01

    Full Text Available The intelligence community is facing a new type of organization, one enabled by the world’s information and communications infrastructure. These asyngnotic networks operate without leadership and are self-organizing in nature. They pose a threat to national security because they are difficult to detect in time for intelligence to provide adequate warning. Social network analysis and link analysis are important tools but can be supplemented by application of neuroscience principles to understand the forces that drive asyngnotic self-organization and triggering of terrorist events. Applying Living Systems Theory (LST to a terrorist attack provides a useful framework to identify hidden asyngnotic networks. There is some antecedent work in propaganda analysis that may help uncover hidden asyngnotic networks, but computerized SIGINT methods face a number of challenges.

  8. Conceptual Model of Business Value of Business Intelligence Systems

    OpenAIRE

    Popovič, Aleš; Turk, Tomaž; Jaklič, Jurij

    2010-01-01

    With advances in the business intelligence area, there is an increasing interest for the introduction of business intelligence systems into organizations. Although the opinion about business intelligence and its creation of business value is generally accepted, economic justification of investments into business intelligence systems is not always clear. Measuring the business value of business intelligence in practice is often not carried out due to the lack of measurement methods and resourc...

  9. Exploration and thinking of dynamic scientific and technical intelligence research

    International Nuclear Information System (INIS)

    Zhang Xupu; Xia Yun

    2014-01-01

    This article discusses the concept and types of dynamic scientific and technical intelligence, describes the characteristics and role of dynamic scientific and technical intelligence, and analyzes methods and procedures of dynamic scientific and technical intelligence research. Combined with the status quo of dynamic scientific and technical intelligence research in library of China Institute of Atomic Energy, this article makes some suggestions for strengthening dynamic scientific and technical intelligence research. (authors)

  10. Second Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Dollman, Thomas (Compiler)

    1988-01-01

    The proceedings of the conference are presented. This second conference on Artificial Intelligence for Space Applications brings together a diversity of scientific and engineering work and is intended to provide an opportunity for those who employ AI methods in space applications to identify common goals and to discuss issues of general interest in the AI community.

  11. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  12. Semantic Business Intelligence - a New Generation of Business Intelligence

    OpenAIRE

    Dinu AIRINEI; Dora-Anca BERTA

    2012-01-01

    Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solutio...

  13. THE SIMULATION DIAGNOSTIC METHODS AND REGENERATION WAYS OF REINFORCED - CONCRETE CONSTRUCTIONS OF BRIDGES IN PROVIDING THEIR OPERATING RELIABILITY AND LONGEVITY

    Directory of Open Access Journals (Sweden)

    B. V. Savchinskiy

    2010-03-01

    Full Text Available On the basis of analysis of existing diagnostic methods and regeneration ways of reinforced-concrete constructions of bridges the recommendations on introduction of new modern technologies of renewal of reinforced-concrete constructions of bridges in providing their operating reliability and longevity are offered.

  14. THE SIMULATION DIAGNOSTIC METHODS AND REGENERATION WAYS OF REINFORCED - CONCRETE CONSTRUCTIONS OF BRIDGES IN PROVIDING THEIR OPERATING RELIABILITY AND LONGEVITY

    OpenAIRE

    B. V. Savchinskiy

    2010-01-01

    On the basis of analysis of existing diagnostic methods and regeneration ways of reinforced-concrete constructions of bridges the recommendations on introduction of new modern technologies of renewal of reinforced-concrete constructions of bridges in providing their operating reliability and longevity are offered.

  15. A Mixed-Methods Investigation of Early Childhood Professional Development for Providers and Recipients in the United States

    Science.gov (United States)

    Linder, Sandra M.; Rembert, Kellye; Simpson, Amber; Ramey, M. Deanna

    2016-01-01

    This multi-phase mixed-methods study explores provider and recipient perceptions of the current state of early childhood professional development in a southeastern area of the United States. Professional development for the early childhood workforce has been shown to positively influence the quality of early childhood classrooms. This study…

  16. Perceptions of vaginal microbicides as an HIV prevention method among health care providers in KwaZulu-Natal, South Africa

    Directory of Open Access Journals (Sweden)

    Mantell Joanne E

    2007-03-01

    Full Text Available Abstract Background The promise of microbicides as an HIV prevention method will not be realized if not supported by health care providers. They are the primary source of sexual health information for potential users, in both the public and private health sectors. Therefore, the aim of this study was to determine perceptions of vaginal microbicides as a potential HIV prevention method among health care providers in Durban and Hlabisa, South Africa, using a combination of quantitative and qualitative methods. Results During 2004, semi structured interviews with 149 health care providers were conducted. Fifty seven percent of hospital managers, 40% of pharmacists and 35% of nurses possessed some basic knowledge of microbicides, such as the product being used intra-vaginally before sex to prevent HIV infection. The majority of them were positive about microbicides and were willing to counsel users regarding potential use. Providers from both public and private sectors felt that an effective microbicide should be available to all people, regardless of HIV status. Providers felt that the product should be accessed over-the-counter in pharmacies and in retail stores. They also felt a need for potential microbicides to be available free of charge, and packaged with clear instructions. The media was seen by health care providers as being an effective strategy for promoting microbicides. Conclusion Overall, health care providers were very positive about the possible introduction of an effective microbicide for HIV prevention. The findings generated by this study illustrated the need for training health care providers prior to making the product accessible, as well as the importance of addressing the potential barriers to use of the product by women. These are important concerns in the health care community, and this study also served to educate them for the day when research becomes reality.

  17. Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks

    International Nuclear Information System (INIS)

    Almonacid, F.; Rus, C.; Perez-Higueras, P.; Hontoria, L.

    2011-01-01

    The use of photovoltaics for electricity generation purposes has recorded one of the largest increases in the field of renewable energies. The energy production of a grid-connected PV system depends on various factors. In a wide sense, it is considered that the annual energy provided by a generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. However, a range of factors is influencing the expected outcome by reducing the generation of energy. The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network developed by the R and D Group for Solar and Automatic Energy at the University of Jaen. The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study, mainly due to the fact that this method takes also into account some second order effects, such as low irradiance, angular and spectral effects. -- Research highlights: → It is considered that the annual energy provided by a PV generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. → A range of factors are influencing the expected outcome by reducing the generation of energy (mismatch losses, dirt and dust, Ohmic losses,.). → The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network. → The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study. While classical methods have only taken into account temperature losses, the method based in

  18. Intelligent instrumentation principles and applications

    CERN Document Server

    Bhuyan, Manabendra

    2011-01-01

    With the advent of microprocessors and digital-processing technologies as catalyst, classical sensors capable of simple signal conditioning operations have evolved rapidly to take on higher and more specialized functions including validation, compensation, and classification. This new category of sensor expands the scope of incorporating intelligence into instrumentation systems, yet with such rapid changes, there has developed no universal standard for design, definition, or requirement with which to unify intelligent instrumentation. Explaining the underlying design methodologies of intelligent instrumentation, Intelligent Instrumentation: Principles and Applications provides a comprehensive and authoritative resource on the scientific foundations from which to coordinate and advance the field. Employing a textbook-like language, this book translates methodologies to more than 80 numerical examples, and provides applications in 14 case studies for a complete and working understanding of the material. Beginn...

  19. Artificial Intelligence for Diabetes Management and Decision Support: Literature Review.

    Science.gov (United States)

    Contreras, Ivan; Vehi, Josep

    2018-05-30

    Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis. The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges. A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review. We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results. We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients' quality of life. ©Ivan Contreras, Josep Vehi. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2018.

  20. Intelligence Level Performance Standards Research for Autonomous Vehicles.

    Science.gov (United States)

    Bostelman, Roger B; Hong, Tsai H; Messina, Elena

    2015-01-01

    United States and European safety standards have evolved to protect workers near Automatic Guided Vehicles (AGV's). However, performance standards for AGV's and mobile robots have only recently begun development. Lessons can be learned from research and standards efforts for mobile robots applied to emergency response and military applications. Research challenges, tests and evaluations, and programs to develop higher intelligence levels for vehicles can also used to guide industrial AGV developments towards more adaptable and intelligent systems. These other efforts also provide useful standards development criteria for AGV performance test methods. Current standards areas being considered for AGVs are for docking, navigation, obstacle avoidance, and the ground truth systems that measure performance. This paper provides a look to the future with standards developments in both the performance of vehicles and the dynamic perception systems that measure intelligent vehicle performance.

  1. Intelligent Design and Intelligent Failure

    Science.gov (United States)

    Jerman, Gregory

    2015-01-01

    Good Evening, my name is Greg Jerman and for nearly a quarter century I have been performing failure analysis on NASA's aerospace hardware. During that time I had the distinct privilege of keeping the Space Shuttle flying for two thirds of its history. I have analyzed a wide variety of failed hardware from simple electrical cables to cryogenic fuel tanks to high temperature turbine blades. During this time I have found that for all the time we spend intelligently designing things, we need to be equally intelligent about understanding why things fail. The NASA Flight Director for Apollo 13, Gene Kranz, is best known for the expression "Failure is not an option." However, NASA history is filled with failures both large and small, so it might be more accurate to say failure is inevitable. It is how we react and learn from our failures that makes the difference.

  2. Smart and Intelligent Sensors

    Science.gov (United States)

    Lansaw, John; Schmalzel, John; Figueroa, Jorge

    2009-01-01

    John C. Stennis Space Center (SSC) provides rocket engine propulsion testing for NASA's space programs. Since the development of the Space Shuttle, every Space Shuttle Main Engine (SSME) has undergone acceptance testing at SSC before going to Kennedy Space Center (KSC) for integration into the Space Shuttle. The SSME is a large cryogenic rocket engine that uses Liquid Hydrogen (LH2) as the fuel. As NASA moves to the new ARES V launch system, the main engines on the new vehicle, as well as the upper stage engine, are currently base lined to be cryogenic rocket engines that will also use LH2. The main rocket engines for the ARES V will be larger than the SSME, while the upper stage engine will be approximately half that size. As a result, significant quantities of hydrogen will be required during the development, testing, and operation of these rocket engines.Better approaches are needed to simplify sensor integration and help reduce life-cycle costs. 1.Smarter sensors. Sensor integration should be a matter of "plug-and-play" making sensors easier to add to a system. Sensors that implement new standards can help address this problem; for example, IEEE STD 1451.4 defines transducer electronic data sheet (TEDS) templates for commonly used sensors such as bridge elements and thermocouples. When a 1451.4 compliant smart sensor is connected to a system that can read the TEDS memory, all information needed to configure the data acquisition system can be uploaded. This reduces the amount of labor required and helps minimize configuration errors. 2.Intelligent sensors. Data received from a sensor be scaled, linearized; and converted to engineering units. Methods to reduce sensor processing overhead at the application node are needed. Smart sensors using low-cost microprocessors with integral data acquisition and communication support offer the means to add these capabilities. Once a processor is embedded, other features can be added; for example, intelligent sensors can make

  3. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  4. Cultural intelligence: A research landscape

    DEFF Research Database (Denmark)

    Alon, Ilan; Lankut, Erik; Richter, Nicole Franziska

    Purpose: This study identifies reviews the most influential literature streams to cultural intelligence by a bibliometric citation analysis and provides recommendations for future research. Design/methodology/approach: Three bibliometric citation tools are used to analyse a sample of 357 articles...... by 823 scholars in 199 different journals published between 1992-2017. Findings: The analysis reveals 10 research clusters within the topic of cultural intelligence and anables the identification of future research within and at the intercept of clusters....

  5. EMOTIONAL INTELLIGENCE AND SUCCESSFUL LEADERSHIP

    OpenAIRE

    Ilić, Egli

    2008-01-01

    The occurrence of the construct of emotional intelligence in the late twentieth century provoked controversies among scientists, due to connecting two, seemingly exclusive psychological notions – intelligence and emotions, with emotions being considered as an obstacle to rational thinking and quality performance. However, numerous studies have proven that, provided they are appropriately managed, emotions may even facilitate rational thinking, influence the appropriate decision-making and per...

  6. Modeling of glucose release from native and modified wheat starch gels during in vitro gastrointestinal digestion using artificial intelligence methods.

    Science.gov (United States)

    Yousefi, A R; Razavi, Seyed M A

    2017-04-01

    Estimation of the amounts of glucose release (AGR) during gastrointestinal digestion can be useful to identify food of potential use in the diet of individuals with diabetes. In this work, adaptive neuro-fuzzy inference system (ANFIS), genetic algorithm-artificial neural network (GA-ANN) and group method of data handling (GMDH) models were applied to estimate the AGR from native (NWS), cross-linked (CLWS) and hydroxypropylated wheat starch (HPWS) gels during digestion under simulated gastrointestinal conditions. The GA-ANN and ANFIS were fed with 3 inputs of digestion time (1-120min), gel volume (7.5 and 15ml) and concentration (8 and 12%, w/w) for prediction of the AGR. The developed ANFIS predictions were close to the experimental data (r=0.977-0.996 and RMSE=0.225-0.619). The optimized GA-ANN, which included 6-7 hidden neurons, predicted the AGR with a good precision (r=0.984-0.993 and RMSE=0.338-0.588). Also, a three layers GMDH model with 3 neurons accurately predicted the AGR (r=0.979-0.986 and RMSE=0.339-0.443). Sensitivity analysis data demonstrated that the gel concentration was the most sensitive factor for prediction of the AGR. The results dedicated that the AGR will be accurately predictable through such soft computing methods providing less computational cost and time. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. A combined usage of stochastic and quantitative risk assessment methods in the worksites: Application on an electric power provider

    International Nuclear Information System (INIS)

    Marhavilas, P.K.; Koulouriotis, D.E.

    2012-01-01

    An individual method cannot build either a realistic forecasting model or a risk assessment process in the worksites, and future perspectives should focus on the combined forecasting/estimation approach. The main purpose of this paper is to gain insight into a risk prediction and estimation methodological framework, using the combination of three different methods, including the proportional quantitative-risk-assessment technique (PRAT), the time-series stochastic process (TSP), and the method of estimating the societal-risk (SRE) by F–N curves. In order to prove the usefulness of the combined usage of stochastic and quantitative risk assessment methods, an application on an electric power provider industry is presented to, using empirical data.

  8. Computational intelligence in automotive applications

    Energy Technology Data Exchange (ETDEWEB)

    Prokhorov, Danil (ed.) [Toyota Motor Engineering and Manufacturing (TEMA), Ann Arbor, MI (United States). Toyota Technical Center

    2008-07-01

    What is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the fields of neural networks (NN), fuzzy logic and evolutionary computation. This edited volume is the first of its kind, suitable to automotive researchers, engineers and students. It provides a representative sample of contemporary CI activities in the area of automotive technology. The volume consists of 13 chapters, including but not limited to these topics: vehicle diagnostics and vehicle system safety, control of vehicular systems, quality control of automotive processes, driver state estimation, safety of pedestrians, intelligent vehicles. All chapters contain overviews of state of the art, and several chapters illustrate their methodologies on examples of real-world systems. About the Editor: Danil Prokhorov began his technical career in St. Petersburg, Russia, after graduating with Honors from Saint Petersburg State University of Aerospace Instrumentation in 1992 (MS in Robotics). He worked as a research engineer in St. Petersburg Institute for Informatics and Automation, one of the institutes of the Russian Academy of Sciences. He came to the US in late 1993 for Ph.D. studies. He became involved in automotive research in 1995 when he was a Summer intern at Ford Scientific Research Lab in Dearborn, MI. Upon his graduation from the EE Department of Texas Tech University, Lubbock, in 1997, he joined Ford to pursue application-driven research on neural networks and other machine learning algorithms. While at Ford, he took part in several production-bound projects including neural network based engine misfire detection. Since 2005 he is with Toyota Technical Center, Ann Arbor, MI, overseeing important mid- and long-term research projects in computational intelligence. (orig.)

  9. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    Schultz, D.E.; Hurd, J.W.; Brown, S.K.

    1987-01-01

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  10. Intelligent Fish Freshness Assessment

    Directory of Open Access Journals (Sweden)

    Hamid Gholam Hosseini

    2008-01-01

    Full Text Available Fish species identification and automated fish freshness assessment play important roles in fishery industry applications. This paper describes a method based on support vector machines (SVMs to improve the performance of fish identification systems. The result is used for the assessment of fish freshness using artificial neural network (ANN. Identification of the fish species involves processing of the images of fish. The most efficient features were extracted and combined with the down-sampled version of the images to create a 1D input vector. Max-Win algorithm applied to the SVM-based classifiers has enhanced the reliability of sorting to 96.46%. The realisation of Cyranose 320 Electronic nose (E-nose, in order to evaluate the fish freshness in real-time, is experimented. Intelligent processing of the sensor patterns involves the use of a dedicated ANN for each species under study. The best estimation of freshness was provided by the most sensitive sensors. Data was collected from four selected species of fishes over a period of ten days. It was concluded that the performance can be increased using individual trained ANN for each specie. The proposed system has been successful in identifying the number of days after catching the fish with an accuracy of up to 91%.

  11. Application of a Method for Intelligent Multi-Criteria Analysis of the Environmental Impact of Tailing Ponds in Northern Kosovo and Metohija

    Directory of Open Access Journals (Sweden)

    Gordana Milentijević

    2016-11-01

    Full Text Available The technological process of exploitation of mineral resources and processing of mined ores to cater to the market results, among other things, in a large amount of tailings deposed on tailing ponds. Because of the chemical composition of the material, the increasing amount of waste, and the mismanagement of recovery and reclamation of ponds, these ponds have become a significant element of negative impact on the surrounding ecosystem. Economics was behind the discharging of this material, resulting in tailing ponds created in inappropriate areas. There is an ongoing process of depositing tailings on old tailing ponds, although no special attention has been paid to the subsequent effect on the environment. Application of intelligent multi-criteria analysis AHP and PROMETHEE has been performed in this paper for the purpose of ranking the degree of negative impact on the environment of tailing ponds. Analysis is performed for five tailing ponds of MMCC (Mining Metallurgy Chemical Combine “Trepča”, whereby two of the ponds are active and three inactive. The ponds are in relatively close proximity to the municipalities of Zvečan and Kosovska Mitrovica, to the north of Kosovo and Metohija, Republic of Serbia. In order to achieve the most objective results, the AHP and PROMETHEE methods were applied. By using these methods for calculations, the following ranking for the flotation tailing waste deposits was obtained, regarding their environmental impact: Žitkovac, Tvrđanski Do, Bostanište, Gornje Polje and Žarkov Potok. This result can contribute to the decision-making process of a prioritizing strategy for rehabilitation and remediation of these five flotation tailings. The analysis illustrates that application of intelligent multi-criteria analysis is a useful environmental management tool to be included in the decision-making process.

  12. An Intelligent Robot Programing

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Seong Yong

    2012-01-15

    This book introduces an intelligent robot programing with background of the begging, introduction of VPL, and SPL, building of environment for robot platform, starting of robot programing, design of simulation environment, robot autonomy drive control programing, simulation graphic. Such as SPL graphic programing graphical image and graphical shapes, and graphical method application, application of procedure for robot control, robot multiprogramming, robot bumper sensor programing, robot LRF sencor programing and robot color sensor programing.

  13. An Intelligent Robot Programing

    International Nuclear Information System (INIS)

    Hong, Seong Yong

    2012-01-01

    This book introduces an intelligent robot programing with background of the begging, introduction of VPL, and SPL, building of environment for robot platform, starting of robot programing, design of simulation environment, robot autonomy drive control programing, simulation graphic. Such as SPL graphic programing graphical image and graphical shapes, and graphical method application, application of procedure for robot control, robot multiprogramming, robot bumper sensor programing, robot LRF sencor programing and robot color sensor programing.

  14. Evaluation of protection factors provided by full-face masks using man-test method at workplace

    International Nuclear Information System (INIS)

    Izumi, Yukio; Kinouchi, Nobuyuki; Ikezawa, Yoshio.

    1994-01-01

    From a practical angle of view to estimate the protection factors (PFs) provided by full-face masks, a number of protection factors were measured with a man-test apparatus just before the wearers started to do radiation work in radiation controlled area. PFs of the total number of 2,279 cases were measured under five simulated working conditions. The measured PFs were widely distributed from 2.3 to 6,700. About 95% of workers obtained PFs more than 50, and about 64% showed much higher PFs more than 1,000 due to good fitting. In the case of some persons, the measured PFs irregularly varied and changed to a large degree. This method is a reliable technique that has been confirmed to protect unexpected internal exposure. From the results obtained, the method should be necessary to provide a better mask and higher PF for each worker. (author)

  15. A METHOD AND AN APPARATUS FOR PROVIDING TIMING SIGNALS TO A NUMBER OF CIRCUITS, AN INTEGRATED CIRCUIT AND A NODE

    DEFF Research Database (Denmark)

    2006-01-01

    A method of providing or transporting a timing signal between a number of circuits, electrical or optical, where each circuit is fed by a node. The nodes forward timing signals between each other, and at least one node is adapted to not transmit a timing signal before having received a timing...... signal from at least two nodes. In this manner, the direction of the timing skew between nodes and circuits is known and data transport between the circuits made easier....

  16. Research on intelligent power distribution system for spacecraft

    Science.gov (United States)

    Xia, Xiaodong; Wu, Jianju

    2017-10-01

    The power distribution system (PDS) mainly realizes the power distribution and management of the electrical load of the whole spacecraft, which is directly related to the success or failure of the mission, and hence is an important part of the spacecraft. In order to improve the reliability and intelligent degree of the PDS, and considering the function and composition of spacecraft power distribution system, this paper systematically expounds the design principle and method of the intelligent power distribution system based on SSPC, and provides the analysis and verification of the test data additionally.

  17. Examining the interrelationships among students' personological characteristics, attitudes toward the Unified Modeling Language, self-efficacy, and multiple intelligences with respect to student achievement in a software design methods course

    Science.gov (United States)

    Stewart-Iles, Gail Marie

    The purpose of this study was to investigate the interrelationships among student's demographics, attitudes toward the Unified Modeling Language (UML), general self-efficacy, and multiple intelligence (MI) profiles, and the use of UML to develop software. The dependent measures were course grades and course project scores. The study was grounded in problem solving theory, self-efficacy theory, and multiple intelligence theory. The sample was an intact class of 18 students who took the junior-level Software Design Methods course, CSE 3421, at Florida Institute of Technology in the Spring 2008 semester. The course incorporated instruction in UML with Java. Attitudes were measured by a researcher-modified instrument derived from the Computer Laboratory Survey by Newby and Fisher, and self-efficacy was measured by the Generalized Self-Efficacy Scale developed by Schwarzer and Jerusalem. MI profiles, which were the proportion of Gardner's eight intelligences, were determined from Shearer's Multiple Intelligence Developmental Assessment Scales. Results from a hierarchical multiple regression analysis showed that only the collective set of MI profiles was significant, but none of the individual intelligences were significant. The study's findings supported what one would expect to find relative to problem solving theory, but were contradictory to self-efficacy theory. The findings also supported Gardner's concept that multiple intelligences must be considered as an integral unit and the importance of not focusing on an individual intelligence. The findings imply that self-efficacy is not a major consideration for a software design methods class that requires a transition to problem solving strategy and suggest that the instructor was instrumental in fostering positive attitudes toward UML. Recommendations for practice include (1) teachers should not be concerned with focusing on a single intelligence simply because they believe one intelligence might be more aligned to a

  18. Social networks a framework of computational intelligence

    CERN Document Server

    Chen, Shyi-Ming

    2014-01-01

    This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

  19. Soft computing in intelligent control

    CERN Document Server

    Jung, Jin-Woo; Kubota, Naoyuki

    2014-01-01

    Nowadays, people have tendency to be fond of smarter machines that are able to collect data, make learning, recognize things, infer meanings, communicate with human and perform behaviors. Thus, we have built advanced intelligent control affecting all around societies; automotive, rail, aerospace, defense, energy, healthcare, telecoms and consumer electronics, finance, urbanization. Consequently, users and consumers can take new experiences through the intelligent control systems. We can reshape the technology world and provide new opportunities for industry and business, by offering cost-effective, sustainable and innovative business models. We will have to know how to create our own digital life. The intelligent control systems enable people to make complex applications, to implement system integration and to meet society’s demand for safety and security. This book aims at presenting the research results and solutions of applications in relevance with intelligent control systems. We propose to researchers ...

  20. Before and Beyond Anticipatory Intelligence: Assessing the Potential for Crowdsourcing and Intelligence Studies

    Directory of Open Access Journals (Sweden)

    Alexander Halman

    2015-10-01

    Full Text Available Crowdsourcing is a new tool for businesses, academics, and now intelligence analysts. Enabled by recent technology, crowdsourcing allows researchers to harness the wisdom of crowds and provide recommendations and insight into complex problems. This paper examines the potential benefits and limitations of crowdsourcing for intelligence analysis and the intelligence community beyond its primary use: anticipatory intelligence. The author constructs a model and compares it to existing crowdsourcing theories in business, information science, and public policy. Finally, he offers advice for intelligence analysis and public policy.

  1. Bridging Home and School through Multiple Intelligences.

    Science.gov (United States)

    Reiff, Judith C.

    1996-01-01

    Suggests that teachers can share information with parents about multiple intelligences and encourage parents to provide activities to nurture their child's own intelligences. Provides teachers with instructional strategies and parents with activities related to linguistic, logical-mathematical, spatial, musical, bodily-kinesthetic, interpersonal,…

  2. Business Intelligence

    OpenAIRE

    Petersen, Anders

    2001-01-01

    Cílem této bakalářské práce je seznámení s Business Intelligence a zpracování vývojového trendu, který ovlivňuje podobu řešení Business Intelligence v podniku ? Business Activity Monitoring. Pro zpracování tohoto tématu byla použita metoda studia odborných pramenů, a to jak v českém, tak v anglickém jazyce. Hlavním přínosem práce je ucelený, v českém jazyce zpracovaný materiál pojednávající o Business Activity Monitoring. Práce je rozdělena do šesti hlavních kapitol. Prvních pět je věnováno p...

  3. Web Intelligence and Artificial Intelligence in Education

    Science.gov (United States)

    Devedzic, Vladan

    2004-01-01

    This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

  4. Intelligent navigation to improve obstetrical sonography.

    Science.gov (United States)

    Yeo, Lami; Romero, Roberto

    2016-04-01

    use of software to perform manual navigation of volume datasets. Diagnostic planes and VIS-Assistance videoclips can be transmitted by telemedicine so that expert consultants can evaluate the images to provide an opinion. The end result is a user-friendly, simple, fast and consistent method of obtaining sonographic images with decreased operator dependency. Intelligent navigation is one approach to improve obstetrical sonography. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  5. A Similarity-Ranking Method on Semantic Computing for Providing Information-Services in Station-Concierge System

    Directory of Open Access Journals (Sweden)

    Motoki Yokoyama

    2017-07-01

    Full Text Available The prevalence of smartphones and wireless broadband networks have been progressing as a new Railway infomration environment. According to the spread of such devices and information technology, various types of information can be obtained from databases connected to the Internet. One scenario of obtaining such a wide variety of information resources is in the phase of user’s transportation. This paper proposes an information provision system, named the Station Concierge System that matches the situation and intention of passengers. The purpose of this system is to estimate the needs of passengers like station staff or hotel concierge and to provide information resources that satisfy user’s expectations dynamically. The most important module of the system is constructed based on a new information ranking method for passenger intention prediction and service recommendation. This method has three main features, which are (1 projecting a user to semantic vector space by using her current context, (2 predicting the intention of a user based on selecting a semantic vector subspace, and (3 ranking the services by a descending order of relevant scores to the user’ intention. By comparing the predicted results of our method with those of two straightforward computation methods, the experimental studies show the effectiveness and efficiency of the proposed method. Using this system, users can obtain transit information and service map that dynamically matches their context.

  6. Advances in Intelligence and Security Informatics

    CERN Document Server

    Mao, Wenji

    2012-01-01

    The Intelligent Systems Series comprises titles that present state of the art knowledge and the latest advances in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. Traditionally, Intelligence and Security Informatics (ISI) research and applications have focused on information sharing and data mining, social network analysis, infrastructure protection and emergency responses for security informatics. With the continuous advance of IT technologies and the increasing sophistication of national and international securi

  7. Ethical Considerations in Artificial Intelligence Courses

    OpenAIRE

    Burton, Emanuelle; Goldsmith, Judy; Koenig, Sven; Kuipers, Benjamin; Mattei, Nicholas; Walsh, Toby

    2017-01-01

    The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses. As instructors we want to develop curriculum that not only prepares students to be artificial intelligence practitioners, but also to understand the moral, ethical, and philosophical impacts that artificial intelligence will have on society. In this article we provide practical case studies and links to resources for ...

  8. Intelligent Metering for Urban Water: A Review

    OpenAIRE

    Rodney Stewart; Stuart White; Candice Moy; Ariane Liu; Pierre Mukheibir; Damien Giurco; Thomas Boyle

    2013-01-01

    This paper reviews the drivers, development and global deployment of intelligent water metering in the urban context. Recognising that intelligent metering (or smart metering) has the potential to revolutionise customer engagement and management of urban water by utilities, this paper provides a summary of the knowledge-base for researchers and industry practitioners to ensure that the technology fosters sustainable urban water management. To date, roll-outs of intelligent metering have been ...

  9. Computational Intelligence in Information Systems Conference

    CERN Document Server

    Au, Thien-Wan; Omar, Saiful

    2017-01-01

    This book constitutes the Proceedings of the Computational Intelligence in Information Systems conference (CIIS 2016), held in Brunei, November 18–20, 2016. The CIIS conference provides a platform for researchers to exchange the latest ideas and to present new research advances in general areas related to computational intelligence and its applications. The 26 revised full papers presented in this book have been carefully selected from 62 submissions. They cover a wide range of topics and application areas in computational intelligence and informatics.

  10. Binary Masking & Speech Intelligibility

    DEFF Research Database (Denmark)

    Boldt, Jesper

    The purpose of this thesis is to examine how binary masking can be used to increase intelligibility in situations where hearing impaired listeners have difficulties understanding what is being said. The major part of the experiments carried out in this thesis can be categorized as either experime......The purpose of this thesis is to examine how binary masking can be used to increase intelligibility in situations where hearing impaired listeners have difficulties understanding what is being said. The major part of the experiments carried out in this thesis can be categorized as either...... experiments under ideal conditions or as experiments under more realistic conditions useful for real-life applications such as hearing aids. In the experiments under ideal conditions, the previously defined ideal binary mask is evaluated using hearing impaired listeners, and a novel binary mask -- the target...... binary mask -- is introduced. The target binary mask shows the same substantial increase in intelligibility as the ideal binary mask and is proposed as a new reference for binary masking. In the category of real-life applications, two new methods are proposed: a method for estimation of the ideal binary...

  11. Intelligent Interactive Multimedia

    CERN Document Server

    Watanabe, Toyohide; Takahashi, Naohisa; 5th International Conference on Intelligent Interactive Multimedia Systems and Services

    2012-01-01

    This volume contains the Proceedings of the 5th International Conference on Intelligent Interactive Multimedia Systems and Services (KES-IIMSS-12).  The Conference was jointly organised by Nagoya University in Japan and the KES International organisation, and held in the attractive city of Gifu.   The KES-IIMSS conference series, (series chairs Prof. Maria Virvou and Prof. George Tsihrintzis), presents novel research in various areas of intelligent multimedia system relevant to the development of a new generation of interactive, user-centric devices and systems.  The aim of the conference is to provide an internationally respected forum for scientific research in the technologies and applications of this new and dynamic research area.

  12. Patterns and Intelligent Systems

    International Nuclear Information System (INIS)

    Cordes, Gail A.

    2003-01-01

    The recognition and analysis of evolving patterns provides a unifying concept for studying and implementing intelligent information processing for open feedback control systems within the nuclear industry. Control is considered as influence of a large system to achieve the goals of the human (who might or might not be part of an open feedback loop) and is not limited to operation of a component within a nuclear power plant. The intelligent control system includes open logic and can automatically react to new data in an unprogrammed way. This application of evolving patterns integrates current research developments in human cognition and scientific semiotics with traditional feedback control. A preliminary implementation of such a system using existing computational techniques is postulated, and tools that are lacking at this time are identified. Proof-of-concept applications for the nuclear industry are referenced

  13. Mechatronical Aided Concept (MAC) in Intelligent Transport Vehicles Design

    OpenAIRE

    Pavel Pavlasek

    2003-01-01

    This article deals with the principles of synergy effect of mechatronical aided concept (MAC) to the design of intelligent transport vehicles products applying CA technologies and virtual reality design methods. Also includes presentation of intelligent railway vehicle development.

  14. Application of computational intelligence in emerging power systems

    African Journals Online (AJOL)

    ... in the electrical engineering applications. This paper highlights the application of computational intelligence methods in power system problems. Various types of CI methods, which are widely used in power system, are also discussed in the brief. Keywords: Power systems, computational intelligence, artificial intelligence.

  15. Development of an Intelligent Car Engine Fault Troubleshooting ...

    African Journals Online (AJOL)

    Development of an Intelligent Car Engine Fault Troubleshooting System (CEFTS) ... and also provides a troubleshooting framework for other researchers to work on. Keywords: ... inference engine, knowledge acquisition, artificial intelligence.

  16. Dysfunction Junction: Intelligence, Peacekeeping, and the United Nations

    National Research Council Canada - National Science Library

    Maceda, Steven E

    2007-01-01

    .... The UN, however, lacks the institutional intelligence capacity to provide guidance, high-level assessments, and tactical/operational intelligence support for the over 100,000 peacekeepers around the world...

  17. The Role of Intelligence Analysis in the War on Terrorism

    National Research Council Canada - National Science Library

    Ormond, Valerie

    2002-01-01

    The United States government must provide the intelligence community's analytical force with the necessary resources and capabilities in order to use intelligence analysis as an effective weapon in the War on Terrorism...

  18. Experiential Learning Using QlikView Business Intelligence Software

    Science.gov (United States)

    Podeschi, R. J.

    2015-01-01

    This paper reports on the use of QlikView business intelligence software for use in a Business Intelligence (BI) course within an undergraduate information systems program. The course provides students with concepts related to data warehousing, data mining, visualizations, and software tools to provide business intelligence solutions for decision…

  19. When does spiritual intelligence particularly predict job engagement? The mediating role of psychological empowerment.

    Science.gov (United States)

    Torabi, Mohsen; Nadali, Iman Zohoorian

    2016-01-01

    Regarding the importance of health care providers such as nurses who are always in stressful environments, it is imperative to better understand how they become more engaged in their work. The purpose of this paper is to focus on health care providers (nurses), and examine how the interaction between spiritual intelligence and psychological empowerment affect job engagement. This descriptive and quantitative study was conducted among nurses at the Faghihi Hospital in Shiraz, Iran in 2010. A sample of nurses ( n = 179) completed standard survey questionnaire including spiritual intelligence, psychological empowerment, and job engagement which included 5 questions for each dimensions. For testing the hypotheses of the study, results were analyzed through structural equation modeling (SEM) using LISREL 8.8. SEM revealed that psychological empowerment could fully mediate the relationship between spiritual intelligence and job engagement. However, the correlation between spiritual intelligence and job engagement was significant but weak using Pearson coefficient method. This can imply that psychological empowerment plays a crucial role in the relationship between spiritual intelligence and job engagement. This paper indicates that spiritual intelligence might affect different organizational parameters, directly or indirectly. Therefore, it is recommended that the researchers evaluate probable relationships between spiritual intelligence and other variables.

  20. SAI Intelligent Systems Conference (IntelliSys) 2015

    CERN Document Server

    Kapoor, Supriya; Bhatia, Rahul

    2016-01-01

    This book is a remarkable collection of chapters covering a wider range of topics, including unsupervised text mining, anomaly and Intrusion Detection, Self-reconfiguring Robotics, application of Fuzzy Logic to development aid, Design and Optimization, Context-Aware Reasoning, DNA Sequence Assembly and Multilayer Perceptron Networks. The twenty-one chapters present extended results from the SAI Intelligent Systems Conference (IntelliSys) 2015 and have been selected based on high recommendations during IntelliSys 2015 review process. This book presents innovative research and development carried out presently in fields of knowledge representation and reasoning, machine learning, and particularly in intelligent systems in a more broad sense. It provides state - of - the - art intelligent methods and techniques for solving real world problems along with a vision of the future research.

  1. Intelligent alarming

    Science.gov (United States)

    Braden, W. B.

    1992-01-01

    This talk discusses the importance of providing a process operator with concise information about a process fault including a root cause diagnosis of the problem, a suggested best action for correcting the fault, and prioritization of the problem set. A decision tree approach is used to illustrate one type of approach for determining the root cause of a problem. Fault detection in several different types of scenarios is addressed, including pump malfunctions and pipeline leaks. The talk stresses the need for a good data rectification strategy and good process models along with a method for presenting the findings to the process operator in a focused and understandable way. A real time expert system is discussed as an effective tool to help provide operators with this type of information. The use of expert systems in the analysis of actual versus predicted results from neural networks and other types of process models is discussed.

  2. A comparison of performance of several artificial intelligence methods for predicting the dynamic viscosity of TiO2/SAE 50 nano-lubricant

    Science.gov (United States)

    Hemmat Esfe, Mohammad; Tatar, Afshin; Ahangar, Mohammad Reza Hassani; Rostamian, Hossein

    2018-02-01

    Since the conventional thermal fluids such as water, oil, and ethylene glycol have poor thermal properties, the tiny solid particles are added to these fluids to increase their heat transfer improvement. As viscosity determines the rheological behavior of a fluid, studying the parameters affecting the viscosity is crucial. Since the experimental measurement of viscosity is expensive and time consuming, predicting this parameter is the apt method. In this work, three artificial intelligence methods containing Genetic Algorithm-Radial Basis Function Neural Networks (GA-RBF), Least Square Support Vector Machine (LS-SVM) and Gene Expression Programming (GEP) were applied to predict the viscosity of TiO2/SAE 50 nano-lubricant with Non-Newtonian power-law behavior using experimental data. The correlation factor (R2), Average Absolute Relative Deviation (AARD), Root Mean Square Error (RMSE), and Margin of Deviation were employed to investigate the accuracy of the proposed models. RMSE values of 0.58, 1.28, and 6.59 and R2 values of 0.99998, 0.99991, and 0.99777 reveal the accuracy of the proposed models for respective GA-RBF, CSA-LSSVM, and GEP methods. Among the developed models, the GA-RBF shows the best accuracy.

  3. A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Deyu Cui

    2018-04-01

    Full Text Available State of charge (SOC estimation is becoming increasingly important, along with electric vehicle (EV rapid development, while SOC is one of the most significant parameters for the battery management system, indicating remaining energy and ensuring the safety and reliability of EV. In this paper, a hybrid wavelet neural network (WNN model combining the discrete wavelet transform (DWT method and adaptive WNN is proposed to estimate the SOC of lithium-ion batteries. The WNN model is trained by Levenberg-Marquardt (L-M algorithm, whose inputs are processed by discrete wavelet decomposition and reconstitution. Compared with back-propagation neural network (BPNN, L-M based BPNN (LMBPNN, L-M based WNN (LMWNN, DWT with L-M based BPNN (DWTLMBPNN and extend Kalman filter (EKF, the proposed intelligent SOC estimation method is validated and proved to be effective. Under the New European Driving Cycle (NEDC, the mean absolute error and maximum error can be reduced to 0.59% and 3.13%, respectively. The characteristics of high accuracy and strong robustness of the proposed method are verified by comparison study and robustness evaluation results (e.g., measurement noise test and untrained driving cycle test.

  4. Behavioural responses to hypoxia provide a non-invasive method for distinguishing between stress coping styles in fish

    DEFF Research Database (Denmark)

    Laursen, Danielle Caroline; Olsén, Hanna L.; Ruiz-Gomez, Maria de Lourdes

    2011-01-01

    . These individual differences may result in suboptimal production and compromised welfare in aquaculture. An approach to overcome these problems could be to sort fish and optimise rearing conditions according to coping style. It has been previously demonstrated that the proactive and reactive coping styles in fish......, these fish provided an opportunity for verifying a method for sorting fish with respect to coping style by exposure to hypoxia. Groups consisting of 24 individually tagged fish, 12 HR and 12 LR were exposed to hypoxia in a two choice system. The system consisted of a “home” tank provided with cover connected...... to a second brightly “illuminated” tank via a closable doorway. During the experiment, the doorway between the two tanks was opened and hypoxic conditions were gradually induced in the “home” tank by bubbling with nitrogen. The latency time to move away from hypoxic conditions to normoxic conditions...

  5. The paradox of compassionate work: a mixed-methods study of satisfying and fatiguing experiences of animal health care providers.

    Science.gov (United States)

    Polachek, Alicia J; Wallace, Jean E

    2018-03-01

    Compassionate work appears paradoxical as it may provide great rewards, but may also come at great costs to care providers. This paper explores the paradox of compassionate work by examining what interactions contribute to compassion satisfaction and what interactions contribute to compassion fatigue. This mixed-methods, cross-sectional study uses qualitative interview data from animal health care providers (N = 20) to identify work interactions that they find satisfying or stressful. Quantitative survey data (N = 572) are used to test hypotheses generated from the interviews regarding predictors of compassion satisfaction and compassion fatigue. Interview transcripts were analyzed using a directed content analysis approach. Survey data were analyzed using ordinary least squares regression. The results highlight the complex nature of compassionate work. As hypothesized, making a difference to animals and building relationships with animal patients and human clients relate to greater compassion satisfaction. Human client barriers to animal care and witnessing client grief relate to greater compassion fatigue, as predicted. None of the predictors relate to less compassion fatigue, but forming relationships with animal patients relates to both greater compassion satisfaction and compassion fatigue. This paper enhances our understanding of provider-client-patient interactions and highlights the paradox of compassionate work.

  6. runjags: An R Package Providing Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS

    Directory of Open Access Journals (Sweden)

    Matthew J. Denwood

    2016-07-01

    Full Text Available The runjags package provides a set of interface functions to facilitate running Markov chain Monte Carlo models in JAGS from within R. Automated calculation of appropriate convergence and sample length diagnostics, user-friendly access to commonly used graphical outputs and summary statistics, and parallelized methods of running JAGS are provided. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. Automated simulation study functions are implemented to facilitate model performance assessment, as well as drop-k type cross-validation studies, using high performance computing clusters such as those provided by parallel. A module extension for JAGS is also included within runjags, providing the Pareto family of distributions and a series of minimally-informative priors including the DuMouchel and half-Cauchy priors. This paper outlines the primary functions of this package, and gives an illustration of a simulation study to assess the sensitivity of two equivalent model formulations to different prior distributions.

  7. DETECTION OF REPORTS FALSIFICATION PROVIDED TO A BANK BY A BORROWER USING THE METHOD OF DYNAMIC PARAMETERS ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. S. Lyuft

    2015-01-01

    Full Text Available Summary. The main stop-factors in a landing were formed in the article according to the procedure of the European Bank for Reconstruction and Development by the means of questioning the leading Russian banks that finance small-scale business. It is given the description of this method, also it is identified the main weaknesses of the EBRD methodology. There is a description of the main methods of the borrowing company’s analytical balance and thereupon it is made the conclusion about the necessity of the analysis of the balance’s principal factors across time. The analysis of indicators and factors in the dynamics enables us to see trends in the development of the company, and to identify deviations in the coefficients. Either materiality or difference from normal values of these coefficients may indicate the factors of the borrowers’ misconduct, and in particular it gives evidence concerning falsification of reports provided to a bank. There are stages of information processing for falsification’s detection, excluding the interest from decision-makers about the possibility of lending in the results of a transaction. The formula that determinates the value of net profit falsification has been made on basis of dynamic parameters of the analytical balance and the connection with the administrative profit-and-loss report. Further, the article provides the second method of a determination of the net profit falsification already based on data of the parameters in dynamics namely business profitability rate. The process of calculation Payment To Income - payment to income - an indicator, in order to obtain good data on who falsify net income. Are key strengths of this method of identifying and conclusions paragraph article.

  8. Intelligence and negotiating

    International Nuclear Information System (INIS)

    George, D.G.

    1990-01-01

    This paper discusses the role of US intelligence during arms control negotiations between 1982 and 1987. It also covers : the orchestration of intelligence projects; an evaluation of the performance of intelligence activities; the effect intelligence work had on actual arms negotiations; and suggestions for improvements in the future

  9. Intelligent products : A survey

    NARCIS (Netherlands)

    Meyer, G.G.; Främling, K.; Holmström, J.

    This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

  10. Intelligence Issues for Congress

    Science.gov (United States)

    2013-04-23

    open source information— osint (newspapers...by user agencies. Section 1052 of the Intelligence Reform Act expressed the sense of Congress that there should be an open source intelligence ...center to coordinate the collection, analysis, production, and dissemination of open source intelligence to other intelligence agencies. An Open Source

  11. Intelligent Governmentality

    Directory of Open Access Journals (Sweden)

    Willem de Lint

    2008-10-01

    Full Text Available Recently, within liberal democracies, the post-Westphalian consolidation of security and intelligence has ushered in the normalization not only of security in ‘securitization’ but also of intelligence in what is proposed here as ‘intelligencification.’ In outlining the features of intelligencified governance, my aim is to interrogate the view that effects or traces, and productivity rather than negation is as persuasive as commonly thought by the constructivists. After all, counter-intelligence is both about purging and reconstructing the archive for undisclosed values. In practice, what is being normalized is the authorized and legalized use of release and retention protocols of politically actionable information. The intelligencification of governmentality affords a sovereignty shell-game or the instrumentalization of sovereign power by interests that are dependent on, yet often inimical to, the power of state, national, and popular sovereignty. On voit le politique et le social comme dépendant de contingences exclusives. Récemment, au sein des démocraties libérales, la consolidation de la sécurité et des services de renseignements de sécurité qui a suivi les traités de la Westphalie a donné lieu à la normalisation non seulement de la sécurité en «sécurisation» mais aussi des services de renseignements de sécurité en ce qui est proposé ici comme «intelligencification» [terme anglais créé par l’auteur, dérivé du mot anglais «intelligence» dans le sens de renseignements des écurité]. En particulier, ce que l’on normalise dans le but de contourner des contingences exclusives est l’utilisation autorisée et légalisée de protocoles de communication et de rétention d’information qui, politiquement, pourrait mener à des poursuites. En esquissant les traits de la gouvernance «intelligencifiée», mon but est d’interroger le point de vue que les effets ou les traces, et la productivité plutôt que la

  12. Pathogen intelligence

    Directory of Open Access Journals (Sweden)

    Michael eSteinert

    2014-01-01

    Full Text Available Different species inhabit different sensory worlds and thus have evolved diverse means of processing information, learning and memory. In the escalated arms race with host defense, each pathogenic bacterium not only has evolved its individual cellular sensing and behaviour, but also collective sensing, interbacterial communication, distributed information processing, joint decision making, dissociative behaviour, and the phenotypic and genotypic heterogeneity necessary for epidemiologic success. Moreover, pathogenic populations take advantage of dormancy strategies and rapid evolutionary speed, which allow them to save co-generated intelligent traits in a collective genomic memory. This review discusses how these mechanisms add further levels of complexity to bacterial pathogenicity and transmission, and how mining for these mechanisms could help to develop new anti-infective strategies.

  13. Intelligent Routines

    CERN Document Server

    Anastassiou, George A

    Intelligent Routines II: Solving Linear Algebra and Differential Geometry with Sage” contains numerous of examples and problems as well as many unsolved problems. This book extensively applies the successful software Sage, which can be found free online http://www.sagemath.org/. Sage is a recent and popular software for mathematical computation, available freely and simple to use. This book is useful to all applied scientists in mathematics, statistics and engineering, as well for late undergraduate and graduate students of above subjects. It is the first such book in solving symbolically with Sage problems in Linear Algebra and Differential Geometry. Plenty of SAGE applications are given at each step of the exposition.

  14. Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems

    Science.gov (United States)

    Fiuzy, Mohammad; Haddadnia, Javad; Mollania, Nasrin; Hashemian, Maryam; Hassanpour, Kazem

    2012-01-01

    Background Accurate Diagnosis of Breast Cancer is of prime importance. Fine Needle Aspiration test or "FNA”, which has been used for several years in Europe, is a simple, inexpensive, noninvasive and accurate technique for detecting breast cancer. Expending the suitable features of the Fine Needle Aspiration results is the most important diagnostic problem in early stages of breast cancer. In this study, we introduced a new algorithm that can detect breast cancer based on combining artificial intelligent system and Fine Needle Aspiration (FNA). Methods We studied the Features of Wisconsin Data Base Cancer which contained about 569 FNA test samples (212 patient samples (malignant) and 357 healthy samples (benign)). In this research, we combined Artificial Intelligence Approaches, such as Evolutionary Algorithm (EA) with Genetic Algorithm (GA), and also used Exact Classifier Systems (here by Fuzzy C-Means (FCM)) to separate malignant from benign samples. Furthermore, we examined artificial Neural Networks (NN) to identify the model and structure. This research proposed a new algorithm for an accurate diagnosis of breast cancer. Results According to Wisconsin Data Base Cancer (WDBC) data base, 62.75% of samples were benign, and 37.25% were malignant. After applying the proposed algorithm, we achieved high detection accuracy of about "96.579%” on 205 patients who were diagnosed as having breast cancer. It was found that the method had 93% sensitivity, 73% specialty, 65% positive predictive value, and 95% negative predictive value, respectively. If done by experts, Fine Needle Aspiration (FNA) can be a reliable replacement for open biopsy in palpable breast masses. Evaluation of FNA samples during aspiration can decrease insufficient samples. FNA can be the first line of diagnosis in women with breast masses, at least in deprived regions, and may increase health standards and clinical supervision of patients. Conclusion Such a smart, economical, non-invasive, rapid

  15. Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

    Science.gov (United States)

    Mehdizadeh, Saeid

    2018-04-01

    Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000-2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external

  16. A comparison of classical and intelligent methods to detect potential thermal anomalies before the 11 August 2012 Varzeghan, Iran, earthquake (Mw = 6.4)

    Science.gov (United States)

    Akhoondzadeh, M.

    2013-04-01

    In this paper, a number of classical and intelligent methods, including interquartile, autoregressive integrated moving average (ARIMA), artificial neural network (ANN) and support vector machine (SVM), have been proposed to quantify potential thermal anomalies around the time of the 11 August 2012 Varzeghan, Iran, earthquake (Mw = 6.4). The duration of the data set, which is comprised of Aqua-MODIS land surface temperature (LST) night-time snapshot images, is 62 days. In order to quantify variations of LST data obtained from satellite images, the air temperature (AT) data derived from the meteorological station close to the earthquake epicenter has been taken into account. For the models examined here, results indicate the following: (i) ARIMA models, which are the most widely used in the time series community for short-term forecasting, are quickly and easily implemented, and can efficiently act through linear solutions. (ii) A multilayer perceptron (MLP) feed-forward neural network can be a suitable non-parametric method to detect the anomalous changes of a non-linear time series such as variations of LST. (iii) Since SVMs are often used due to their many advantages for classification and regression tasks, it can be shown that, if the difference between the predicted value using the SVM method and the observed value exceeds the pre-defined threshold value, then the observed value could be regarded as an anomaly. (iv) ANN and SVM methods could be powerful tools in modeling complex phenomena such as earthquake precursor time series where we may not know what the underlying data generating process is. There is good agreement in the results obtained from the different methods for quantifying potential anomalies in a given LST time series. This paper indicates that the detection of the potential thermal anomalies derive credibility from the overall efficiencies and potentialities of the four integrated methods.

  17. Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues.

    Science.gov (United States)

    Del Valle, José C; Gallardo-López, Antonio; Buide, Mª Luisa; Whittall, Justen B; Narbona, Eduardo

    2018-03-01

    Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer-level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content-chroma ratio, anthocyanin content-chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r 2 and normalized root-mean-square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the

  18. Development of quality indicators for low-risk labor care provided by midwives using a RAND-modified Delphi method.

    Science.gov (United States)

    Ueda, Kayo; Ohtera, Shosuke; Kaso, Misato; Nakayama, Takeo

    2017-09-22

    In childbirth, most deliveries are low-risk, defined as spontaneous labor at full term without special high-risk facts or complications, especially in high-resource countries where maternal and perinatal mortality rates are very low. Indeed, the majority of mothers and infants have no serious conditions during labor. However, the quality of care provided is not assured, and performance may vary by birthing facility and provider. The overuse of technology in childbirth in some parts of the world is almost certainly based on assumptions like, "something can go wrong at any minute." There is a need to assess the quality of care provided for mothers and infants in low-risk labor. We aimed to develop specific quality indicators for low-risk labor care provided primarily by midwives in Japan. We used a RAND-modified Delphi method, which integrates evidence review with expert consensus development. The procedure comprises five steps: (1) literature review, including clinical practice guidelines, to extract and develop quality indicator candidates; (2) formation of a multidisciplinary panel; (3) independent panel ratings (Round 1); (4) panel meeting and independent panel ratings (Round 2); and (5) independent panel ratings (Round 3). The three independent panel ratings (Rounds 1-3) were held between July and December 2012. The assembled multidisciplinary panel comprised eight clinicians (two pediatricians, three obstetricians, and three midwives) and three mothers who were nonclinicians. Evidentiary review extracted 166 key recommendations from 32 clinical practice guidelines, and 31 existing quality indicators were added. After excluding duplicate recommendations and quality indicators, the panel discussed 25 candidate indicators. Of these, 18 were adopted, one was modified, six were not adopted, and four were added during the meeting, respectively. We established 23 quality indicators for low-risk labor care provided by midwives in labor units in Japan.

  19. A mixed-methods examination of communication between oncologists and primary care providers among primary care physicians in underserved communities.

    Science.gov (United States)

    Shen, Megan Johnson; Binz-Scharf, Maria; D'Agostino, Tom; Blakeney, Natasha; Weiss, Elisa; Michaels, Margo; Patel, Shilpa; McKee, M Diane; Bylund, Carma L

    2015-03-15

    Research has demonstrated that communication and care coordination improve cancer patient outcomes. To improve communication and care coordination, it is important to understand primary care providers' (PCPs') perceptions of communication with oncologists as well as PCPs' communication needs. A mixed-methods approach was used in the present study. In the qualitative phase of the study, 18 PCPs practicing in underserved, minority communities were interviewed about their experiences communicating with oncologists. In the quantitative phase of the study, 128 PCPs completed an online survey about their preferences, experiences, and satisfaction with communication with oncologists. Results indicated a PCP-oncologist gap in communication occurred between diagnosis and treatment. PCPs wanted more communication with oncologists, updates on their patients' prognosis throughout treatment, and to be contacted via telephone or email and saw their role as crucial in providing supportive care for their patients. Although PCPs recognize that they play a critical, proactive role in supporting patients throughout the continuum of their cancer care experience, existing norms regarding postreferral engagement and oncologist-PCP communication often hinder activation of this role among PCPs. Expected standards regarding the method, frequency, and quality of postreferral communication should be jointly articulated and made accountable between PCPs and oncologists to help improve cancer patients' quality of care, particularly in minority communities. © 2014 American Cancer Society.

  20. Applications of computational intelligence in nuclear reactors

    International Nuclear Information System (INIS)

    Jayalal, M.L.; Jehadeesan, R.

    2016-01-01

    Computational intelligence techniques have been successfully employed in a wide range of applications which include the domains of medical, bioinformatics, electronics, communications and business. There has been progress in applying of computational intelligence in the nuclear reactor domain during the last two decades. The stringent nuclear safety regulations pertaining to reactor environment present challenges in the application of computational intelligence in various nuclear sub-systems. The applications of various methods of computational intelligence in the domain of nuclear reactors are discussed in this paper. (author)

  1. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  2. Intelligence for Human-Assistant Planetary Surface Robots

    Science.gov (United States)

    Hirsh, Robert; Graham, Jeffrey; Tyree, Kimberly; Sierhuis, Maarten; Clancey, William J.

    2006-01-01

    The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.

  3. Artificial intelligence in cardiology

    Directory of Open Access Journals (Sweden)

    Srishti Sharma

    2017-01-01

    Full Text Available Artificial intelligence (AI provides machines with the ability to learn and respond the way humans do and is also referred to as machine learning. The step to building an AI system is to provide the data to learn from so that it can map relations between inputs and outputs and set up parameters such as “weights”/decision boundaries to predict responses for inputs in the future. Then, the model is tested on a second data set. This article outlines the promise this analytic approach has in medicine and cardiology.

  4. Reviewing the development of an artificial intelligence based risk program

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    A successful application of nonconventional programming methods has been achieved in computer-assisted probabilistic risk assessment (PRA). The event tree sequence importance calculator, SQUIMP, provides for prompted data entry, generic expansion, on-line pruning, boolean reductions, and importance factor selection. SQUIMP employs constructs typically found in artificial intelligence (AI) programs. The development history of SQUIMP is outlined and its internal structure described as background for a discussion on the applicability of symbolic programming methods in PRA

  5. Probabilistic reasoning in intelligent systems networks of plausible inference

    CERN Document Server

    Pearl, Judea

    1988-01-01

    Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provid

  6. Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

    Science.gov (United States)

    Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

    2017-12-01

    To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

  7. A New Method for Rating Hazard from Intense Sounds: Implications for Hearing Protection, Speech Intelligibility, and Situation Awareness

    National Research Council Canada - National Science Library

    Price, G. R

    2005-01-01

    The auditory hazard assessment algorithm for the human (AHAAH), developed by the U.S. Army Research Laboratory, is theoretically based and has been demonstrated to rate hazard from intense sounds much more accurately than existing methods...

  8. Family building using embryo adoption: relationships and contact arrangements between provider and recipient families-a mixed-methods study.

    Science.gov (United States)

    Frith, Lucy; Blyth, Eric; Lui, Steve

    2017-05-01

    What contact arrangements are established between providers and recipients of embryos using Snowflakes® Embryo Adoption Program? Contact arrangements varied considerably and were generally positively described, although some challenges were acknowledged. Reproductive technologies create new and diverse family forms, and the ways in which families created by embryo adoption are negotiated in practice have not been extensively investigated. This exploratory, mixed-methods study had two phases: (i) an online survey (open May-September 2013) and (ii) qualitative semi-structured interviews by email (conducted between 2014 and 2015), exploring participants' experiences of contact with their embryo provider or recipient. Phase I included 17 providers (14 women and 3 men) and 28 recipients (27 women and 1 man). Phase II included 8 providers (5 women and 3 men) and 12 recipients (10 women and 2 men). All participants, except one, were located in the US. This study illustrates how embryo adoption in the US, as a form of conditional donation, can operate and how the participants define and negotiate these emerging relationships. All families were open with their children about how they were conceived and early contact between recipients and providers (frequently before birth) was valued. On the whole, participants were happy with the amount and type of contact they had, and where the current contact did not involve the children, it was seen as a way of keeping the channels open for future contact when the children were older. Participants often portrayed the opportunities for contact as being in the best interests of the child. The study participants are a particular group who had chosen to either receive or give their embryos via a conditional embryo adoption agency in the US and had established contact. Therefore, this is not a representative sample of those who provide or receive embryos for family building. This embryo adoption model clearly fulfils a need; some people

  9. New trends in computational collective intelligence

    CERN Document Server

    Kim, Sang-Wook; Trawiński, Bogdan

    2015-01-01

    This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

  10. Views of Chinese Psychologists toward Intelligence

    Science.gov (United States)

    Yan, Gonggu; Saklofske, Donald H.; Oakland, Thomas

    2009-01-01

    The concepts of intelligence and methods to assess it constitute important contributions to psychology and have had a profound impact on school psychology practice. While the perspectives and practices of North American and European psychologists toward the construct and assessment of intelligence generally are well known, the views held by…

  11. Intelligent Augmented Reality Training for Motherboard Assembly

    Science.gov (United States)

    Westerfield, Giles; Mitrovic, Antonija; Billinghurst, Mark

    2015-01-01

    We investigate the combination of Augmented Reality (AR) with Intelligent Tutoring Systems (ITS) to assist with training for manual assembly tasks. Our approach combines AR graphics with adaptive guidance from the ITS to provide a more effective learning experience. We have developed a modular software framework for intelligent AR training…

  12. Taking a multiple intelligences (MI) perspective.

    Science.gov (United States)

    Gardner, Howard

    2017-01-01

    The theory of multiple intelligences (MI) seeks to describe and encompass the range of human cognitive capacities. In challenging the concept of general intelligence, we can apply an MI perspective that may provide a more useful approach to cognitive differences within and across species.

  13. Quest for business intelligence in health care.

    Science.gov (United States)

    Van De Graaff, Joe; Cameron, Austin

    2013-02-01

    In an era of reform, providers are examining more forward-thinking business intelligence strategies, according to a recent study. Enterprise business intelligence tool sets offer a breadth of design and functionality that often are capable of serving the enterprise. One limitation of broader tool sets is that they may lack needed application-specific functionality or prebuilt healthcare content for a specific department.

  14. Measuring Components of Intelligence: Mission Impossible?

    Science.gov (United States)

    Gregoire, Jacques

    2013-01-01

    The two studies conducted by Weiss, Keith, Zhu, and Chen in 2013 on the Wechsler Adult Intelligence Scale (WAIS-IV) and the Wechsler Intelligence Scale for Children (WISC-IV), respectively, provide strong evidence for the validity of a four-factor solution corresponding to the current hierarchical model of both scales. These analyses support the…

  15. The Relationship between Intellectual Intelligence and Emotional Intelligence and some Demographic variables among Students of the Faculty of Nursing and Midwifery, Ilam University of Medical Sciences in 2014

    OpenAIRE

    Hamed Tavan; Sajjad Tavan; Zahra Ahmadi; Fatemeh Zandnia

    2015-01-01

    Background and Objective: There is a relationship between emotional intelligence and spiritual intelligence. Therefore, this study was aimed to investigate the relationship between intellectual intelligence and emotional intelligence and some demographic variables among students of Nursing and Midwifery Faculty, Ilam University of Medical Sciences. Methods: Using a cross-correlation method of study, the standard 24-item questionnaire for spiritual intelligence and the standard 90-item que...

  16. IMIS: An intelligence microscope imaging system

    Science.gov (United States)

    Caputo, Michael; Hunter, Norwood; Taylor, Gerald

    1994-01-01

    Until recently microscope users in space relied on traditional microscopy techniques that required manual operation of the microscope and recording of observations in the form of written notes, drawings, or photographs. This method was time consuming and required the return of film and drawings from space for analysis. No real-time data analysis was possible. Advances in digital and video technologies along with recent developments in article intelligence will allow future space microscopists to have a choice of three additional modes of microscopy: remote coaching, remote control, and automation. Remote coaching requires manual operations of the microscope with instructions given by two-way audio/video transmission during critical phases of the experiment. When using the remote mode of microscopy, the Principal Investigator controls the microscope from the ground. The automated mode employs artificial intelligence to control microscope functions and is the only mode that can be operated in the other three modes as well. The purpose of this presentation is to discuss the advantages and disadvantages of the four modes of of microscopy and how the IMIS, a proposed intelligent microscope imaging system, can be used as a model for developing and testing concepts, operating procedures, and equipment design of specifications required to provide a comprehensive microscopy/imaging capability onboard Space Station Freedom.

  17. An analytical solution of Richards' equation providing the physical basis of SCS curve number method and its proportionality relationship

    Science.gov (United States)

    Hooshyar, Milad; Wang, Dingbao

    2016-08-01

    The empirical proportionality relationship, which indicates that the ratio of cumulative surface runoff and infiltration to their corresponding potentials are equal, is the basis of the extensively used Soil Conservation Service Curve Number (SCS-CN) method. The objective of this paper is to provide the physical basis of the SCS-CN method and its proportionality hypothesis from the infiltration excess runoff generation perspective. To achieve this purpose, an analytical solution of Richards' equation is derived for ponded infiltration in shallow water table environment under the following boundary conditions: (1) the soil is saturated at the land surface; and (2) there is a no-flux boundary which moves downward. The solution is established based on the assumptions of negligible gravitational effect, constant soil water diffusivity, and hydrostatic soil moisture profile between the no-flux boundary and water table. Based on the derived analytical solution, the proportionality hypothesis is a reasonable approximation for rainfall partitioning at the early stage of ponded infiltration in areas with a shallow water table for coarse textured soils.

  18. Evaluating the impact of healthcare provider training to improve tuberculosis management: a systematic review of methods and outcome indicators used.

    Science.gov (United States)

    Wu, Shishi; Roychowdhury, Imara; Khan, Mishal

    2017-03-01

    Developing human resources capacity is vital for tuberculosis (TB) control in low- and middle-income countries. Although investments in TB healthcare provider (HCP) training programmes have increased, it is unclear whether these are robustly evaluated. The objective of this systematic review was to synthesize the methods and outcome indicators used to assess TB HCP training programmes. A systematic scoping review of publications reporting on evaluations of training programmes for TB HCPs - including doctors, nurses, paramedics, and lay health workers - was conducted through a search in three electronic databases, Google Scholar, and five websites of non-profit organizations. Data on the study location, population trained, outcomes assessed, and evaluation approach were extracted. After screening 499 unique publications, 21 were eligible for inclusion in the analysis. The majority of evaluations were conducted in Africa. The most common evaluation methods were a review of patient records (n=8, 38%) and post-training interview with trainees (n=7, 33%). In terms of outcomes, more than half of the studies (n=12, 57%) evaluated knowledge acquisition of trainees, with only six (29%) assessing on-the-job behaviour change. Even though more funds have been invested in TB HCP training, publications from robust evaluations assessing the impact on quality of care and behaviour change are limited. Copyright © 2016. Published by Elsevier Ltd.

  19. Team dynamics, clinical work satisfaction, and patient care coordination between primary care providers: A mixed methods study.

    Science.gov (United States)

    Song, Hummy; Ryan, Molly; Tendulkar, Shalini; Fisher, Josephine; Martin, Julia; Peters, Antoinette S; Frolkis, Joseph P; Rosenthal, Meredith B; Chien, Alyna T; Singer, Sara J

    Team-based care is essential for delivering high-quality, comprehensive, and coordinated care. Despite considerable research about the effects of team-based care on patient outcomes, few studies have examined how team dynamics relate to provider outcomes. The aim of this study was to examine relationships among team dynamics, primary care provider (PCP) clinical work satisfaction, and patient care coordination between PCPs in 18 Harvard-affiliated primary care practices participating in Harvard's Academic Innovations Collaborative. First, we administered a cross-sectional survey to all 548 PCPs (267 attending clinicians, 281 resident physicians) working at participating practices; 65% responded. We assessed the relationship of team dynamics with PCPs' clinical work satisfaction and perception of patient care coordination between PCPs, respectively, and the potential mediating effect of patient care coordination on the relationship between team dynamics and work satisfaction. In addition, we embedded a qualitative evaluation within the quantitative evaluation to achieve a convergent mixed methods design to help us better understand our findings and illuminate relationships among key variables. Better team dynamics were positively associated with clinical work satisfaction and quality of patient care coordination between PCPs. Coordination partially mediated the relationship between team dynamics and satisfaction for attending clinicians, suggesting that higher satisfaction depends, in part, on better teamwork, yielding more coordinated patient care. We found no mediating effects for resident physicians. Qualitative results suggest that sources of satisfaction from positive team dynamics for PCPs may be most relevant to attending clinicians. Improving primary care team dynamics could improve clinical work satisfaction among PCPs and patient care coordination between PCPs. In addition to improving outcomes that directly concern health care providers, efforts to

  20. Computational intelligence in biomedical imaging

    CERN Document Server

    2014-01-01

    This book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in biomedical images with emphasis on biomedical decision making. Biomedical imaging offers useful information on patients’ medical conditions and clues to causes of their symptoms and diseases. Biomedical images, however, provide a large number of images which physicians must interpret. Therefore, computer aids are demanded and become indispensable in physicians’ decision making. This book discusses major technical advancements and research findings in the field of computational intelligence in biomedical imaging, for example, computational intelligence in computer-aided diagnosis for breast cancer, prostate cancer, and brain disease, in lung function analysis, and in radiation therapy. The book examines technologies and studies that have reached the practical level, and those technologies that are becoming available in clinical practices in hospitals rapidly such as computational inte...