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Sample records for intelligence approach combining

  1. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

  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. 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.

  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. A model predictive control approach combined unscented Kalman filter vehicle state estimation in intelligent vehicle trajectory tracking

    Directory of Open Access Journals (Sweden)

    Hongxiao Yu

    2015-05-01

    Full Text Available Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

  6. Approaches to Enhance Sensemaking for Intelligence Analysis

    National Research Council Canada - National Science Library

    McBeth, Michael

    2002-01-01

    ..., and to apply persuasion skills to interact more productively with others. Each approach is explained from a sensemaking perspective and linked to Richard Heuer's Psychology of Intelligence Analysis...

  7. Approaches for Intelligent Traffic System: A Survey

    OpenAIRE

    Pratishtha Gupta; G.N Purohit; Amrita Dadhich

    2012-01-01

    This survey presents various approaches for intelligent traffic systems. The potential research fields in which Intelligent Traffic System emerges as an important application area are highlighted andvarious issues have been identified which need to be handled while developing such a system for an urban area, where an efficient traffic management has become the need of hour.A model is also proposed capable of managing intelligent traffic system using CCTV cameras and WAN. The proposed model wi...

  8. An intelligent approach to nanotechnology

    Science.gov (United States)

    Demming, Anna

    2013-11-01

    Control counts for little without a guiding principle. Whether manipulating atoms with a scanning probe or controlling carrier concentration in thin film deposition, intelligent intervention is required to steer the process from aimless precision towards a finely optimized design. In this issue G M Sacha and P Varona describe how artificial intelligence approaches can help towards modelling and simulating nanosystems, increasing our grasp of the nuances of these systems and how to optimize them for specific applications [1]. More than a labour-saving technique their review also suggests how genetic algorithms and artificial neural networks can supersede existing capabilities to tackle some of the challenges in moving a range of nanotechnologies forward. Research has made giant strides in determining not just what system parameters enhance performance but how. Nanoparticle synthesis is a typical example, where the field has shifted from simple synthesis and observation to unearthing insights as to dominating factors that can be identified and enlisted to control the morphological and chemical properties of synthesized products. One example is the neat study on reaction media viscosity for silver nanocrystal synthesis, where Park, Im and Park in Korea demonstrated a level of size control that had previously proved hard to achieve [2]. Silver nanoparticles have many potential applications including catalysis [3], sensing [4] and surface enhanced Raman scattering [5]. In their study, Park and colleagues obtain size-controlled 30 nm silver nanocrystals in a viscosity controlled medium of 1,5-pentanediol and demonstrate their use as sacrificial cores for the fabrication of a low-refractive filler. Another nanomaterial that has barely seen an ebb in research activity over the past two decades is ZnO, with a legion of reports detailing how to produce ZnO in different nanoscale forms from rods [6], belts [7] and flowers [8] to highly ordered arrays of vertically aligned

  9. 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.  .

  10. Artificial intelligence in drug combination therapy.

    Science.gov (United States)

    Tsigelny, Igor F

    2018-02-09

    Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a physician often meets a patient having a genomic profile including more than five molecular aberrations. Drug combination therapy has been an area of interest for a while, for example the classical work of Loewe devoted to the synergism of drugs was published in 1928-and it is still used in calculations for optimal drug combinations. More recently, over the past several years, there has been an explosion in the available information related to the properties of drugs and the biomedical parameters of patients. For the drugs, hundreds of 2D and 3D molecular descriptors for medicines are now available, while for patients, large data sets related to genetic/proteomic and metabolomics profiles of the patients are now available, as well as the more traditional data relating to the histology, history of treatments, pretreatment state of the organism, etc. Moreover, during disease progression, the genetic profile can change. Thus, the ability to optimize drug combinations for each patient is rapidly moving beyond the comprehension and capabilities of an individual physician. This is the reason, that biomedical informatics methods have been developed and one of the more promising directions in this field is the application of artificial intelligence (AI). In this review, we discuss several AI methods that have been successfully implemented in several instances of combination drug therapy from HIV, hypertension, infectious diseases to cancer. The data clearly show that the combination of rule-based expert systems with machine learning algorithms may be promising direction in this field. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  11. Integrated Artificial Intelligence Approaches for Disease Diagnostics.

    Science.gov (United States)

    Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

    2018-06-01

    Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.

  12. Intelligent process control operator aid -- An artificial intelligence approach

    International Nuclear Information System (INIS)

    Sharma, D.D.; Miller, D.D.; Hajek, B.; Chandrasekaran, B.

    1986-01-01

    This paper describes an approach for designing intelligent process and power plant control operator aids. It is argued that one of the key aspects of an intelligent operator aid is the capability for dynamic procedure synthesis with incomplete definition of initial state, unknown goal states, and the dynamic world situation. The dynamic world state is used to determine the goal, select appropriate plan steps from prespecified procedures to achieve the goal, control the execution of the synthesized plan, and provide for dynamic recovery from failure often using a goal hierarchy. The dynamic synthesis of a plan requires integration of various problems solving capabilities such as plan generation, plan synthesis, plan modification, and failure recovery from a plan. The programming language for implementing the DPS framework provides a convenient tool for developing applications. An application of the DPS approach to a Nuclear Power Plant emergency procedure synthesis is also described. Initial test results indicate that the approach is successful in dynamically synthesizing the procedures. The authors realize that the DPS framework is not a solution for all control tasks. However, many existing process and plant control problems satisfy the requirements discussed in the paper and should be able to benefit from the framework described

  13. 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). .

  14. Creative-Dynamics Approach To Neural Intelligence

    Science.gov (United States)

    Zak, Michail A.

    1992-01-01

    Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

  15. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  16. Representation of architectural artifacts: definition of an approach combining the complexity of the 3d digital instance with the intelligibility of the theoretical model.

    Directory of Open Access Journals (Sweden)

    David Lo Buglio

    2012-12-01

    Full Text Available EnWith the arrival of digital technologies in the field of architectural documentation, many tools and methods for data acquisition have been considerably developed. However, these developments are primarily used for recording colorimetric and dimensional properties of the objects processed. The actors, of the disciplines concerned by 3D digitization of architectural heritage, are facing with a large number of data, leaving the survey far from its cognitive dimension. In this context, it seems necessary to provide innovative solutions in order to increase the informational value of the representations produced by strengthen relations between "multiplicity" of data and "intelligibility" of the theoretical model. With the purpose of answering to the lack of methodology we perceived, this article therefore offers an approach to the creation of representation systems that articulate the digital instance with the geometric/semantic model.ItGrazie all’introduzione delle tecnologie digitali nel campo della documentazione architettonica, molti strumenti e metodi di acquisizione hanno avuto un notevole sviluppo. Tuttavia, questi sviluppi si sono principalmente concentrati sulla registrazione e sulla restituzione delle proprietà geometriche e colorimetriche degli oggetti di studio. Le discipline interessate alla digitalizzazione 3D del patrimonio architettonico hanno pertanto la possibilità di produrre delle grandi quantità di dati attraverso un’evoluzione delle pratiche di documentazione che potrebbero progressivamente far scomparire la dimensione cognitiva del rilievo. In questo contesto, appare necessario fornire soluzioni innovative per aumentare il valore informativo delle rappresentazioni digitali tramite l’identificazione delle relazioni potenziali che è possibile costruire fra le nozioni di "molteplicità" ed "intelligibilità". Per rispondere a questo deficit metodologico, questo articolo presenta le basi di un approccio per la

  17. A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

    Science.gov (United States)

    2017-12-05

    A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

  18. Combined approach for gynecomastia

    Directory of Open Access Journals (Sweden)

    El-Sabbagh, Ahmed Hassan

    2016-02-01

    Full Text Available Background: Gynecomastia is a deformity of male chest. Treatment of gynecomastia varied from direct surgical excision to other techniques (mainly liposuction to a combination of both. Skin excision is done according to the grade. In this study, experience of using liposuction adjuvant to surgical excision was described. Patients and methods: Between September 2012 and April 2015, a total of 14 patients were treated with liposuction and surgical excision through a periareolar incision. Preoperative evaluation was done in all cases to exclude any underlying cause of gynecomastia. Results: All fourteen patients were treated bilaterally (28 breast tissues. Their ages ranged between 13 and 33 years. Two patients were classified as grade I, and four as grade IIa, IIb or III, respectively. The first showed seroma. Partial superficial epidermolysis of areola occurred in 2 cases. Superficial infection of incision occurred in one case and was treated conservatively. Conclusion: All grades of gynecomastia were managed by the same approach. Skin excision was added to a patient that had severe skin excess with limited activity and bad skin complexion. No cases required another setting or asked for 2 opinion.

  19. Combined approach for gynecomastia.

    Science.gov (United States)

    El-Sabbagh, Ahmed Hassan

    2016-01-01

    Gynecomastia is a deformity of male chest. Treatment of gynecomastia varied from direct surgical excision to other techniques (mainly liposuction) to a combination of both. Skin excision is done according to the grade. In this study, experience of using liposuction adjuvant to surgical excision was described. Between September 2012 and April 2015, a total of 14 patients were treated with liposuction and surgical excision through a periareolar incision. Preoperative evaluation was done in all cases to exclude any underlying cause of gynecomastia. All fourteen patients were treated bilaterally (28 breast tissues). Their ages ranged between 13 and 33 years. Two patients were classified as grade I, and four as grade IIa, IIb or III, respectively. The first 3 patients showed seroma. Partial superficial epidermolysis of areola occurred in 2 cases. Superficial infection of incision occurred in one case and was treated conservatively. All grades of gynecomastia were managed by the same approach. Skin excision was added to a patient that had severe skin excess with limited activity and bad skin complexion. No cases required another setting or asked for 2(nd) opinion.

  20. Artificial intelligence approach to interwell log correlation

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Jong-Se [Korea Maritime University, Pusan(Korea); Kang, Joo Myung [Seoul National University, Seoul(Korea); Kim, Jung Whan [Korea National Oil Corp., Anyang(Korea)

    2000-04-30

    This paper describes a new approach to automated interwell log correlation using artificial intelligence and principal component analysis. The approach to correlate wire line logging data is on the basis of a large set of subjective rules that are intended to represent human logical processes. The data processed are mainly the qualitative information such as the characteristics of the shapes extracted along log traces. The apparent geologic zones are identified by pattern recognition for the specific characteristics of log trace collected as a set of objects by object oriented programming. The correlation of zones between wells is made by rule-based inference program. The reliable correlation can be established from the first principal component logs derived from both the important information around well bore and the largest common part of variances of all available well log data. Correlation with field log data shows that this approach can make interwell log correlation more reliable and accurate. (author). 6 refs., 7 figs.

  1. Issues on combining human and non-human intelligence

    Science.gov (United States)

    Statler, Irving C.; Connors, Mary M.

    1991-01-01

    The purpose here is to call attention to some of the issues confronting the designer of a system that combines human and non-human intelligence. We do not know how to design a non-human intelligence in such a way that it will fit naturally into a human organization. The author's concern is that, without adequate understanding and consideration of the behavioral and psychological limitations and requirements of the human member(s) of the system, the introduction of artificial intelligence (AI) subsystems can exacerbate operational problems. We have seen that, when these technologies are not properly applied, an overall degradation of performance at the system level can occur. Only by understanding how human and automated systems work together can we be sure that the problems introduced by automation are not more serious than the problems solved.

  2. Business Intelligence Approach In A Business Performance Context

    OpenAIRE

    Muntean, Mihaela; Cabau, Liviu Gabriel

    2011-01-01

    Subordinated to performance management, Business Intelligence approaches help firms to optimize business performance. Key performance indicators will be added to the multidimensional model grounding the performance perspectives. With respect to the Business Intelligence value chain, a theoretical approach was introduced and a practice example, based on Microsoft SQL Server specific services, for the customer perspective was implemented.

  3. Social collective intelligence combining the powers of humans and machines to build a smarter society

    CERN Document Server

    Miorandi, Daniele; Rovatsos, Michael

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT.Social Collective Intelligence opens a number of challenges for researchers in both computer science and social sciences; at the same time it provides an innovative approach to solve challenges in diverse application domains, ranging from health to education

  4. Intelligent Machine Learning Approaches for Aerospace Applications

    Science.gov (United States)

    Sathyan, Anoop

    Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire

  5. An Intelligent Systems Approach to Reservoir Characterization

    Energy Technology Data Exchange (ETDEWEB)

    Shahab D. Mohaghegh; Jaime Toro; Thomas H. Wilson; Emre Artun; Alejandro Sanchez; Sandeep Pyakurel

    2005-08-01

    Today, the major challenge in reservoir characterization is integrating data coming from different sources in varying scales, in order to obtain an accurate and high-resolution reservoir model. The role of seismic data in this integration is often limited to providing a structural model for the reservoir. Its relatively low resolution usually limits its further use. However, its areal coverage and availability suggest that it has the potential of providing valuable data for more detailed reservoir characterization studies through the process of seismic inversion. In this paper, a novel intelligent seismic inversion methodology is presented to achieve a desirable correlation between relatively low-frequency seismic signals, and the much higher frequency wireline-log data. Vertical seismic profile (VSP) is used as an intermediate step between the well logs and the surface seismic. A synthetic seismic model is developed by using real data and seismic interpretation. In the example presented here, the model represents the Atoka and Morrow formations, and the overlying Pennsylvanian sequence of the Buffalo Valley Field in New Mexico. Generalized regression neural network (GRNN) is used to build two independent correlation models between; (1) Surface seismic and VSP, (2) VSP and well logs. After generating virtual VSP's from the surface seismic, well logs are predicted by using the correlation between VSP and well logs. The values of the density log, which is a surrogate for reservoir porosity, are predicted for each seismic trace through the seismic line with a classification approach having a correlation coefficient of 0.81. The same methodology is then applied to real data taken from the Buffalo Valley Field, to predict inter-well gamma ray and neutron porosity logs through the seismic line of interest. The same procedure can be applied to a complete 3D seismic block to obtain 3D distributions of reservoir properties with less uncertainty than the geostatistical

  6. New approaches in intelligent control techniques, methodologies and applications

    CERN Document Server

    Kountchev, Roumen

    2016-01-01

    This volume introduces new approaches in intelligent control area from both the viewpoints of theory and application. It consists of eleven contributions by prominent authors from all over the world and an introductory chapter. This volume is strongly connected to another volume entitled "New Approaches in Intelligent Image Analysis" (Eds. Roumen Kountchev and Kazumi Nakamatsu). The chapters of this volume are self-contained and include summary, conclusion and future works. Some of the chapters introduce specific case studies of various intelligent control systems and others focus on intelligent theory based control techniques with applications. A remarkable specificity of this volume is that three chapters are dealing with intelligent control based on paraconsistent logics.

  7. Artificial intelligence approaches to astronomical observation scheduling

    Science.gov (United States)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

    Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

  8. Herd Clustering: A synergistic data clustering approach using collective intelligence

    KAUST Repository

    Wong, Kachun; Peng, Chengbin; Li, Yue; Chan, Takming

    2014-01-01

    , this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances

  9. Knowledge representation an approach to artificial intelligence

    CERN Document Server

    Bench-Capon, TJM

    1990-01-01

    Although many texts exist offering an introduction to artificial intelligence (AI), this book is unique in that it places an emphasis on knowledge representation (KR) concepts. It includes small-scale implementations in PROLOG to illustrate the major KR paradigms and their developments.****back cover copy:**Knowledge representation is at the heart of the artificial intelligence enterprise: anyone writing a program which seeks to work by encoding and manipulating knowledge needs to pay attention to the scheme whereby he will represent the knowledge, and to be aware of the consequences of the ch

  10. Intelligence for embedded systems a methodological approach

    CERN Document Server

    Alippi, Cesare

    2014-01-01

    Addressing current issues of which any engineer or computer scientist should be aware, this monograph is a response to the need to adopt a new computational paradigm as the methodological basis for designing pervasive embedded systems with sensor capabilities. The requirements of this paradigm are to control complexity, to limit cost and energy consumption, and to provide adaptation and cognition abilities allowing the embedded system to interact proactively with the real world. The quest for such intelligence requires the formalization of a new generation of intelligent systems able to exploit advances in digital architectures and in sensing technologies. The book sheds light on the theory behind intelligence for embedded systems with specific focus on: ·        robustness (the robustness of a computational flow and its evaluation); ·        intelligence (how to mimic the adaptation and cognition abilities of the human brain), ·        the capacity to learn in non-stationary and evolv...

  11. Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    OpenAIRE

    Stephen Fox

    2017-01-01

    Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI) are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, t...

  12. Artificial intelligence approach to legal reasoning

    International Nuclear Information System (INIS)

    Gardner, A.V.D.L.

    1984-01-01

    For artificial intelligence, understanding the forms of human reasoning is a central goal. Legal reasoning is a form that makes a new set of demands on artificial intelligence methods. Most importantly, a computer program that reasons about legal problems must be able to distinguish between questions it is competent to answer and questions that human lawyers could seriously argue either way. In addition, a program for analyzing legal problems should be able to use both general legal rules and decisions in past cases; and it should be able to work with technical concepts that are only partly defined and subject to shifts of meaning. Each of these requirements has wider applications in artificial intelligence, beyond the legal domain. This dissertation presents a computational framework for legal reasoning, within which such requirements can be accommodated. The development of the framework draws significantly on the philosophy of law, in which the elucidation of legal reasoning is an important topic. A key element of the framework is the legal distinction between hard cases and clear cases. In legal writing, this distinction has been taken for granted more often than it has been explored. Here, some initial heuristics are proposed by which a program might make the distinction

  13. Toward Intelligent Hemodynamic Monitoring: A Functional Approach

    Directory of Open Access Journals (Sweden)

    Pierre Squara

    2012-01-01

    Full Text Available Technology is now available to allow a complete haemodynamic analysis; however this is only used in a small proportion of patients and seems to occur when the medical staff have the time and inclination. As a result of this, significant delays occur between an event, its diagnosis and therefore, any treatment required. We can speculate that we should be able to collect enough real time information to make a complete, real time, haemodynamic diagnosis in all critically ill patients. This article advocates for “intelligent haemodynamic monitoring”. Following the steps of a functional analysis, we answered six basic questions. (1 What is the actual best theoretical model for describing haemodynamic disorders? (2 What are the needed and necessary input/output data for describing this model? (3 What are the specific quality criteria and tolerances for collecting each input variable? (4 Based on these criteria, what are the validated available technologies for monitoring each input variable, continuously, real time, and if possible non-invasively? (5 How can we integrate all the needed reliably monitored input variables into the same system for continuously describing the global haemodynamic model? (6 Is it possible to implement this global model into intelligent programs that are able to differentiate clinically relevant changes as opposed to artificial changes and to display intelligent messages and/or diagnoses?

  14. 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

  15. New approaches in intelligent image analysis techniques, methodologies and applications

    CERN Document Server

    Nakamatsu, Kazumi

    2016-01-01

    This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

  16. Approaches to the study of intelligence

    Science.gov (United States)

    Norman, Donald A.

    1991-01-01

    A survey and an evaluation are conducted for the Rosenbloom et al. (1991) 'SOAR' model of intelligence, both as found in humans and in prospective AI systems, which views it as a representational system for goal-oriented symbolic activity based on a physical symbol system. Attention is given to SOAR's implications for semantic and episodic memory, symbol processing, and search within a uniform problem space; also noted are the relationships of SOAR to competing AI schemes, and its potential usefulness as a theoretical tool for cognitive psychology.

  17. Optimizing radiologic workup: An artificial intelligence approach

    International Nuclear Information System (INIS)

    Swett, H.A.; Rothschild, M.; Weltin, G.G.; Fisher, P.R.; Miller, P.L.

    1987-01-01

    The increasing complexity of diagnostic imaging is presenting an ever-expanding variety of radiologic test options to referring clinicians, making it more difficult for them to plan efficient workup. Diagnosis-oriented reimbursement systems are providing new incentives for hospitals and radiologists to use imaging modalities judiciously. This paper describes DxCON, a developmental artificial intelligence-based computer system, which gives advice to physicians about the optimum sequencing of radiologic tests. DxCON analyzes a physician's proposed workup plan and discusses its strengths and weaknesses. The domain chosen for this research is the imaging workup of obstructive jaundice

  18. Convergence Analysis of a Class of Computational Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Junfeng Chen

    2013-01-01

    Full Text Available Computational intelligence approaches is a relatively new interdisciplinary field of research with many promising application areas. Although the computational intelligence approaches have gained huge popularity, it is difficult to analyze the convergence. In this paper, a computational model is built up for a class of computational intelligence approaches represented by the canonical forms of generic algorithms, ant colony optimization, and particle swarm optimization in order to describe the common features of these algorithms. And then, two quantification indices, that is, the variation rate and the progress rate, are defined, respectively, to indicate the variety and the optimality of the solution sets generated in the search process of the model. Moreover, we give four types of probabilistic convergence for the solution set updating sequences, and their relations are discussed. Finally, the sufficient conditions are derived for the almost sure weak convergence and the almost sure strong convergence of the model by introducing the martingale theory into the Markov chain analysis.

  19. An intelligent software approach to ultrasonic flaw classification in weldments

    International Nuclear Information System (INIS)

    Song, Sung Jin; Kim, Hak Joon; Lee, Hyun

    1997-01-01

    Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress on this methodology, it has not been widely used in practical ultrasonic inspection of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments using various tools in artificial intelligence such as neural networks. This software shows excellent performances in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks.

  20. Beyond AI: Multi-Intelligence (MI Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

    Directory of Open Access Journals (Sweden)

    Stephen Fox

    2017-06-01

    Full Text Available Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, the extensive post-anthropocentric research into intelligence is not given sufficient consideration. Third, AI is discussed often in reductionist mechanistic terms. Rather than in organicist emergentist terms as a contributor to multi-intelligence (MI hybrid beings and/or systems. Thus, current framing of AI can be a self-validating reduction within which AI development is focused upon AI becoming the single-variable mechanism causing future effects. In this paper, AI is reframed as a contributor to MI.

  1. An artificial intelligence approach towards disturbance analysis

    International Nuclear Information System (INIS)

    Fiedler, U.; Lindner, A.; Baldeweg, F.; Klebau, J.

    1986-01-01

    Scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in well-known situations. But in cases of emergencies, the operator needs more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence (AI) methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application to nuclear power plants. Problems related to man-machine communication will be gone into more detail, because their solution will influence end-user acceptance considerably. (author)

  2. The fundamentals of computational intelligence system approach

    CERN Document Server

    Zgurovsky, Mikhail Z

    2017-01-01

    This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy ris...

  3. 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.

  4. An Artificial Intelligence Approach to Transient Stability Assessment

    OpenAIRE

    Akella, Vijay Ahaskar; Khincha, HP; Kumar, Sreerama R

    1991-01-01

    An artificial intelligence approach to online transient stability assessment is briefly discussed, and some crucial requirements for this algorithm are identified. Solutions to these are proposed. Some new attributes are suggested so as to reflect machine dynamics and changes in the network. Also a new representative learning set algorithm has been developed.

  5. Multiple Intelligences within the Cross-Curricular Approach

    Directory of Open Access Journals (Sweden)

    Anthoula Vaiou

    2010-02-01

    Full Text Available The present study was realized in a Greek 6th grade State Primary School class and was based on Howard Gardner’s theory of multiple intelligences, which was first introduced in 1983. More particularly, it was explored to what extent the young learners possess multiple intelligences through the use of a specially-designed questionnaire and a series of interviews. The findings of the above have served as a tool to the construction of a project work based on students’ learning preferences within a cross-curricular framework, easily applicable to the Greek State School curriculum. All learners were activated to participate within a school environment that traditionally promotes linguistic and mathematical skills matching dominant multiple intelligences or a combination of some of them to thematic units already taught by Greek teachers. The suggested project was assessed through observation and student portfolio, showing that the young learners’ multiple intelligences were exploited to a great extent, promoting the learning process satisfactorily. The results of this study can provide a contribution to the literature of multiple intelligences in the Greek reality and suggest a need for further consideration and exploration in the field. Finally, the researcher of this study hopes the present work could function as a springboard for more elaborated studies in the future.

  6. Energy Demand Forecasting: Combining Cointegration Analysis and Artificial Intelligence Algorithm

    Directory of Open Access Journals (Sweden)

    Junbing Huang

    2018-01-01

    Full Text Available Energy is vital for the sustainable development of China. Accurate forecasts of annual energy demand are essential to schedule energy supply and provide valuable suggestions for developing related industries. In the existing literature on energy use prediction, the artificial intelligence-based (AI-based model has received considerable attention. However, few econometric and statistical evidences exist that can prove the reliability of the current AI-based model, an area that still needs to be addressed. In this study, a new energy demand forecasting framework is presented at first. On the basis of historical annual data of electricity usage over the period of 1985–2015, the coefficients of linear and quadratic forms of the AI-based model are optimized by combining an adaptive genetic algorithm and a cointegration analysis shown as an example. Prediction results of the proposed model indicate that the annual growth rate of electricity demand in China will slow down. However, China will continue to demand about 13 trillion kilowatt hours in 2030 because of population growth, economic growth, and urbanization. In addition, the model has greater accuracy and reliability compared with other single optimization methods.

  7. APPROACH ON INTELLIGENT OPTIMIZATION DESIGN BASED ON COMPOUND KNOWLEDGE

    Institute of Scientific and Technical Information of China (English)

    Yao Jianchu; Zhou Ji; Yu Jun

    2003-01-01

    A concept of an intelligent optimal design approach is proposed, which is organized by a kind of compound knowledge model. The compound knowledge consists of modularized quantitative knowledge, inclusive experience knowledge and case-based sample knowledge. By using this compound knowledge model, the abundant quantity information of mathematical programming and the symbolic knowledge of artificial intelligence can be united together in this model. The intelligent optimal design model based on such a compound knowledge and the automatically generated decomposition principles based on it are also presented. Practically, it is applied to the production planning, process schedule and optimization of production process of a refining & chemical work and a great profit is achieved. Specially, the methods and principles are adaptable not only to continuous process industry, but also to discrete manufacturing one.

  8. An artificial intelligence approach to well log correlation

    International Nuclear Information System (INIS)

    Startzman, R.A.; Kuo, T.B.

    1986-01-01

    This paper shows how an expert computer system was developed to correlate two well logs in at least moderately difficult situations. A four step process was devised to process log trace information and apply a set of rules to identify zonal correlations. Some of the advantages and problems with the artificial intelligence approach are shown using field logs. The approach is useful and, if properly and systematically applied, it can result in good correlations

  9. Intelligent cognitive radio jamming - a game-theoretical approach

    Science.gov (United States)

    Dabcevic, Kresimir; Betancourt, Alejandro; Marcenaro, Lucio; Regazzoni, Carlo S.

    2014-12-01

    Cognitive radio (CR) promises to be a solution for the spectrum underutilization problems. However, security issues pertaining to cognitive radio technology are still an understudied topic. One of the prevailing such issues are intelligent radio frequency (RF) jamming attacks, where adversaries are able to exploit on-the-fly reconfigurability potentials and learning mechanisms of cognitive radios in order to devise and deploy advanced jamming tactics. In this paper, we use a game-theoretical approach to analyze jamming/anti-jamming behavior between cognitive radio systems. A non-zero-sum game with incomplete information on an opponent's strategy and payoff is modelled as an extension of Markov decision process (MDP). Learning algorithms based on adaptive payoff play and fictitious play are considered. A combination of frequency hopping and power alteration is deployed as an anti-jamming scheme. A real-life software-defined radio (SDR) platform is used in order to perform measurements useful for quantifying the jamming impacts, as well as to infer relevant hardware-related properties. Results of these measurements are then used as parameters for the modelled jamming/anti-jamming game and are compared to the Nash equilibrium of the game. Simulation results indicate, among other, the benefit provided to the jammer when it is employed with the spectrum sensing algorithm in proactive frequency hopping and power alteration schemes.

  10. Forecasting daily lake levels using artificial intelligence approaches

    Science.gov (United States)

    Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

    2012-04-01

    Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.

  11. An Intelligent Alternative Approach to the efficient Network Management

    Directory of Open Access Journals (Sweden)

    MARTÍN, A.

    2012-12-01

    Full Text Available Due to the increasing complexity and heterogeneity of networks and services, many efforts have been made to develop intelligent techniques for management. Network intelligent management is a key technology for operating large heterogeneous data transmission networks. This paper presents a proposal for an architecture that integrates management object specifications and the knowledge of expert systems. We present a new approach named Integrated Expert Management, for learning objects based on expert management rules and describe the design and implementation of an integrated intelligent management platform based on OSI and Internet management models. The main contributions of our approach is the integration of both expert system and managed models, so we can make use of them to construct more flexible intelligent management network. The prototype SONAP (Software for Network Assistant and Performance is accuracy-aware since it can control and manage a network. We have tested our system on real data to the fault diagnostic in a telecommunication system of a power utility. The results validate the model and show a significant improvement with respect to the number of rules and the error rate in others systems.

  12. Intelligent Transportation and Evacuation Planning A Modeling-Based Approach

    CERN Document Server

    Naser, Arab

    2012-01-01

    Intelligent Transportation and Evacuation Planning: A Modeling-Based Approach provides a new paradigm for evacuation planning strategies and techniques. Recently, evacuation planning and modeling have increasingly attracted interest among researchers as well as government officials. This interest stems from the recent catastrophic hurricanes and weather-related events that occurred in the southeastern United States (Hurricane Katrina and Rita). The evacuation methods that were in place before and during the hurricanes did not work well and resulted in thousands of deaths. This book offers insights into the methods and techniques that allow for implementing mathematical-based, simulation-based, and integrated optimization and simulation-based engineering approaches for evacuation planning. This book also: Comprehensively discusses the application of mathematical models for evacuation and intelligent transportation modeling Covers advanced methodologies in evacuation modeling and planning Discusses principles a...

  13. Automation of seismic network signal interpolation: an artificial intelligence approach

    International Nuclear Information System (INIS)

    Chiaruttini, C.; Roberto, V.

    1988-01-01

    After discussing the current status of the automation in signal interpretation from seismic networks, a new approach, based on artificial-intelligence tecniques, is proposed. The knowledge of the human expert analyst is examined, with emphasis on its objects, strategies and reasoning techniques. It is argued that knowledge-based systems (or expert systems) provide the most appropriate tools for designing an automatic system, modelled on the expert behaviour

  14. Assessing risk from intelligent attacks: A perspective on approaches

    International Nuclear Information System (INIS)

    Guikema, Seth D.; Aven, Terje

    2010-01-01

    Assessing the uncertainties in and severity of the consequences of intelligent attacks are fundamentally different from risk assessment for accidental events and other phenomena with inherently random failures. Intelligent attacks against a system involve adaptation on the part of the adversary. The probabilities of the initiating events depend on the risk management actions taken, and they may be more difficult to assess due to high degrees of epistemic uncertainty about the motivations and future actions of adversaries. Several fundamentally different frameworks have been proposed for assessing risk from intelligent attacks. These include basing risk assessment and management on game theoretic modelling of attacker actions, using a probabilistic risk analysis (PRA) approach based on eliciting probabilities of different initiating events from appropriate experts, assessing uncertainties beyond probabilities and expected values, and ignoring the probabilities of the attacks and choosing to protect highest valued targets. In this paper we discuss and compare the fundamental assumptions that underlie each of these approaches. We then suggest a new framework that makes the fundamental assumptions underlying the approaches clear to decision makers and presents them with a suite of results from conditional risk analysis methods. Each of the conditional methods presents the risk from a specified set of fundamental assumptions, allowing the decision maker to see the impacts of these assumptions on the risk management strategies considered and to weight the different conditional results with their assessments of the relative likelihood of the different sets of assumptions.

  15. Energy Demand Forecasting: Combining Cointegration Analysis and Artificial Intelligence Algorithm

    OpenAIRE

    Huang, Junbing; Tang, Yuee; Chen, Shuxing

    2018-01-01

    Energy is vital for the sustainable development of China. Accurate forecasts of annual energy demand are essential to schedule energy supply and provide valuable suggestions for developing related industries. In the existing literature on energy use prediction, the artificial intelligence-based (AI-based) model has received considerable attention. However, few econometric and statistical evidences exist that can prove the reliability of the current AI-based model, an area that still needs to ...

  16. Reliability Prediction Approaches For Domestic Intelligent Electric Energy Meter Based on IEC62380

    Science.gov (United States)

    Li, Ning; Tong, Guanghua; Yang, Jincheng; Sun, Guodong; Han, Dongjun; Wang, Guixian

    2018-01-01

    The reliability of intelligent electric energy meter is a crucial issue considering its large calve application and safety of national intelligent grid. This paper developed a procedure of reliability prediction for domestic intelligent electric energy meter according to IEC62380, especially to identify the determination of model parameters combining domestic working conditions. A case study was provided to show the effectiveness and validation.

  17. A novel approach to painting powered by Ambient Intelligence

    Directory of Open Access Journals (Sweden)

    N. Partarakis

    2016-04-01

    Full Text Available Today, many forms of art are influenced by the emergence of interactive technologies, including the mixing of physical media with digital technology for forming new hybrid works of art and the usage of mobile phones to create art projected on public spaces. Many artists and painters use digital technology to augment their work creatively and technically. Many believe that the time of transition from traditional analogue art to postmodern digital art that is, to an art grounded in codes rather than images has arrived*. The research work described in this paper contributes towards supporting, through the use of Ambient Intelligence technologies, traditional painters’ creativity, as well as methods and techniques of art masters. The paper presents the design, implementation and evaluation of an intelligent environment and its software infrastructure, to form a digitally augmented Art Workshop. Its practical deployment was conducted in an Ambient Intelligence (AmI simulation space and four feasibility studies were conducted. In each of these studies an oil painting was created following an alternative, yet accredited by artists, approach. The workshop was also evaluated with the involvement of real users and artists in the context of a user based usability study.

  18. Efficient drilling problem detection. Early fault detection by the combination of physical models and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Nyboe, Roar

    2009-09-15

    The drilling of an oil or gas well is an expensive undertaking. Hence, it is not surprising that mistakes and accidents during drilling incur a high cost. Accidents could result in the loss of expensive equipment and subsequent delays setting back the operation for days or weeks and thus running up large bills on rig-time and personnel hours. Some types of accidents also pose a risk to the personnel or the environment. In this dissertation we study alarm systems which could give the driller an early warning of upcoming problems, and thus provide time to avoid these accidents. We explore alarm systems which combine advanced physical models of the well and drilling process with artificial intelligence and time series analysis. Finally, we determine the advantages as well as the challenges of this approach. It is our hope that this dissertation is accessible to both practitioners in machine learning and control engineering, as well as to petroleum engineers with a passing familiarity with machine learning. Hence this dissertation starts with a quick introduction to drilling problems and some terms from time series analysis and machine learning. We then briefly describe the theory of observer-based fault detection and isolation. Theories of supervisory control systems are also introduced, as these concern both the choice of algorithms and how AI-based alarm systems integrate with the rest of the operation. From chapter 6 and onward, the challenges to fault detection in drilling are discussed. We focus on clarifying what restrictions the available training data put on our choice of machine learning methods. In chapter 8 and 9, we propose ways to combine machine learning and observer-based fault detection. Experimental results are presented in chapter 10, before we end with concluding remarks in chapter 11. Our main conclusion, reflected in our experimental results, is that physical models and artificial intelligence can be combined to produce hybrid alarm systems that

  19. 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.

  20. A novel approach for intelligent distribution of data warehouses

    Directory of Open Access Journals (Sweden)

    Abhay Kumar Agarwal

    2016-07-01

    Full Text Available With the continuous growth in the amount of data, data storage systems have come a long way from flat files systems to RDBMS, Data Warehousing (DW and Distributed Data Warehousing systems. This paper proposes a new distributed data warehouse model. The model is built on a novel approach, for the intelligent distribution of data warehouse. Overall the model is named as Intelligent and Distributed Data Warehouse (IDDW. The proposed model has N-levels and is based on top-down hierarchical design approach of building distributed data warehouse. The building process of IDDW starts with the identification of various locations where DW may be built. Initially, a single location is considered at top-most level of IDDW where DW is built. Thereafter, DW at any other location of any level may be built. A method, to transfer concerned data from any upper level DW to concerned lower level DW, is also presented in the paper. The paper also presents IDDW modeling, its architecture based on modeling, the internal organization of IDDW via which all the operations within IDDW are performed.

  1. Using Intelligent System Approaches for Simulation of Electricity Markets

    Science.gov (United States)

    Hamagami, Tomoki

    Significances and approaches of applying intelligent systems to artificial electricity market is discussed. In recent years, with the moving into restructuring of electric system in Japan, the deregulation for the electric market is progressing. The most major change of the market is a founding of JEPX (Japan Electric Power eXchange.) which is expected to help lower power bills through effective use of surplus electricity. The electricity market designates exchange of electric power between electric power suppliers (supplier agents) themselves. In the market, the goal of each supplier agents is to maximize its revenue for the entire trading period, and shows complex behavior, which can model by a multiagent platform. Using the multiagent simulations which have been studied as “artificial market" helps to predict the spot prices, to plan investments, and to discuss the rules of market. Moreover, intelligent system approaches provide for constructing more reasonable policies of each agents. This article, first, makes a brief summary of the electricity market in Japan and the studies of artificial markets. Then, a survey of tipical studies of artificial electricity market is listed. Through these topics, the future vision is presented for the studies.

  2. [An object-oriented intelligent engineering design approach for lake pollution control].

    Science.gov (United States)

    Zou, Rui; Zhou, Jing; Liu, Yong; Zhu, Xiang; Zhao, Lei; Yang, Ping-Jian; Guo, Huai-Cheng

    2013-03-01

    Regarding the shortage and deficiency of traditional lake pollution control engineering techniques, a new lake pollution control engineering approach was proposed in this study, based on object-oriented intelligent design (OOID) from the perspective of intelligence. It can provide a new methodology and framework for effectively controlling lake pollution and improving water quality. The differences between the traditional engineering techniques and the OOID approach were compared. The key points for OOID were described as object perspective, cause and effect foundation, set points into surface, and temporal and spatial optimization. The blue algae control in lake was taken as an example in this study. The effect of algae control and water quality improvement were analyzed in details from the perspective of object-oriented intelligent design based on two engineering techniques (vertical hydrodynamic mixer and pumping algaecide recharge). The modeling results showed that the traditional engineering design paradigm cannot provide scientific and effective guidance for engineering design and decision-making regarding lake pollution. Intelligent design approach is based on the object perspective and quantitative causal analysis in this case. This approach identified that the efficiency of mixers was much higher than pumps in achieving the goal of low to moderate water quality improvement. However, when the objective of water quality exceeded a certain value (such as the control objective of peak Chla concentration exceeded 100 microg x L(-1) in this experimental water), the mixer cannot achieve this goal. The pump technique can achieve the goal but with higher cost. The efficiency of combining the two techniques was higher than using one of the two techniques alone. Moreover, the quantitative scale control of the two engineering techniques has a significant impact on the actual project benefits and costs.

  3. Advanced multiresponse process optimisation an intelligent and integrated approach

    CERN Document Server

    Šibalija, Tatjana V

    2016-01-01

    This book presents an intelligent, integrated, problem-independent method for multiresponse process optimization. In contrast to traditional approaches, the idea of this method is to provide a unique model for the optimization of various processes, without imposition of assumptions relating to the type of process, the type and number of process parameters and responses, or interdependences among them. The presented method for experimental design of processes with multiple correlated responses is composed of three modules: an expert system that selects the experimental plan based on the orthogonal arrays; the factor effects approach, which performs processing of experimental data based on Taguchi’s quality loss function and multivariate statistical methods; and process modeling and optimization based on artificial neural networks and metaheuristic optimization algorithms. The implementation is demonstrated using four case studies relating to high-tech industries and advanced, non-conventional processes.

  4. An Intelligent Approach to Observability of Distribution Networks

    DEFF Research Database (Denmark)

    Pokhrel, Basanta Raj; Nainar, Karthikeyan; Bak-Jensen, Birgitte

    2018-01-01

    This paper presents a novel intelligent observability approach for active distribution systems. Observability assessment of the measured power system network, which is a preliminary task in state estimation, is handled via an algebraic method that uses the triangular factors of singular, symmetric...... gain matrix accompanied by a minimum meter placement technique. In available literature, large numbers of pseudo measurements are used to cover the scarcity of sufficient real measurements in distribution systems; the values of these virtual meters are calculated value based on the available real...... measurements, network topology, and network parameters. However, since there are large margin of errors exist in the calculation phase, estimated states may be significantly differed from the actual values though network is classified as observable. Hence, an approach based on numerical observability analysis...

  5. Intelligent approaches for the synthesis of petrophysical logs

    International Nuclear Information System (INIS)

    Rezaee, M Reza; Kadkhodaie-Ilkhchi, Ali; Alizadeh, Pooya Mohammad

    2008-01-01

    Log data are of prime importance in acquiring petrophysical data from hydrocarbon reservoirs. Reliable log analysis in a hydrocarbon reservoir requires a complete set of logs. For many reasons, such as incomplete logging in old wells, destruction of logs due to inappropriate data storage and measurement errors due to problems with logging apparatus or hole conditions, log suites are either incomplete or unreliable. In this study, fuzzy logic and artificial neural networks were used as intelligent tools to synthesize petrophysical logs including neutron, density, sonic and deep resistivity. The petrophysical data from two wells were used for constructing intelligent models in the Fahlian limestone reservoir, Southern Iran. A third well from the field was used to evaluate the reliability of the models. The results showed that fuzzy logic and artificial neural networks were successful in synthesizing wireline logs. The combination of the results obtained from fuzzy logic and neural networks in a simple averaging committee machine (CM) showed a significant improvement in the accuracy of the estimations. This committee machine performed better than fuzzy logic or the neural network model in the problem of estimating petrophysical properties from well logs

  6. Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Jui-Yu Wu

    2013-01-01

    Full Text Available Stochastic global optimization (SGO algorithms such as the particle swarm optimization (PSO approach have become popular for solving unconstrained global optimization (UGO problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO method and an artificial immune algorithm-based PSO (AIA-PSO method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

  7. Intelligence and the brain: a model-based approach

    NARCIS (Netherlands)

    Kievit, R.A.; van Rooijen, H.; Wicherts, J.M.; Waldorp, L.J.; Kan, K.-J.; Scholte, H.S.; Borsboom, D.

    2012-01-01

    Various biological correlates of general intelligence (g) have been reported. Despite this, however, the relationship between neurological measurements and g is not fully clear. We use structural equation modeling to model the relationship between behavioral Wechsler Adult Intelligence Scale (WAIS)

  8. Herd Clustering: A synergistic data clustering approach using collective intelligence

    KAUST Repository

    Wong, Kachun

    2014-10-01

    Traditional data mining methods emphasize on analytical abilities to decipher data, assuming that data are static during a mining process. We challenge this assumption, arguing that we can improve the analysis by vitalizing data. In this paper, this principle is used to develop a new clustering algorithm. Inspired by herd behavior, the clustering method is a synergistic approach using collective intelligence called Herd Clustering (HC). The novel part is laid in its first stage where data instances are represented by moving particles. Particles attract each other locally and form clusters by themselves as shown in the case studies reported. To demonstrate its effectiveness, the performance of HC is compared to other state-of-the art clustering methods on more than thirty datasets using four performance metrics. An application for DNA motif discovery is also conducted. The results support the effectiveness of HC and thus the underlying philosophy. © 2014 Elsevier B.V.

  9. ROBOT LITERACY AN APPROACH FOR SHARING SOCIETY WITH INTELLIGENT ROBOTS

    Directory of Open Access Journals (Sweden)

    Hidetsugu Suto

    2013-12-01

    Full Text Available A novel concept of media education called “robot literacy” is proposed. Here, robot literacy refers to the means of forming an appropriate relationship with intelligent robots. It can be considered a kind of media literacy. People who were born after the Internet age can be considered “digital natives” who have new morals and values and behave differently than previous generations in Internet societies. This can cause various problems among different generations. Thus, the necessity of media literacy education is increasing. Internet technologies, as well as robotics technologies are growing rapidly, and people who are born after the “home robot age,” whom the author calls “robot natives,” will be expected to have a certain degree of “robot literacy.” In this paper, the concept of robot literacy is defined and an approach to robot literacy education is discussed.

  10. Improved Intelligent Underlay-Overlay Combined with Frequency Hopping in GSM

    DEFF Research Database (Denmark)

    Wigard, Jeroen; Nielsen, Thomas Toftegaard; Mogensen, Preben Elgaard

    1997-01-01

    IUO (intelligent underlay-overlay) in a combination with random frequency hopping in GSM is analysed. Several improvements to the original IUO concept analysed in Nielsen et al. (1997) are introduced. With the improved IUO concept it is possible to load a network configuration consisting of 4...

  11. Social collective intelligence: combining the powers of humans and machines to build a smarter society

    NARCIS (Netherlands)

    Miorandi, Daniele; Maltese, Vincenzo; Rovatsos, Michael; Nijholt, Antinus; Stewart, James

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and

  12. Intelligent Systems Approaches to Product Sound Quality Analysis

    Science.gov (United States)

    Pietila, Glenn M.

    As a product market becomes more competitive, consumers become more discriminating in the way in which they differentiate between engineered products. The consumer often makes a purchasing decision based on the sound emitted from the product during operation by using the sound to judge quality or annoyance. Therefore, in recent years, many sound quality analysis tools have been developed to evaluate the consumer preference as it relates to a product sound and to quantify this preference based on objective measurements. This understanding can be used to direct a product design process in order to help differentiate the product from competitive products or to establish an impression on consumers regarding a product's quality or robustness. The sound quality process is typically a statistical tool that is used to model subjective preference, or merit score, based on objective measurements, or metrics. In this way, new product developments can be evaluated in an objective manner without the laborious process of gathering a sample population of consumers for subjective studies each time. The most common model used today is the Multiple Linear Regression (MLR), although recently non-linear Artificial Neural Network (ANN) approaches are gaining popularity. This dissertation will review publicly available published literature and present additional intelligent systems approaches that can be used to improve on the current sound quality process. The focus of this work is to address shortcomings in the current paired comparison approach to sound quality analysis. This research will propose a framework for an adaptive jury analysis approach as an alternative to the current Bradley-Terry model. The adaptive jury framework uses statistical hypothesis testing to focus on sound pairings that are most interesting and is expected to address some of the restrictions required by the Bradley-Terry model. It will also provide a more amicable framework for an intelligent systems approach

  13. 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

  14. 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.

  15. A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

    Science.gov (United States)

    Becker, Lee A.

    1987-01-01

    Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

  16. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2014-01-01

    Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

  17. Combining NDE and fracture mechanics by artifical intelligence expert systems techniques

    International Nuclear Information System (INIS)

    Mucciardi, A.N.; Riccardella, P.C.

    1986-01-01

    This paper reports on the development of a PC-based expert system for non-destructive evaluation. Software tools from the expert systems subfield of artificial intelligence are being used to combine both NDE and fracture mechanics algorithms into one, unified package. The system incorporates elements of computer-enhanced ultrasonic signal processing, featuring artificial intelligence learning capability, state-of-the-art fracture mechanics analytical tools, and all relevant metallurgical and design data necessary to emulate the decisions of the panel(s) of experts typically involved in generating and dispositioning NDE data

  18. An Intelligent Systems Approach to Reservoir Characterization. Final Report

    International Nuclear Information System (INIS)

    Shahab D. Mohaghegh; Jaime Toro; Thomas H. Wilson; Emre Artun; Alejandro Sanchez; Sandeep Pyakurel

    2005-01-01

    Today, the major challenge in reservoir characterization is integrating data coming from different sources in varying scales, in order to obtain an accurate and high-resolution reservoir model. The role of seismic data in this integration is often limited to providing a structural model for the reservoir. Its relatively low resolution usually limits its further use. However, its areal coverage and availability suggest that it has the potential of providing valuable data for more detailed reservoir characterization studies through the process of seismic inversion. In this paper, a novel intelligent seismic inversion methodology is presented to achieve a desirable correlation between relatively low-frequency seismic signals, and the much higher frequency wireline-log data. Vertical seismic profile (VSP) is used as an intermediate step between the well logs and the surface seismic. A synthetic seismic model is developed by using real data and seismic interpretation. In the example presented here, the model represents the Atoka and Morrow formations, and the overlying Pennsylvanian sequence of the Buffalo Valley Field in New Mexico. Generalized regression neural network (GRNN) is used to build two independent correlation models between; (1) Surface seismic and VSP, (2) VSP and well logs. After generating virtual VSP's from the surface seismic, well logs are predicted by using the correlation between VSP and well logs. The values of the density log, which is a surrogate for reservoir porosity, are predicted for each seismic trace through the seismic line with a classification approach having a correlation coefficient of 0.81. The same methodology is then applied to real data taken from the Buffalo Valley Field, to predict inter-well gamma ray and neutron porosity logs through the seismic line of interest. The same procedure can be applied to a complete 3D seismic block to obtain 3D distributions of reservoir properties with less uncertainty than the geostatistical

  19. Strategic Management Model with Lens of Knowledge Management and Competitive Intelligence: A Review Approach

    OpenAIRE

    Shujahat, Muhammad; Hussain, Saddam; Javed, Sammar; Muhammad, Imran Malik; Thursamy, Ramayah; Ali, Junaid

    2017-01-01

    Purpose:\\ud First purpose of this study is to discuss the synergic and separate use of knowledge and\\ud intelligence, via knowledge management and competitive intelligence, in each stage of strategic\\ud management process. Second purpose is to discuss the implications of each stage of strategic\\ud management process for knowledge management and competitive intelligence and vice versa.\\ud Methodology/Design/Approach:\\ud A systematic literature review was performed within timeframe of 2000 to 2...

  20. Managing knowledge business intelligence: A cognitive analytic approach

    Science.gov (United States)

    Surbakti, Herison; Ta'a, Azman

    2017-10-01

    The purpose of this paper is to identify and analyze integration of Knowledge Management (KM) and Business Intelligence (BI) in order to achieve competitive edge in context of intellectual capital. Methodology includes review of literatures and analyzes the interviews data from managers in corporate sector and models established by different authors. BI technologies have strong association with process of KM for attaining competitive advantage. KM have strong influence from human and social factors and turn them to the most valuable assets with efficient system run under BI tactics and technologies. However, the term of predictive analytics is based on the field of BI. Extracting tacit knowledge is a big challenge to be used as a new source for BI to use in analyzing. The advanced approach of the analytic methods that address the diversity of data corpus - structured and unstructured - required a cognitive approach to provide estimative results and to yield actionable descriptive, predictive and prescriptive results. This is a big challenge nowadays, and this paper aims to elaborate detail in this initial work.

  1. Advanced approaches to intelligent information and database systems

    CERN Document Server

    Boonjing, Veera; Chittayasothorn, Suphamit

    2014-01-01

    This book consists of 35 chapters presenting different theoretical and practical aspects of Intelligent Information and Database Systems. Nowadays both Intelligent and Database Systems are applied in most of the areas of human activities which necessitates further research in these areas. In this book various interesting issues related to the intelligent information models and methods as well as their advanced applications, database systems applications, data models and their analysis, and digital multimedia methods and applications are presented and discussed both from the practical and theoretical points of view. The book is organized in four parts devoted to intelligent systems models and methods, intelligent systems advanced applications, database systems methods and applications, and multimedia systems methods and applications. The book will be interesting for both practitioners and researchers, especially graduate and PhD students of information technology and computer science, as well more experienced ...

  2. Empirical Approaches to Measuring the Intelligibility of Different Varieties of English in Predicting Listener Comprehension

    Science.gov (United States)

    Kang, Okim; Thomson, Ron I.; Moran, Meghan

    2018-01-01

    This study compared five research-based intelligibility measures as they were applied to six varieties of English. The objective was to determine which approach to measuring intelligibility would be most reliable for predicting listener comprehension, as measured through a listening comprehension test similar to the Test of English as a Foreign…

  3. The Emotional Intelligence Approach for Enhancing Skills in Leadership

    Directory of Open Access Journals (Sweden)

    Radu Herman

    2014-05-01

    Full Text Available An appreciated manager coordinates efficiently the team and both his abilities to be a leader and assume his decisions is crucial for the success of the project. In the empirical study “O nouă abordare asupra învățării practice” several conclusions show that some leadership problems were related to the prioritization of the objectives, an efficient coordination of the members by the leaders, fear in assuming the leadership, not defending the leadership position and tension within the group when facing competition. As a leader, a certain state of mind is required to solve a long-term goal, to have a consistent behavior and adapt a certain leadership style to motivate in a specific situation the members of a team. In an emotional intelligence approach, controlling the afflictions of the mind means reducing the barriers towards being “able to”manifest a leadership style. The aim of this article is to argue that the quest of developing leadership skills can become useless when the leader fells into an inappropriate state of mind.

  4. Intelligent Resource Management for Local Area Networks: Approach and Evolution

    Science.gov (United States)

    Meike, Roger

    1988-01-01

    The Data Management System network is a complex and important part of manned space platforms. Its efficient operation is vital to crew, subsystems and experiments. AI is being considered to aid in the initial design of the network and to augment the management of its operation. The Intelligent Resource Management for Local Area Networks (IRMA-LAN) project is concerned with the application of AI techniques to network configuration and management. A network simulation was constructed employing real time process scheduling for realistic loads, and utilizing the IEEE 802.4 token passing scheme. This simulation is an integral part of the construction of the IRMA-LAN system. From it, a causal model is being constructed for use in prediction and deep reasoning about the system configuration. An AI network design advisor is being added to help in the design of an efficient network. The AI portion of the system is planned to evolve into a dynamic network management aid. The approach, the integrated simulation, project evolution, and some initial results are described.

  5. Error Management in ATLAS TDAQ: An Intelligent Systems approach

    CERN Document Server

    Slopper, John Erik

    2010-01-01

    This thesis is concerned with the use of intelligent system techniques (IST) within a large distributed software system, specically the ATLAS TDAQ system which has been developed and is currently in use at the European Laboratory for Particle Physics(CERN). The overall aim is to investigate and evaluate a range of ITS techniques in order to improve the error management system (EMS) currently used within the TDAQ system via error detection and classication. The thesis work will provide a reference for future research and development of such methods in the TDAQ system. The thesis begins by describing the TDAQ system and the existing EMS, with a focus on the underlying expert system approach, in order to identify areas where improvements can be made using IST techniques. It then discusses measures of evaluating error detection and classication techniques and the factors specic to the TDAQ system. Error conditions are then simulated in a controlled manner using an experimental setup and datasets were gathered fro...

  6. A new approach to PWR power control using intelligent techniques

    International Nuclear Information System (INIS)

    Boroushaki, M.; Ghofrani, M.B.; Lucas, C.; Yazdanpanah, M.J.; Sadati, N.

    2004-01-01

    Improved load following capability is one of the main technical performances of advanced PWR(APWR). Controlling the nuclear reactor core during load following operation encounters some difficulties. These difficulties mainly arise from nuclear reactor core limitations in local power peaking, while the core is subject to large and sharp variation of local power density during transients. Axial offset (A.O) is the parameter usually used to represent of core power peaking, in form of a practical parameter. This paper, proposes a new intelligent approach to A.o control of PWR nuclear reactors core during load following operation. This method uses a neural network model of the core to predict the dynamic behavior of the core and a fuzzy critic based on the operator knowledge and experience for the purpose of decision-making during load following operations. Simulation results show that this method can use optimum control rod groups maneuver with variable overlapping and may improve the reactor load following capability

  7. Intelligent condition monitoring of railway catenary systems : A Bayesian Network approach

    NARCIS (Netherlands)

    Wang, H.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Liu, Zhigang; Chen, Junwen; Spiryagin, Maksym; Gordon, Timothy; Cole, Colin; McSweeney, Tim

    2017-01-01

    This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of railway catenary systems. It combines five types of measurements related to catenary condition, namely the contact wire stagger, contact wire height, pantograph head displacement, pantograph head

  8. EMOTIONAL INTELLIGENCE AND ORGANIZATIONAL COMPETITIVENESS: MANAGEMENT MODEL APPROACH

    Directory of Open Access Journals (Sweden)

    John N. N. Ugoani

    2016-09-01

    Full Text Available Modern organization theory considers emotional intelligence as the index of competencies that help organizations to develop a vision for competitiveness. It also allows organizational leaders to enthusiastically commit to the vision, and energize organizational members to achieve the vision. To maximize competiveness organizations use models to simplify and clarify thinking, to identify important aspects, to suggest explanations and to predict consequences, and explore other performance areas that would otherwise be hidden in an excess of words. The survey research design was used to explore the relationship between emotional intelligence and organizational competitiveness. The study found that emotional intelligence has strong positive relationship with organizational competitiveness

  9. Bio-inspired approach for intelligent unattended ground sensors

    Science.gov (United States)

    Hueber, Nicolas; Raymond, Pierre; Hennequin, Christophe; Pichler, Alexander; Perrot, Maxime; Voisin, Philippe; Moeglin, Jean-Pierre

    2015-05-01

    Improving the surveillance capacity over wide zones requires a set of smart battery-powered Unattended Ground Sensors capable of issuing an alarm to a decision-making center. Only high-level information has to be sent when a relevant suspicious situation occurs. In this paper we propose an innovative bio-inspired approach that mimics the human bi-modal vision mechanism and the parallel processing ability of the human brain. The designed prototype exploits two levels of analysis: a low-level panoramic motion analysis, the peripheral vision, and a high-level event-focused analysis, the foveal vision. By tracking moving objects and fusing multiple criteria (size, speed, trajectory, etc.), the peripheral vision module acts as a fast relevant event detector. The foveal vision module focuses on the detected events to extract more detailed features (texture, color, shape, etc.) in order to improve the recognition efficiency. The implemented recognition core is able to acquire human knowledge and to classify in real-time a huge amount of heterogeneous data thanks to its natively parallel hardware structure. This UGS prototype validates our system approach under laboratory tests. The peripheral analysis module demonstrates a low false alarm rate whereas the foveal vision correctly focuses on the detected events. A parallel FPGA implementation of the recognition core succeeds in fulfilling the embedded application requirements. These results are paving the way of future reconfigurable virtual field agents. By locally processing the data and sending only high-level information, their energy requirements and electromagnetic signature are optimized. Moreover, the embedded Artificial Intelligence core enables these bio-inspired systems to recognize and learn new significant events. By duplicating human expertise in potentially hazardous places, our miniature visual event detector will allow early warning and contribute to better human decision making.

  10. Distributed Collaborative Analysis: A New Approach for Intelligence Analysis

    National Research Council Canada - National Science Library

    Greene, Gus

    2001-01-01

    ... calls for resource reductions by the public. At the same time, the rapid pace of this growth has caused decision makers at all echelons - tactical to strategic - to challenge the Intelligence Community to become more responsive and agile...

  11. Application of Wireless Intelligent Control System for HPS Lamps and LEDs Combined Illumination in Road Tunnel

    Science.gov (United States)

    Lai, Jinxing; Qiu, Junling; Chen, Jianxun; Wang, Yaqiong; Fan, Haobo

    2014-01-01

    Because of the particularity of the environment in the tunnel, the rational tunnel illumination system should be developed, so as to optimize the tunnel environment. Considering the high cost of traditional tunnel illumination system with high-pressure sodium (HPS) lamps as well as the effect of a single light source on tunnel entrance, the energy-saving illumination system with HPS lamps and LEDs combined illumination in road tunnel, which could make full use of these two kinds of lamps, was proposed. The wireless intelligent control system based on HPS lamps and LEDs combined illumination and microcontrol unit (MCU) Si1000 wireless communication technology was designed. And the remote monitoring, wireless communication, and PWM dimming module of this system were designed emphatically. Intensity detector and vehicle flow detector can be configured in wireless intelligent control system, which gather the information to the master control unit, and then the information is sent to the monitoring center through the Ethernet. The control strategies are got by the monitoring center according to the calculated results, and the control unit wirelessly sends parameters to lamps, which adjust the luminance of each segment of the tunnel and realize the wireless intelligent control of combined illumination in road tunnel. PMID:25587266

  12. Effective Approach to Elevate the Intelligence of Management Decision System

    Institute of Scientific and Technical Information of China (English)

    杨保安; 朱明; 唐志杰; 陈思

    2003-01-01

    Based on the sticking point of the low intelligence of the existing management decision system,this paper puts forward the idea of enriching and refining the knowledge of the system and endowing it with the ability to learn by means of adopting three types of heterogeneous knowledge representation and knowledge management measures.At length,this paper outlines the basic framework of an intelligence system for the sake of management decision problem.

  13. Practical Approach of the PEST Analysis from the Perspective of the Territorial Intelligence

    Directory of Open Access Journals (Sweden)

    Alexandru Bîrsan

    2016-01-01

    Digging deeper in the Knowledge Economy, we propose as the subject of this paper and as apart of our research, a theoretical approach in assessing and analyzing a region from theperspective of both territorial intelligence and smart developing.

  14. MLED_BI: a new BI Design Approach to Support Multilingualism in Business Intelligence

    Directory of Open Access Journals (Sweden)

    Nedim Dedić

    2017-11-01

    Full Text Available Existing approaches to support Multilingualism (ML in Business Intelligence (BI create problems for business users, present a number of challenges from the technical perspective, and lead to issues with logical dependence in the star schema. In this paper, we propose MLED_BI (Multilingual Enabled Design for Business Intelligence, a novel BI design approach to support the application of ML in BI Environment, which overcomes the issues and problems found with existing approaches. The approach is based on a revision of the data warehouse dimensional modelling approach and treats the Star Schema as a higher level entity. This paper describes MLED_BI and the validation and evaluation approach used.

  15. Combining accounting approaches to practice valuation.

    Science.gov (United States)

    Schwartzben, D; Finkler, S A

    1998-06-01

    Healthcare organizations that wish to acquire physician or ambulatory care practices can choose from a variety of practice valuation approaches. Basic accounting methods assess the value of a physician practice on the basis of a historical, balance-sheet description of tangible assets. Yet these methods alone are inadequate to determine the true financial value of a practice. By using a combination of accounting approaches to practice valuation that consider factors such as fair market value, opportunity cost, and discounted cash flow over a defined time period, organizations can more accurately assess a practice's actual value.

  16. THE COMBINED USE OF BUSINESS MANAGEMENT WITH FACILITY MANAGEMENT AS AN OPTION FOR INTELLIGENT BUILDING

    Directory of Open Access Journals (Sweden)

    Andreas Dittmar Weise

    2014-01-01

    Full Text Available Words like Business Management (BM and Facility Management (FM are well known as separate management methods. FM offers transparency about their property costs and exploitation, starting from the planning phase until its demolition. The investor sees this in the property invested capital and its recoverable yield. This means they also want a profit with their real estates. Besides this, changes in the social and environmental requirements become necessary to adapt the properties. The solution is called Intelligent Building. Its primary aim is to collect and select previous knowledge and information about Facility Management and Business Management. It is an application, mainly with sight to characterize and describe the possibilities of use of intelligent buildings as a combination of Facility and Business Management. This paper is an indirect survey carried out through a documental procedure in the form of a bibliographic research and theoretician study. Intelligent Building as combination of FM and BM is new, but in our times necessary to satisfy the needs of the demand. This type of building needs to be flexible in its structure and services, open for changes in environmental requirements, e.g. saving energy, and needs a lot of technology to realize their functions. Consequently, it will be sustainable for a value enhancement. With a Computer Aided Facilities Management system this is possible and the company will be more flexible in relation to the competitors and future changes.

  17. Heart failure analysis dashboard for patient's remote monitoring combining multiple artificial intelligence technologies.

    Science.gov (United States)

    Guidi, G; Pettenati, M C; Miniati, R; Iadanza, E

    2012-01-01

    In this paper we describe an Heart Failure analysis Dashboard that, combined with a handy device for the automatic acquisition of a set of patient's clinical parameters, allows to support telemonitoring functions. The Dashboard's intelligent core is a Computer Decision Support System designed to assist the clinical decision of non-specialist caring personnel, and it is based on three functional parts: Diagnosis, Prognosis, and Follow-up management. Four Artificial Intelligence-based techniques are compared for providing diagnosis function: a Neural Network, a Support Vector Machine, a Classification Tree and a Fuzzy Expert System whose rules are produced by a Genetic Algorithm. State of the art algorithms are used to support a score-based prognosis function. The patient's Follow-up is used to refine the diagnosis.

  18. Appropriate Combination of Artificial Intelligence and Algorithms for Increasing Predictive Accuracy Management

    Directory of Open Access Journals (Sweden)

    Shahram Gilani Nia

    2010-03-01

    Full Text Available In this paper a simple and effective expert system to predict random data fluctuation in short-term period is established. Evaluation process includes introducing Fourier series, Markov chain model prediction and comparison (Gray combined with the model prediction Gray- Fourier- Markov that the mixed results, to create an expert system predicted with artificial intelligence, made this model to predict the effectiveness of random fluctuation in most data management programs to increase. The outcome of this study introduced artificial intelligence algorithms that help detect that the computer environment to create a system that experts predict the short-term and unstable situation happens correctly and accurately predict. To test the effectiveness of the algorithm presented studies (Chen Tzay len,2008, and predicted data of tourism demand for Iran model is used. Results for the two countries show output model has high accuracy.

  19. A PHILOSOPHICAL APPROACH TO ARTIFICIAL INTELLIGENCE AND ISLAMIC VALUES

    Directory of Open Access Journals (Sweden)

    Ali Akbar Ziaee

    2012-02-01

    Full Text Available Artificial Intelligence has the potential to empower humans through enhanced learning and performance. But if this potential is to be realized and accepted, the ethical aspects as well as the technical must be addressed. Many engineers claim that AI will be smarter than human brains, including scientific creativity, general wisdom and social skills, so we must consider it an important factor for making decisions in our social life and especially in our Islamic societies. The most important challenges will be the quality of representing the Islamic values like piety, obedience, Halal and Haram, and etc in the form of semantics. In this paper, I want to emphasize on the role of Divine Islamic values in the application of AI and discuss it according to philosophy of AI and Islamic perspective.Keywords- Value, expert, Community Development, Artificial Intelligence, Superintelligence, Friendly Artificial Intelligence

  20. Intelligent networks recent approaches and applications in medical systems

    CERN Document Server

    Ahamed, Syed V

    2013-01-01

    This textbook offers an insightful study of the intelligent Internet-driven revolutionary and fundamental forces at work in society. Readers will have access to tools and techniques to mentor and monitor these forces rather than be driven by changes in Internet technology and flow of money. These submerged social and human forces form a powerful synergistic foursome web of (a) processor technology, (b) evolving wireless networks of the next generation, (c) the intelligent Internet, and (d) the motivation that drives individuals and corporations. In unison, the technological forces can tear

  1. Intelligent Flowcharting Developmental Approach to Legal Knowledge Based System

    Directory of Open Access Journals (Sweden)

    Nitin Balaji Bilgi

    2011-10-01

    Full Text Available The basic aim of this research, described in this paper is to develop a hybrid legal expert system/ knowledge based system, with specific reference to the transfer of property act, within the Indian legal system which is often in demand. In this paper the authors discuss an traditional approach to combining two types of reasoning methodologies, Rule Based Reasoning (RBR and Case Based Reasoning (CBR. In RBR module we have interpreted and implemented rules that occur in legal statutes of the Transfer of property act. In the CBR module we have an implementation to find the related cases. The VisiRule software made available by Logic Programming Associates is used in the development of RBR part this expert system. The authors have used java Net Beans for development of CBR. VisiRule is a decision charting tool, in which the rules are defined by a combination of graphical shapes and pieces of text, and produces rules.

  2. Intelligent Approach to Inventory Control in Logistics under Uncertainty Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Więcek, P.

    2016-07-01

    The article presents a proposal for a combined application of fuzzy logic and genetic algorithms to control the procurement process in the enterprise. The approach presented in this paper draws particular attention to the impact of external random factors in the form of demand and lead time uncertainty. The model uses time-variable membership function parameters in a dynamic fashion to describe the modelled output fuzzy (sets) values. An additional element is the use of genetic algorithms for optimisation of fuzzy rule base in the proposed method. The approach presented in this paper was veryfied according to four criteria based on a computer simulation performed on the basis of the actual data from an enterprise. (Author)

  3. An Approach to quantify the Costs of Business Process Intelligence.

    NARCIS (Netherlands)

    Mutschler, B.B.; Bumiller, J.; Reichert, M.U.; Desel, J.; Frank, U.

    2005-01-01

    Today, enterprises are forced to continuously optimize their business as well as service processes. In this context the process-centered alignment of information systems is crucial. The use of business process intelligence (BPI) tools offers promising perspectives in this respect. However, when

  4. 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.

  5. A computational intelligence approach to the Mars Precision Landing problem

    Science.gov (United States)

    Birge, Brian Kent, III

    Various proposed Mars missions, such as the Mars Sample Return Mission (MRSR) and the Mars Smart Lander (MSL), require precise re-entry terminal position and velocity states. This is to achieve mission objectives including rendezvous with a previous landed mission, or reaching a particular geographic landmark. The current state of the art footprint is in the magnitude of kilometers. For this research a Mars Precision Landing is achieved with a landed footprint of no more than 100 meters, for a set of initial entry conditions representing worst guess dispersions. Obstacles to reducing the landed footprint include trajectory dispersions due to initial atmospheric entry conditions (entry angle, parachute deployment height, etc.), environment (wind, atmospheric density, etc.), parachute deployment dynamics, unavoidable injection error (propagated error from launch on), etc. Weather and atmospheric models have been developed. Three descent scenarios have been examined. First, terminal re-entry is achieved via a ballistic parachute with concurrent thrusting events while on the parachute, followed by a gravity turn. Second, terminal re-entry is achieved via a ballistic parachute followed by gravity turn to hover and then thrust vector to desired location. Third, a guided parafoil approach followed by vectored thrusting to reach terminal velocity is examined. The guided parafoil is determined to be the best architecture. The purpose of this study is to examine the feasibility of using a computational intelligence strategy to facilitate precision planetary re-entry, specifically to take an approach that is somewhat more intuitive and less rigid, and see where it leads. The test problems used for all research are variations on proposed Mars landing mission scenarios developed by NASA. A relatively recent method of evolutionary computation is Particle Swarm Optimization (PSO), which can be considered to be in the same general class as Genetic Algorithms. An improvement over

  6. Business intelligence and financial decision-making: a theoretical approach

    OpenAIRE

    Mary Julieth Murillo Junco; Gustavo Cáceres Castellanos

    2013-01-01

    This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication ...

  7. Human-Assisted AI: an Intelligence Augmentation Approach

    OpenAIRE

    Alicea, Bradly

    2018-01-01

    As a flavor of Human-Computer Interaction (HCI), Human-Assisted AI can serve to both augment both human performance and artificial systems. This talk will feature a discussion of Human-assisted AI as an instance of Intelligence Augmentation (IA). We will discuss instances of weak and strong IA, in addition to contemporary examples of and paths forward for such systems. In the variety of models presented, data plays a critical role in the structure of interactions between human and artificial ...

  8. Business intelligence and financial decision-making: a theoretical approach

    Directory of Open Access Journals (Sweden)

    Mary Julieth Murillo Junco

    2013-01-01

    Full Text Available This paper deals with a literature review about the origin, development and implementation of Business Intelligence focused directly to solving problems in the financial area of the different organizations. Wanted contextualize how it tools have been incorporated into the decision making processes of modern business. A feature of the way it makes decisions has to do with the rational use made of the information available, and it is in this field where information technology and communication play a role today

  9. An 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. An Artificial Intelligence Approach for Gears Diagnostics in AUVs.

    Science.gov (United States)

    Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano

    2016-04-12

    In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

  11. Approaching Artificial Intelligence for Games – the Turing Test revisited

    Directory of Open Access Journals (Sweden)

    Jenny Eriksson Lundström

    2008-07-01

    Full Text Available Today's powerful computers have increasingly more resources available, which can be used for incorporating more sophisticated AI into home applications like computer games. The perhaps obvious way of using AI to enhance the experience of a game is to make the player perceive the computer-controlled entities as intelligent. The traditional idea of how to determine whether a machine can pass as intelligent is the Turing Test. In this paper we show that it is possible and useful to conduct a test adhering to the intention of the original Turing test. We present an empirical study exploring human discrimination of artificial intelligence from the behaviour of a computer-controlled entity used in its specific context and how the behaviour responds to the user's expectations. In our empirical study the context is a real-time strategy computer game and the purpose of the AI is merely to pass as an acceptable opponent. We discuss the results of the empirical study and its implications for AI in computer applications.

  12. An Artificial Intelligence Approach for Gears Diagnostics in AUVs

    Directory of Open Access Journals (Sweden)

    Graciliano Nicolás Marichal

    2016-04-01

    Full Text Available In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles, where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.

  13. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

  14. Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

    International Nuclear Information System (INIS)

    Town, G.G.; Stratton, R.C.

    1985-01-01

    A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artificial intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

  15. Combination of artificial intelligence and procedural language programs in a computer application system supporting nuclear reactor operations

    International Nuclear Information System (INIS)

    Stratton, R.C.; Town, G.G.

    1985-01-01

    A computer application system is described which provides nuclear reactor power plant operators with an improved decision support system. This system combines traditional computer applications such as graphics display with artifical intelligence methodologies such as reasoning and diagnosis so as to improve plant operability. This paper discusses the issues, and a solution, involved with the system integration of applications developed using traditional and artificial intelligence languages

  16. Government Approaches to Foster Competitive Intelligence Practice in SMEs: A Comparative Study of Eight Governments.

    Science.gov (United States)

    Bergeron, Pierrette

    2000-01-01

    Presents results from a study examining approaches developed by seven governments to foster competitive intelligence practice in SMEs (small and medium enterprises) and compares them with the approach taken by the government of Quebec. Suggests a need for a better understanding of information needs and uses in SMEs. (Contains 22 references.)…

  17. The application of multiple intelligence approach to the learning of human circulatory system

    Science.gov (United States)

    Kumalasari, Lita; Yusuf Hilmi, A.; Priyandoko, Didik

    2017-11-01

    The purpose of this study is to offer an alternative teaching approach or strategies which able to accommodate students’ different ability, intelligence and learning style. Also can gives a new idea for the teacher as a facilitator for exploring how to teach the student in creative ways and more student-center activities, for a lesson such as circulatory system. This study was carried out at one private school in Bandung involved eight students to see their responses toward the lesson that delivered by using Multiple Intelligence approach which is include Linguistic, Logical-Mathematical, Visual-Spatial, Musical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Naturalistic. Students were test by using MI test based on Howard Gardner’s MI model to see their dominant intelligence. The result showed the percentage of top three ranks of intelligence are Bodily-Kinesthetic (73%), Visual-Spatial (68%), and Logical-Mathematical (61%). The learning process is given by using some different multimedia and activities to engaged their learning style and intelligence such as mini experiment, short clip, and questions. Student response is given by using self-assessment and the result is all students said the lesson gives them a knowledge and skills that useful for their life, they are clear with the explanation given, they didn’t find difficulties to understand the lesson and can complete the assignment given. At the end of the study, it is reveal that the students who are learned by Multiple Intelligence instructional approach have more enhance to the lesson given. It’s also found out that the students participated in the learning process which Multiple Intelligence approach was applied enjoyed the activities and have great fun.

  18. Training teachers to observation: an approach through multiple intelligences theory

    Directory of Open Access Journals (Sweden)

    Nicolini, P.

    2010-11-01

    Full Text Available Observation is a daily practice in scholastic and educational contexts, but it needs to develop into a professional competence in order to be helpful. In fact, to design an educative and didactic plan and to provide useful tools, activities and tasks to their students, teachers and educators need to collect information about learners. For these reasons we’ll built a Web-Observation (Web-Ob application, a tool able to support good practices in observation. In particular, the Web-Ob can provide Multiple Intelligences Theory as a framework through which children’s behaviors and attitudes can be observed, assessed and evaluated.

  19. ICON: An artificial intelligence approach to radiologic differential diagnosis

    International Nuclear Information System (INIS)

    Swett, H.A.; Miller, P.L.

    1986-01-01

    ICON is a computer system, developed using artificial intelligence techniques, that is designed to help radiologists manage the large body of knowledge needed to perform differential diagnosis in radiology. The system's domain is lung disease in patients with lymphoproliferative disorders. The radiologist proposes a diagnostic hypothesis which he or she thinks explains the known clinical and chest radiographic findings. ICON responds with an English-language prose critique that discusses how and why the proposed diagnosis is or is not supported by the clinical literature and suggests further findings or clinical information that might make the diagnosis more secure

  20. The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility.

    Science.gov (United States)

    Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten

    2018-01-01

    Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.

  1. The Relationship between a Linear Combination of Intelligence, Musical Background, Rhythm Ability and Tapping Ability to Typewriting Speed and Accuracy.

    Science.gov (United States)

    Fante, Cheryl H.

    This study was conducted in an attempt to identify any predictor or combination of predictors of a beginning typewriting student's success. Variables of intelligence, rhythmic ability, musical background, and tapping ability were combined to study their relationship to typewriting speed and accuracy. A sample of 109 high school students was…

  2. 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

  3. Combining engineering and data-driven approaches

    DEFF Research Database (Denmark)

    Fischer, Katharina; De Sanctis, Gianluca; Kohler, Jochen

    2015-01-01

    Two general approaches may be followed for the development of a fire risk model: statistical models based on observed fire losses can support simple cost-benefit studies but are usually not detailed enough for engineering decision-making. Engineering models, on the other hand, require many assump...... to the calibration of a generic fire risk model for single family houses to Swiss insurance data. The example demonstrates that the bias in the risk estimation can be strongly reduced by model calibration.......Two general approaches may be followed for the development of a fire risk model: statistical models based on observed fire losses can support simple cost-benefit studies but are usually not detailed enough for engineering decision-making. Engineering models, on the other hand, require many...... assumptions that may result in a biased risk assessment. In two related papers we show how engineering and data-driven modelling can be combined by developing generic risk models that are calibrated to statistical data on observed fire events. The focus of the present paper is on the calibration procedure...

  4. An approach to efficient mobility management in intelligent networks

    Science.gov (United States)

    Murthy, K. M. S.

    1995-01-01

    Providing personal communication systems supporting full mobility require intelligent networks for tracking mobile users and facilitating outgoing and incoming calls over different physical and network environments. In realizing the intelligent network functionalities, databases play a major role. Currently proposed network architectures envision using the SS7-based signaling network for linking these DB's and also for interconnecting DB's with switches. If the network has to support ubiquitous, seamless mobile services, then it has to support additionally mobile application parts, viz., mobile origination calls, mobile destination calls, mobile location updates and inter-switch handovers. These functions will generate significant amount of data and require them to be transferred between databases (HLR, VLR) and switches (MSC's) very efficiently. In the future, the users (fixed or mobile) may use and communicate with sophisticated CPE's (e.g. multimedia, multipoint and multisession calls) which may require complex signaling functions. This will generate volumness service handling data and require efficient transfer of these message between databases and switches. Consequently, the network providers would be able to add new services and capabilities to their networks incrementally, quickly and cost-effectively.

  5. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

    Science.gov (United States)

    Abbasi, Maryam; El Hanandeh, Ali

    2016-10-01

    Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Indoor Smartphone Navigation Using a Combination of Wi-Fi and Inertial Navigation with Intelligent Checkpoints

    Science.gov (United States)

    Hofer, H.; Retscher, G.

    2017-09-01

    For Wi-Fi positioning location fingerprinting is one of the most commonly employed localization technique. To achieve an acceptable level of positioning accuracy on the few meter level, i.e., to provide at least room resolution in buildings, such an approach is very labour consuming as it requires a high density of reference points. Thus, the novel approach developed aims at a significant reduction of workload for the training phase. The basic idea is to intelligently choose waypoints along possible users' trajectories in the indoor environment. These waypoints are termed intelligent checkpoints (iCPs) and serve as reference points for the fingerprinting localization approach. They are selected along the trajectories in such a way that they define a logical sequence with their ascending order. Thereby, the iCPs are located, for instance, at doors at entrances to buildings, rooms, along corridors, etc., or in low density along the trajectory to provide a suitable absolute user localization. Continuous positioning between these iCPs is obtained with the help of the smartphones' inertial sensors. While walking along a selected trajectory to the destination a dynamic recognition of the iCPs is performed and the drift of the inertial sensors is reduced as the iCP recognition serves as absolute position update. Conducted experiments in a multi-storey office building have shown that positioning accuracy of around 2.0 m are achievable which goes along with a reduction of workload by three quarter using this novel approach. The iCP concept and performance are presented and demonstrated in this paper.

  7. Time-series prediction and applications a machine intelligence approach

    CERN Document Server

    Konar, Amit

    2017-01-01

    This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at...

  8. A genetic-neural artificial intelligence approach to resins optimization

    International Nuclear Information System (INIS)

    Cabral, Denise C.; Barros, Marcio P.; Lapa, Celso M.F.; Pereira, Claudio M.N.A.

    2005-01-01

    This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

  9. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

  10. Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

    Science.gov (United States)

    Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

    2017-11-01

    For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

  11. The Dynamic Interplay among EFL Learners' Ambiguity Tolerance, Adaptability, Cultural Intelligence, Learning Approach, and Language Achievement

    Science.gov (United States)

    Alahdadi, Shadi; Ghanizadeh, Afsaneh

    2017-01-01

    A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…

  12. Predicting Speech Intelligibility with a Multiple Speech Subsystems Approach in Children with Cerebral Palsy

    Science.gov (United States)

    Lee, Jimin; Hustad, Katherine C.; Weismer, Gary

    2014-01-01

    Purpose: Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems. Method: Nine acoustic variables reflecting different subsystems, and…

  13. Improving Students' Creative Thinking and Achievement through the Implementation of Multiple Intelligence Approach with Mind Mapping

    Science.gov (United States)

    Widiana, I. Wayan; Jampel, I. Nyoman

    2016-01-01

    This classroom action research aimed to improve the students' creative thinking and achievement in learning science. It conducted through the implementation of multiple intelligences with mind mapping approach and describing the students' responses. The subjects of this research were the fifth grade students of SD 8 Tianyar Barat, Kubu, and…

  14. A Mindful Approach to Teaching Emotional Intelligence to Undergraduate Students Online and in Person

    Science.gov (United States)

    Cotler, Jami L.; DiTursi, Dan; Goldstein, Ira; Yates, Jeff; DelBelso, Deb

    2017-01-01

    In this paper we examine whether emotional intelligence (EI) can be taught online and, if so, what key variables influence the successful implementation of this online learning model. Using a 3 x 2 factorial quasi-experimental design, this mixed-methods study found that a team-based learning environment using a blended teaching approach, supported…

  15. Interindividual Differences in Learning Performance: The Effects of Age, Intelligence, and Strategic Task Approach

    Science.gov (United States)

    Kliegel, Matthias; Altgassen, Mareike

    2006-01-01

    The present study investigated fluid and crystallized intelligence as well as strategic task approaches as potential sources of age-related differences in adult learning performance. Therefore, 45 young and 45 old adults were asked to learn pictured objects. Overall, young participants outperformed old participants in this learning test. However,…

  16. Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey

    Directory of Open Access Journals (Sweden)

    Lefeng Cheng

    2018-04-01

    Full Text Available Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA, including expert system (EPS, artificial neural network (ANN, fuzzy theory, rough sets theory (RST, grey system theory (GST, swarm intelligence (SI algorithms, data mining technology, machine learning (ML, and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as

  17. Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

    Science.gov (United States)

    Bennett, Casey C; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

  18. Novel approach for dam break flow modeling using computational intelligence

    Science.gov (United States)

    Seyedashraf, Omid; Mehrabi, Mohammad; Akhtari, Ali Akbar

    2018-04-01

    A new methodology based on the computational intelligence (CI) system is proposed and tested for modeling the classic 1D dam-break flow problem. The reason to seek for a new solution lies in the shortcomings of the existing analytical and numerical models. This includes the difficulty of using the exact solutions and the unwanted fluctuations, which arise in the numerical results. In this research, the application of the radial-basis-function (RBF) and multi-layer-perceptron (MLP) systems is detailed for the solution of twenty-nine dam-break scenarios. The models are developed using seven variables, i.e. the length of the channel, the depths of the up-and downstream sections, time, and distance as the inputs. Moreover, the depths and velocities of each computational node in the flow domain are considered as the model outputs. The models are validated against the analytical, and Lax-Wendroff and MacCormack FDM schemes. The findings indicate that the employed CI models are able to replicate the overall shape of the shock- and rarefaction-waves. Furthermore, the MLP system outperforms RBF and the tested numerical schemes. A new monolithic equation is proposed based on the best fitting model, which can be used as an efficient alternative to the existing piecewise analytic equations.

  19. INTERVENTIONS IN HUMAN RESOURCE TRAINING FOR COMPETENCIES WITHIN THE INTELLIGENT ORGANIZATIONS APPROACH

    Directory of Open Access Journals (Sweden)

    César A. Valecillos

    2013-11-01

    Full Text Available This article describes the results of a study on interventions for human talent training programs for competency within the Intelligent Organizations focus. The theoretical foundation is supported by Organizational Development and approaches from Senge (1994 , Lewin ( 1946 , Leboyer (2000 and Obeso (2003 . The methodology is embedded in the qualitative - interpretive paradigm and action research. Results showed programs focused on Senge's learning disciplines to to promote change and competence skills that help staff to cope with the challenges and opportunities facing modern business towards organizational intelligence.

  20. A survey on computational intelligence approaches for predictive modeling in prostate cancer

    OpenAIRE

    Cosma, G; Brown, D; Archer, M; Khan, M; Pockley, AG

    2017-01-01

    Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex forconventional statistical techniques to process quickly and eciently. These advanced approaches are based on mathematical models that have been especially developed for dealing with the uncertainty an...

  1. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

    2011-02-15

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  2. Artificial intelligence and tutoring systems computational and cognitive approaches to the communication of knowledge

    CERN Document Server

    Wenger, Etienne

    2014-01-01

    Artificial Intelligence and Tutoring Systems: Computational and Cognitive Approaches to the Communication of Knowledge focuses on the cognitive approaches, methodologies, principles, and concepts involved in the communication of knowledge. The publication first elaborates on knowledge communication systems, basic issues, and tutorial dialogues. Concerns cover natural reasoning and tutorial dialogues, shift from local strategies to multiple mental models, domain knowledge, pedagogical knowledge, implicit versus explicit encoding of knowledge, knowledge communication, and practical and theoretic

  3. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

    2011-01-01

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  4. An 'intelligent' approach to radioimmunoassay sample counting employing a microprocessor-controlled sample counter

    International Nuclear Information System (INIS)

    Ekins, R.P.; Sufi, S.; Malan, P.G.

    1978-01-01

    The enormous impact on medical science in the last two decades of microanalytical techniques employing radioisotopic labels has, in turn, generated a large demand for automatic radioisotopic sample counters. Such instruments frequently comprise the most important item of capital equipment required in the use of radioimmunoassay and related techniques and often form a principle bottleneck in the flow of samples through a busy laboratory. It is therefore imperative that such instruments should be used 'intelligently' and in an optimal fashion to avoid both the very large capital expenditure involved in the unnecessary proliferation of instruments and the time delays arising from their sub-optimal use. Most of the current generation of radioactive sample counters nevertheless rely on primitive control mechanisms based on a simplistic statistical theory of radioactive sample counting which preclude their efficient and rational use. The fundamental principle upon which this approach is based is that it is useless to continue counting a radioactive sample for a time longer than that required to yield a significant increase in precision of the measurement. Thus, since substantial experimental errors occur during sample preparation, these errors should be assessed and must be related to the counting errors for that sample. The objective of the paper is to demonstrate that the combination of a realistic statistical assessment of radioactive sample measurement, together with the more sophisticated control mechanisms that modern microprocessor technology make possible, may often enable savings in counter usage of the order of 5- to 10-fold to be made. (author)

  5. An Intelligent Approach to Strengthening of the Rural Electrical Power Supply Using Renewable Energy Resources

    Science.gov (United States)

    Robert, F. C.; Sisodia, G. S.; Gopalan, S.

    2017-08-01

    The healthy growth of economy lies in the balance between rural and urban development. Several developing countries have achieved a successful growth of urban areas, yet rural infrastructure has been neglected until recently. The rural electrical grids are weak with heavy losses and low capacity. Renewable energy represents an efficient way to generate electricity locally. However, the renewable energy generation may be limited by the low grid capacity. The current solutions focus on grid reinforcement only. This article presents a model for improving renewable energy integration in rural grids with the intelligent combination of three strategies: 1) grid reinforcement, 2) use of storage and 3) renewable energy curtailments. Such approach provides a solution to integrate a maximum of renewable energy generation on low capacity grids while minimising project cost and increasing the percentage of utilisation of assets. The test cases show that a grid connection agreement and a main inverter sized at 60 kW (resp. 80 kW) can accommodate a 100 kWp solar park (resp. 100 kW wind turbine) with minimal storage.

  6. HYBRID HUMAN-ARTIFICIAL INTELLIGENCE APPROACH FOR PAVEMENT DISTRESS ASSESSMENT (PICUCHA

    Directory of Open Access Journals (Sweden)

    Reus Salini

    2017-07-01

    Full Text Available The pavement surface condition assessment is a critical component for a proper pavement management system as well as for pavement rehabilitation design. A number of devices were developed to automatically record surface distresses in a continuous survey mode, but the software required for automatic distress identification remains a big challenge. In this study, a new method named PICture Unsupervised Classification with Human Analysis (PICUCHA is proposed to circumvent many of the limitations of existing approaches, based on a combination of human and artificial intelligence. It was designed from scratch to be capable to identify sealed and unsealed cracks, potholes, patches, different types of pavements and others. The self-learning algorithms do not use any distresses predefinition and can process images taken by cameras with different brands, technologies and resolution. This study describes some key aspects of the new method and provides examples in which PICUCHA was tested in real conditions showing accuracy up to 96.9% in image pattern detection and classification.

  7. An Intelligent Information Retrieval Approach Based on Two Degrees of Uncertainty Fuzzy Ontology

    Directory of Open Access Journals (Sweden)

    Maryam Hourali

    2011-01-01

    Full Text Available In spite of the voluminous studies in the field of intelligent retrieval systems, effective retrieving of information has been remained an important unsolved problem. Implementations of different conceptual knowledge in the information retrieval process such as ontology have been considered as a solution to enhance the quality of results. Furthermore, the conceptual formalism supported by typical ontology may not be sufficient to represent uncertainty information due to the lack of clear-cut boundaries between concepts of the domains. To tackle this type of problems, one possible solution is to insert fuzzy logic into ontology construction process. In this article, a novel approach for fuzzy ontology generation with two uncertainty degrees is proposed. Hence, by implementing linguistic variables, uncertainty level in domain's concepts (Software Maintenance Engineering (SME domain has been modeled, and ontology relations have been modeled by fuzzy theory consequently. Then, we combined these uncertain models and proposed a new ontology with two degrees of uncertainty both in concept expression and relation expression. The generated fuzzy ontology was implemented for expansion of initial user's queries in SME domain. Experimental results showed that the proposed model has better overall retrieval performance comparing to keyword-based or crisp ontology-based retrieval systems.

  8. 'Intelligent' approach to radioimmunoassay sample counting employing a microprocessor controlled sample counter

    International Nuclear Information System (INIS)

    Ekins, R.P.; Sufi, S.; Malan, P.G.

    1977-01-01

    The enormous impact on medical science in the last two decades of microanalytical techniques employing radioisotopic labels has, in turn, generated a large demand for automatic radioisotopic sample counters. Such instruments frequently comprise the most important item of capital equipment required in the use of radioimmunoassay and related techniques and often form a principle bottleneck in the flow of samples through a busy laboratory. It is therefore particularly imperitive that such instruments should be used 'intelligently' and in an optimal fashion to avoid both the very large capital expenditure involved in the unnecessary proliferation of instruments and the time delays arising from their sub-optimal use. The majority of the current generation of radioactive sample counters nevertheless rely on primitive control mechanisms based on a simplistic statistical theory of radioactive sample counting which preclude their efficient and rational use. The fundamental principle upon which this approach is based is that it is useless to continue counting a radioactive sample for a time longer than that required to yield a significant increase in precision of the measurement. Thus, since substantial experimental errors occur during sample preparation, these errors should be assessed and must be releted to the counting errors for that sample. It is the objective of this presentation to demonstrate that the combination of a realistic statistical assessment of radioactive sample measurement, together with the more sophisticated control mechanisms that modern microprocessor technology make possible, may often enable savings in counter usage of the order of 5-10 fold to be made. (orig.) [de

  9. On Combining Language Models: Oracle Approach

    National Research Council Canada - National Science Library

    Hacioglu, Kadri; Ward, Wayne

    2001-01-01

    In this paper, we address the of combining several language models (LMs). We find that simple interpolation methods, like log-linear and linear interpolation, improve the performance but fall short of the performance of an oracle...

  10. Wound healing: time to look for intelligent, 'natural' immunological approaches?

    Science.gov (United States)

    Garraud, Olivier; Hozzein, Wael N; Badr, Gamal

    2017-06-21

    There is now good evidence that cytokines and growth factors are key factors in tissue repair and often exert anti-infective activities. However, engineering such factors for global use, even in the most remote places, is not realistic. Instead, we propose to examine how such factors work and to evaluate the reparative tools generously provided by 'nature.' We used two approaches to address these objectives. The first approach was to reappraise the internal capacity of the factors contributing the most to healing in the body, i.e., blood platelets. The second was to revisit natural agents such as whey proteins, (honey) bee venom and propolis. The platelet approach elucidates the inflammation spectrum from physiology to pathology, whereas milk and honey derivatives accelerate diabetic wound healing. Thus, this review aims at offering a fresh view of how wound healing can be addressed by natural means.

  11. Intelligent assembly time analysis, using a digital knowledge based approach

    NARCIS (Netherlands)

    Jin, Y.; Curran, R.; Butterfield, J.; Burke, R.; Welch, B.

    2009-01-01

    The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for

  12. An Intelligent Systems Approach to Automated Object Recognition: A Preliminary Study

    Science.gov (United States)

    Maddox, Brian G.; Swadley, Casey L.

    2002-01-01

    Attempts at fully automated object recognition systems have met with varying levels of success over the years. However, none of the systems have achieved high enough accuracy rates to be run unattended. One of the reasons for this may be that they are designed from the computer's point of view and rely mainly on image-processing methods. A better solution to this problem may be to make use of modern advances in computational intelligence and distributed processing to try to mimic how the human brain is thought to recognize objects. As humans combine cognitive processes with detection techniques, such a system would combine traditional image-processing techniques with computer-based intelligence to determine the identity of various objects in a scene.

  13. Myth of the Master Detective: Reliability of Interpretations for Kaufman's "Intelligent Testing" Approach to the WISC-III.

    Science.gov (United States)

    Macmann, Gregg M.; Barnett, David W.

    1997-01-01

    Used computer simulation to examine the reliability of interpretations for Kaufman's "intelligent testing" approach to the Wechsler Intelligence Scale for Children (3rd ed.) (WISC-III). Findings indicate that factor index-score differences and other measures could not be interpreted with confidence. Argues that limitations of IQ testing…

  14. 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…

  15. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  16. Improving content marketing processes with the approaches by artificial intelligence

    OpenAIRE

    Kose, Utku; Sert, Selcuk

    2017-01-01

    Content marketing is todays one of the most remarkable approaches in the context of marketing processes of companies. Value of this kind of marketing has improved in time, thanks to the latest developments regarding to computer and communication technologies. Nowadays, especially social media based platforms have a great importance on enabling companies to design multimedia oriented, interactive content. But on the other hand, there is still something more to do for improved content marketing...

  17. Intelligent Torque Vectoring Approach for Electric Vehicles with Per-Wheel Motors

    Directory of Open Access Journals (Sweden)

    Alberto Parra

    2018-01-01

    Full Text Available Transport electrification is currently a priority for authorities, manufacturers, and research centers around the world. The development of electric vehicles and the improvement of their functionalities are key elements in this strategy. As a result, there is a need for further research in emission reduction, efficiency improvement, or dynamic handling approaches. In order to achieve these objectives, the development of suitable Advanced Driver-Assistance Systems (ADAS is required. Although traditional control techniques have been widely used for ADAS implementation, the complexity of electric multimotor powertrains makes intelligent control approaches appropriate for these cases. In this work, a novel intelligent Torque Vectoring (TV system, composed of a neuro-fuzzy vertical tire forces estimator and a fuzzy yaw moment controller, is proposed, which allows enhancing the dynamic behaviour of electric multimotor vehicles. The proposed approach is compared with traditional strategies using the high fidelity vehicle dynamics simulator Dynacar. Results show that the proposed intelligent Torque Vectoring system is able to increase the efficiency of the vehicle by 10%, thanks to the optimal torque distribution and the use of a neuro-fuzzy vertical tire forces estimator which provides 3 times more accurate estimations than analytical approaches.

  18. POSSIBILITIES FOR INNOVATIVE SCIENTIFIC APPROACH: INFORMATION VISUALIZATION AND EXPERIMENT IN INTELLIGENCE RESEARCH

    Directory of Open Access Journals (Sweden)

    Dejan Ulcej

    2013-09-01

    Full Text Available In addition to universal social changes, the information revolution also brought a lot of innovation to the workings of intelligence services, which are traditionally the part of the national security system that is conducting data analyses and for which information is the primary product. If in the past the main problem and challenge has been the timely acquisition of data, today most agencies are faced with an entirely different problem - information overload. This problem is being tackled by technical as well as systemic measures that combine various types of intelligence work. However, there are still unanswered questions regarding the applicability of intelligence products for decision makers. Here we have to point out information visualization as the subject of an interdisciplinary scientific research that definitely shows a lot of potential in the context of the defense science as well. This article points out three key requirements that allow the application of information visualization to defense research: (1 the concept of the intelligence cycle can be used as a good basis for the information that is subject to visualization; (2 the quality of decision-making support information depends on proper visualization; (3 the first two requirements offer a stable theoretical and empirical basis for the introduction of innovative scientific methods in the field of defense science, such as experiments.

  19. Prediction of biochar yield from cattle manure pyrolysis via least squares support vector machine intelligent approach.

    Science.gov (United States)

    Cao, Hongliang; Xin, Ya; Yuan, Qiaoxia

    2016-02-01

    To predict conveniently the biochar yield from cattle manure pyrolysis, intelligent modeling approach was introduced in this research. A traditional artificial neural networks (ANN) model and a novel least squares support vector machine (LS-SVM) model were developed. For the identification and prediction evaluation of the models, a data set with 33 experimental data was used, which were obtained using a laboratory-scale fixed bed reaction system. The results demonstrated that the intelligent modeling approach is greatly convenient and effective for the prediction of the biochar yield. In particular, the novel LS-SVM model has a more satisfying predicting performance and its robustness is better than the traditional ANN model. The introduction and application of the LS-SVM modeling method gives a successful example, which is a good reference for the modeling study of cattle manure pyrolysis process, even other similar processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. 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.

  1. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2011-10-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and costsensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method;candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal parameters

  2. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2012-02-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and cost-sensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method; candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal

  3. INTERVENTIONS IN HUMAN RESOURCE TRAINING FOR COMPETENCIES WITHIN THE INTELLIGENT ORGANIZATIONS APPROACH

    OpenAIRE

    César A. Valecillos

    2013-01-01

    This article describes the results of a study on interventions for human talent training programs for competency within the Intelligent Organizations focus. The theoretical foundation is supported by Organizational Development and approaches from Senge (1994 ) , Lewin ( 1946 ) , Leboyer (2000) and Obeso (2003 ) . The methodology is embedded in the qualitative - interpretive paradigm and action research. Results showed programs focused on Senge's learning disciplines to to promote change and c...

  4. Automatic classification of hyperactive children: comparing multiple artificial intelligence approaches.

    Science.gov (United States)

    Delavarian, Mona; Towhidkhah, Farzad; Gharibzadeh, Shahriar; Dibajnia, Parvin

    2011-07-12

    Automatic classification of different behavioral disorders with many similarities (e.g. in symptoms) by using an automated approach will help psychiatrists to concentrate on correct disorder and its treatment as soon as possible, to avoid wasting time on diagnosis, and to increase the accuracy of diagnosis. In this study, we tried to differentiate and classify (diagnose) 306 children with many similar symptoms and different behavioral disorders such as ADHD, depression, anxiety, comorbid depression and anxiety and conduct disorder with high accuracy. Classification was based on the symptoms and their severity. With examining 16 different available classifiers, by using "Prtools", we have proposed nearest mean classifier as the most accurate classifier with 96.92% accuracy in this research. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  5. A new distributed systems scheduling algorithm: a swarm intelligence approach

    Science.gov (United States)

    Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi

    2011-12-01

    The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.

  6. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    Science.gov (United States)

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

  7. The dynamic interplay among EFL learners’ ambiguity tolerance, adaptability, cultural intelligence, learning approach, and language achievement

    Directory of Open Access Journals (Sweden)

    Shadi Alahdadi

    2017-01-01

    Full Text Available A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and language achievement as manifestations of the above competencies within a single model. The participants comprised one hundred eighty BA and MA Iranian university students studying English language teaching and translation. The instruments used in this study consisted of the translated versions of four questionnaires: second language tolerance of ambiguity scale, adaptability taken from emotional intelligence inventory, cultural intelligence (CQ inventory, and the revised study process questionnaire measuring surface and deep learning. The results estimated via structural equation modeling (SEM revealed that the proposed model containing the variables under study had a good fit with the data. It was found that all the variables except adaptability directly influenced language achievement with deep approach having the highest impact and ambiguity tolerance having the lowest influence. In addition, ambiguity tolerance was a positive and significant predictor of deep approach. CQ was found to be under the influence of both ambiguity tolerance and adaptability. The findings were discussed in the light of the yielded results.

  8. Intelligent fuzzy approach for fast fractal image compression

    Science.gov (United States)

    Nodehi, Ali; Sulong, Ghazali; Al-Rodhaan, Mznah; Al-Dhelaan, Abdullah; Rehman, Amjad; Saba, Tanzila

    2014-12-01

    Fractal image compression (FIC) is recognized as a NP-hard problem, and it suffers from a high number of mean square error (MSE) computations. In this paper, a two-phase algorithm was proposed to reduce the MSE computation of FIC. In the first phase, based on edge property, range and domains are arranged. In the second one, imperialist competitive algorithm (ICA) is used according to the classified blocks. For maintaining the quality of the retrieved image and accelerating algorithm operation, we divided the solutions into two groups: developed countries and undeveloped countries. Simulations were carried out to evaluate the performance of the developed approach. Promising results thus achieved exhibit performance better than genetic algorithm (GA)-based and Full-search algorithms in terms of decreasing the number of MSE computations. The number of MSE computations was reduced by the proposed algorithm for 463 times faster compared to the Full-search algorithm, although the retrieved image quality did not have a considerable change.

  9. A theoretical approach to artificial intelligence systems in medicine.

    Science.gov (United States)

    Spyropoulos, B; Papagounos, G

    1995-10-01

    The various theoretical models of disease, the nosology which is accepted by the medical community and the prevalent logic of diagnosis determine both the medical approach as well as the development of the relevant technology including the structure and function of the A.I. systems involved. A.I. systems in medicine, in addition to the specific parameters which enable them to reach a diagnostic and/or therapeutic proposal, entail implicitly theoretical assumptions and socio-cultural attitudes which prejudice the orientation and the final outcome of the procedure. The various models -causal, probabilistic, case-based etc. -are critically examined and their ethical and methodological limitations are brought to light. The lack of a self-consistent theoretical framework in medicine, the multi-faceted character of the human organism as well as the non-explicit nature of the theoretical assumptions involved in A.I. systems restrict them to the role of decision supporting "instruments" rather than regarding them as decision making "devices". This supporting role and, especially, the important function which A.I. systems should have in the structure, the methods and the content of medical education underscore the need of further research in the theoretical aspects and the actual development of such systems.

  10. Intelligent data analysis: the best approach for chronic heart failure (CHF) follow up management.

    Science.gov (United States)

    Mohammadzadeh, Niloofar; Safdari, Reza; Baraani, Alireza; Mohammadzadeh, Farshid

    2014-08-01

    Intelligent data analysis has ability to prepare and present complex relations between symptoms and diseases, medical and treatment consequences and definitely has significant role in improving follow-up management of chronic heart failure (CHF) patients, increasing speed ​​and accuracy in diagnosis and treatments; reducing costs, designing and implementation of clinical guidelines. The aim of this article is to describe intelligent data analysis methods in order to improve patient monitoring in follow and treatment of chronic heart failure patients as the best approach for CHF follow up management. Minimum data set (MDS) requirements for monitoring and follow up of CHF patient designed in checklist with six main parts. All CHF patients that discharged in 2013 from Tehran heart center have been selected. The MDS for monitoring CHF patient status were collected during 5 months in three different times of follow up. Gathered data was imported in RAPIDMINER 5 software. Modeling was based on decision trees methods such as C4.5, CHAID, ID3 and k-Nearest Neighbors algorithm (K-NN) with k=1. Final analysis was based on voting method. Decision trees and K-NN evaluate according to Cross-Validation. Creating and using standard terminologies and databases consistent with these terminologies help to meet the challenges related to data collection from various places and data application in intelligent data analysis. It should be noted that intelligent analysis of health data and intelligent system can never replace cardiologists. It can only act as a helpful tool for the cardiologist's decisions making.

  11. SOA enabled ELTA: approach in designing business intelligence solutions in Era of Big Data

    Directory of Open Access Journals (Sweden)

    Viktor Dmitriyev

    2015-01-01

    Full Text Available The current work presents a new approach for designing business intelligence solutions. In the Era of Big Data, former and robust analytical concepts and utilities need to adapt themselves to the changed market circumstances. The main focus of this work is to address the acceleration of building process of a “data-centric” Business Intelligence (BI solution besides preparing BI solutions for Big Data utilization. This research addresses the following goals: reducing the time spent during business intelligence solution’s design phase; achieving flexibility of BI solution by adding new data sources; and preparing BI solution for utilizing Big Data concepts. This research proposes an extension of the existing Extract, Load and Transform (ELT approach to the new one Extract, Load, Transform and Analyze (ELTA supported by service-orientation concept. Additionally, the proposed model incorporates Service-Oriented Architecture concept as a mediator for the transformation phase. On one side, such incorporation brings flexibility to the BI solution and on the other side; it reduces the complexity of the whole system by moving some responsibilities to external authorities.

  12. The Innovative Approaches to Packaging – Comparison Analysis of Intelligent and Active Packaging Perceptions in Slovakia

    Directory of Open Access Journals (Sweden)

    Loucanova Erika

    2017-06-01

    Full Text Available Packaging has always served a practical function - to hold goods together and protect it when moving toward the customer through distribution channel. Today packaging is also a container for promoting the product and making it easier and safer to use. The sheer importance of packaging functions is still growing and consequently the interest of the company is to access to the packaging more innovative and creative. The paper deals with the innovative approaches to packaging resulting in the creation of packaging with interactive active features in the form of active and intelligent packaging. Using comparative analysis, we monitored the perception of the active packaging functions in comparison to intelligent packaging function among different age categories. We identified the age categories which are most interested in these functions.

  13. A Dynamic Intelligent Decision Approach to Dependency Modeling of Project Tasks in Complex Engineering System Optimization

    Directory of Open Access Journals (Sweden)

    Tinggui Chen

    2013-01-01

    Full Text Available Complex engineering system optimization usually involves multiple projects or tasks. On the one hand, dependency modeling among projects or tasks highlights structures in systems and their environments which can help to understand the implications of connectivity on different aspects of system performance and also assist in designing, optimizing, and maintaining complex systems. On the other hand, multiple projects or tasks are either happening at the same time or scheduled into a sequence in order to use common resources. In this paper, we propose a dynamic intelligent decision approach to dependency modeling of project tasks in complex engineering system optimization. The approach takes this decision process as a two-stage decision-making problem. In the first stage, a task clustering approach based on modularization is proposed so as to find out a suitable decomposition scheme for a large-scale project. In the second stage, according to the decomposition result, a discrete artificial bee colony (ABC algorithm inspired by the intelligent foraging behavior of honeybees is developed for the resource constrained multiproject scheduling problem. Finally, a certain case from an engineering design of a chemical processing system is utilized to help to understand the proposed approach.

  14. Artificial Intelligence and Semantics through the Prism of Structural, Post-Structural and Transcendental Approaches.

    Science.gov (United States)

    Gasparyan, Diana

    2016-12-01

    There is a problem associated with contemporary studies of philosophy of mind, which focuses on the identification and convergence of human and machine intelligence. This is the problem of machine emulation of sense. In the present study, analysis of this problem is carried out based on concepts from structural and post-structural approaches that have been almost entirely overlooked by contemporary philosophy of mind. If we refer to the basic definitions of "sign" and "meaning" found in structuralism and post-structuralism, we see a fundamental difference between the capabilities of a machine and the human brain engaged in the processing of a sign. This research will exemplify and provide additional evidence to support distinctions between syntactic and semantic aspects of intelligence, an issue widely discussed by adepts of contemporary philosophy of mind. The research will demonstrate that some aspect of a number of ideas proposed in relation to semantics and semiosis in structuralism and post-structuralism are similar to those we find in contemporary analytical studies related to the theory and philosophy of artificial intelligence. The concluding part of the paper offers an interpretation of the problem of formalization of sense, connected to its metaphysical (transcendental) properties.

  15. Telerobotic Surgery: An Intelligent Systems Approach to Mitigate the Adverse Effects of Communication Delay. Chapter 4

    Science.gov (United States)

    Cardullo, Frank M.; Lewis, Harold W., III; Panfilov, Peter B.

    2007-01-01

    An extremely innovative approach has been presented, which is to have the surgeon operate through a simulator running in real-time enhanced with an intelligent controller component to enhance the safety and efficiency of a remotely conducted operation. The use of a simulator enables the surgeon to operate in a virtual environment free from the impediments of telecommunication delay. The simulator functions as a predictor and periodically the simulator state is corrected with truth data. Three major research areas must be explored in order to ensure achieving the objectives. They are: simulator as predictor, image processing, and intelligent control. Each is equally necessary for success of the project and each of these involves a significant intelligent component in it. These are diverse, interdisciplinary areas of investigation, thereby requiring a highly coordinated effort by all the members of our team, to ensure an integrated system. The following is a brief discussion of those areas. Simulator as a predictor: The delays encountered in remote robotic surgery will be greater than any encountered in human-machine systems analysis, with the possible exception of remote operations in space. Therefore, novel compensation techniques will be developed. Included will be the development of the real-time simulator, which is at the heart of our approach. The simulator will present real-time, stereoscopic images and artificial haptic stimuli to the surgeon. Image processing: Because of the delay and the possibility of insufficient bandwidth a high level of novel image processing is necessary. This image processing will include several innovative aspects, including image interpretation, video to graphical conversion, texture extraction, geometric processing, image compression and image generation at the surgeon station. Intelligent control: Since the approach we propose is in a sense predictor based, albeit a very sophisticated predictor, a controller, which not only

  16. The unknown-unknowns: Revealing the hidden insights in massive biomedical data using combined artificial intelligence and knowledge networks

    Directory of Open Access Journals (Sweden)

    Chris Yoo

    2017-12-01

    Full Text Available Genomic data is estimated to be doubling every seven months with over 2 trillion bases from whole genome sequence studies deposited in Genbank in just the last 15 years alone. Recent advances in compute and storage have enabled the use of artificial intelligence techniques in areas such as feature recognition in digital pathology and chemical synthesis for drug development. To apply A.I. productively to multidimensional data such as cellular processes and their dysregulation, the data must be transformed into a structured format, using prior knowledge to create contextual relationships and hierarchies upon which computational analysis can be performed. Here we present the organization of complex data into hypergraphs that facilitate the application of A.I. We provide an example use case of a hypergraph containing hundreds of biological data values and the results of several classes of A.I. algorithms applied in a popular compute cloud. While multiple, biologically insightful correlations between disease states, behavior, and molecular features were identified, the insights of scientific import were revealed only when exploration of the data included visualization of subgraphs of represented knowledge. The results suggest that while machine learning can identify known correlations and suggest testable ones, the greater probability of discovering unexpected relationships between seemingly independent variables (unknown-unknowns requires a context-aware system – hypergraphs that impart biological meaning in nodes and edges. We discuss the implications of a combined hypergraph-A.I. analysis approach to multidimensional data and the pre-processing requirements for such a system.

  17. Hypnotherapy: A Combined Approach Using Psychotherapy and Behavior Modification.

    Science.gov (United States)

    Goldberg, Bruce

    1987-01-01

    Discusses use of hypnosis in traditional psychoanalysis, compares use of hypnosis in behavior modification therapy versus psychoanalysis, and presents a hypno-behavioral model which combines both approaches using hypnosis as the medium. (Author/NB)

  18. Freedom and privacy in ambient intelligence

    NARCIS (Netherlands)

    Brey, Philip A.E.

    2006-01-01

    This paper analyzes ethical aspects of the new paradigm of Ambient Intelligence, which is a combination of Ubiquitous Computing and Intelligent User Interfaces (IUI’s). After an introduction to the approach, two key ethical dimensions will be analyzed: freedom and privacy. It is argued that Ambient

  19. A constraint-based approach to intelligent support of nuclear reactor design

    International Nuclear Information System (INIS)

    Furuta, Kazuo

    1993-01-01

    Constraint is a powerful representation to formulate and solve problems in design; a constraint-based approach to intelligent support of nuclear reactor design is proposed. We first discuss the features of the approach, and then present the architecture of a nuclear reactor design support system under development. In this design support system, the knowledge base contains constraints useful to structure the design space as object class definitions, and several types of constraint resolvers are provided as design support subsystems. The adopted method of constraint resolution are explained in detail. The usefulness of the approach is demonstrated using two design problems: Design window search and multiobjective optimization in nuclear reactor design. (orig./HP)

  20. 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.

  1. Worldwide Intelligent Systems: Approaches to Telecommunications and Network Management. Frontiers in Artificial Intelligence and Applications, Volume 24.

    Science.gov (United States)

    Liebowitz, Jay, Ed.; Prerau, David S., Ed.

    This is an international collection of 12 papers addressing artificial intelligence (AI) and knowledge technology applications in telecommunications and network management. It covers the latest and emerging AI technologies as applied to the telecommunications field. The papers are: "The Potential for Knowledge Technology in…

  2. Rectal duplication cyst: a combined abdominal and endoanal operative approach.

    Science.gov (United States)

    Rees, Clare M; Woodward, Mark; Grier, David; Cusick, Eleri

    2007-04-01

    Rectal duplication cysts are rare, comprising duplications. Early excision is the treatment of choice and a number of surgical approaches have been described. We present a 3-week-old infant with a 3 cm cyst that was excised using a previously unreported combined abdominal and endoanal approach.

  3. Combined Interhemispheric and Transsylvian Approach for Resection of Craniopharyngioma.

    Science.gov (United States)

    Inoue, Tomohiro; Ono, Hideaki; Tamura, Akira; Saito, Isamu

    2018-04-01

    We present a 37-year-old male case of cystic suprasellar huge craniopharyngioma, who presented with significant memory disturbance due to obstructive hydrocephalus. Combined interhemispheric and pterional approach was chosen to resect huge suprasellar tumor. Interhemispheric trans-lamina terminalis approach was quite effective to resect third ventricular tumor, while pterional approach was useful to dissect tumor out of basilar perforators and stalk. The link to the video can be found at: https://youtu.be/BoYIPa96kdo .

  4. A Real-Time Temperature Data Transmission Approach for Intelligent Cooling Control of Mass Concrete

    Directory of Open Access Journals (Sweden)

    Peng Lin

    2014-01-01

    Full Text Available The primary aim of the study presented in this paper is to propose a real-time temperature data transmission approach for intelligent cooling control of mass concrete. A mathematical description of a digital temperature control model is introduced in detail. Based on pipe mounted and electrically linked temperature sensors, together with postdata handling hardware and software, a stable, real-time, highly effective temperature data transmission solution technique is developed and utilized within the intelligent mass concrete cooling control system. Once the user has issued the relevant command, the proposed programmable logic controllers (PLC code performs all necessary steps without further interaction. The code can control the hardware, obtain, read, and perform calculations, and display the data accurately. Hardening concrete is an aggregate of complex physicochemical processes including the liberation of heat. The proposed control system prevented unwanted structural change within the massive concrete blocks caused by these exothermic processes based on an application case study analysis. In conclusion, the proposed temperature data transmission approach has proved very useful for the temperature monitoring of a high arch dam and is able to control thermal stresses in mass concrete for similar projects involving mass concrete.

  5. Games and machine learning: a powerful combination in an artificial intelligence course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-03-01

    Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

  6. Developing a fluid intelligence scale through a combination of Rasch modeling and cognitive psychology.

    Science.gov (United States)

    Primi, Ricardo

    2014-09-01

    Ability testing has been criticized because understanding of the construct being assessed is incomplete and because the testing has not yet been satisfactorily improved in accordance with new knowledge from cognitive psychology. This article contributes to the solution of this problem through the application of item response theory and Susan Embretson's cognitive design system for test development in the development of a fluid intelligence scale. This study is based on findings from cognitive psychology; instead of focusing on the development of a test, it focuses on the definition of a variable for the creation of a criterion-referenced measure for fluid intelligence. A geometric matrix item bank with 26 items was analyzed with data from 2,797 undergraduate students. The main result was a criterion-referenced scale that was based on information from item features that were linked to cognitive components, such as storage capacity, goal management, and abstraction; this information was used to create the descriptions of selected levels of a fluid intelligence scale. The scale proposed that the levels of fluid intelligence range from the ability to solve problems containing a limited number of bits of information with obvious relationships through the ability to solve problems that involve abstract relationships under conditions that are confounded with an information overload and distraction by mixed noise. This scale can be employed in future research to provide interpretations for the measurements of the cognitive processes mastered and the types of difficulty experienced by examinees. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  7. Comparing Multiple Intelligences Approach with Traditional Teaching on Eight Grade Students' Achievement in and Attitudes toward Science

    Science.gov (United States)

    Kaya, Osman Nafiz; Dogan, Alev; Gokcek, Nur; Kilic, Ziya; Kilic, Esma

    2007-01-01

    The purpose of this study was to investigate the effects of multiple intelligences (MI) teaching approach on 8th Grade students' achievement in and attitudes toward science. This study used a pretest-posttest control group experimental design. While the experimental group (n=30) was taught a unit on acids and bases using MI teaching approach, the…

  8. Deep Learning-Based Noise Reduction Approach to Improve Speech Intelligibility for Cochlear Implant Recipients.

    Science.gov (United States)

    Lai, Ying-Hui; Tsao, Yu; Lu, Xugang; Chen, Fei; Su, Yu-Ting; Chen, Kuang-Chao; Chen, Yu-Hsuan; Chen, Li-Ching; Po-Hung Li, Lieber; Lee, Chin-Hui

    2018-01-20

    We investigate the clinical effectiveness of a novel deep learning-based noise reduction (NR) approach under noisy conditions with challenging noise types at low signal to noise ratio (SNR) levels for Mandarin-speaking cochlear implant (CI) recipients. The deep learning-based NR approach used in this study consists of two modules: noise classifier (NC) and deep denoising autoencoder (DDAE), thus termed (NC + DDAE). In a series of comprehensive experiments, we conduct qualitative and quantitative analyses on the NC module and the overall NC + DDAE approach. Moreover, we evaluate the speech recognition performance of the NC + DDAE NR and classical single-microphone NR approaches for Mandarin-speaking CI recipients under different noisy conditions. The testing set contains Mandarin sentences corrupted by two types of maskers, two-talker babble noise, and a construction jackhammer noise, at 0 and 5 dB SNR levels. Two conventional NR techniques and the proposed deep learning-based approach are used to process the noisy utterances. We qualitatively compare the NR approaches by the amplitude envelope and spectrogram plots of the processed utterances. Quantitative objective measures include (1) normalized covariance measure to test the intelligibility of the utterances processed by each of the NR approaches; and (2) speech recognition tests conducted by nine Mandarin-speaking CI recipients. These nine CI recipients use their own clinical speech processors during testing. The experimental results of objective evaluation and listening test indicate that under challenging listening conditions, the proposed NC + DDAE NR approach yields higher intelligibility scores than the two compared classical NR techniques, under both matched and mismatched training-testing conditions. When compared to the two well-known conventional NR techniques under challenging listening condition, the proposed NC + DDAE NR approach has superior noise suppression capabilities and gives less distortion

  9. An integrated approach for integrated intelligent instrumentation and control system (I3CS)

    International Nuclear Information System (INIS)

    Jung, C.H.; Kim, J.T.; Kwon, K.C.

    1997-01-01

    Nuclear power plants to guarantee the safety of public should be designed to reduce the operator intervention resulting in operating human errors, identify the process states in transients, and aid to make a decision of their tasks and guide operator actions. For the sake of this purpose, MMIS(MAN-Machine Interface System) in NPPs should be the integrated top-down approach tightly focused on the function-based task analysis including an advanced digital technology, an operator support function, and so on. The advanced I and C research team in KAERI has embarked on developing an Integrated Intelligent Instrumentation and Control System (I 3 CS) for Korea's next generation nuclear power plants. I 3 CS bases the integrated top-down approach on the function-based task analysis, modern digital technology, standardization and simplification, availability and reliability, and protection of investment. (author). 4 refs, 6 figs

  10. An integrated approach for integrated intelligent instrumentation and control system (I{sup 3}CS)

    Energy Technology Data Exchange (ETDEWEB)

    Jung, C H; Kim, J T; Kwon, K C [Korea Atomic Energy Research Inst., Yusong, Taejon (Korea, Republic of)

    1997-07-01

    Nuclear power plants to guarantee the safety of public should be designed to reduce the operator intervention resulting in operating human errors, identify the process states in transients, and aid to make a decision of their tasks and guide operator actions. For the sake of this purpose, MMIS(MAN-Machine Interface System) in NPPs should be the integrated top-down approach tightly focused on the function-based task analysis including an advanced digital technology, an operator support function, and so on. The advanced I and C research team in KAERI has embarked on developing an Integrated Intelligent Instrumentation and Control System (I{sup 3}CS) for Korea`s next generation nuclear power plants. I{sup 3}CS bases the integrated top-down approach on the function-based task analysis, modern digital technology, standardization and simplification, availability and reliability, and protection of investment. (author). 4 refs, 6 figs.

  11. State and Local Intelligence Fusion Centers: An Evaluative Approach in Modeling a State Fusion Center

    National Research Council Canada - National Science Library

    Forsyth, William A

    2005-01-01

    .... Effective terrorism prevention, however, requires information and intelligence fusion as a cooperative process at all levels of government so that the flow of intelligence can be managed to support...

  12. High Resolution Dsm and Classified Volumetric Generation: AN Operational Approach to the Improvement of Geospatial Intelligence

    Science.gov (United States)

    Boccardo, P.; Gentili, G.

    2011-09-01

    As mentioned by Bacastow and Bellafiore, Geospatial Intelligence (GEOINT) is a field of knowledge, a process, and a profession. As knowledge, it is information integrated in a coherent space-time context that supports descriptions, explanations, or forecasts of human activities with which decision makers take action. As a process, it is the means by which data and information are collected, manipulated, geospatially reasoned, and disseminated to decision-makers. The geospatial intelligence professional establishes the scope of activities, interdisciplinary associations, competencies, and standards in academe, government, and the private sectors. Taking into account the fact that GEOINT is crucial for broad organizations, BLOM Group, a leading International provider within acquisition, processing and modeling of geographic information and ITHACA, a non-profit organization devoted to products and services delivering to the UN System in the field of geomatics, set up and provided GEOINT data to the main Italian companies operating in the field of mobile phone networking. This data, extremely useful for telecom network planning, have derived and produced using a standardized and effective (from the production point of view) approach. In this paper, all the procedures used for the production are described and tested with the aim to investigate the suitability of the data and the procedures themselves to any others possible fields of application.

  13. Preliminary Findings from RULER Approach in Spanish Teachers' Emotional Intelligence and Work Engagement

    Science.gov (United States)

    Castillo-Gualda, Ruth; García, Valme; Pena, Mario; Galán, Arturo; Brackett, Marc A.

    2017-01-01

    Introduction: The goal of this study was to assess the effectiveness of a socio-emotional learning program, RULER, on enhancing both the emotional intelligence and work-related outcomes in Spanish teachers. Measures included: Ability emotional intelligence, assessed by the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) and work-related…

  14. Decay of Iconic Memory Traces Is Related to Psychometric Intelligence: A Fixed-Links Modeling Approach

    Science.gov (United States)

    Miller, Robert; Rammsayer, Thomas H.; Schweizer, Karl; Troche, Stefan J.

    2010-01-01

    Several memory processes have been examined regarding their relation to psychometric intelligence with the exception of sensory memory. This study examined the relation between decay of iconic memory traces, measured with a partial-report task, and psychometric intelligence, assessed with the Berlin Intelligence Structure test, in 111…

  15. SNMP-SI: A Network Management Tool Based on Slow Intelligence System Approach

    Science.gov (United States)

    Colace, Francesco; de Santo, Massimo; Ferrandino, Salvatore

    The last decade has witnessed an intense spread of computer networks that has been further accelerated with the introduction of wireless networks. Simultaneously with, this growth has increased significantly the problems of network management. Especially in small companies, where there is no provision of personnel assigned to these tasks, the management of such networks is often complex and malfunctions can have significant impacts on their businesses. A possible solution is the adoption of Simple Network Management Protocol. Simple Network Management Protocol (SNMP) is a standard protocol used to exchange network management information. It is part of the Transmission Control Protocol/Internet Protocol (TCP/IP) protocol suite. SNMP provides a tool for network administrators to manage network performance, find and solve network problems, and plan for network growth. SNMP has a big disadvantage: its simple design means that the information it deals with is neither detailed nor well organized enough to deal with the expanding modern networking requirements. Over the past years much efforts has been given to improve the lack of Simple Network Management Protocol and new frameworks has been developed: A promising approach involves the use of Ontology. This is the starting point of this paper where a novel approach to the network management based on the use of the Slow Intelligence System methodologies and Ontology based techniques is proposed. Slow Intelligence Systems is a general-purpose systems characterized by being able to improve performance over time through a process involving enumeration, propagation, adaptation, elimination and concentration. Therefore, the proposed approach aims to develop a system able to acquire, according to an SNMP standard, information from the various hosts that are in the managed networks and apply solutions in order to solve problems. To check the feasibility of this model first experimental results in a real scenario are showed.

  16. SIMON [Semi-Intelligent Mobile Observing Navigator] combines radiation hardness with computer power

    International Nuclear Information System (INIS)

    Weber, P.J.; Vanecek, C.W.

    1990-01-01

    SIMON - the Semi-Intelligent Mobile Observing Navigator - has been under development at the US Department of Energy's (DoE's) Savannah River Laboratory for four years. The robot's on-board intelligence units are designed to be radiation-resistant, making it able to function for extended periods within a remotely operated facility. In its current form, SIMON is being developed by the laboratory's Robotics Group for use in the site's production reactors, but it can be adapted for use in any nuclear facility, including commercial reactors. The challenge for Savannah River Laboratory engineers was to eliminate the need for human inspection of certain components. To do this, they designed a robot that could do three things for reactor operators: measure radiation; measure temperature; and provide televised views inside the reactor facility. To be useful, the robot has to be extremely mobile, and its components had to be able to survive months without maintenance in the radiation, temperature and humidity encountered in nuclear facilities. The robot also had to be cost-effective. (author)

  17. AN ARTIFICIAL INTELLIGENCE APPROACH FOR THE PREDICTION OF SURFACE ROUGHNESS IN CO2 LASER CUTTING

    Directory of Open Access Journals (Sweden)

    MILOŠ MADIĆ

    2012-12-01

    Full Text Available In laser cutting, the cut quality is of great importance. Multiple non-linear effects of process parameters and their interactions make very difficult to predict cut quality. In this paper, artificial intelligence (AI approach was applied to predict the surface roughness in CO2 laser cutting. To this aim, artificial neural network (ANN model of surface roughness was developed in terms of cutting speed, laser power and assist gas pressure. The experimental results obtained from Taguchi’s L25 orthogonal array were used to develop ANN model. The ANN mathematical model of surface roughness was expressed as explicit nonlinear function of the selected input parameters. Statistical results indicate that the ANN model can predict the surface roughness with good accuracy. It was showed that ANNs may be used as a good alternative in analyzing the effects of cutting parameters on the surface roughness.

  18. The Viewpoint Paradigm: a semiotic based approach for the intelligibility of a cooperative designing process

    Directory of Open Access Journals (Sweden)

    Pierre-Jean Charrel

    2002-11-01

    Full Text Available The concept of viewpoint is studied in the field of the modelling and the knowledge management concerned in the upstream phases of a designing process. The concept is approached by semiotics, i.e. in dealing with the requirements so that an actor gives sense to an object. This gives means to transform the intuitive concepts of viewpoint and relation between viewpoints into the Viewpoint Paradigm: the sense of an object is the integration of the viewpoints which exert on it. The elements of this paradigm are integrated in a general model, which defines two concepts formally: Viewpoint and Correlation of viewpoints. The Viewpoint Paradigm is then implemented in operational concerns which are related with the intelligibility of the designing process. Two models of viewpoint and correlation are proposed. They raise of viewpoints management such as one can identify them in the written documents of a project.

  19. Prediction of a service demand using combined forecasting approach

    Science.gov (United States)

    Zhou, Ling

    2017-08-01

    Forecasting facilitates cutting down operational and management costs while ensuring service level for a logistics service provider. Our case study here is to investigate how to forecast short-term logistic demand for a LTL carrier. Combined approach depends on several forecasting methods simultaneously, instead of a single method. It can offset the weakness of a forecasting method with the strength of another, which could improve the precision performance of prediction. Main issues of combined forecast modeling are how to select methods for combination, and how to find out weight coefficients among methods. The principles of method selection include that each method should apply to the problem of forecasting itself, also methods should differ in categorical feature as much as possible. Based on these principles, exponential smoothing, ARIMA and Neural Network are chosen to form the combined approach. Besides, least square technique is employed to settle the optimal weight coefficients among forecasting methods. Simulation results show the advantage of combined approach over the three single methods. The work done in the paper helps manager to select prediction method in practice.

  20. Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

    Directory of Open Access Journals (Sweden)

    Ahmed Hussein

    2018-01-01

    Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

  1. Computational intelligence approach for NOx emissions minimization in a coal-fired utility boiler

    International Nuclear Information System (INIS)

    Zhou Hao; Zheng Ligang; Cen Kefa

    2010-01-01

    The current work presented a computational intelligence approach used for minimizing NO x emissions in a 300 MW dual-furnaces coal-fired utility boiler. The fundamental idea behind this work included NO x emissions characteristics modeling and NO x emissions optimization. First, an objective function aiming at estimating NO x emissions characteristics from nineteen operating parameters of the studied boiler was represented by a support vector regression (SVR) model. Second, four levels of primary air velocities (PA) and six levels of secondary air velocities (SA) were regulated by using particle swarm optimization (PSO) so as to achieve low NO x emissions combustion. To reduce the time demanding, a more flexible stopping condition was used to improve the computational efficiency without the loss of the quality of the optimization results. The results showed that the proposed approach provided an effective way to reduce NO x emissions from 399.7 ppm to 269.3 ppm, which was much better than a genetic algorithm (GA) based method and was slightly better than an ant colony optimization (ACO) based approach reported in the earlier work. The main advantage of PSO was that the computational cost, typical of less than 25 s under a PC system, is much less than those required for ACO. This meant the proposed approach would be more applicable to online and real-time applications for NO x emissions minimization in actual power plant boilers.

  2. Creating Intelligent Computer Workstation of a Freight Officer in a Single Information Space of Railway Transport: Synergetic Approach

    Science.gov (United States)

    Malybaev, Saken K.; Malaybaev, Nurlan S.; Isina, Botakoz M.; Kenzhekeeva, Akbope R.; Khuangan, Nurbol

    2016-01-01

    The article presents the results of researches aimed at the creation of automated workplaces for railway transport specialists with the help of intelligent information systems. The analysis of tendencies of information technologies development in the transport network was conducted. It was determined that the most effective approach is to create…

  3. 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…

  4. The Comparison of Think Talk Write and Think Pair Share Model with Realistic Mathematics Education Approach Viewed from Mathematical-Logical Intelligence

    Directory of Open Access Journals (Sweden)

    Himmatul Afthina

    2017-12-01

    Full Text Available The aims of this research to determine the effect of Think Talk Write (TTW and Think Pair Share (TPS model with Realistic Mathematics Education (RME approach viewed from mathematical-logical intelligence. This research employed the quasi experimental research. The population of research was all students of the eight graders of junior high school in Karangamyar Regency in academic year 2016/2017. The result of this research shows that (1 TTW with RME approach gave better mathematics achievement than TPS with RME approach, (2 Students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one, (3 In TTW model with RME approach, students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average and low mathematical-logical intelligence gave same mathematics achievement, and  in TPS model with RME approach students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one (4 In each category of  mathematical-logical intelligence, TTW with RME approach and TPS with RME approach gave same mathematics achievement.

  5. The impact of a multiple intelligences teaching approach drug education programme on drug refusal skills of Nigerian pupils.

    Science.gov (United States)

    Nwagu, Evelyn N; Ezedum, Chuks E; Nwagu, Eric K N

    2015-09-01

    The rising incidence of drug abuse among youths in Nigeria is a source of concern for health educators. This study was carried out on primary six pupils to determine the effect of a Multiple Intelligences Teaching Approach Drug Education Programme (MITA-DEP) on pupils' acquisition of drug refusal skills. A programme of drug education based on the Multiple Intelligences Teaching Approach (MITA) was developed. An experimental group was taught using this programme while a control group was taught using the same programme but developed based on the Traditional Teaching Approach. Pupils taught with the MITA acquired more drug refusal skills than those taught with the Traditional Teaching Approach. Urban pupils taught with the MITA acquired more skills than rural pupils. There was no statistically significant difference in the mean refusal skills of male and female pupils taught with the MITA. © The Author(s) 2014.

  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. 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

  8. 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.

  9. 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.

  10. Combined SAFE/SNAP approach to safeguards evaluation

    International Nuclear Information System (INIS)

    Engi, D.; Chapman, L.D.; Grant, F.H.; Polito, J.

    1980-01-01

    The scope of a safeguards evaluation model can efficiently address one of two issues: (1) global safeguards effectiveness or (2) vulnerability analysis for individual scenarios. The Safeguards Automated Facility Evaluation (SAFE) focuses on the first issue, while the Safeguards Network Analysis Procedure (SNAP) is directed towards the second. A combined SAFE/SNAP approach to the problem of safeguards evaluation is described and illustrated through an example. 4 refs

  11. Combined endoscopic approach in the management of suprasellar craniopharyngioma.

    Science.gov (United States)

    Deopujari, Chandrashekhar E; Karmarkar, Vikram S; Shah, Nishit; Vashu, Ravindran; Patil, Rahul; Mohanty, Chandan; Shaikh, Salman

    2018-05-01

    Craniopharyngiomas are dysontogenic tumors with benign histology but aggressive behavior. The surgical challenges posed by the tumor are well recognized. Neuroendoscopy has recently contributed to its surgical management. This study focuses on our experience in managing craniopharyngiomas in recent years, highlighting the role of combined endoscopic trans-ventricular and endonasal approach. Ninety-two patients have been treated for craniopharyngioma from 2000 to 2016 by the senior author. A total of 125 procedures, microsurgical (58) and endoscopic (67), were undertaken. Combined endoscopic approach was carried out in 18 of these patients, 16 children and 2 young adults. All of these patients presented with a large cystic suprasellar mass associated with hydrocephalus. In the first instance, they were treated with a transventricular endoscopic procedure to decompress the cystic component. This was followed by an endonasal transsphenoidal procedure for excision within the next 2 to 6 days. All these patients improved after the initial cyst decompression with relief of hydrocephalus while awaiting remaining tumor removal in a more elective setting. Gross total resection could be done in 84% of these patients. Diabetes insipidus was the most common postsurgical complication seen in 61% patients in the immediate period but was persistent in only two patients at 1-year follow-up. None of the children in this group developed morbid obesity. There was one case of CSF leak requiring repair after initial surgery. Peri-operative mortality was seen in one patient secondary to ventriculitis. The patients who benefit most from the combined approach are those who present with raised intracranial pressure secondary to a large tumor with cyst causing hydrocephalus. Intraventricular endoscopic cyst drainage allows resolution of hydrocephalus with restoration of normal intracranial pressure, gives time for proper preoperative work up, and has reduced incidence of CSF leak after

  12. Combined endoscopic approaches to the cardiac sphincter achalasia treatment

    Directory of Open Access Journals (Sweden)

    V. N. Klimenko

    2015-12-01

    Full Text Available Aim. To assess combined endoscopic approaches to the cardiac sphincter achalasia treatment. Results. There are preliminary results of treatment and methods of carrying out of combined endoscopic pneumocardiodilatation and injections of botulotoxin type A ‘Disport’ at achalasia cardia are described in the article. Aethio-pathogenetic aspects in the development of achalasia cardia, action of botulotoxin type A and balloon pneumocardiodilatation of the esophagus, were described. And modern roentgen-endoscopic classification of achalasia cardia was given. Prognostic estimation scale of possibility to implement further combined endoscopic or surgical treatment is defined and is being in subsequent working out. Conclusion. Described clinical cases most brightly demonstrate variety of clinical achalasia cardia manifestations and also determine of the earlier display of surgical treatment.

  13. Identification of time-varying structural dynamic systems - An artificial intelligence approach

    Science.gov (United States)

    Glass, B. J.; Hanagud, S.

    1992-01-01

    An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

  14. An Integrated Open Approach to Capturing Systematic Knowledge for Manufacturing Process Innovation Based on Collective Intelligence

    Directory of Open Access Journals (Sweden)

    Gangfeng Wang

    2018-02-01

    Full Text Available Process innovation plays a vital role in the manufacture realization of increasingly complex new products, especially in the context of sustainable development and cleaner production. Knowledge-based innovation design can inspire designers’ creative thinking; however, the existing scattered knowledge has not yet been properly captured and organized according to Computer-Aided Process Innovation (CAPI. Therefore, this paper proposes an integrated approach to tackle this non-trivial issue. By analyzing the design process of CAPI and technical features of open innovation, a novel holistic paradigm of process innovation knowledge capture based on collective intelligence (PIKC-CI is constructed from the perspective of the knowledge life cycle. Then, a multi-source innovation knowledge fusion algorithm based on semantic elements reconfiguration is applied to form new public knowledge. To ensure the credibility and orderliness of innovation knowledge refinement, a collaborative editing strategy based on knowledge lock and knowledge–social trust degree is explored. Finally, a knowledge management system MPI-OKCS integrating the proposed techniques is implemented into the pre-built CAPI general platform, and a welding process innovation example is provided to illustrate the feasibility of the proposed approach. It is expected that our work would lay the foundation for the future knowledge-inspired CAPI and smart process planning.

  15. Artificial Intelligence Approach to the Determination of Physical Properties of Eclipsing Binaries. I. The EBAI Project

    Science.gov (United States)

    Prša, A.; Guinan, E. F.; Devinney, E. J.; DeGeorge, M.; Bradstreet, D. H.; Giammarco, J. M.; Alcock, C. R.; Engle, S. G.

    2008-11-01

    Achieving maximum scientific results from the overwhelming volume of astronomical data to be acquired over the next few decades demands novel, fully automatic methods of data analysis. Here we concentrate on eclipsing binary (EB) stars, a prime source of astrophysical information, of which only some hundreds have been rigorously analyzed, but whose numbers will reach millions in a decade. We describe the artificial neural network (ANN) approach which is able to surmount the human bottleneck and permit EB-based scientific yield to keep pace with future data rates. The ANN, following training on a sample of 33,235 model light curves, outputs a set of approximate model parameters [T2/T1, (R1 + R2)/a, esin ω , ecos ω , and sin i] for each input light curve data set. The obtained parameters can then be readily passed to sophisticated modeling engines. We also describe a novel method polyfit for preprocessing observational light curves before inputting their data to the ANN and present the results and analysis of testing the approach on synthetic data and on real data including 50 binaries from the Catalog and Atlas of Eclipsing Binaries (CALEB) database and 2580 light curves from OGLE survey data. The success rate, defined by less than a 10% error in the network output parameter values, is approximately 90% for the OGLE sample and close to 100% for the CALEB sample—sufficient for a reliable statistical analysis. The code is made available to the public. Our approach is applicable to EB light curves of all classes; this first paper in the eclipsing binaries via artificial intelligence (EBAI) series focuses on detached EBs, which is the class most challenging for this approach.

  16. The Relationship between Transformational Leadership and Emotional Intelligence from a Gendered Approach

    Science.gov (United States)

    Lopez-Zafra, Esther; Garcia-Retamero, Rocio; Martos, M. Pilar Berrios

    2012-01-01

    Studies on both transformational leadership and emotional intelligence have analyzed the relationship between emotions and leadership. Yet the relationships among these concepts and gender roles have not been documented. In this study, we investigated the relations among transformational leadership, emotional intelligence, and gender stereotypes.…

  17. Intelligence and Metacognition as Predictors of Foreign Language Achievement: A Structural Equation Modeling Approach

    Science.gov (United States)

    Pishghadam, Reza; Khajavy, Gholam Hassan

    2013-01-01

    This study examined the role of metacognition and intelligence in foreign language achievement on a sample of 143 Iranian English as a Foreign Language (EFL) learners. Participants completed Raven's Advanced Progressive Matrices as a measure of intelligence, and Metacognitive Awareness Inventory as a measure of metacognition. Learners' scores at…

  18. Improving the Fine-Tuning of Metaheuristics: An Approach Combining Design of Experiments and Racing Algorithms

    Directory of Open Access Journals (Sweden)

    Eduardo Batista de Moraes Barbosa

    2017-01-01

    Full Text Available Usually, metaheuristic algorithms are adapted to a large set of problems by applying few modifications on parameters for each specific case. However, this flexibility demands a huge effort to correctly tune such parameters. Therefore, the tuning of metaheuristics arises as one of the most important challenges in the context of research of these algorithms. Thus, this paper aims to present a methodology combining Statistical and Artificial Intelligence methods in the fine-tuning of metaheuristics. The key idea is a heuristic method, called Heuristic Oriented Racing Algorithm (HORA, which explores a search space of parameters looking for candidate configurations close to a promising alternative. To confirm the validity of this approach, we present a case study for fine-tuning two distinct metaheuristics: Simulated Annealing (SA and Genetic Algorithm (GA, in order to solve the classical traveling salesman problem. The results are compared considering the same metaheuristics tuned through a racing method. Broadly, the proposed approach proved to be effective in terms of the overall time of the tuning process. Our results reveal that metaheuristics tuned by means of HORA achieve, with much less computational effort, similar results compared to the case when they are tuned by the other fine-tuning approach.

  19. Intelligent Approach for Analysis of Respiratory Signals and Oxygen Saturation in the Sleep Apnea/Hypopnea Syndrome

    Science.gov (United States)

    Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena

    2014-01-01

    This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints. PMID:25035712

  20. Emotional intelligence in professional nursing practice: A concept review using Rodgers's evolutionary analysis approach

    Directory of Open Access Journals (Sweden)

    Angelina E. Raghubir

    2018-04-01

    Full Text Available Background: Knowledge around emotional intelligence originated in the 1990s from research regarding thoughts, emotions and abilities. The concept of emotional intelligence has evolved over the last 25 years; however, the understanding and use is still unclear. Despite this, emotional intelligence has been a widely-considered concept within professions such as business, management, education, and within the last 10 years has gained traction within nursing practice. Aims and objectives: The aim of this concept review is to clarify the understanding of the concept emotional intelligence, what attributes signify emotional intelligence, what are its antecedents, consequences, related terms and implications to advance nursing practice. Method: A computerized search was guided by Rodger's evolutional concept analysis. Data courses included: CINAHL, PyschINFO, Scopus, EMBASE and ProQuest, focusing on articles published in Canada and the United Stated during 1990–2017. Results: A total of 23 articles from various bodies of disciplines were included in this integrative concept review. The analysis reveals that there are many inconsistencies regarding the description of emotional intelligence, however, four common attributes were discovered: self-awareness, self-management, social awareness and social/relationship management. These attributes facilitate the emotional well-being among advance practice nurses and enhances the ability to practice in a way that will benefit patients, families, colleagues and advance practice nurses as working professionals and as individuals. Conclusion: The integration of emotional intelligence is supported within several disciplines as there is consensus on the impact that emotional intelligence has on job satisfaction, stress level, burnout and helps to facilitate a positive environment. Explicit to advance practice nursing, emotional intelligence is a concept that may be central to nursing practice as it has the

  1. Combining Multiple Types of Intelligence to Generate Probability Maps of Moving Targets

    Science.gov (United States)

    2013-09-01

    normalization coefficient k similar to Demspter-Shafer’s combination rule. d. Mass Mean This rule of combination is the most straightforward one... coefficient , we can state that without normalizing, the updated distribution is: fupdate t   qk k t M 1 qk n k t M        (3.3) 36...Lawrence, KS. Chen, Z. (2003). Bayesian filtering: From Kalman filters to particle filters and beyond. Technical report, McMaster University. Dempster

  2. Approaches to modernize the combination drug development paradigm

    Directory of Open Access Journals (Sweden)

    Daphne Day

    2016-10-01

    Full Text Available Abstract Recent advances in genomic sequencing and omics-based capabilities are uncovering tremendous therapeutic opportunities and rapidly transforming the field of cancer medicine. Molecularly targeted agents aim to exploit key tumor-specific vulnerabilities such as oncogenic or non-oncogenic addiction and synthetic lethality. Additionally, immunotherapies targeting the host immune system are proving to be another promising and complementary approach. Owing to substantial tumor genomic and immunologic complexities, combination strategies are likely to be required to adequately disrupt intricate molecular interactions and provide meaningful long-term benefit to patients. To optimize the therapeutic success and application of combination therapies, systematic scientific discovery will need to be coupled with novel and efficient clinical trial approaches. Indeed, a paradigm shift is required to drive precision medicine forward, from the traditional “drug-centric” model of clinical development in pursuit of small incremental benefits in large heterogeneous groups of patients, to a “strategy-centric” model to provide customized transformative treatments in molecularly stratified subsets of patients or even in individual patients. Crucially, to combat the numerous challenges facing combination drug development—including our growing but incomplete understanding of tumor biology, technical and informatics limitations, and escalating financial costs—aligned goals and multidisciplinary collaboration are imperative to collectively harness knowledge and fuel continual innovation.

  3. The systems approach for applying artificial intelligence to space station automation (Invited Paper)

    Science.gov (United States)

    Grose, Vernon L.

    1985-12-01

    The progress of technology is marked by fragmentation -- dividing research and development into ever narrower fields of specialization. Ultimately, specialists know everything about nothing. And hope for integrating those slender slivers of specialty into a whole fades. Without an integrated, all-encompassing perspective, technology becomes applied in a lopsided and often inefficient manner. A decisionary model, developed and applied for NASA's Chief Engineer toward establishment of commercial space operations, can be adapted to the identification, evaluation, and selection of optimum application of artificial intelligence for space station automation -- restoring wholeness to a situation that is otherwise chaotic due to increasing subdivision of effort. Issues such as functional assignments for space station task, domain, and symptom modules can be resolved in a manner understood by all parties rather than just the person with assigned responsibility -- and ranked by overall significance to mission accomplishment. Ranking is based on the three basic parameters of cost, performance, and schedule. This approach has successfully integrated many diverse specialties in situations like worldwide terrorism control, coal mining safety, medical malpractice risk, grain elevator explosion prevention, offshore drilling hazards, and criminal justice resource allocation -- all of which would have otherwise been subject to "squeaky wheel" emphasis and support of decision-makers.

  4. Augmenting Tertiary Students' Soft Skills Via Multiple Intelligences Instructional Approach: Literature Courses in Focus

    Directory of Open Access Journals (Sweden)

    El Sherief Eman

    2017-01-01

    Full Text Available The second half of the twentieth century is a witness to an unprecedentedly soaring increase in the number of students joining the arena of higher education(UNESCO,2001. Currently, the number of students at Saudi universities and colleges exceeds one million vis-à-vis 7000 in 1970(Royal Embassy of Saudi Arabia, Washington. Such enormous body of learners in higher education is per se diverse enough to embrace distinct learning styles, assorted repertoire of backgrounds, prior knowledge, experiences, and perspectives; at this juncture, they presumably share common aspiration which is hooking a compatible post in the labor market upon graduation, and to subsequently be capable of acting competently in a scrupulously competitive workplace environment. Bunch of potentialities and skills are patently vital for a graduate to reach such a prospect. Such bunch of skills in a conventional undergraduate paradigm of education were given no heed, being rather postponed to the post-graduation phase. The current Paper postulated tremendous  merits of deploying the Multiple Intelligences theory as a project-based approach, within  literature classes in higher education; a strategy geared towards reigniting students’ engagement, nurturing their critical thinking capabilities, sustaining their individualistic dispositions, molding them as inquiry-seekers, and ending up engendering life-long, autonomous learners,  well-armed with the substantial skills for traversing the rigorous competition in future labor market.

  5. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

  6. Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Hanning Chen

    2014-01-01

    Full Text Available The development of radio frequency identification (RFID technology generates the most challenging RFID network planning (RNP problem, which needs to be solved in order to operate the large-scale RFID network in an optimal fashion. RNP involves many objectives and constraints and has been proven to be a NP-hard multi-objective problem. The application of evolutionary algorithm (EA and swarm intelligence (SI for solving multiobjective RNP (MORNP has gained significant attention in the literature, but these algorithms always transform multiple objectives into a single objective by weighted coefficient approach. In this paper, we use multiobjective EA and SI algorithms to find all the Pareto optimal solutions and to achieve the optimal planning solutions by simultaneously optimizing four conflicting objectives in MORNP, instead of transforming multiobjective functions into a single objective function. The experiment presents an exhaustive comparison of three successful multiobjective EA and SI, namely, the recently developed multiobjective artificial bee colony algorithm (MOABC, the nondominated sorting genetic algorithm II (NSGA-II, and the multiobjective particle swarm optimization (MOPSO, on MORNP instances of different nature, namely, the two-objective and three-objective MORNP. Simulation results show that MOABC proves to be more superior for planning RFID networks than NSGA-II and MOPSO in terms of optimization accuracy and computation robustness.

  7. A generic flexible and robust approach for intelligent real-time video-surveillance systems

    Science.gov (United States)

    Desurmont, Xavier; Delaigle, Jean-Francois; Bastide, Arnaud; Macq, Benoit

    2004-05-01

    In this article we present a generic, flexible and robust approach for an intelligent real-time video-surveillance system. A previous version of the system was presented in [1]. The goal of these advanced tools is to provide help to operators by detecting events of interest in visual scenes and highlighting alarms and compute statistics. The proposed system is a multi-camera platform able to handle different standards of video inputs (composite, IP, IEEE1394 ) and which can basically compress (MPEG4), store and display them. This platform also integrates advanced video analysis tools, such as motion detection, segmentation, tracking and interpretation. The design of the architecture is optimised to playback, display, and process video flows in an efficient way for video-surveillance application. The implementation is distributed on a scalable computer cluster based on Linux and IP network. It relies on POSIX threads for multitasking scheduling. Data flows are transmitted between the different modules using multicast technology and under control of a TCP-based command network (e.g. for bandwidth occupation control). We report here some results and we show the potential use of such a flexible system in third generation video surveillance system. We illustrate the interest of the system in a real case study, which is the indoor surveillance.

  8. HIGH: A Hexagon-based Intelligent Grouping Approach in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    FAN, C.-S.

    2016-02-01

    Full Text Available In a random deployment or uniform deployment strategy, sensor nodes are scattered randomly or uniformly in the sensing field, respectively. Hence, the coverage ratio cannot be guaranteed. The coverage ratio of uniform deployment, in general, is larger than that of the random deployment strategy. However, a random deployment or uniform deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs. Therefore, cluster heads (CHs around the sink have larger loads than those farther away from the sink. That is, CHs close to the sink exhaust their energy earlier. In order to overcome the above problem, we propose a Hexagon-based Intelligent Grouping approacH in WSNs (called HIGH. The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed HIGH scheme. The simulation results validate our theoretical analysis and show that the proposed HIGH scheme achieves a satisfactory coverage ratio, balances the energy consumption among sensor nodes, and extends network lifetime significantly.

  9. Artificial Intelligence and the 'Good Society': the US, EU, and UK approach.

    Science.gov (United States)

    Cath, Corinne; Wachter, Sandra; Mittelstadt, Brent; Taddeo, Mariarosaria; Floridi, Luciano

    2018-04-01

    In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence (AI). In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a 'good AI society'. To do so, we examine how each report addresses the following three topics: (a) the development of a 'good AI society'; (b) the role and responsibility of the government, the private sector, and the research community (including academia) in pursuing such a development; and (c) where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a 'good AI society'. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach.

  10. Integrated Transport Planning Framework Involving Combined Utility Regret Approach

    DEFF Research Database (Denmark)

    Wang, Yang; Monzon, Andres; Di Ciommo, Floridea

    2014-01-01

    Sustainable transport planning requires an integrated approach involving strategic planning, impact analysis, and multicriteria evaluation. This study aimed at relaxing the utility-based decision-making assumption by newly embedding anticipated-regret and combined utility regret decision mechanisms...... in a framework for integrated transport planning. The framework consisted of a two-round Delphi survey, integrated land use and transport model for Madrid, and multicriteria analysis. Results show that (a) the regret-based ranking has a similar mean but larger variance than the utility-based ranking does, (b......) the least-regret scenario forms a compromise between the desired and the expected scenarios, (c) the least-regret scenario can lead to higher user benefits in the short term and lower user benefits in the long term, (d) the utility-based, the regret-based, and the combined utility- and regret...

  11. Combination approaches with immune checkpoint blockade in cancer therapy

    Directory of Open Access Journals (Sweden)

    Maarten Swart

    2016-11-01

    Full Text Available In healthy individuals, immune checkpoint molecules prevent autoimmune responses and limit immune cell-mediated tissue damage. Tumors frequently exploit these molecules to evade eradication by the immune system. Over the past years, immune checkpoint blockade of cytotoxic T lymphocyte antigen-4 (CTLA-4 and programmed death-1 (PD-1 emerged as promising strategies to activate anti-tumor cytotoxic T cell responses. Although complete regression and long-term survival is achieved in some patients, not all patients respond. This review describes promising, novel combination approaches involving immune checkpoint blockade, aimed at increasing response-rates to the single treatments.

  12. Transbasal versus endoscopic endonasal versus combined approaches for olfactory groove meningiomas: importance of approach selection.

    Science.gov (United States)

    Liu, James K; Silva, Nicole A; Sevak, Ilesha A; Eloy, Jean Anderson

    2018-04-01

    OBJECTIVE There has been much debate regarding the optimal surgical approach for resecting olfactory groove meningiomas (OGMs). In this paper, the authors analyzed the factors involved in approach selection and reviewed the surgical outcomes in a series of OGMs. METHODS A retrospective review of 28 consecutive OGMs from a prospective database was conducted. Each tumor was treated via one of 3 approaches: transbasal approach (n = 15), pure endoscopic endonasal approach (EEA; n = 5), and combined (endoscope-assisted) transbasal-EEA (n = 8). RESULTS The mean tumor volume was greatest in the transbasal (92.02 cm 3 ) and combined (101.15 cm 3 ) groups. Both groups had significant lateral dural extension over the orbits (transbasal 73.3%, p 95%) was achieved in 20% of transbasal and 37.5% of combined cases, all due to tumor adherence to the critical neurovascular structures. The rate of CSF leakage was 0% in the transbasal and combined groups, and there was 1 leak in the EEA group (20%), resulting in an overall CSF leakage rate of 3.6%. Olfaction was preserved in 66.7% in the transbasal group. There was no significant difference in length of stay or 30-day readmission rate between the 3 groups. The mean modified Rankin Scale score was 0.79 after the transbasal approach, 2.0 after EEA, and 2.4 after the combined approach (p = 0.0604). The mean follow-up was 14.5 months (range 1-76 months). CONCLUSIONS The transbasal approach provided the best clinical outcomes with the lowest rate of complications for large tumors (> 40 mm) and for smaller tumors (OGMs invading the sinonasal cavity. Careful patient selection using an individualized, tailored strategy is important to optimize surgical outcomes.

  13. Prioritizing the refactoring need for critical component using combined approach

    Directory of Open Access Journals (Sweden)

    Rajni Sehgal

    2018-10-01

    Full Text Available One of the most promising strategies that will smooth out the maintainability issues of the software is refactoring. Due to lack of proper design approach, the code often inherits some bad smells which may lead to improper functioning of the code, especially when it is subject to change and requires some maintenance. A lot of studies have been performed to optimize the refactoring strategy which is also a very expensive process. In this paper, a component based system is considered, and a Fuzzy Multi Criteria Decision Making (FMCDM model is proposed by combining subjective and objective weights to rank the components as per their urgency of refactoring. Jdeodorant tool is used to detect the code smells from the individual components of a software system. The objective method uses the Entropy approach to rank the component having the code smell. The subjective method uses the Fuzzy TOPSIS approach based on decision makers’ judgement, to identify the critically and dependency of these code smells on the overall software. The suggested approach is implemented on component-based software having 15 components. The constitute components are ranked based on refactoring requirements.

  14. 2015 Chinese Intelligent Systems Conference

    CERN Document Server

    Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

    2016-01-01

    This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

  15. A Three Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents

    Science.gov (United States)

    2006-10-01

    Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents. In Visualising Network...University at the start of each fall semester, when numerous new students arrive on campus and begin downloading extensive amounts of audio and...SIGGRAPH ’92 • C. Cruz-Neira, D.J. Sandin, T.A. DeFanti, R.V. Kenyon and J.C. Hart, "The CAVE: Audio Visual Experience Automatic Virtual Environment

  16. BASIC APPROACH TO ANALYZING THE ESSENCE AND STRUCTURE OF INTELLIGENCE OF THE FUTURE OFFICERS OF INTERIOR MINISTRY TROOPS RUSSIA

    Directory of Open Access Journals (Sweden)

    Sergey Valerevich Orlenko

    2015-11-01

    Full Text Available The article, based on an analysis of various scientific sources, presented results of a study the problem of formation and development of future intelligence officers, consideration of the main approaches to the analysis of the nature and structure of the phenomenon. The authors substantiate the relevance of such work, consider the results lead the views of various authors on the subject. On the basis of these conclusions are drawn, which can be used in educational practice of military high school.

  17. Decision Support for Software Process Management Teams: An Intelligent Software Agent Approach

    National Research Council Canada - National Science Library

    Church, Lori

    2000-01-01

    ... to market, eliminate redundancy, and ease job stress. This thesis proposes a conceptual model for software process management decision support in the form of an intelligent software agent network...

  18. Dural opening/removal for combined petrosal approach: technical note.

    Science.gov (United States)

    Terasaka, Shunsuke; Asaoka, Katsuyuki; Kobayashi, Hiroyuki; Sugiyama, Taku; Yamaguchi, Shigeru

    2011-03-01

    Detailed descriptions of stepwise dural opening/removal for combined petrosal approach are presented. Following maximum bone work, the first dural incision was made along the undersurface of the temporal lobe parallel to the superior petrosal sinus. Posterior extension of the dural incision was made in a curved fashion, keeping away from the transverse-sigmoid junction and taking care to preserve the vein of Labbé. A second incision was made perpendicular to the first incision. After sectioning the superior petrosal sinus around the porus trigeminus, the incision was extended toward the posterior fossa dura in the middle fossa region. The tentorium was incised toward the incisura at a point just posterior to the entrance of the trochlear nerve. A third incision was made longitudinally between the superior petrosal sinus and the jugular bulb. A final incision was initiated perpendicular to the third incision in the presigmoid region and extended parallel to the superior petrosal sinus connecting the second incision. The dural complex consisting of the temporal lobe dura, the posterior fossa dura, and the freed tentorium could then be removed. In addition to extensive bone resection, our strategic cranial base dural opening/removal can yield true advantages for the combined petrosal approach.

  19. 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.

  20. 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.

  1. Non-Intrusive Intelligibility Prediction Using a Codebook-Based Approach

    DEFF Research Database (Denmark)

    Sørensen, Charlotte; Kavalekalam, Mathew Shaji; Xenaki, Angeliki

    2017-01-01

    It could be beneficial for users of hearing aids if these were able to automatically adjust the processing according to the speech intelligibility in the specific acoustic environment. Most speech intelligibility metrics are intrusive, i.e., they require a clean reference signal, which is rarely...... a high correlation between the proposed non-intrusive codebookbased STOI (NIC-STOI) and the intrusive STOI indicating that NIC-STOI is a suitable metric for automatic classification of speech signals...

  2. 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...

  3. 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 ...

  4. Information gathering, management and transferring for geospatial intelligence - A conceptual approach to create a spatial data infrastructure

    Science.gov (United States)

    Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

    2017-06-01

    Since long ago, information is a key factor for military organizations. In military context the success of joint and combined operations depends on the accurate information and knowledge flow concerning the operational theatre: provision of resources, environment evolution, targets' location, where and when an event will occur. Modern military operations cannot be conceive without maps and geospatial information. Staffs and forces on the field request large volume of information during the planning and execution process, horizontal and vertical geospatial information integration is critical for decision cycle. Information and knowledge management are fundamental to clarify an environment full of uncertainty. Geospatial information (GI) management rises as a branch of information and knowledge management, responsible for the conversion process from raw data collect by human or electronic sensors to knowledge. Geospatial information and intelligence systems allow us to integrate all other forms of intelligence and act as a main platform to process and display geospatial-time referenced events. Combining explicit knowledge with person know-how to generate a continuous learning cycle that supports real time decisions, mitigates the influences of fog of war and provides the knowledge supremacy. This paper presents the analysis done after applying a questionnaire and interviews about the GI and intelligence management in a military organization. The study intended to identify the stakeholder's requirements for a military spatial data infrastructure as well as the requirements for a future software system development.

  5. Fostering collective intelligence education

    Directory of Open Access Journals (Sweden)

    Jaime Meza

    2016-06-01

    Full Text Available New educational models are necessary to update learning environments to the digitally shared communication and information. Collective intelligence is an emerging field that already has a significant impact in many areas and will have great implications in education, not only from the side of new methodologies but also as a challenge for education. This paper proposes an approach to a collective intelligence model of teaching using Internet to combine two strategies: idea management and real time assessment in the class. A digital tool named Fabricius has been created supporting these two elements to foster the collaboration and engagement of students in the learning process. As a result of the research we propose a list of KPI trying to measure individual and collective performance. We are conscious that this is just a first approach to define which aspects of a class following a course can be qualified and quantified.

  6. A study of the importance of occupancy to building cooling load in prediction by intelligent approach

    International Nuclear Information System (INIS)

    Kwok, Simon S.K.; Lee, Eric W.M.

    2011-01-01

    Research highlights: → The building occupancy affecting the cooling load prediction is studied. → PENN model is adopted in this study for predicting the building cooling load. → Statistical approach is adopted to result a less prejudice prediction performance. → Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact on the required cooling load of buildings, practices currently adopted in modeling the presence and activity of people in buildings do not reflect the complexity of the impact occupants have on building cooling load. In contrast to previous artificial neural network (ANN) models, most of which employ a fixed schedule or historic load data to represent building occupancy in simulating building cooling load, this paper introduces two input parameters, dynamic occupancy area and rate and uses it to mimic building cooling load. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing grade A mega office buildings in Hong Kong with tenants including many multi-national financial companies that require 24-h air conditioning seven days a week. The dynamic changes that occur in the occupancy of these buildings therefore make it very difficult to forecast building cooling load by means of a fixed time schedule. The performance of simulation results

  7. A study of the importance of occupancy to building cooling load in prediction by intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Kwok, Simon S.K. [Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong); Lee, Eric W.M., E-mail: ericlee@cityu.edu.h [Department of Building and Construction, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong)

    2011-07-15

    Research highlights: {yields} The building occupancy affecting the cooling load prediction is studied. {yields} PENN model is adopted in this study for predicting the building cooling load. {yields} Statistical approach is adopted to result a less prejudice prediction performance. {yields} Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact on the required cooling load of buildings, practices currently adopted in modeling the presence and activity of people in buildings do not reflect the complexity of the impact occupants have on building cooling load. In contrast to previous artificial neural network (ANN) models, most of which employ a fixed schedule or historic load data to represent building occupancy in simulating building cooling load, this paper introduces two input parameters, dynamic occupancy area and rate and uses it to mimic building cooling load. The training samples used include weather data obtained from the Hong Kong Observatory and building-related data acquired from an existing grade A mega office buildings in Hong Kong with tenants including many multi-national financial companies that require 24-h air conditioning seven days a week. The dynamic changes that occur in the occupancy of these buildings therefore make it very difficult to forecast building cooling load by means of a fixed time schedule. The performance of

  8. 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

  9. Developing emotional intelligence ability in oncology nurses: a clinical rounds approach.

    Science.gov (United States)

    Codier, Estelle; Freitas, Beth; Muneno, Lynn

    2013-01-01

    To explore the feasibility and impact of an emotional intelligence ability development program on staff and patient care. A mixed method, pre/post-test design. A tertiary care hospital in urban Honolulu, HI. Rounds took place on a 24-bed inpatient oncology unit. 33 RNs in an oncology unit. After collection of baseline data, the emotional intelligence rounds were conducted in an inpatient oncology nursing unit on all shifts during a 10-month period. Demographic information, emotional intelligence scores, data from rounds, chart reviews of emotional care documentation, and unit-wide satisfaction and safety data. The ability to identify emotions in self and others was demonstrated less frequently than expected in this population. The low test response rate prevented comparison of scores pre- and postintervention. The staff's 94% participation in rounds, the positive (100%) evaluation of rounds, and poststudy improvements in emotional care documentation and emotional care planning suggest a positive effect from the intervention. Additional research is recommended over a longer period of time to evaluate the impact emotional intelligence specifically has on the staff's identification of emotions. Because the intervention involved minimal time and resources, feasibility for continuation of the intervention poststudy was rated "high" by the research team. Research in other disciplines suggests that improvement in emotional intelligence ability in clinical staff nurses may improve retention, performance, and teamwork in nursing, which would be of particular significance in high-risk clinical practice environments. Few research studies have explored development of emotional intelligence abilities in clinical staff nurses. Evidence from this study suggests that interventions in the clinical environment may be used to develop emotional intelligence ability. Impact from such development may be used in the future to not only improve the quality of nursing care, but also

  10. Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

    Science.gov (United States)

    Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

    2013-09-01

    The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Modeling the binding affinity of structurally diverse industrial chemicals to carbon using the artificial intelligence approaches.

    Science.gov (United States)

    Gupta, Shikha; Basant, Nikita; Rai, Premanjali; Singh, Kunwar P

    2015-11-01

    Binding affinity of chemical to carbon is an important characteristic as it finds vast industrial applications. Experimental determination of the adsorption capacity of diverse chemicals onto carbon is both time and resource intensive, and development of computational approaches has widely been advocated. In this study, artificial intelligence (AI)-based ten different qualitative and quantitative structure-property relationship (QSPR) models (MLPN, RBFN, PNN/GRNN, CCN, SVM, GEP, GMDH, SDT, DTF, DTB) were established for the prediction of the adsorption capacity of structurally diverse chemicals to activated carbon following the OECD guidelines. Structural diversity of the chemicals and nonlinear dependence in the data were evaluated using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. The generalization and prediction abilities of the constructed models were established through rigorous internal and external validation procedures performed employing a wide series of statistical checks. In complete dataset, the qualitative models rendered classification accuracies between 97.04 and 99.93%, while the quantitative models yielded correlation (R(2)) values of 0.877-0.977 between the measured and the predicted endpoint values. The quantitative prediction accuracies for the higher molecular weight (MW) compounds (class 4) were relatively better than those for the low MW compounds. Both in the qualitative and quantitative models, the Polarizability was the most influential descriptor. Structural alerts responsible for the extreme adsorption behavior of the compounds were identified. Higher number of carbon and presence of higher halogens in a molecule rendered higher binding affinity. Proposed QSPR models performed well and outperformed the previous reports. A relatively better performance of the ensemble learning models (DTF, DTB) may be attributed to the strengths of the bagging and boosting algorithms which enhance the predictive accuracies. The

  12. Combined SAFE/SNAP approach to safeguards evaluation

    International Nuclear Information System (INIS)

    Engi, D.; Chapman, L.D.; Grant, F.H.; Polito, J.

    1980-01-01

    Generally, the scope of a safeguards evaluation model can efficiently address one of two issues, (1) global safeguards effectiveness, or (2) vulnerability analysis for individual scenarios. The Safeguards Automated Facility Evaluation (SAFE) focuses on (1) while the Safeguards Network Analysis Procedure (SNAP) is directed at (2). SAFE addresses (1) in that it considers the entire facility, i.e., the composite system of hardware and human components, in one global analysis. SNAP addresses (2) by providing a safeguards modeling symbology sufficiently flexible to represent quite complex scenarios from the standpoint of hardware interfaces while also accounting for a rich variety of human decision making. A combined SAFE/SNAP approach to the problem of safeguards evaluation is described and illustrated through an example

  13. Combining genomic and proteomic approaches for epigenetics research

    Science.gov (United States)

    Han, Yumiao; Garcia, Benjamin A

    2014-01-01

    Epigenetics is the study of changes in gene expression or cellular phenotype that do not change the DNA sequence. In this review, current methods, both genomic and proteomic, associated with epigenetics research are discussed. Among them, chromatin immunoprecipitation (ChIP) followed by sequencing and other ChIP-based techniques are powerful techniques for genome-wide profiling of DNA-binding proteins, histone post-translational modifications or nucleosome positions. However, mass spectrometry-based proteomics is increasingly being used in functional biological studies and has proved to be an indispensable tool to characterize histone modifications, as well as DNA–protein and protein–protein interactions. With the development of genomic and proteomic approaches, combination of ChIP and mass spectrometry has the potential to expand our knowledge of epigenetics research to a higher level. PMID:23895656

  14. Antiviral Combination Approach as a Perspective to Combat Enterovirus Infections.

    Science.gov (United States)

    Galabov, Angel S; Nikolova, Ivanka; Vassileva-Pencheva, Ralitsa; Stoyanova, Adelina

    2015-01-01

    Human enteroviruses distributed worldwide are causative agents of a broad spectrum of diseases with extremely high morbidity, including a series of severe illnesses of the central nervous system, heart, endocrine pancreas, skeleton muscles, etc., as well as the common cold contributing to the development of chronic respiratory diseases, including the chronic obstructive pulmonary disease. The above mentioned diseases along with the significantly high morbidity and mortality in children, as well as in the high-risk populations (immunodeficiencies, neonates) definitely formulate the chemotherapy as the main tool for the control of enterovirus infections. At present, clinically effective antivirals for use in the treatment of enteroviral infection do not exist, in spite of the large amount of work carried out in this field. The main reason for this is the development of drug resistance. We studied the process of development of resistance to the strongest inhibitors of enteroviruses, WIN compounds (VP1 protein hydrophobic pocket blockers), especially in the models in vivo, Coxsackievirus B (CV-B) infections in mice. We introduced the tracing of a panel of phenotypic markers (MIC50 value, plaque shape and size, stability at 50℃, pathogenicity in mice) for characterization of the drug-mutants (resistant and dependent) as a very important stage in the study of enterovirus inhibitors. Moreover, as a result of VP1 RNA sequence analysis performed on the model of disoxaril mutants of CVB1, we determined the molecular basis of the drug-resistance. The monotherapy courses were the only approach used till now. For the first time in the research for anti-enterovirus antivirals our team introduced the testing of combination effect of the selective inhibitors of enterovirus replication with different mode of action. This study resulted in the selection of a number of very effective in vitro double combinations with synergistic effect and a broad spectrum of sensitive

  15. Market Intelligence Precursors for the Entrepreneurial Resilience Approach: The Case of the Romanian Eco-Label Product Retailers

    Directory of Open Access Journals (Sweden)

    Adrian Micu

    2018-01-01

    Full Text Available The entrepreneurial resilience of eco-label product retailers emphasises their adaptive capability for renewal after the economic crisis. This paper explores the resilience of the market intelligence techniques adopted by the eco-label product retailers in order to contribute to sustainable development of this market in Romania. The research, conducted on a sample of Romanian retailers of eco-label products, analyses the main sources for gathering data about their competitors, the reasons for monitoring the strategic options of their competitors and the specific market intelligence techniques employed within the entrepreneurial resilience approach, aiming to overcome the negative crisis effects. The research outlines, from an entrepreneurial resilience perspective, several positioning opportunities of the eco-label product retailers after the crisis, which have affected the Romanian economy in the period 2008–2009 and have implicitly affected the eco-label market.

  16. Orchestrating Multiple Intelligences

    Science.gov (United States)

    Moran, Seana; Kornhaber, Mindy; Gardner, Howard

    2006-01-01

    Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

  17. Designing with computational intelligence

    CERN Document Server

    Lopes, Heitor; Mourelle, Luiza

    2017-01-01

    This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

  18. 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.

  19. A multilevel approach to the relationship between birth order and intelligence.

    Science.gov (United States)

    Wichman, Aaron L; Rodgers, Joseph Lee; MacCallum, Robert C

    2006-01-01

    Many studies show relationships between birth order and intelligence but use cross-sectional designs or manifest other threats to internal validity. Multilevel analyses with a control variable show that when these threats are removed, two major results emerge: (a) birth order has no significant influence on children's intelligence and (b) earlier reported birth order effects on intelligence are attributable to factors that vary between, not within, families. Analyses on 7- to 8 - and 13- to 14-year-old children from the National Longitudinal Survey of Youth support these conclusions. When hierarchical data structures, age variance of children, and within-family versus between-family variance sources are taken into account, previous research is seen in a new light.

  20. FCJ-206 From Braitenberg’s Vehicles to Jansen’s Beach Animals: Towards an Ecological Approach to the Design of Non-Organic Intelligence

    Directory of Open Access Journals (Sweden)

    Maaike Bleeker

    2016-12-01

    Full Text Available This article presents a comparison of two proposals for how to conceive of the evolution of non-organic intelligence. One is Valentino Braitenberg’s 1984 essay ‘Vehicles: Experiments in Synthetic Psychology’. The other is the Strandbeesten (beach animals of Dutch engineer-artist Theo Jansen. Jansen’s beach animals are not robots. Yet, as semi-autonomous non-organic agents created by humans, they are interesting in the context of the development of robots for how they present an ecological approach to the design of non-organic intelligence. Placing Braitenberg’s and Jansen’s approaches side by side illuminates how Jansen’s approach implies a radically different take than Braitenberg’s on non-organic intelligence, on intelligence as environmental, and on what the relationship between agency and behaviour might comprise.

  1. A multi-objective approach to evolving platooning strategies in intelligent transportation systems

    NARCIS (Netherlands)

    Illigen, W. van; Haasdijk, E.; Kester, L.J.H.M.

    2013-01-01

    The research in this paper is inspired by a vision of intelligent vehicles that autonomously move along motorways: they join and leave trains of vehicles (platoons), overtake other vehicles, etc. We propose a multi-objective evolutionary algorithm based on NEAT and SPEA2 that evolves highlevel

  2. A Case-Based Reasoning Approach to Internet Intelligent Tutoring System (ITS) Authoring

    National Research Council Canada - National Science Library

    Stottler, Richard

    1998-01-01

    Report developed under SBIR contract. Intelligent tutoring systems (lTSs) have shown great promise in a variety of training domains and can achieve many of the same benefits as one-on-one instruction, in a cost-effective manner...

  3. Fluid Intelligence as a Predictor of Learning: A Longitudinal Multilevel Approach Applied to Math

    Science.gov (United States)

    Primi, Ricardo; Ferrao, Maria Eugenia; Almeida, Leandro S.

    2010-01-01

    The association between fluid intelligence and inter-individual differences was investigated using multilevel growth curve modeling applied to data measuring intra-individual improvement on math achievement tests. A sample of 166 students (88 boys and 78 girls), ranging in age from 11 to 14 (M = 12.3, SD = 0.64), was tested. These individuals took…

  4. Personality Traits and General Intelligence as Predictors of Academic Performance: A Structural Equation Modelling Approach

    Science.gov (United States)

    Rosander, Pia; Backstrom, Martin; Stenberg, Georg

    2011-01-01

    The aim of the present study was to investigate the extent to which personality traits, after controlling for general intelligence, predict academic performance in different school subjects. Upper secondary school students in Sweden (N=315) completed the Wonderlic IQ test (Wonderlic, 1992) and the IPIP-NEO-PI test (Goldberg, 1999). A series of…

  5. A Multi-Objective Approach to Evolving Platooning Strategies in Intelligent Transportation Systems

    NARCIS (Netherlands)

    van Willigen, W; Haasdijk, E; Kester, Leon

    2013-01-01

    The research in this paper is inspired by a vision of intelligent vehicles that autonomously move along motorways: they join and leave trains of vehicles (platoons), overtake other vehicles, etc. We propose a multi-objective evolutionary algorithm based on NEAT and SPEA2 that evolves high-level

  6. Theoretical Framework of Organizational Intelligence: A Managerial Approach to Promote Renewable Energy in Rural Economies

    Directory of Open Access Journals (Sweden)

    Nicolae Istudor

    2016-08-01

    Full Text Available The companies involved in the energy sector must reinvent themselves to be innovative and adaptable to contemporary environmental changes. The promotion of renewable energy in rural communities is a great challenge for these companies. They should focus on improving the environment scanning actions and the knowledge management (KM system and enhancing the collective intelligence to avoid the loss of information, to foster innovation, and to maintain a competitive advantage. To achieve these goals, energy companies require appropriate management tools and practices. The purpose of this study is to propose a theoretical framework of organizational intelligence (OI supported by a cross-perspective analysis of various aspects: economic intelligence (EI and KM practices, entropy processes, and organizational enablers. A pilot investigation for testing the framework in the case of Transelectrica S.A. has been elaborated. The findings reveal that the elements of the OI framework are embedded in Transelectrica’s system and they need to be further developed. As an intelligent company acting in the Romanian energy market, Transelectrica has a higher potential to promote projects in the renewable energy sector. The main conclusion highlights that OI is a multidimensional construct that provides the organization the ability to deal with environmental challenges in a “new economy”.

  7. Scientific approaches and techniques for negotiation : a game theoretic and artificial intelligence perspective

    NARCIS (Netherlands)

    E.H. Gerding (Enrico); D.D.B. van Bragt; J.A. La Poutré (Han)

    2000-01-01

    textabstractDue to the rapid growth of electronic environments (such as the Internet) much research is currently being performed on autonomous trading mechanisms. This report contains an overview of the current literature on negotiations in the fields of game theory and artificial intelligence (AI).

  8. Speech intelligibility problems of Sudanese learners of English : an experimental approach

    NARCIS (Netherlands)

    Tajeldin Ali, Ezzeldin Mahmoud

    2011-01-01

    This is a study on the pronunciation and perception of English sounds and words by university students of English in Sudan, whose native language is Sudanese Arabic. The study aims to establish the intelligibility of Sudanese-Arabic (SA) accented English for native English (British and American)

  9. The artificial neural networks: An approach to artificial intelligence; Un approccio ``biologico`` all`intelligenza artificiale

    Energy Technology Data Exchange (ETDEWEB)

    Taraglio, Sergio; Zanela, Andrea [ENEA, Casaccia (Italy). Dipt. Innovazione

    1997-05-01

    The artificial neural networks try to simulate the functionalities of the nervous system through a complex network of simple computing elements. In this work is presented an introduction to the neural networks and some of their possible applications, especially in the field of Artificial Intelligence.

  10. Example of a distributed-intelligence data-acquisition system using the CAMAC approach

    International Nuclear Information System (INIS)

    Francis, J.E. Jr.; Stewart, C.R.; Overbey, D.R.

    1982-03-01

    The Fusion Energy Division has many diagnostics connected to the same experiment, and correlating the data acquired is very important. The system described in this paper is modular in concept, provides intelligence to the various modules, and yields high throughput by the use of parallel processing and high-speed interfaces. Two examples of how this system was implemented are given

  11. Supporting tactical intelligence using collaborative environments and social networking

    Science.gov (United States)

    Wollocko, Arthur B.; Farry, Michael P.; Stark, Robert F.

    2013-05-01

    Modern military environments place an increased emphasis on the collection and analysis of intelligence at the tactical level. The deployment of analytical tools at the tactical level helps support the Warfighter's need for rapid collection, analysis, and dissemination of intelligence. However, given the lack of experience and staffing at the tactical level, most of the available intelligence is not exploited. Tactical environments are staffed by a new generation of intelligence analysts who are well-versed in modern collaboration environments and social networking. An opportunity exists to enhance tactical intelligence analysis by exploiting these personnel strengths, but is dependent on appropriately designed information sharing technologies. Existing social information sharing technologies enable users to publish information quickly, but do not unite or organize information in a manner that effectively supports intelligence analysis. In this paper, we present an alternative approach to structuring and supporting tactical intelligence analysis that combines the benefits of existing concepts, and provide detail on a prototype system embodying that approach. Since this approach employs familiar collaboration support concepts from social media, it enables new-generation analysts to identify the decision-relevant data scattered among databases and the mental models of other personnel, increasing the timeliness of collaborative analysis. Also, the approach enables analysts to collaborate visually to associate heterogeneous and uncertain data within the intelligence analysis process, increasing the robustness of collaborative analyses. Utilizing this familiar dynamic collaboration environment, we hope to achieve a significant reduction of time and skill required to glean actionable intelligence in these challenging operational environments.

  12. Promoting a combination approach to paediatric HIV psychosocial support.

    Science.gov (United States)

    Amzel, Anouk; Toska, Elona; Lovich, Ronnie; Widyono, Monique; Patel, Tejal; Foti, Carrie; Dziuban, Eric J; Phelps, B Ryan; Sugandhi, Nandita; Mark, Daniella; Altschuler, Jenny

    2013-11-01

    is still limited evidence demonstrating which interventions have positive effects on the well being of HIV-infected children. Interventions that improve the psychosocial well being of children living with HIV must be replicable in resource-limited settings, avoiding dependence on specialized staff for implementation.This paper advocates for combination approaches that strengthen the capacity of service providers, expand the availability of age appropriate and family-centred support and equip schools to be more protective and supportive of children living with HIV. The coordination of care with other community-based interventions is also needed to foster more supportive and less stigmatizing environments. To ensure effective, feasible, and scalable interventions, improving the evidence base to document improved outcomes and longer term impact as well as implementation of operational studies to document delivery approaches are needed.

  13. Setting research priorities by applying the combined approach matrix.

    Science.gov (United States)

    Ghaffar, Abdul

    2009-04-01

    Priority setting in health research is a dynamic process. Different organizations and institutes have been working in the field of research priority setting for many years. In 1999 the Global Forum for Health Research presented a research priority setting tool called the Combined Approach Matrix or CAM. Since its development, the CAM has been successfully applied to set research priorities for diseases, conditions and programmes at global, regional and national levels. This paper briefly explains the CAM methodology and how it could be applied in different settings, giving examples and describing challenges encountered in the process of setting research priorities and providing recommendations for further work in this field. The construct and design of the CAM is explained along with different steps needed, including planning and organization of a priority-setting exercise and how it could be applied in different settings. The application of the CAM are described by using three examples. The first concerns setting research priorities for a global programme, the second describes application at the country level and the third setting research priorities for diseases. Effective application of the CAM in different and diverse environments proves its utility as a tool for setting research priorities. Potential challenges encountered in the process of research priority setting are discussed and some recommendations for further work in this field are provided.

  14. How to define and build an effective cyber threat intelligence capability how to understand, justify and implement a new approach to security

    CERN Document Server

    Dalziel, Henry; Carnall, James

    2014-01-01

    Intelligence-Led Security: How to Understand, Justify and Implement a New Approach to Security is a concise review of the concept of Intelligence-Led Security. Protecting a business, including its information and intellectual property, physical infrastructure, employees, and reputation, has become increasingly difficult. Online threats come from all sides: internal leaks and external adversaries; domestic hacktivists and overseas cybercrime syndicates; targeted threats and mass attacks. And these threats run the gamut from targeted to indiscriminate to entirely accidental. Amo

  15. A control strategy for DC-link voltage control containing PV generation and energy storage — An intelligent approach

    OpenAIRE

    Rouzbehi, Kumars; Miranian, Arash; Candela García, José Ignacio; Luna Alloza, Álvaro; Rodríguez Cortés, Pedro

    2014-01-01

    In this paper, DC-link voltage control in DC microgrids with photovoltaic (PV) generation and battery, is addressed based on an intelligent approach. The proposed strategy is based on the modeling of the power interface, i.e. power electronic converter, located between the PV array, battery and DC bus, by use of measurement data. For this purpose, a local model network (LMN) is developed to model the converter and then a local linear control (LLC) strategy is designed based on the LMN. Simula...

  16. Treatment of premature ejaculation: a new combined approach

    Directory of Open Access Journals (Sweden)

    Adel Kurkar

    2015-01-01

    Causes of PE differ considerably. In this paper, we compared the outcomes of two single treatment lines together with a combination of both. The combination therapy was more effective than either line alone.

  17. Intelligent Information Fusion in the Aviation Domain: A Semantic-Web based Approach

    Science.gov (United States)

    Ashish, Naveen; Goforth, Andre

    2005-01-01

    Information fusion from multiple sources is a critical requirement for System Wide Information Management in the National Airspace (NAS). NASA and the FAA envision creating an "integrated pool" of information originally coming from different sources, which users, intelligent agents and NAS decision support tools can tap into. In this paper we present the results of our initial investigations into the requirements and prototype development of such an integrated information pool for the NAS. We have attempted to ascertain key requirements for such an integrated pool based on a survey of DSS tools that will benefit from this integrated pool. We then advocate key technologies from computer science research areas such as the semantic web, information integration, and intelligent agents that we believe are well suited to achieving the envisioned system wide information management capabilities.

  18. Granular, soft and fuzzy approaches for intelligent systems dedicated to professor Ronald R. Yager

    CERN Document Server

    Filev, Dimitar; Beliakov, Gleb

    2017-01-01

    This book offers a comprehensive report on the state-of-the art in the broadly-intended field of “intelligent systems”. After introducing key theoretical issues, it describes a number of promising models for data and system analysis, decision making, and control. It discusses important theories, including possibility theory, the Dempster-Shafer theory, the theory of approximate reasoning, as well as computing with words, together with novel applications in various areas, such as information aggregation and fusion, linguistic data summarization, participatory learning, systems modeling, and many others. By presenting the methods in their application contexts, the book shows how granular computing, soft computing and fuzzy logic techniques can provide novel, efficient solutions to real-world problems. It is dedicated to Professor Ronald R. Yager for his great scientific and scholarly achievements, and for his long-lasting service to the fuzzy logic, and the artificial and computational intelligence communit...

  19. A Combined Approach to Measure Micropollutant Behaviour during Riverbank Filtration

    Science.gov (United States)

    van Driezum, Inge; Saracevic, Ernis; Derx, Julia; Kirschner, Alexander; Sommer, Regina; Farnleitner, Andreas; Blaschke, Alfred Paul

    2016-04-01

    Riverbank filtration (RBF) systems are widely used as natural treatment process. The advantages of RBF over surface water abstraction are the elimination of for example suspended solids, biodegradable compounds (like specific micropollutants), bacteria and viruses (Hiscock and Grischek, 2002). However, in contrast to its importance, remarkably less is known on the respective external (e.g. industrial or municipal sewage) and the internal (e.g. wildlife and agricultural influence) sources of contaminants, the environmental availability and fate of the various hazardous substances, and its potential transport during soil and aquifer passage. The goal of this study is to get an insight in the behaviour of various micropollutants and microbial indicators during riverbank filtration. Field measurements were combined with numerical modelling approaches. The study area comprises an alluvial backwater and floodplain area downstream of Vienna. The river is highly dynamic, with discharges ranging from 900 m3/s during low flow to 11000 m3/s during flood events. Samples were taken in several monitoring wells along a transect extending from the river towards a backwater river in the floodplain. Three of the piezometers were situated in the first 20 meters away from the river in order to obtain information about micropollutant behaviour close to the river. A total of 9 different micropollutants were analysed in grab samples taken under different river flow conditions (n=33). Following enrichment using SPE, analysis was performed using high performance liquid chromatography-tandem mass spectrometry. Faecal indicators (E. coli and enterococci) and bacterial spores were enumerated in sample volumes of 1 L each using cultivation based methods (ISO 16649-1, ISO 7899-2:2000 and ISO 6222). The analysis showed that some compounds, e.g. ibuprofen and diclofenac, were only found in the river. These compounds were already degraded in the first ten meters away from the river. Analysis of

  20. Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach

    OpenAIRE

    Bennett, Casey C.; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This serves two potential functions: 1) a simulation environment for expl...

  1. Automated design of analog and high-frequency circuits a computational intelligence approach

    CERN Document Server

    Liu, Bo; Fernández, Francisco V

    2014-01-01

    Computational intelligence techniques are becoming more and more important for automated problem solving nowadays. Due to the growing complexity of industrial applications and the increasingly tight time-to-market requirements, the time available for thorough problem analysis and development of tailored solution methods is decreasing. There is no doubt that this trend will continue in the foreseeable future. Hence, it is not surprising that robust and general automated problem solving methods with satisfactory performance are needed.

  2. Intelligible design a realistic approach to the philosophy and history of science

    CERN Document Server

    Gonzalo, Julio A

    2014-01-01

    This book provides realistic answers to hotly debated scientific topics: Science is about quantitative aspects of natural realities (physical, chemical, biological) but it is the result of human intellectual inquiry and therefore not "per se" materialistic. This book, with contributions from experts in physics, cosmology, mathematics, engineering, biology and genetics, covers timely and relevant topics such as the origin of the universe, the origin of life on Earth, the origin of man (intelligent life) and the origin of science.

  3. Synergy between Software Product Line and Intelligent Pervasive Middleware-a PLIPerM Approach

    DEFF Research Database (Denmark)

    Zhang, Weishan

    2008-01-01

    with OWL ontology reasoning enhanced BDI (Belief-Desire-Intention) agents, which are the basic building blocks of PLIPerM. Besides the advantages of a software product line, our approachcan handle ontology evolution and keep all related assets in a consistent state. Other advantages include the ability...... to configure Jadex BDI agents for different purpose and to enhance agent intelligence by adding logic reasoning capabilities indirectly to agent beliefs....

  4. A Non-Cognitive Formal Approach to Knowledge Representation in Artificial Intelligence.

    Science.gov (United States)

    1986-06-01

    example, Duda and others translated production rules into a partitioned semantic network (73). Representations were also translated into production...153. Berlin: Springer-Verlag, 1982. 38. Blikle, Andrzej . "Equational Languages," Information and Control, 21: 134-147 (September 1972). 285 39. Ezawa...Conference on Artificial Intelligence, IJCAI-75. 115-121. William Kaufmann, Inc., Los Altos CA, 1975. 73. Duda , Richard 0. and others. "Semantic

  5. An Intelligent Information Retrieval Approach Based on Two Degrees of Uncertainty Fuzzy Ontology

    OpenAIRE

    Maryam Hourali; Gholam Ali Montazer

    2011-01-01

    In spite of the voluminous studies in the field of intelligent retrieval systems, effective retrieving of information has been remained an important unsolved problem. Implementations of different conceptual knowledge in the information retrieval process such as ontology have been considered as a solution to enhance the quality of results. Furthermore, the conceptual formalism supported by typical ontology may not be sufficient to represent uncertainty information due to the lack of clear-cut ...

  6. The prediction of breast cancer biopsy outcomes using two CAD approaches that both emphasize an intelligible decision process

    International Nuclear Information System (INIS)

    Elter, M.; Schulz-Wendtland, R.; Wittenberg, T.

    2007-01-01

    Mammography is the most effective method for breast cancer screening available today. However, the low positive predictive value of breast biopsy resulting from mammogram interpretation leads to approximately 70% unnecessary biopsies with benign outcomes. To reduce the high number of unnecessary breast biopsies, several computer-aided diagnosis (CAD) systems have been proposed in the last several years. These systems help physicians in their decision to perform a breast biopsy on a suspicious lesion seen in a mammogram or to perform a short term follow-up examination instead. We present two novel CAD approaches that both emphasize an intelligible decision process to predict breast biopsy outcomes from BI-RADS findings. An intelligible reasoning process is an important requirement for the acceptance of CAD systems by physicians. The first approach induces a global model based on decison-tree learning. The second approach is based on case-based reasoning and applies an entropic similarity measure. We have evaluated the performance of both CAD approaches on two large publicly available mammography reference databases using receiver operating characteristic (ROC) analysis, bootstrap sampling, and the ANOVA statistical significance test. Both approaches outperform the diagnosis decisions of the physicians. Hence, both systems have the potential to reduce the number of unnecessary breast biopsies in clinical practice. A comparison of the performance of the proposed decision tree and CBR approaches with a state of the art approach based on artificial neural networks (ANN) shows that the CBR approach performs slightly better than the ANN approach, which in turn results in slightly better performance than the decision-tree approach. The differences are statistically significant (p value <0.001). On 2100 masses extracted from the DDSM database, the CRB approach for example resulted in an area under the ROC curve of A(z)=0.89±0.01, the decision-tree approach in A(z)=0.87±0

  7. Combined daylight and intelligent LED lighting - getting the daylight into the buildings; Kombineret dagslys og intelligent LED belysning - fae dagslys ind i bygningerne. Slutrapport

    Energy Technology Data Exchange (ETDEWEB)

    Dam-Hansen, C.; Corell, D.D.; Thorseth, A.; Behrensdorff Poulsen, P. [Technical Univ. of Denmark, DTU Fotonik, DTU Risoe Campus, Roskilde (Denmark); Markvart, J.; Iversen, A.; Logadottir, A. [Aalborg Univ., Statens Byggeforskningsinstitut (SBi), Koebenhavn (Denmark)

    2013-03-15

    The main result of the project is the construction of the new intelligent and dynamic LED lighting system for demonstration and research purposes, and a number of extensive user testing is completed. The LED lighting system is a total system for office lighting with ceiling fixtures and desk lamps, which has made it possible to create a general and workplace lighting in two offices each with two work places. The system is installed in a day light laboratory for such two office spaces. All lamps can be controlled via a developed computer interface, and the desk lamps are further manually controllable by a user via two buttons for color temperature and brightness, respectively. The new intelligent and dynamic lighting system is based on color mixing LED technology and makes it possible to control the color composition, color coordinates and thus the color temperature of the light. Control-wise, the system is pre-programmed to produce white light with a correlated color temperature from 2700 K to 7000 K. The color composition is optimized from the desire for a very good color given at a general CRI value of 92-97 over the area. The system can be dimmed 20-100 %, with no significant change in the light's color properties. A mini-spectrometer is calibrated and built-in in the system and provides the current estimate of daylight brightness and color temperature through measurement of daylight color scheme in the visible range. The system uses daylight properties to control the light from the LED lighting system. The results of user tests show, that the developed possibility to automatically control of light in the office depending on the daylight color temperature is considered to be equally preferred and results in equally satisfied users as a traditional lighting system with even lighting in the room. On the other hand, user results showed that there were both energy savings and more satisfied users to be gained by providing users the opportunity to self-adjust either

  8. Heparan Sulfate Induces Necroptosis in Murine Cardiomyocytes: A Medical-In silico Approach Combining In vitro Experiments and Machine Learning.

    Science.gov (United States)

    Zechendorf, Elisabeth; Vaßen, Phillip; Zhang, Jieyi; Hallawa, Ahmed; Martincuks, Antons; Krenkel, Oliver; Müller-Newen, Gerhard; Schuerholz, Tobias; Simon, Tim-Philipp; Marx, Gernot; Ascheid, Gerd; Schmeink, Anke; Dartmann, Guido; Thiemermann, Christoph; Martin, Lukas

    2018-01-01

    Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical- In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p  machine learning algorithms.

  9. A computational intelligent approach to multi-factor analysis of violent crime information system

    Science.gov (United States)

    Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

    2017-02-01

    Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

  10. A Crowd-Based Intelligence Approach for Measurable Security, Privacy, and Dependability in Internet of Automated Vehicles with Vehicular Fog

    Directory of Open Access Journals (Sweden)

    Ashish Rauniyar

    2018-01-01

    Full Text Available With the advent of Internet of things (IoT and cloud computing technologies, we are in the era of automation, device-to-device (D2D and machine-to-machine (M2M communications. Automated vehicles have recently gained a huge attention worldwide, and it has created a new wave of revolution in automobile industries. However, in order to fully establish automated vehicles and their connectivity to the surroundings, security, privacy, and dependability always remain a crucial issue. One cannot deny the fact that such automatic vehicles are highly vulnerable to different kinds of security attacks. Also, today’s such systems are built from generic components. Prior analysis of different attack trends and vulnerabilities enables us to deploy security solutions effectively. Moreover, scientific research has shown that a “group” can perform better than individuals in making decisions and predictions. Therefore, this paper deals with the measurable security, privacy, and dependability of automated vehicles through the crowd-based intelligence approach that is inspired from swarm intelligence. We have studied three use case scenarios of automated vehicles and systems with vehicular fog and have analyzed the security, privacy, and dependability metrics of such systems. Our systematic approaches to measuring efficient system configuration, security, privacy, and dependability of automated vehicles are essential for getting the overall picture of the system such as design patterns, best practices for configuration of system, metrics, and measurements.

  11. An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

    Energy Technology Data Exchange (ETDEWEB)

    El Hariri, Mohamad [Florida Intl Univ., Miami, FL (United States); Faddel, Samy [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States)

    2017-11-01

    Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted to verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.

  12. Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

    Science.gov (United States)

    Broderick, Ron

    1997-01-01

    The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network

  13. Open Peer Review: Collective Intelligence as a Framework for Theorizing Approaches to Peer Review in the Humanities

    Directory of Open Access Journals (Sweden)

    Jenna Pack Sheffield

    2013-06-01

    Full Text Available This article takes a moderate approach, balancing suggestions for when open peer review can benefit scholarship in the humanities, while offering important concerns authors and editors must consider before deciding to implement the process. I focus on online commenting functions and how they have been—and can be—used for open peer review to help improve the quality of an author’s scholarly work and change the way publishers go about their peer review processes. While open peer review is not necessarily digital, digital technologies allow for a broader range of participants and faster dissemination of knowledge, which is why this article focuses on online open peer review. Open Peer Review: Collective Intelligence as a Framework for Theorizing Approaches to Peer Review in the Humanities, by Jenna Pack Sheffield

  14. An intelligent approach for cooling radiator fault diagnosis based on infrared thermal image processing technique

    International Nuclear Information System (INIS)

    Taheri-Garavand, Amin; Ahmadi, Hojjat; Omid, Mahmoud; Mohtasebi, Seyed Saeid; Mollazade, Kaveh; Russell Smith, Alan John; Carlomagno, Giovanni Maria

    2015-01-01

    This research presents a new intelligent fault diagnosis and condition monitoring system for classification of different conditions of cooling radiator using infrared thermal images. The system was adopted to classify six types of cooling radiator faults; radiator tubes blockage, radiator fins blockage, loose connection between fins and tubes, radiator door failure, coolant leakage, and normal conditions. The proposed system consists of several distinct procedures including thermal image acquisition, image pre-processing, image processing, two-dimensional discrete wavelet transform (2D-DWT), feature extraction, feature selection using a genetic algorithm (GA), and finally classification by artificial neural networks (ANNs). The 2D-DWT is implemented to decompose the thermal images. Subsequently, statistical texture features are extracted from the original images and are decomposed into thermal images. The significant selected features are used to enhance the performance of the designed ANN classifier for the 6 types of cooling radiator conditions (output layer) in the next stage. For the tested system, the input layer consisted of 16 neurons based on the feature selection operation. The best performance of ANN was obtained with a 16-6-6 topology. The classification results demonstrated that this system can be employed satisfactorily as an intelligent condition monitoring and fault diagnosis for a class of cooling radiator. - Highlights: • Intelligent fault diagnosis of cooling radiator using thermal image processing. • Thermal image processing in a multiscale representation structure by 2D-DWT. • Selection features based on a hybrid system that uses both GA and ANN. • Application of ANN as classifier. • Classification accuracy of fault detection up to 93.83%

  15. Multiple Intelligences: Current Trends in Assessment

    Science.gov (United States)

    Harman, Marsha J.; Kordinak, S. Thomas; Bruce, A. Jerry

    2009-01-01

    With his theory of multiple intelligences, Howard Gardner challenged the presumption that intelligence is a single innate entity. He maintained that multiple intelligences exist and are related to specific brain areas and symbol systems. Each of the intelligences has its merits and limits, but by using a multiple intelligences approach, more…

  16. An artificial intelligence approach towards disturbance analysis in nuclear power plants

    International Nuclear Information System (INIS)

    Lindner, A.; Klebau, J.; Fielder, U.; Baldeweg, F.

    1987-01-01

    The scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in wellknown situations. But in cases of emergencies, the operator staff needs a more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application in nuclear power plants. 9 refs. (author)

  17. Smart-system of distance learning of visually impaired people based on approaches of artificial intelligence

    Science.gov (United States)

    Samigulina, Galina A.; Shayakhmetova, Assem S.

    2016-11-01

    Research objective is the creation of intellectual innovative technology and information Smart-system of distance learning for visually impaired people. The organization of the available environment for receiving quality education for visually impaired people, their social adaptation in society are important and topical issues of modern education.The proposed Smart-system of distance learning for visually impaired people can significantly improve the efficiency and quality of education of this category of people. The scientific novelty of proposed Smart-system is using intelligent and statistical methods of processing multi-dimensional data, and taking into account psycho-physiological characteristics of perception and awareness learning information by visually impaired people.

  18. iWordNet: A New Approach to Cognitive Science and Artificial Intelligence

    OpenAIRE

    Chang, Mark; Chang, Monica

    2017-01-01

    One of the main challenges in artificial intelligence or computational linguistics is understanding the meaning of a word or concept. We argue that the connotation of the term “understanding,” or the meaning of the word “meaning,” is merely a word mapping game due to unavoidable circular definitions. These circular definitions arise when an individual defines a concept, the concepts in its definition, and so on, eventually forming a personalized network of concepts, which we call an iWordNet....

  19. Association analysis of multiple traits by an approach of combining ...

    Indian Academy of Sciences (India)

    Lili Chen

    diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic ... genthaler and Thilly 2007), the combined multivariate and ... Because of using reverse regression model, our.

  20. Combination Drug Delivery Approaches in Metastatic Breast Cancer

    Directory of Open Access Journals (Sweden)

    Jun H. Lee

    2012-01-01

    Full Text Available Disseminated metastatic breast cancer needs aggressive treatment due to its reduced response to anticancer treatment and hence low survival and quality of life. Although in theory a combination drug therapy has advantages over single-agent therapy, no appreciable survival enhancement is generally reported whereas increased toxicity is frequently seen in combination treatment especially in chemotherapy. Currently used combination treatments in metastatic breast cancer will be discussed with their challenges leading to the introduction of novel combination anticancer drug delivery systems that aim to overcome these challenges. Widely studied drug delivery systems such as liposomes, dendrimers, polymeric nanoparticles, and water-soluble polymers can concurrently carry multiple anticancer drugs in one platform. These carriers can provide improved target specificity achieved by passive and/or active targeting mechanisms.

  1. Combining formal and functional approaches to topic structure

    NARCIS (Netherlands)

    Zellers, M.; Post, B.

    2012-01-01

    Fragmentation between formal and functional approaches to prosodic variation is an ongoing problem in linguistic research. In particular, the frameworks of the Phonetics of Talk-in-Interaction (PTI) and Empirical Phonology (EP) take very different theoretical and methodological approaches to this

  2. Combining Formal and Functional Approaches to Topic Structure

    Science.gov (United States)

    Zellers, Margaret; Post, Brechtje

    2012-01-01

    Fragmentation between formal and functional approaches to prosodic variation is an ongoing problem in linguistic research. In particular, the frameworks of the Phonetics of Talk-in-Interaction (PTI) and Empirical Phonology (EP) take very different theoretical and methodological approaches to this kind of variation. We argue that it is fruitful to…

  3. Artificial Intelligence approaches in hematopoietic cell transplant: A review of the current status and future directions.

    Science.gov (United States)

    Muhsen, Ibrahim N; ElHassan, Tusneem; Hashmi, Shahrukh K

    2018-06-08

    Currently, the evidence-based literature on healthcare is expanding exponentially. The opportunities provided by the advancement in artificial intelligence (AI) tools i.e. machine learning are appealing in tackling many of the current healthcare challenges. Thus, AI integration is expanding in most fields of healthcare, including the field of hematology. This study aims to review the current applications of AI in the field hematopoietic cell transplant (HCT). Literature search was done involving the following databases: Ovid-Medline including in-Process and Other Non-Indexed Citations and google scholar. The abstracts of the following professional societies: American Society of Haematology (ASH), American Society for Blood and Marrow Transplantation (ASBMT) and European Society for Blood and Marrow Transplantation (EBMT) were also screened. Literature review showed that the integration of AI in the field of HCT has grown remarkably in the last decade and confers promising avenues in diagnosis and prognosis within HCT populations targeting both pre and post-transplant challenges. Studies on AI integration in HCT have many limitations that include poorly tested algorithms, lack of generalizability and limited use of different AI tools. Machine learning techniques in HCT is an intense area of research that needs a lot of development and needs extensive support from hematology and HCT societies / organizations globally since we believe that this would be the future practice paradigm. Key words: Artificial intelligence, machine learning, hematopoietic cell transplant.

  4. Improving societal acceptance of rad waste management policy decisions: an approach based on complex intelligence

    International Nuclear Information System (INIS)

    Rao, Suman

    2008-01-01

    In today's context elaborate public participation exercises are conducted around the world to elicit and incorporate societal risk perceptions into nuclear policy Decision-Making. However, on many occasions, such as in the case of rad waste management, the society remains unconvinced about these decisions. This naturally leads to the questions: are techniques for incorporating societal risk perceptions into the rad waste policy decision making processes sufficiently mature? How could societal risk perceptions and legal normative principles be better integrated in order to render the decisions more equitable and convincing to society? Based on guidance from socio-psychological research this paper postulates that a critical factor for gaining/improving societal acceptance is the quality and adequacy of criteria for option evaluation that are used in the policy decision making. After surveying three rad waste public participation cases, the paper identifies key lacunae in criteria abstraction processes as currently practiced. A new policy decision support model CIRDA: Complex Intelligent Risk Discourse Abstraction model that is based on the heuristic of Risk-Risk Analysis is proposed to overcome these lacunae. CIRDA's functionality of rad waste policy decision making is modelled as a policy decision-making Abstract Intelligent Agent and the agent program/abstraction mappings are presented. CIRDA is then applied to a live (U.K.) rad waste management case and the advantages of this method as compared to the Value Tree Method as practiced in the GB case are demonstrated. (author)

  5. TIPS Placement via Combined Transjugular and Transhepatic Approach for Cavernous Portal Vein Occlusion: Targeted Approach

    Directory of Open Access Journals (Sweden)

    Natanel Jourabchi

    2013-01-01

    Full Text Available Purpose. We report a novel technique which aided recanalization of an occluded portal vein for transjugular intrahepatic portosystemic shunt (TIPS creation in a patient with symptomatic portal vein thrombosis with cavernous transformation. Some have previously considered cavernous transformation a contraindication to TIPS. Case Presentation. 62-year-old man with chronic pancreatitis, portal vein thrombosis, portal hypertension and recurrent variceal bleeding presents with melena and hematemesis. The patient was severely anemic, hemodynamically unstable, and required emergent portal decompression. Attempts to recanalize the main portal vein using traditional transjugular access were unsuccessful. After percutaneous transhepatic right portal vein access and navigation of a wire through the occluded main portal vein, an angioplasty balloon was inflated at the desired site of shunt takeoff. The balloon was targeted and punctured from the transjugular approach, and a wire was passed into the portal system. TIPS placement then proceeded routinely. Conclusion. Although occlusion of the portal vein increases difficulty of performing TIPS, it should not be considered an absolute contraindication. We have described a method for recanalizing an occluded portal vein using a combined transhepatic and transjugular approach for TIPS. This approach may be useful to relieve portal hypertension in patients who fail endoscopic and/or surgical therapies.

  6. A New Approach for Flexible Molecular Docking Based on Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Yi Fu

    2015-01-01

    Full Text Available Molecular docking methods play an important role in the field of computer-aided drug design. In the work, on the basis of the molecular docking program AutoDock, we present QLDock as a tool for flexible molecular docking. For the energy evaluation, the algorithm uses the binding free energy function that is provided by the AutoDock 4.2 tool. The new search algorithm combines the features of a quantum-behaved particle swarm optimization (QPSO algorithm and local search method of Solis and Wets for solving the highly flexible protein-ligand docking problem. We compute the interaction of 23 protein-ligand complexes and compare the results with those of the QDock and AutoDock programs. The experimental results show that our approach leads to substantially lower docking energy and higher docking precision in comparison to Lamarckian genetic algorithm and QPSO algorithm alone. QPSO-ls algorithm was able to identify the correct binding mode of 74% of the complexes. In comparison, the accuracy of QPSO and LGA is 52% and 61%, respectively. This difference in performance rises with increasing complexity of the ligand. Thus, the novel algorithm QPSO-ls may be used to dock ligand with many rotatable bonds with high accuracy.

  7. Vision Guided Intelligent Robot Design And Experiments

    Science.gov (United States)

    Slutzky, G. D.; Hall, E. L.

    1988-02-01

    The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

  8. Clinical Performance of a Combined Approach for the Esthetic ...

    African Journals Online (AJOL)

    2017-09-14

    Sep 14, 2017 ... leads to mild to severe esthetic problems requiring esthetic ... esthetic management of dental fluorosis, ranging from bleaching ... approaches such involving the use of composite or ceramic .... smoking or poor dental health.

  9. A Combined Approach for Component-based Software Design

    NARCIS (Netherlands)

    Guareis de farias, Cléver; van Sinderen, Marten J.; Ferreira Pires, Luis; Quartel, Dick; Baldoni, R.

    2001-01-01

    Component-based software development enables the construction of software artefacts by assembling binary units of production, distribution and deployment, the so-called software components. Several approaches addressing component-based development have been proposed recently. Most of these

  10. Heterogeneity in consumer preference data: A combined approach

    DEFF Research Database (Denmark)

    Poulsen, Carsten Stig; Brockhoff, Per M. B.; Erichsen, Lars

    1997-01-01

    This paper will provide an overview of the problem of heterogeneity in consumer data and various ways of coping with it analytically. It will present a new model that combines latent class regression analysis with randon coefficient regression mod together with principal components regression. Fi...

  11. Management of Combined Natural Risks - A New Approach: Keynote Address

    Science.gov (United States)

    Hanisch, Jörg

    A new attempt is made to illustrate and to quantify the relationships of individual natural hazards, their combinations and the human vulnerability to natural hazards. During many catastrophic events, combinations of different natural events aggravate their occurrence substantially. Earthquakes are frequently associated with heavy landsliding (El Salvador 2001) and heavy rainstorms are able to trigger fast running debris flows and not only floods (like during the Mitch disaster in Central America in 1998). That signifies that natural hazard maps should show the combinations of different hazards and their genetic relationships. To put into effect this, first, the individual hazards have to be assessed and presented in hazard zones (0 to 3). Then these hazards zones will be overlain using GIS techniques. In this way, e.g., an earthquake-prone area which coincides with an area susceptible to landslides (ranking 0 to 3 as well) can show hazard concentrations of up to a value of 6, simply adding the individual hazard zones. To get the result of the corresponding risk zones, the vulnerability maps of human settlements and infra-structure have to be overlain on the maps of these combinations of natural hazards.

  12. Artificial intelligence (AI)-based relational matching and multimodal medical image fusion: generalized 3D approaches

    Science.gov (United States)

    Vajdic, Stevan M.; Katz, Henry E.; Downing, Andrew R.; Brooks, Michael J.

    1994-09-01

    A 3D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on Artificial Intelligence paradigms--in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and segmented into non-touching and non-overlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a `goodness' of matching function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centers of gravity, images are ready for fusion and visualization into a single 3D image of higher clarity.

  13. Control Strategy for Automatic Gantry Crane Systems: A Practical and Intelligent Approach

    Directory of Open Access Journals (Sweden)

    Wahyudi

    2007-12-01

    Full Text Available The use of gantry crane systems for transporting payload is very common in building constructions. However, moving the payload using the crane is not an easy task especially when strict specifications on the swing angle and on the transfer time need to be satisfied. Various attempts in controlling gantry cranes system based on open- loop and closed-loop control systems were proposed. However, most of the proposed controllers were designed based on the model and parameter of the crane system. In general, modeling and parameter identifications are troublesome and time consuming task. To overcome this problem, in this paper, a practical and intelligent control method for automatic gantry crane is introduced and evaluated experimentally. The results show that the proposed method is not only effective for controlling the crane but also robust to parameter variation.

  14. Control Strategy for Automatic Gantry Crane Systems: A Practical and Intelligent Approach

    Directory of Open Access Journals (Sweden)

    Wahyudi

    2008-11-01

    Full Text Available The use of gantry crane systems for transporting payload is very common in building constructions. However, moving the payload using the crane is not an easy task especially when strict specifications on the swing angle and on the transfer time need to be satisfied. Various attempts in controlling gantry cranes system based on open- loop and closed-loop control systems were proposed. However, most of the proposed controllers were designed based on the model and parameter of the crane system. In general, modeling and parameter identifications are troublesome and time consuming task. To overcome this problem, in this paper, a practical and intelligent control method for automatic gantry crane is introduced and evaluated experimentally. The results show that the proposed method is not only effective for controlling the crane but also robust to parameter variation.

  15. Knowledge creation using artificial intelligence: a twin approach to improve breast screening attendance.

    Science.gov (United States)

    Baskaran, Vikraman; Bali, Rajeev K; Arochena, Hisbel; Naguib, Rauf N G; Wallis, Matthew; Wheaton, Margot

    2006-01-01

    Knowledge management (KM) is rapidly becoming established as a core organizational element within the healthcare industry to assist in the delivery of better patient care. KM is a cyclical process which typically starts with knowledge creation (KC), progresses to knowledge sharing, knowledge accessibility and eventually results in new KC (in the same or a related domain). KC plays a significant role in KM as it creates the necessary "seeds" for propagating many more knowledge cycles. This paper addresses the potential of KC in the context of the UK's National Health Service (NHS) breast screening service. KC can be automated to a greater extent by embedding processes within an artificial intelligence (AI) based environment. The UK breast screening service is concerned about non-attendance and this paper discusses issues pertaining to increasing attendance.

  16. Evaluation of trade influence on economic growth rate by computational intelligence approach

    Science.gov (United States)

    Sokolov-Mladenović, Svetlana; Milovančević, Milos; Mladenović, Igor

    2017-01-01

    In this study was analyzed the influence of trade parameters on the economic growth forecasting accuracy. Computational intelligence method was used for the analyzing since the method can handle highly nonlinear data. It is known that the economic growth could be modeled based on the different trade parameters. In this study five input parameters were considered. These input parameters were: trade in services, exports of goods and services, imports of goods and services, trade and merchandise trade. All these parameters were calculated as added percentages in gross domestic product (GDP). The main goal was to select which parameters are the most impactful on the economic growth percentage. GDP was used as economic growth indicator. Results show that the imports of goods and services has the highest influence on the economic growth forecasting accuracy.

  17. ACCOUNTING INFORMATION SYSTEMS: AN APPROACH FOCUSED ON OBJECTS WITH INTELLIGENT AGENTS

    Directory of Open Access Journals (Sweden)

    Marcelo Botelho da Costa Moraes

    2010-01-01

    Full Text Available Accounting aims at the treatment of information related to economic events within organizations. In order to do so, the double entry method is used (debt and credit accounting, which only considers monetary variations. With the development of information technologies, accounting information systems are born. In the 1980’s, the REA model (economic Resources, economic Events and economic Agents is created, which focuses on accounting information records, based on the association of economic resources, economic events and economic agents. The objective of this work is to demonstrate an object-oriented modeling with intelligent agents use, for information development and analysis focused on users. The proposed model is also analyzed according to accounting information quality, necessary for accounting information users, capable to comply with the needs of different user groups, with advantages in applications.

  18. Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

    Science.gov (United States)

    Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

    2014-06-01

    This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

  19. A multi-agent approach to intelligent monitoring in smart grids

    Science.gov (United States)

    Vallejo, D.; Albusac, J.; Glez-Morcillo, C.; Castro-Schez, J. J.; Jiménez, L.

    2014-04-01

    In this paper, we propose a scalable multi-agent architecture to give support to smart grids, paying special attention to the intelligent monitoring of distribution substations. The data gathered by multiple sensors are used by software agents that are responsible for monitoring different aspects or events of interest, such as normal voltage values or unbalanced intensity values that can end up blowing fuses and decreasing the quality of service of end consumers. The knowledge bases of these agents have been built by means of a formal model for normality analysis that has been successfully used in other surveillance domains. The architecture facilitates the integration of new agents and can be easily configured and deployed to monitor different environments. The experiments have been conducted over a power distribution network.

  20. Resilient control of cyber-physical systems against intelligent attacker: a hierarchal stackelberg game approach

    Science.gov (United States)

    Yuan, Yuan; Sun, Fuchun; Liu, Huaping

    2016-07-01

    This paper is concerned with the resilient control under denial-of-service attack launched by the intelligent attacker. The resilient control system is modelled as a multi-stage hierarchical game with a corresponding hierarchy of decisions made at cyber and physical layer, respectively. Specifically, the interaction in the cyber layer between different security agents is modelled as a static infinite Stackelberg game, while in the underlying physical layer the full-information H∞ minimax control with package drops is modelled as a different Stackelberg game. Both games are solved sequentially, which is consistent with the actual situations. Finally, the proposed method is applied to the load frequency control of the power system, which demonstrates its effectiveness.

  1. Exploring multiple intelligences theory in the context of science education: An action research approach

    Science.gov (United States)

    Goodnough, Karen Catherine

    2000-10-01

    Since the publication of Frames of Mind: The Theory in Practice, multiple intelligences, theory (Gardner, 1983) has been used by practitioners in a variety of ways to make teaching and learning more meaningful. However, little attention has been focused on exploring the potential of the theory for science teaching and learning. Consequently, this research study was designed to: (1) explore Howard Gardner's theory of multiple intelligences (1983) and its merit for making science teaching and learning more meaningful; (2) provide a forum for teachers to engage in critical self-reflection about their theory and practice in science education; (3) study the process of action research in the context of science education; and (4) describe the effectiveness of collaborative action research as a framework for teacher development and curriculum development. The study reports on the experiences of four teachers (two elementary teachers, one junior high teacher, and one high school teacher) and myself, a university researcher-facilitator, as we participated in a collaborative action research project. The action research group held weekly meetings over a five-month period (January--May, 1999). The inquiry was a qualitative case study (Stake, 1994) that aimed to understand the perspectives of those directly involved. This was achieved by using multiple methods to collect data: audiotaped action research meetings, fieldnotes, semi-structured interviews, journal writing, and concept mapping. All data were analysed on an ongoing basis. Many positive outcomes resulted from the study in areas such as curriculum development, teacher development, and student learning in science. Through the process of action research, research participants became more reflective about their practice and thus, enhanced their pedagogical content knowledge (Shulman, 1987) in science. Students became more engaged in learning science, gained a greater understanding of how they learn, and experienced a

  2. 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...

  3. Multi-modal Intelligent Seizure Acquisition (MISA) system - A new approach towards seizure detection based on full body motion measures

    DEFF Research Database (Denmark)

    Conradsen, Isa; Beniczky, Sándor; Wolf, Peter

    2009-01-01

    Many epilepsy patients cannot call for help during a seizure, because they are unconscious or because of the affection of their motor system or speech function. This can lead to injuries, medical complications and at worst death. An alarm system setting off at seizure onset could help to avoid...... hazards. Today no reliable alarm systems are available. A Multi-modal Intelligent Seizure Acquisition (MISA) system based on full body motion data seems as a good approach towards detection of epileptic seizures. The system is the first to provide a full body description for epilepsy applications. Three...... test subjects were used for this pilot project. Each subject simulated 15 seizures and in addition performed some predefined normal activities, during a 4-hour monitoring with electromyography (EMG), accelerometer, magnetometer and gyroscope (AMG), electrocardiography (ECG), electroencephalography (EEG...

  4. Combining qualitative and quantitative research approaches in understanding pain

    DEFF Research Database (Denmark)

    Moore, R.

    1996-01-01

    findings. Furthermore, with specific scientific assumptions, combining methods can aid in estimating minimum sample size required for theoretical generalizations from even a qualitative sample. This is based on measures of how accurately subjects describe a given social phenomenon and degree of agreement......There are many research issues about validity and especially reliability in regards to qualitative research results. Generalizability is brought into question to any population base from which a relatively small number of informants are drawn. Sensitivity to new discoveries is an advantage...... of qualitative research while the advantage of quantified survey data is their reliability. This paper argues for combining qualitative and quantitative methods to improve concurrent validity of results by triangulating interviews, observations or focus group data with short surveys for validation of main...

  5. Negative pressure dressing combined with a traditional approach for ...

    African Journals Online (AJOL)

    2011-07-21

    Jul 21, 2011 ... Deep burns of the calvarium due to high-voltage electrical current present serious therapeutic challenges in the healing. In this study, as an alternative approach to the treatment of burned skull, negative pressure dressing is used to facilitate separation of the necrotic bones from healthy margins of the ...

  6. The Effect of Group Therapy With Transactional Analysis Approach on Emotional Intelligence, Executive Functions and Drug Dependency.

    Science.gov (United States)

    Forghani, Masoomeh; Ghanbari Hashem Abadi, Bahram Ali

    2016-06-01

    The aim of the present study was to evaluate the effect of group psychotherapy with transactional analysis (TA) approach on emotional intelligence (EI), executive functions and substance dependency among drug-addicts at rehabilitation centers in Mashhad city, Iran, in 2013. In this quasi-experimental study with pretest, posttest, case- control stages, 30 patients were selected from a rehabilitation center and randomly divided into two groups. The case group received 12 sessions of group psychotherapy with transactional analysis approach. Then the effects of independent variable (group psychotherapy with TA approach) on EI, executive function and drug dependency were assessed. The Bar-on test was used for EI, Stroop test for measuring executive function and morphine test, meth-amphetamines and B2 test for evaluating drug dependency. Data were analyzed using multifactorial covariance analysis, Levenes' analysis, MANCOVA, t-student and Pearson correlation coefficient tests t with SPSS software. Our results showed that group psychotherapy with the TA approach was effective in improving EI, executive functions and decreasing drug dependency (P addicts and prevents addiction recurrence by improving the coping capabilities and some mental functions of the subjects. However, there are some limitations regarding this study including follow-up duration and sample size.

  7. 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.

  8. Combined Modality Approaches in the Management of Adult Glioblastoma

    International Nuclear Information System (INIS)

    Shirazi, Haider A.; Grimm, Sean; Raizer, Jeffrey; Mehta, Minesh P.

    2011-01-01

    Over the past two decades, management of newly diagnosed glioblastoma has undergone significant evolution. While surgery has long been a mainstay of management for this disease, and while radiotherapy has a proven survival role, initial efforts at radiotherapy dose escalation, use of radiosurgery, brachytherapy, and altered fractionation did not improve patient survival. Recently, multiple modality therapy integrating maximal safe resection, postoperative radiation, and new systemic therapies have resulted in improved patient outcomes compared with older regimens utilizing surgery and postoperative radiation alone. Numerous trials are currently underway investigating the combination of surgery, radiation, and systemic therapy with targeted agents to find ways to further improve outcomes for adults with glioblastoma.

  9. Combined Modality Approaches in the Management of Adult Glioblastoma

    Energy Technology Data Exchange (ETDEWEB)

    Shirazi, Haider A. [Department of Radiation Oncology, Feinberg School of Medicine, Northwestern University, Chicago, IL (United States); Grimm, Sean; Raizer, Jeffrey [Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL (United States); Mehta, Minesh P., E-mail: mmehta@nmff.org [Department of Radiation Oncology, Feinberg School of Medicine, Northwestern University, Chicago, IL (United States)

    2011-10-28

    Over the past two decades, management of newly diagnosed glioblastoma has undergone significant evolution. While surgery has long been a mainstay of management for this disease, and while radiotherapy has a proven survival role, initial efforts at radiotherapy dose escalation, use of radiosurgery, brachytherapy, and altered fractionation did not improve patient survival. Recently, multiple modality therapy integrating maximal safe resection, postoperative radiation, and new systemic therapies have resulted in improved patient outcomes compared with older regimens utilizing surgery and postoperative radiation alone. Numerous trials are currently underway investigating the combination of surgery, radiation, and systemic therapy with targeted agents to find ways to further improve outcomes for adults with glioblastoma.

  10. Multicomponent Pharmaceutical Cocrystals: A Novel Approach for Combination Therapy.

    Science.gov (United States)

    Fatima, Zeeshan; Srivastava, Dipti; Kaur, Chanchal Deep

    2018-03-05

    Cocrystallization is a technique for modifying the physicochemical and pharmacokinetic properties of an active pharmaceutical ingredient (API) embodying the concept of supramolecular synthon. Most of the examples cited in the literature are of cocrystals formed between an API and a coformer chosen from the generally recognized as safe (GRAS) substance list, however, few examples exist where a cocrystal consists of two or more APIs. These cocrystals are commonly known as multi API, multi drug or drug- drug cocrystals. The formation of such cocrystals is feasible by virtue of non covalent interactions between the APIs, which help them in retaining their biologic activity. In addition, drug- drug cocrystals also offer the potential solution to the limitations such as solubility, stability differences and chemical interaction between the APIs which is often faced during the traditional combination therapy. Cocrystallization of two or more APIs can be employed for delivery of combination drugs for the better and efficacious management of many complex disorders where existing monotherapies do not furnish the desired therapeutic effect. This review on the existing drug-drug cocrystals is to gain insight for better designing of multi API cocrystals with improved physicochemical and pharmacokinetic profile and its application in multiple target therapy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  11. Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

    Science.gov (United States)

    Noor, Ahmed K.

    2013-12-01

    Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of

  12. Sign language recognition and translation: a multidisciplined approach from the field of artificial intelligence.

    Science.gov (United States)

    Parton, Becky Sue

    2006-01-01

    In recent years, research has progressed steadily in regard to the use of computers to recognize and render sign language. This paper reviews significant projects in the field beginning with finger-spelling hands such as "Ralph" (robotics), CyberGloves (virtual reality sensors to capture isolated and continuous signs), camera-based projects such as the CopyCat interactive American Sign Language game (computer vision), and sign recognition software (Hidden Markov Modeling and neural network systems). Avatars such as "Tessa" (Text and Sign Support Assistant; three-dimensional imaging) and spoken language to sign language translation systems such as Poland's project entitled "THETOS" (Text into Sign Language Automatic Translator, which operates in Polish; natural language processing) are addressed. The application of this research to education is also explored. The "ICICLE" (Interactive Computer Identification and Correction of Language Errors) project, for example, uses intelligent computer-aided instruction to build a tutorial system for deaf or hard-of-hearing children that analyzes their English writing and makes tailored lessons and recommendations. Finally, the article considers synthesized sign, which is being added to educational material and has the potential to be developed by students themselves.

  13. Policy Design for Competitive Retail Electric Institutions: Artificial Intelligence Representations for a Common Property Resource Approach

    Science.gov (United States)

    Pandit, Nitin S.

    The U.S. electricity industry is being restructured to increase competition. Although existing policies may lead to efficient wholesale institutions, designing policies for the retail level is more complex because of intricate interactions between individuals and quasi-monopolistic institutions. It is argued that Hirshman's ideas of "exit" and "voice" (Hirshman, 1970) provide powerful abstractions for design of retail institutions. While competition is a known mechanism of "exit," a novel design of the "voice" mechanism is demonstrated through an artificial intelligence (AI) based software process model. The process model of "voice" in retail institutions is designed within the economic context of electricity distribution -- a common property resource (CPR), characterized by technological uncertainty and path-dependency. First, it is argued that participant feedback (voice) has to be used effectively to manage the CPR. Further, it is noted that the decision process, of using participant feedback (voice) to incrementally manage uncertainty and path-dependencies, is non-monotonic because it requires the decision makers to often retract previously made assumptions and decisions. An AI based process model of "voice" is developed using an assumption-based truth maintenance system. The model can emulate the non-monotonic decision making process and therefore assist in decision support. Such a systematic framework is flexible, consistent, and easily reorganized as assumptions change. It can provide an effective, formal "voice" mechanism to the retail customers and improve institutional performance.

  14. Predicting adsorptive removal of chlorophenol from aqueous solution using artificial intelligence based modeling approaches.

    Science.gov (United States)

    Singh, Kunwar P; Gupta, Shikha; Ojha, Priyanka; Rai, Premanjali

    2013-04-01

    The research aims to develop artificial intelligence (AI)-based model to predict the adsorptive removal of 2-chlorophenol (CP) in aqueous solution by coconut shell carbon (CSC) using four operational variables (pH of solution, adsorbate concentration, temperature, and contact time), and to investigate their effects on the adsorption process. Accordingly, based on a factorial design, 640 batch experiments were conducted. Nonlinearities in experimental data were checked using Brock-Dechert-Scheimkman (BDS) statistics. Five nonlinear models were constructed to predict the adsorptive removal of CP in aqueous solution by CSC using four variables as input. Performances of the constructed models were evaluated and compared using statistical criteria. BDS statistics revealed strong nonlinearity in experimental data. Performance of all the models constructed here was satisfactory. Radial basis function network (RBFN) and multilayer perceptron network (MLPN) models performed better than generalized regression neural network, support vector machines, and gene expression programming models. Sensitivity analysis revealed that the contact time had highest effect on adsorption followed by the solution pH, temperature, and CP concentration. The study concluded that all the models constructed here were capable of capturing the nonlinearity in data. A better generalization and predictive performance of RBFN and MLPN models suggested that these can be used to predict the adsorption of CP in aqueous solution using CSC.

  15. An Intelligent System Approach for Asthma Prediction in Symptomatic Preschool Children

    Directory of Open Access Journals (Sweden)

    E. Chatzimichail

    2013-01-01

    Full Text Available Objectives. In this study a new method for asthma outcome prediction, which is based on Principal Component Analysis and Least Square Support Vector Machine Classifier, is presented. Most of the asthma cases appear during the first years of life. Thus, the early identification of young children being at high risk of developing persistent symptoms of the disease throughout childhood is an important public health priority. Methods. The proposed intelligent system consists of three stages. At the first stage, Principal Component Analysis is used for feature extraction and dimension reduction. At the second stage, the pattern classification is achieved by using Least Square Support Vector Machine Classifier. Finally, at the third stage the performance evaluation of the system is estimated by using classification accuracy and 10-fold cross-validation. Results. The proposed prediction system can be used in asthma outcome prediction with 95.54 % success as shown in the experimental results. Conclusions. This study indicates that the proposed system is a potentially useful decision support tool for predicting asthma outcome and that some risk factors enhance its predictive ability.

  16. Software Development for Auto-Generation of Interlocking Knowledge base using Artificial Intelligence Approach

    Energy Technology Data Exchange (ETDEWEB)

    Ko, Yun Seok [Nanseoul University (Korea); Kim, JOng Sun [Kwangwoon University (Korea)

    1999-06-01

    This paper proposes IIKBAG (Intelligent Interlocking Knowledge Base Generator) which can build automatically the interlocking knowledge base utilized as the real-time interlocking strategy of the electronic interlocking system in order to enhance it's reliability and expansion. The IIKBAG consists of the inference engine and the knowledge base. The former has an auto-learning function which searches all the train routes for the given station model based on heuristic search technique while dynamically searching the model, and then generates automatically the interlocking patterns obtained from the interlocking relations of signal facilities on the routes. The latter is designed as the structure which the real-time expert system embedded on IS (Interlocking System) can use directly in order to enhances the reliability and accuracy. The IIKBAG is implemented in C computer language for the purpose of the build and interface of the station structure database. And, a typical station model is simulated to prove the validity of the proposed IIKBAG. (author). 13 refs., 5 figs., 2 tabs.

  17. Approaches to optimal aquifer management and intelligent control in a multiresolutional decision support system

    Science.gov (United States)

    Orr, Shlomo; Meystel, Alexander M.

    2005-03-01

    Despite remarkable new developments in stochastic hydrology and adaptations of advanced methods from operations research, stochastic control, and artificial intelligence, solutions of complex real-world problems in hydrogeology have been quite limited. The main reason is the ultimate reliance on first-principle models that lead to complex, distributed-parameter partial differential equations (PDE) on a given scale. While the addition of uncertainty, and hence, stochasticity or randomness has increased insight and highlighted important relationships between uncertainty, reliability, risk, and their effect on the cost function, it has also (a) introduced additional complexity that results in prohibitive computer power even for just a single uncertain/random parameter; and (b) led to the recognition in our inability to assess the full uncertainty even when including all uncertain parameters. A paradigm shift is introduced: an adaptation of new methods of intelligent control that will relax the dependency on rigid, computer-intensive, stochastic PDE, and will shift the emphasis to a goal-oriented, flexible, adaptive, multiresolutional decision support system (MRDS) with strong unsupervised learning (oriented towards anticipation rather than prediction) and highly efficient optimization capability, which could provide the needed solutions of real-world aquifer management problems. The article highlights the links between past developments and future optimization/planning/control of hydrogeologic systems. Malgré de remarquables nouveaux développements en hydrologie stochastique ainsi que de remarquables adaptations de méthodes avancées pour les opérations de recherche, le contrôle stochastique, et l'intelligence artificielle, solutions pour les problèmes complexes en hydrogéologie sont restées assez limitées. La principale raison est l'ultime confiance en les modèles qui conduisent à des équations partielles complexes aux paramètres distribués (PDE) à une

  18. Development of artificial intelligence approach to forecasting oyster norovirus outbreaks along Gulf of Mexico coast.

    Science.gov (United States)

    Chenar, Shima Shamkhali; Deng, Zhiqiang

    2018-02-01

    This paper presents an artificial intelligence-based model, called ANN-2Day model, for forecasting, managing and ultimately eliminating the growing risk of oyster norovirus outbreaks. The ANN-2Day model was developed using Artificial Neural Network (ANN) Toolbox in MATLAB Program and 15-years of epidemiological and environmental data for six independent environmental predictors including water temperature, solar radiation, gage height, salinity, wind, and rainfall. It was found that oyster norovirus outbreaks can be forecasted with two-day lead time using the ANN-2Day model and daily data of the six environmental predictors. Forecasting results of the ANN-2Day model indicated that the model was capable of reproducing 19years of historical oyster norovirus outbreaks along the Northern Gulf of Mexico coast with the positive predictive value of 76.82%, the negative predictive value of 100.00%, the sensitivity of 100.00%, the specificity of 99.84%, and the overall accuracy of 99.83%, respectively, demonstrating the efficacy of the ANN-2Day model in predicting the risk of norovirus outbreaks to human health. The 2-day lead time enables public health agencies and oyster harvesters to plan for management interventions and thus makes it possible to achieve a paradigm shift of their daily management and operation from primarily reacting to epidemic incidents of norovirus infection after they have occurred to eliminating (or at least reducing) the risk of costly incidents. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2011-03-01

    Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning. Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city (e.g., Mauritius using a reactive search technique (named as Tabu Search assisted by rough set. Rough set is being used for the extraction of uncertain rules that exist in the databases of parking situations. The inclusion of rough set theory depicts the accuracy and roughness, which are used to characterize uncertainty of the parking lot. Approximation accuracy is employed to depict accuracy of a rough classification [1] according to different dynamic parking scenarios. And as such, the hybrid metaphor proposed comprising of Tabu Search and rough set could provide substantial research directions for other similar hard optimization problems.

  20. 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...

  1. Combined approach to reduced duration integrated leakage rate testing

    International Nuclear Information System (INIS)

    Galanti, P.J.

    1987-01-01

    Even though primary reactor containment allowable leakage rates are expressed in weight percent per day of contained air, engineers have been attempting to define acceptable methods to test in < 24 h as long as these tests have been performed. The reasons to reduce testing duration are obvious, because time not generating electricity is time not generating revenue for the utilities. The latest proposed revision to 10CFR50 Appendix J, concerning integrated leakage rate testing (ILRTs), was supplemented with a draft regulatory guide proposing yet another method. This paper proposes a method that includes elements of currently accepted concepts for short duration testing with a standard statistical check for criteria acceptance. Following presentation of the method, several cases are presented showing the results of these combined criteria

  2. Combination radioimmunotherapy approaches and quantification of immuno-PET

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jin Su [Molecular Imaging Research Center, Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2016-06-15

    Monoclonal antibodies (mAbs), which play a prominent role in cancer therapy, can interact with specific antigens on cancer cells, thereby enhancing the patient' immune response via various mechanisms, or mAbs can act against cell growth factors and, thereby, arrest the proliferation of tumor cells. Radionuclide-labeled mAbs, which are used in radioimmunotherapy (RIT), are effective for cancer treatment because tumor associated-mAbs linked to cytotoxic radionuclides can selectively bind to tumor antigens and release targeted cytotoxic radiation. Immunological positron emission tomography (immuno-PET), which is the combination of PET with mAb, is an attractive option for improving tumor detection and mAb quantification. However, RIT remains a challenge because of the limited delivery of mAb into tumors. The transport and uptake of mAb into tumors is slow and heterogeneous. The tumor microenvironment contributed to the limited delivery of the mAb. During the delivery process of mAb to tumor, mechanical drug resistance such as collagen distribution or physiological drug resistance such as high intestinal pressure or absence of lymphatic vessel would be the limited factor of mAb delivery to the tumor at a potentially lethal mAb concentration. When α-emitter-labeled mAbs were used, deeper penetration of α-emitter-labeled mAb inside tumors was more important because of the short range of the α emitter. Therefore, combination therapy strategies aimed at improving mAb tumor penetration and accumulation would be beneficial for maximizing their therapeutic efficacy against solid tumors.

  3. 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 ...

  4. Modelling traffic flows with intelligent cars and intelligent roads

    NARCIS (Netherlands)

    van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

    2003-01-01

    This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

  5. Inteligência biológica versus inteligência artificial: uma abordagem crítica Biologic intelligence versus artificial intelligence: a critical approach

    Directory of Open Access Journals (Sweden)

    Wilson Luiz Sanvito

    1995-09-01

    Full Text Available Após considerações iniciais sobre inteligência, um estudo comparativo entre inteligência biológica e inteligência artificial é feito. Os especialistas em Inteligência Artificial são de opinião que inteligência é simplesmente uma matéria de manipulação de símbolos físicos. Neste sentido, o objetivo da Inteligência Artificial é entender como a inteligência cerebral funciona em termos de conceitos e técnicas de engenharia. De modo diverso os filósofos da ciência acreditam que os computadores podem ter uma sintaxe, porém não têm uma semântica. No presente trabalho é ressaltado que o complexo cérebro/mente constitui um sistema monolítico, que funciona com funções emergentes em vários níveis de organização hierárquica. Esses níveis hierárquicos não são redutíveis um ao outro. Eles são, no mínimo, três (neuronal, funcional e semântico e funcionam dentro de um plano interacional. Do ponto de vista epistemológico, o complexo cérebro/mente se utiliza de mecanismos lógicos e não-lógicos para lidar com os problemas do dia-a-dia. A lógica é necessária para o processo do pensamento, porém não é suficiente. Ênfase é dada aos mecanismos não-lógicos (lógica nebulosa, heurística, raciocínio intuitivo, os quais permitem à mente desenvolver estratégias para encontrar soluções.After brief considerations about intelligence, a comparative study between biologic and artificial intelligence is made. The specialists in Artificial Intelligence found that intelligence is purely a matter of physical symbol manipulation. The enterprise of Artificial Intelligence aims to understand what we might call Brain Intelligence in terms of concepts and techniques of engineering. However the philosophers believed that computer-machine can have syntax, but can never have semantics. In other words, that they can follow rules, such as those of arithmetic or grammar, but not understand what to us are meanings of symbols

  6. Combining qualitative with quantitative approaches to study contraceptive pill use.

    Science.gov (United States)

    Oakley, D; Yu, M Y; Zhang, Y M; Zhu, X L; Chen, W H; Yao, L

    1999-03-01

    According to large-scale studies, oral contraceptive users become pregnant at rates that exceed ideal use failure rates. It is thought that a major cause is missed pills, but current research on consistent contraceptive pill taking is characterized by inadequate measures and a failure to investigate women's thinking about their own patterns of use. The purpose of this study was to gain some understanding about women's interpretations of consistency in their own pill taking through combining qualitative with quantitative data. The study was conducted in China, where contraception is free and widely available. Five urban and five rural oral contraceptive users were followed for up to three pill-taking cycles during 1996 for a total of 759 person-days. Consistency of pill taking was measured with electronic data obtained from a new blister package made by Anderson Clinical Technologies (Elmhurst, IL). Data from these devices were reviewed and interpreted by the study participants during in-depth private interviews. The users' reasons for missing pills included disruptions in their daily routines, their husband's absence, spotting, and trouble implementing the family planning program's instructions to take one pill per day for 22 days and start the next cycle on the fifth day of menses. One user gave these reasons for two cycles but denied missing numerous pills in her third cycle. Data from a series of four questionnaires showed that most demographic, psychosocial, and service system characteristics were not related to missed pills. However, results suggested that the daily routines of rural living may make consistent use more likely and that instructions for taking the pill may be associated with prolonged pill-free intervals and skipping pills during episodes of spotting. Three of the 10 women were at increased risk of pregnancy during the study period because of their pill-taking pattern. We concluded that the combination of qualitative with quantitative data

  7. A combined PLC and CPU approach to multiprocessor control

    International Nuclear Information System (INIS)

    Harris, J.J.; Broesch, J.D.; Coon, R.M.

    1995-10-01

    A sophisticated multiprocessor control system has been developed for use in the E-Power Supply System Integrated Control (EPSSIC) on the DIII-D tokamak. EPSSIC provides control and interlocks for the ohmic heating coil power supply and its associated systems. Of particular interest is the architecture of this system: both a Programmable Logic Controller (PLC) and a Central Processor Unit (CPU) have been combined on a standard VME bus. The PLC and CPU input and output signals are routed through signal conditioning modules, which provide the necessary voltage and ground isolation. Additionally these modules adapt the signal levels to that of the VME I/O boards. One set of I/O signals is shared between the two processors. The resulting multiprocessor system provides a number of advantages: redundant operation for mission critical situations, flexible communications using conventional TCP/IP protocols, the simplicity of ladder logic programming for the majority of the control code, and an easily maintained and expandable non-proprietary system

  8. The benefit of combining a deep neural network architecture with ideal ratio mask estimation in computational speech segregation to improve speech intelligibility

    DEFF Research Database (Denmark)

    Bentsen, Thomas; May, Tobias; Kressner, Abigail Anne

    2018-01-01

    Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements....... A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech......, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where...

  9. A Computationally Intelligent Approach to the Detection of Wormhole Attacks in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mohammad Nurul Afsar Shaon

    2017-05-01

    Full Text Available A wormhole attack is one of the most critical and challenging security threats for wireless sensor networks because of its nature and ability to perform concealed malicious activities. This paper proposes an innovative wormhole detection scheme to detect wormhole attacks using computational intelligence and an artificial neural network (ANN. Most wormhole detection schemes reported in the literature assume the sensors are uniformly distributed in a network, and, furthermore, they use statistical and topological information and special hardware for their detection. However, these schemes may perform poorly in non-uniformly distributed networks, and, moreover, they may fail to defend against “out of band” and “in band” wormhole attacks. The aim of the proposed research is to develop a detection scheme that is able to detect all kinds of wormhole attacks in both uniformly and non-uniformly distributed sensor networks. Furthermore, the proposed research does not require any special hardware and causes no significant network overhead throughout the network. Most importantly, the probable location of the malicious nodes can be identified by the proposed ANN based detection scheme. We evaluate the efficacy of the proposed detection scheme in terms of detection accuracy, false positive rate, and false negative rate. The performance of the proposed algorithm is also compared with other machine learning techniques (i.e. SVM and regularized nonlinear logistic regression (LR based detection models. The simulation results show that proposed ANN based algorithm outperforms the SVM or LR based detection schemes in terms of detection accuracy, false positive rate, and false negative rates.

  10. 视觉移动机器人的模糊智能路径规划%Intelligent Path Planning of Vision- Based Mobile Robot with Fuzzy Approach

    Institute of Scientific and Technical Information of China (English)

    张一巍; 黄源清

    2002-01-01

    The path planning problem for intelligent mobile robots inwbves two main problems: the represent of task emionment including obstacles and the development of a strategy to determine a collision - free route. In this paper, new approaches have been developed to solve these problems .The first problem was solve using the fuzzy system approach, which represent obstacles with a circle. The other problem was overcome throughthe use of a strategy selector, which chooses the best stategy between velocity control strategy and direction control strategy.

  11. A combined ANP-delphi approach to evaluate sustainable tourism

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Melon, Monica, E-mail: mgarciam@dpi.upv.es [INGENIO (CSIC-UPV), Universitat Politecnica de Valencia, Camino de Vera s/n, 46022 Valencia (Spain); Gomez-Navarro, Tomas, E-mail: tgomez@dpi.upv.es [Depto. Proyectos Ingenieria, Universitat Politecnica de Valencia, Camino de Vera s/n 46022 Valencia (Spain); Acuna-Dutra, Silvia, E-mail: sacuna@unime.edu.ve [Universidad Metropolitana de Caracas, Caracas (Venezuela, Bolivarian Republic of)

    2012-04-15

    The evaluation of sustainable tourism strategies promoted by National Parks (NP) related stakeholders is a key concern for NP managers. To help them in their strategic evaluation procedures, in this paper we propose a methodology based on the Analytic Network Process and a Delphi-type judgment-ensuring procedure. The approach aims at involving stakeholders in a participatory and consensus-building process. The methodology was applied to Los Roques NP in Venezuela. The problem included three sustainable tourism strategies defined by the stakeholders: eco-efficient resorts, eco-friendly leisure activities and ecological transportation systems. Representatives of eight stakeholders participated in the methodology. 13 sustainability criteria were selected. Results provide some important insights into the overall philosophy and underlying participants' conception of what sustainable development of Los Roques NP means. This conception is broadly shared by stakeholders as they coincided in the weights of most of the criteria, which were assigned individually through the questionnaire. It is particularly noteworthy that tourists and environmentalists almost fully match in their assessments of criteria but not of the alternatives. Moreover, there is a great agreement in the final assessment. This suggests that the regular contact among the different stakeholders, i.e. tourists with inhabitants, authorities with environmentalists, tour operators with representatives of the ministry, etc. has led to a common understanding of the opportunities and threats for the NP. They all agreed that the procedure enhances participation and transparency and it is a necessary source of information and support for their decisions.

  12. EPR design: A combined approach on safety and economic competitiveness

    International Nuclear Information System (INIS)

    Griedl, R.; Sturm, J.; Degrave, C.; Kappler, F.; Martin-Onraet, M.

    2001-01-01

    Starting in 1991, the French and German cooperation led to common work based on the experience of the two designers FRAMATOME and SIEMENS KWU with all their know how, the most important utilities in France and Germany operating NPP and the technical supports of the Licensing Authorities GRS and IPSN. The conclusion of that work was the issue in November 1997 and February 1999 respectively of two Basic Design reports for a European Pressurized Reactor (EPR) with a power of 4250 MWth and 4900 MWth. The Basic Design approach was led under two key items: Enhancement of the overall safety level by implementation of design measures to: make the plant less dependant to common cause failures; practically eliminate all high pressure core melt sequences which could lead to important radioactive releases to the environment; implement specific systems to face severe accident situation with low-pressure core melt. Use of the many years of experiences in two different nuclear designs is to reach an overall availability figure over 91%, partly due to design improvements on the safety level. With such an objective, demonstrated by feedback of experience on already operating plants, the EPR project can be proposed as a competitive alternative to the most recent fossil plants. (author)

  13. A combined ANP-delphi approach to evaluate sustainable tourism

    International Nuclear Information System (INIS)

    García-Melón, Mónica; Gómez-Navarro, Tomás; Acuña-Dutra, Silvia

    2012-01-01

    The evaluation of sustainable tourism strategies promoted by National Parks (NP) related stakeholders is a key concern for NP managers. To help them in their strategic evaluation procedures, in this paper we propose a methodology based on the Analytic Network Process and a Delphi-type judgment-ensuring procedure. The approach aims at involving stakeholders in a participatory and consensus-building process. The methodology was applied to Los Roques NP in Venezuela. The problem included three sustainable tourism strategies defined by the stakeholders: eco-efficient resorts, eco-friendly leisure activities and ecological transportation systems. Representatives of eight stakeholders participated in the methodology. 13 sustainability criteria were selected. Results provide some important insights into the overall philosophy and underlying participants' conception of what sustainable development of Los Roques NP means. This conception is broadly shared by stakeholders as they coincided in the weights of most of the criteria, which were assigned individually through the questionnaire. It is particularly noteworthy that tourists and environmentalists almost fully match in their assessments of criteria but not of the alternatives. Moreover, there is a great agreement in the final assessment. This suggests that the regular contact among the different stakeholders, i.e. tourists with inhabitants, authorities with environmentalists, tour operators with representatives of the ministry, etc. has led to a common understanding of the opportunities and threats for the NP. They all agreed that the procedure enhances participation and transparency and it is a necessary source of information and support for their decisions.

  14. Using a Competitive Approach to Improve Military Simulation Artificial Intelligence Design

    National Research Council Canada - National Science Library

    Stoykov, Sevdalin

    2008-01-01

    ...) design can lead to improvement of the AI solutions used in military simulations. To demonstrate the potential of the competitive approach, ORTS, a real-time strategy game engine, and its competition setup are used...

  15. Intelligent measurement and compensation of linear motor force ripple: a projection-based learning approach in the presence of noise

    Science.gov (United States)

    Liu, Yang; Song, Fazhi; Yang, Xiaofeng; Dong, Yue; Tan, Jiubin

    2018-06-01

    Due to their structural simplicity, linear motors are increasingly receiving attention for use in high velocity and high precision applications. The force ripple, as a space-periodic disturbance, however, would deteriorate the achievable dynamic performance. Conventional force ripple measurement approaches are time-consuming and have high requirements on the experimental conditions. In this paper, a novel learning identification algorithm is proposed for force ripple intelligent measurement and compensation. Existing identification schemes always use all the error signals to update the parameters in the force ripple. However, the error induced by noise is non-effective for force ripple identification, and even deteriorates the identification process. In this paper only the most pertinent information in the error signal is utilized for force ripple identification. Firstly, the effective error signals caused by the reference trajectory and the force ripple are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the linear motor as well as the sinusoidal model of the force ripple. The time delay in the linear motor is compensated in the basis functions. Then, a data-driven approach is proposed to design the learning gain. It balances the trade-off between convergence speed and robustness against noise. Simulation and experimental results validate the proposed method and confirm its effectiveness and superiority.

  16. Engineering nanomaterials with a combined electrochemical and molecular biomimetic approach

    Science.gov (United States)

    Dai, Haixia

    Biocomposite materials, such as bones, teeth, and shells, are created using mild aqueous solution-based processes near room temperature. Proteins add flexibility to these processes by facilitating the nucleation, growth, and ordering of specific inorganic materials into hierarchical structures. We aim to develop a biomimetic strategy for engineering technologically relevant inorganic materials with controlled compositions and structures, as Nature does, using proteins to orchestrate material formation and assembly. This approach involves three basic steps: (i) preparation of inorganic substrates compatible with combinatorial polypeptide screening; (ii) identification of inorganic-binding polypeptides and their engineering into inorganic-binding proteins; and (iii) protein-mediated inorganic nucleation and organization. Cuprous oxide (Cu2O), a p-type semiconductor, has been used to demonstrate all three steps. Zinc oxide (ZnO), an n-type semiconductor, has been used to show the generality of selected steps. Step (i), preparation of high quality inorganic substrates to select inorganic-binding polypeptides, was accomplished using electrochemical microfabrication to grow and pattern Cu2O and ZnO. Raman spectroscopy and x-ray photoelectron spectroscopy were used to verify phase purity and compositional stability of these surfaces during polypeptide screening. Step (ii), accomplished in collaboration with personnel in Prof Baneyx' lab at the University of Washington, involved incubating the inorganic substrates with the FliTrx(TM) random peptide library to identify cysteine-constrained dodecapeptides that bind the targeted inorganic. Insertion of a Cu2O-binding dodecapeptide into the DNA-binding protein TraI endowed the engineered TraI with strong affinity for Cu2O (Kd ≈ 10 -8 M). Finally, step (iii) involved nonequilibrium synthesis and organization of Cu2O nanoparticles, taking advantage of the inorganic and DNA recognition properties of the engineered TraI. The

  17. Surgical treatment of traumatic cervical facet dislocation: anterior, posterior or combined approaches?

    Directory of Open Access Journals (Sweden)

    Catarina C. Lins

    Full Text Available ABSTRACT Surgical treatment is well accepted for patients with traumatic cervical facet joint dislocations (CFD, but there is uncertainty over which approach is better: anterior, posterior or combined. We performed a systematic literature review to evaluate the indications for anterior and posterior approaches in the management of CFD. Anterior approaches can restore cervical lordosis, and cause less postoperative pain and less wound problems. Posterior approaches are useful for direct reduction of locked facet joints and provide stronger fixation from a biomechanical point of view. Combined approaches can be used in more complex cases. Although both anterior and posterior approaches can be used interchangeably, there are some patients who may benefit from one of them over the other, as discussed in this review. Surgeons who treat cervical spine trauma should be able to perform both procedures as well as combined approaches to adequately manage CFD and improve patients’ final outcomes.

  18. 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.

  19. Conflicts versus analytical redundancy relations: a comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives.

    Science.gov (United States)

    Cordier, Marie-Odile; Dague, Philippe; Lévy, François; Montmain, Jacky; Staroswiecki, Marcel; Travé-Massuyès, Louise

    2004-10-01

    Two distinct and parallel research communities have been working along the lines of the model-based diagnosis approach: the fault detection and isolation (FDI) community and the diagnostic (DX) community that have evolved in the fields of automatic control and artificial intelligence, respectively. This paper clarifies and links the concepts and assumptions that underlie the FDI analytical redundancy approach and the DX consistency-based logical approach. A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.

  20. Combining metric episodes with semantic event concepts within the Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS)

    Science.gov (United States)

    Kelley, Troy D.; McGhee, S.

    2013-05-01

    This paper describes the ongoing development of a robotic control architecture that inspired by computational cognitive architectures from the discipline of cognitive psychology. The Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS) combines symbolic and sub-symbolic representations of knowledge into a unified control architecture. The new architecture leverages previous work in cognitive architectures, specifically the development of the Adaptive Character of Thought-Rational (ACT-R) and Soar. This paper details current work on learning from episodes or events. The use of episodic memory as a learning mechanism has, until recently, been largely ignored by computational cognitive architectures. This paper details work on metric level episodic memory streams and methods for translating episodes into abstract schemas. The presentation will include research on learning through novelty and self generated feedback mechanisms for autonomous systems.

  1. An exploratory trial exploring the use of a multiple intelligences teaching approach (MITA) for teaching clinical skills to first year undergraduate nursing students.

    Science.gov (United States)

    Sheahan, Linda; While, Alison; Bloomfield, Jacqueline

    2015-12-01

    The teaching and learning of clinical skills is a key component of nurse education programmes. The clinical competency of pre-registration nursing students has raised questions about the proficiency of teaching strategies for clinical skill acquisition within pre-registration education. This study aimed to test the effectiveness of teaching clinical skills using a multiple intelligences teaching approach (MITA) compared with the conventional teaching approach. A randomised controlled trial was conducted. Participants were randomly allocated to an experimental group (MITA intervention) (n=46) and a control group (conventional teaching) (n=44) to learn clinical skills. Setting was in one Irish third-level educational institution. Participants were all first year nursing students (n=90) in one institution. The experimental group was taught using MITA delivered by the researcher while the control group was taught by a team of six experienced lecturers. Participant preference for learning was measured by the Index of Learning Styles (ILS). Participants' multiple intelligence (MI) preferences were measured with a multiple intelligences development assessment scale (MIDAS). All participants were assessed using the same objective structured clinical examination (OSCE) at the end of semester one and semester two. MI assessment preferences were measured by a multiple intelligences assessment preferences questionnaire. The MITA intervention was evaluated using a questionnaire. The strongest preference on ILS for both groups was the sensing style. The highest MI was interpersonal intelligence. Participants in the experimental group had higher scores in all three OSCEs (pmultiple choice questions as methods of assessment. MITA was evaluated positively. The study findings support the use of MITA for clinical skills teaching and advance the understanding of how MI teaching approaches may be used in nursing education. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Fostering Creativity: A Multiple Intelligences Approach to Designing Learning in Undergraduate Fine Art

    Science.gov (United States)

    Clarke, Angela; Cripps, Peter

    2012-01-01

    Curriculum and pedagogy in undergraduate fine art can promote an approach to learning creativity that is more about being an artist than knowing about art. Lecturers can provide a road map for developing particular dispositions, in relation to student ideas and perceptions, to foster personalised creativity. This requires that lecturers have an…

  3. Artificial Intelligence and Second Language Learning: An Efficient Approach to Error Remediation

    Science.gov (United States)

    Dodigovic, Marina

    2007-01-01

    While theoretical approaches to error correction vary in the second language acquisition (SLA) literature, most sources agree that such correction is useful and leads to learning. While some point out the relevance of the communicative context in which the correction takes place, others stress the value of consciousness-raising. Trying to…

  4. An evolutionary approach for business process redesign : towards an intelligent system

    NARCIS (Netherlands)

    Netjes, M.; Limam Mansar, S.; Reijers, H.A.; Aalst, van der W.M.P.; Cardoso, J.; Cordeiro, J.; Filipe, J.

    2007-01-01

    Although extensive literature on BPR is available, there is still a lack of concrete guidance on actually changing processes for the better. It is our goal to provide a redesign approach which describes and supports the steps to derive from an existing process a better performing redesign. In this

  5. Competitive Intelligence and the Information Center.

    Science.gov (United States)

    Greene, H. Frances

    1988-01-01

    Examines the competitive intelligence approach to corporate information gathering, and discusses how it differs from the traditional library information center approach. Steps for developing a competitive intelligence system in the library information center are suggested. (33 references) (MES)

  6. Comparing detection and disclosure of traffic incidents in social networks: an intelligent approach based on Twitter vs. Waze

    Directory of Open Access Journals (Sweden)

    Sebastián Vallejos

    2018-03-01

    Full Text Available Nowadays, social networks have become  in a  communication  medium widely  used to disseminate any type  of  information. In  particular,  the  shared  information  in  social  networks  usually  includes  a  considerable number of traffic incidents reports of specific cities. In light of this, specialized social networks have emerged for detecting and disseminating traffic incidents, differentiating from generic social networks in which a wide variety of  topics  are  communicated.  In this  context,  Twitter  is  a  case  in  point  of  a  generic  social  network  in  which  its users often share information about traffic incidents, while Waze is a social network specialized in traffic. In this paper we present a comparative study between Waze and an intelligent approach that detects traffic incidents by analyzing publications shared in Twitter. The comparative study was carried out considering Ciudad Autónoma de Buenos  Aires  (CABA,  Argentina,  as  the  region  of  interest.  The results of this work suggest that both social networks should be considered as complementary sources of information. This conclusion is based on the fact that the proportion of mutual detections, i.e. traffic incidents detected by both approaches, was considerably low since it did not exceed 6% of the cases. Moreover, the results do not show that any of the approaches tend to anticipate in time to the other one in the detection of traffic incidents.

  7. 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

  8. A business intelligence approach using web search tools and online data reduction techniques to examine the value of product-enabled services

    DEFF Research Database (Denmark)

    Tanev, Stoyan; Liotta, Giacomo; Kleismantas, Andrius

    2015-01-01

    in Canada and Europe. It adopts an innovative methodology based on online textual data that could be implemented in advanced business intelligence tools aiming at the facilitation of innovation, marketing and business decision making. Combinations of keywords referring to different aspects of service value......-service innovation as a competitive advantage on the marketplace. On the other hand, the focus of EU firms on innovative hybrid offerings is not explicitly related to business differentiation and competitiveness....

  9. Copyright on the internet: achieving security through electronic devices an artificial intelligence approach

    OpenAIRE

    Niebla Zatarain, Jesus Manuel

    2018-01-01

    This thesis aims to provide a novel approach to ensure copyright compliance online, appropriate for the Internet of Things and the robotic revolution. To achieve this, three different aims are pursued: - A novel application of “by design” solutions to copyright protection is introduced and its advantages and disadvantages discussed from a jurisprudential and doctrinal perspective. - On the basis of this, a new theoretical framework for legal AI is developed that draws on ...

  10. An approach to modeling operator's cognitive behavior using artificial intelligence techniques in emergency operating event sequences

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Sur, Sang Moon; Lee, Yong Hee; Park, Young Taeck; Moon, Sang Joon

    1994-01-01

    Computer modeling of an operator's cognitive behavior is a promising approach for the purpose of human factors study and man-machine systems assessment. In this paper, the states of the art in modeling operator behavior and the current status in developing an operator's model (MINERVA - NPP) are presented. The model is constructed as a knowledge-based system of a blackboard framework and is simulated based on emergency operating procedures

  11. Intelligent control system Cellular Robotics Approach to Nuclear Plant control and maintenance

    International Nuclear Information System (INIS)

    Fukuda, Toshio; Sekiyama, Kousuke; Xue Guoqing; Ueyama, Tsuyoshi.

    1994-01-01

    This paper presents the concept of Cellular Robotic System (CEBOT) and describe the strategy of a distributed sensing, control and planning as a Cellular Robotics Approach to the Nuclear Plant control and maintenance. Decentralized System is effective in large plant and The CEBOT possesses desirable features for realization of Nuclear Plant control and maintenance because of its flexibility and adaptability. Also, as related on going research work, self-organizing manipulator and communication issues are mentioned. (author)

  12. Role of theory of mind and executive function in explaining social intelligence: a structural equation modeling approach.

    Science.gov (United States)

    Yeh, Zai-Ting

    2013-01-01

    Social intelligence is the ability to understand others and the social context effectively and thus to interact with people successfully. Research has suggested that the theory of mind (ToM) and executive function may play important roles in explaining social intelligence. The specific aim of the present study was to test with structural equation modeling (SEM) the hypothesis that performance on ToM tasks is more associated with social intelligence in the elderly than is performance on executive functions. One hundred and seventy-seven participants (age 56-96) completed ToM, executive function, and other basic cognition tasks, and were rated with social intelligence scales. The SEM results showed that ToM and executive function were strongly correlated (0.54); however, only the path coefficient from ToM to social intelligence, and not from executive function, was significant (0.37). ToM performance, but not executive function, was strongly correlated with social intelligence among elderly individuals. ToM and executive function might play different roles in social behavior during normal aging; however, based on the present results, it is possible that ToM might play an important role in social intelligence.

  13. Prediction of hearing loss among the noise-exposed workers in a steel factory using artificial intelligence approach.

    Science.gov (United States)

    Aliabadi, Mohsen; Farhadian, Maryam; Darvishi, Ebrahim

    2015-08-01

    Prediction of hearing loss in noisy workplaces is considered to be an important aspect of hearing conservation program. Artificial intelligence, as a new approach, can be used to predict the complex phenomenon such as hearing loss. Using artificial neural networks, this study aims to present an empirical model for the prediction of the hearing loss threshold among noise-exposed workers. Two hundred and ten workers employed in a steel factory were chosen, and their occupational exposure histories were collected. To determine the hearing loss threshold, the audiometric test was carried out using a calibrated audiometer. The personal noise exposure was also measured using a noise dosimeter in the workstations of workers. Finally, data obtained five variables, which can influence the hearing loss, were used for the development of the prediction model. Multilayer feed-forward neural networks with different structures were developed using MATLAB software. Neural network structures had one hidden layer with the number of neurons being approximately between 5 and 15 neurons. The best developed neural networks with one hidden layer and ten neurons could accurately predict the hearing loss threshold with RMSE = 2.6 dB and R(2) = 0.89. The results also confirmed that neural networks could provide more accurate predictions than multiple regressions. Since occupational hearing loss is frequently non-curable, results of accurate prediction can be used by occupational health experts to modify and improve noise exposure conditions.

  14. 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.

  15. 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,...

  16. 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)

  17. 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

  18. Comet Methy-sens and DNMTs transcriptional analysis as a combined approach in epigenotoxicology

    Directory of Open Access Journals (Sweden)

    Alessio Perotti

    2015-05-01

    In conclusion, our data demonstrate that Comet Methy-sens, in combination with the analysis of transcriptional levels of DNA methyl transferases, represents a simple and multifunctional approach to implement biomonitoring studies on epigenotoxicological effects of known and unknown xenobiotics.

  19. An Adaptive Intelligent Integrated Lighting Control Approach for High-Performance Office Buildings

    Science.gov (United States)

    Karizi, Nasim

    An acute and crucial societal problem is the energy consumed in existing commercial buildings. There are 1.5 million commercial buildings in the U.S. with only about 3% being built each year. Hence, existing buildings need to be properly operated and maintained for several decades. Application of integrated centralized control systems in buildings could lead to more than 50% energy savings. This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.'s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.

  20. 10th International Symposium on Intelligent Distributed Computing

    CERN Document Server

    Seghrouchni, Amal; Beynier, Aurélie; Camacho, David; Herpson, Cédric; Hindriks, Koen; Novais, Paulo

    2017-01-01

    This book presents the combined peer-reviewed proceedings of the tenth International Symposium on Intelligent Distributed Computing (IDC’2016), which was held in Paris, France from October 10th to 12th, 2016. The 23 contributions address a range of topics related to theory and application of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

  1. Application of algorithms and artificial-intelligence approach for locating multiple harmonics in distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Y.-Y.; Chen, Y.-C. [Chung Yuan University (China). Dept. of Electrical Engineering

    1999-05-01

    A new method is proposed for locating multiple harmonic sources in distribution systems. The proposed method first determines the proper locations for metering measurement using fuzzy clustering. Next, an artificial neural network based on the back-propagation approach is used to identify the most likely location for multiple harmonic sources. A set of systematic algorithmic steps is developed until all harmonic locations are identified. The simulation results for an 18-busbar system show that the proposed method is very efficient in locating the multiple harmonics in a distribution system. (author)

  2. An Artificial Intelligence Approach for Modeling and Prediction of Water Diffusion Inside a Carbon Nanotube

    Science.gov (United States)

    2009-01-01

    Modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS) is presented to solve this problem. The proposed ANFIS approach can construct an input–output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input–output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down. PMID:20596382

  3. An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications

    Science.gov (United States)

    Schutte, P. C.; Abbott, K. H.

    1986-01-01

    Real-time onboard fault monitoring and diagnosis for aircraft applications, whether performed by the human pilot or by automation, presents many difficult problems. Quick response to failures may be critical, the pilot often must compensate for the failure while diagnosing it, his information about the state of the aircraft is often incomplete, and the behavior of the aircraft changes as the effect of the failure propagates through the system. A research effort was initiated to identify guidelines for automation of onboard fault monitoring and diagnosis and associated crew interfaces. The effort began by determining the flight crew's information requirements for fault monitoring and diagnosis and the various reasoning strategies they use. Based on this information, a conceptual architecture was developed for the fault monitoring and diagnosis process. This architecture represents an approach and a framework which, once incorporated with the necessary detail and knowledge, can be a fully operational fault monitoring and diagnosis system, as well as providing the basis for comparison of this approach to other fault monitoring and diagnosis concepts. The architecture encompasses all aspects of the aircraft's operation, including navigation, guidance and controls, and subsystem status. The portion of the architecture that encompasses subsystem monitoring and diagnosis was implemented for an aircraft turbofan engine to explore and demonstrate the AI concepts involved. This paper describes the architecture and the implementation for the engine subsystem.

  4. Management of interstitial ectopic pregnancies with a combined intra-amniotic and systemic approach.

    Science.gov (United States)

    Swank, Morgan L; Harken, Tabetha R; Porto, Manuel

    2013-08-01

    Approximately 2% of all pregnancies are ectopic; of these, 4% are interstitial or cervical. There exists no clear consensus as to whether surgical or medical management is superior. We present three cases of advanced nonfallopian tube ectopic pregnancies from 6 to 8 weeks of gestation. Our first two cases were managed with a combined intrafetal, intra-amniotic and systemic approach using methotrexate and potassium chloride, whereas our third case was managed with an intra-amniotic approach alone. Our combined approach cases were successful, with resolution of human chorionic gonadotropin in 50 and 34 days, whereas our single approach case re-presented with bleeding requiring uterine artery embolization and operative removal of products of conception. Patients presenting with advanced interstitial or cervical pregnancies who are clinically stable can be offered medical management with a combined approach.

  5. Artificial intelligence and finite element modelling for monitoring flood defence structures

    NARCIS (Netherlands)

    Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

    2011-01-01

    We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the

  6. Critical combinations of radiation dose and volume predict intelligence quotient and academic achievement scores after craniospinal irradiation in children with medulloblastoma.

    Science.gov (United States)

    Merchant, Thomas E; Schreiber, Jane E; Wu, Shengjie; Lukose, Renin; Xiong, Xiaoping; Gajjar, Amar

    2014-11-01

    To prospectively follow children treated with craniospinal irradiation to determine critical combinations of radiation dose and volume that would predict for cognitive effects. Between 1996 and 2003, 58 patients (median age 8.14 years, range 3.99-20.11 years) with medulloblastoma received risk-adapted craniospinal irradiation followed by dose-intense chemotherapy and were followed longitudinally with multiple cognitive evaluations (through 5 years after treatment) that included intelligence quotient (estimated intelligence quotient, full-scale, verbal, and performance) and academic achievement (math, reading, spelling) tests. Craniospinal irradiation consisted of 23.4 Gy for average-risk patients (nonmetastatic) and 36-39.6 Gy for high-risk patients (metastatic or residual disease >1.5 cm(2)). The primary site was treated using conformal or intensity modulated radiation therapy using a 2-cm clinical target volume margin. The effect of clinical variables and radiation dose to different brain volumes were modeled to estimate cognitive scores after treatment. A decline with time for all test scores was observed for the entire cohort. Sex, race, and cerebrospinal fluid shunt status had a significant impact on baseline scores. Age and mean radiation dose to specific brain volumes, including the temporal lobes and hippocampi, had a significant impact on longitudinal scores. Dichotomized dose distributions at 25 Gy, 35 Gy, 45 Gy, and 55 Gy were modeled to show the impact of the high-dose volume on longitudinal test scores. The 50% risk of a below-normal cognitive test score was calculated according to mean dose and dose intervals between 25 Gy and 55 Gy at 10-Gy increments according to brain volume and age. The ability to predict cognitive outcomes in children with medulloblastoma using dose-effects models for different brain subvolumes will improve treatment planning, guide intervention, and help estimate the value of newer methods of irradiation. Copyright © 2014

  7. Key performance indicators (KPIs) and priority setting in using the multi-attribute approach for assessing sustainable intelligent buildings

    Energy Technology Data Exchange (ETDEWEB)

    ALwaer, H. [The University of Dundee, School of Architecture, Matthew Building, 13 Perth Road, Dundee DD1 4HT (United Kingdom); Clements-Croome, D.J. [School of Construction Management and Engineering, The University of Reading, Whiteknights, PO Box 219, Reading RG6 6AW (United Kingdom)

    2010-04-15

    The main objectives of this paper are to: firstly, identify key issues related to sustainable intelligent buildings (environmental, social, economic and technological factors); develop a conceptual model for the selection of the appropriate KPIs; secondly, test critically stakeholder's perceptions and values of selected KPIs intelligent buildings; and thirdly develop a new model for measuring the level of sustainability for sustainable intelligent buildings. This paper uses a consensus-based model (Sustainable Built Environment Tool- SuBETool), which is analysed using the analytical hierarchical process (AHP) for multi-criteria decision-making. The use of the multi-attribute model for priority setting in the sustainability assessment of intelligent buildings is introduced. The paper commences by reviewing the literature on sustainable intelligent buildings research and presents a pilot-study investigating the problems of complexity and subjectivity. This study is based upon a survey perceptions held by selected stakeholders and the value they attribute to selected KPIs. It is argued that the benefit of the new proposed model (SuBETool) is a 'tool' for 'comparative' rather than an absolute measurement. It has the potential to provide useful lessons from current sustainability assessment methods for strategic future of sustainable intelligent buildings in order to improve a building's performance and to deliver objective outcomes. Findings of this survey enrich the field of intelligent buildings in two ways. Firstly, it gives a detailed insight into the selection of sustainable building indicators, as well as their degree of importance. Secondly, it tesst critically stakeholder's perceptions and values of selected KPIs intelligent buildings. It is concluded that the priority levels for selected criteria is largely dependent on the integrated design team, which includes the client, architects, engineers and facilities managers

  8. A combined rheology and time domain NMR approach for determining water distributions in protein blends

    NARCIS (Netherlands)

    Dekkers, Birgit L.; Kort, de Daan W.; Grabowska, Katarzyna J.; Tian, Bei; As, Van Henk; Goot, van der Atze Jan

    2016-01-01

    We present a combined time domain NMR and rheology approach to quantify the water distribution in a phase separated protein blend. The approach forms the basis for a new tool to assess the microstructural properties of phase separated biopolymer blends, making it highly relevant for many food and

  9. Combining Statistical Methodologies in Water Quality Monitoring in a Hydrological Basin - Space and Time Approaches

    OpenAIRE

    Costa, Marco; A. Manuela Gonçalves

    2012-01-01

    In this work are discussed some statistical approaches that combine multivariate statistical techniques and time series analysis in order to describe and model spatial patterns and temporal evolution by observing hydrological series of water quality variables recorded in time and space. These approaches are illustrated with a data set collected in the River Ave hydrological basin located in the Northwest region of Portugal.

  10. A combined stochastic programming and optimal control approach to personal finance and pensions

    DEFF Research Database (Denmark)

    Konicz, Agnieszka Karolina; Pisinger, David; Rasmussen, Kourosh Marjani

    2015-01-01

    The paper presents a model that combines a dynamic programming (stochastic optimal control) approach and a multi-stage stochastic linear programming approach (SLP), integrated into one SLP formulation. Stochastic optimal control produces an optimal policy that is easy to understand and implement....

  11. Combining a survey approach and energy and indoor environment auditing in historic buildings

    DEFF Research Database (Denmark)

    Rohdin, Patrik; Dalewski, Mariusz; Moshfegh, Bahram

    2016-01-01

    Purpose – This paper presents an approach where a survey study is combined with energy and indoor environment auditing in the built environment. The combination of methods presented in this paper is one way to obtain a wider perspective on the indoor environment and energy use and also let...... this research project. Design/methodology/approach – A combination of energy and indoor environment auditing and standardized occupant surveys. Findings – The main findings in the paper are related to the good agreement between results from standardized occupant surveys and physical measurements...

  12. Quality by design approach: application of artificial intelligence techniques of tablets manufactured by direct compression.

    Science.gov (United States)

    Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Ozer, Ozgen; Güneri, Tamer; York, Peter

    2012-12-01

    The publication of the International Conference of Harmonization (ICH) Q8, Q9, and Q10 guidelines paved the way for the standardization of quality after the Food and Drug Administration issued current Good Manufacturing Practices guidelines in 2003. "Quality by Design", mentioned in the ICH Q8 guideline, offers a better scientific understanding of critical process and product qualities using knowledge obtained during the life cycle of a product. In this scope, the "knowledge space" is a summary of all process knowledge obtained during product development, and the "design space" is the area in which a product can be manufactured within acceptable limits. To create the spaces, artificial neural networks (ANNs) can be used to emphasize the multidimensional interactions of input variables and to closely bind these variables to a design space. This helps guide the experimental design process to include interactions among the input variables, along with modeling and optimization of pharmaceutical formulations. The objective of this study was to develop an integrated multivariate approach to obtain a quality product based on an understanding of the cause-effect relationships between formulation ingredients and product properties with ANNs and genetic programming on the ramipril tablets prepared by the direct compression method. In this study, the data are generated through the systematic application of the design of experiments (DoE) principles and optimization studies using artificial neural networks and neurofuzzy logic programs.

  13. An applied artificial intelligence approach towards assessing building performance simulation tools

    Energy Technology Data Exchange (ETDEWEB)

    Yezioro, Abraham [Faculty of Architecture and Town Planning, Technion IIT (Israel); Dong, Bing [Center for Building Performance and Diagnostics, School of Architecture, Carnegie Mellon University (United States); Leite, Fernanda [Department of Civil and Environmental Engineering, Carnegie Mellon University (United States)

    2008-07-01

    With the development of modern computer technology, a large amount of building energy simulation tools is available in the market. When choosing which simulation tool to use in a project, the user must consider the tool's accuracy and reliability, considering the building information they have at hand, which will serve as input for the tool. This paper presents an approach towards assessing building performance simulation results to actual measurements, using artificial neural networks (ANN) for predicting building energy performance. Training and testing of the ANN were carried out with energy consumption data acquired for 1 week in the case building called the Solar House. The predicted results show a good fitness with the mathematical model with a mean absolute error of 0.9%. Moreover, four building simulation tools were selected in this study in order to compare their results with the ANN predicted energy consumption: Energy{sub 1}0, Green Building Studio web tool, eQuest and EnergyPlus. The results showed that the more detailed simulation tools have the best simulation performance in terms of heating and cooling electricity consumption within 3% of mean absolute error. (author)

  14. Pervasive Monitoring—An Intelligent Sensor Pod Approach for Standardised Measurement Infrastructures

    Directory of Open Access Journals (Sweden)

    Michael Lippautz

    2010-12-01

    Full Text Available Geo-sensor networks have traditionally been built up in closed monolithic systems, thus limiting trans-domain usage of real-time measurements. This paper presents the technical infrastructure of a standardised embedded sensing device, which has been developed in the course of the Live Geography approach. The sensor pod implements data provision standards of the Sensor Web Enablement initiative, including an event-based alerting mechanism and location-aware Complex Event Processing functionality for detection of threshold transgression and quality assurance. The goal of this research is that the resultant highly flexible sensing architecture will bring sensor network applications one step further towards the realisation of the vision of a “digital skin for planet earth”. The developed infrastructure can potentially have far-reaching impacts on sensor-based monitoring systems through the deployment of ubiquitous and fine-grained sensor networks. This in turn allows for the straight-forward use of live sensor data in existing spatial decision support systems to enable better-informed decision-making.

  15. Towards sustainability: artificial intelligent based approach for soil stabilization using various pozzolans

    KAUST Repository

    Ouf, M. S.

    2012-07-03

    Due to the gradual depletion in the conventional resources, searching for a more rational road construction approach aimed at reducing the dependence on imported materials while improving the quality and durability of the roads is necessary. A previous study carried out on a sample of Egyptian soil aimed at reducing the road construction cost, protect the environment and achieving sustainability. RoadCem, ground granulated blast furnace slag (GGBS), lime and ordinary Portland cement (OPC) were employed to stabilise the Egyptian clayey soil. The results revealed that the unconfined compressive strength (UCS) of the test soil increased while the free swelling percent (FSP) decreased with an increase in the total stabiliser and the curing period. This paper discusses attempts to reach optimum stabilization through: (1) Recognizing the relationship between the UCS/FSP of stabilized soil and the stabilization parameters using artificial neural network (ANN); and (2) Performing a backward optimization on the developed (ANN) model using general algorithm (GA) to meet practical design preferences. © 2012 WIT Press.

  16. Intelligence analysis – the royal discipline of Competitive Intelligence

    Directory of Open Access Journals (Sweden)

    František Bartes

    2011-01-01

    Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

  17. Close ISR Support: Re-organizing the Combined Forces Air Component Commander’s Intelligence, Surveillance and Reconnaissance Processes and Agencies

    Science.gov (United States)

    2009-12-01

    Intelligence IO–Information Operations IOT –In Order To IP–Iraqi Police IPB–Intelligence Preparation of the Battlespace IR–infrared xxiii IROC... forensic backtracking highlighted potential cache sites or improvised explosive device (IED) emplacement areas which could then be better analyzed by the...target indicator (GMTI) forensic backtracking to link suspicious GMTI movements with other intelligence signatures.388 As will be discussed in

  18. An intelligent approach to optimize the EDM process parameters using utility concept and QPSO algorithm

    Directory of Open Access Journals (Sweden)

    Chinmaya P. Mohanty

    2017-04-01

    Full Text Available Although significant research has gone into the field of electrical discharge machining (EDM, analysis related to the machining efficiency of the process with different electrodes has not been adequately made. Copper and brass are frequently used as electrode materials but graphite can be used as a potential electrode material due to its high melting point temperature and good electrical conductivity. In view of this, the present work attempts to compare the machinability of copper, graphite and brass electrodes while machining Inconel 718 super alloy. Taguchi’s L27 orthogonal array has been employed to collect data for the study and analyze effect of machining parameters on performance measures. The important performance measures selected for this study are material removal rate, tool wear rate, surface roughness and radial overcut. Machining parameters considered for analysis are open circuit voltage, discharge current, pulse-on-time, duty factor, flushing pressure and electrode material. From the experimental analysis, it is observed that electrode material, discharge current and pulse-on-time are the important parameters for all the performance measures. Utility concept has been implemented to transform a multiple performance characteristics into an equivalent performance characteristic. Non-linear regression analysis is carried out to develop a model relating process parameters and overall utility index. Finally, the quantum behaved particle swarm optimization (QPSO and particle swarm optimization (PSO algorithms have been used to compare the optimal level of cutting parameters. Results demonstrate the elegance of QPSO in terms of convergence and computational effort. The optimal parametric setting obtained through both the approaches is validated by conducting confirmation experiments.

  19. Représentation de coupes géologiques : une approche intelligence artificielle Representation of Geological Cross-Sections : an Artificial Intelligence Approach

    Directory of Open Access Journals (Sweden)

    Bessis F.

    2006-11-01

    Full Text Available La description d'une coupe géologique est actuellement réalisée par des représentations numériques. Ce type de représentation est inadapté pour effectuer des raisonnements géologiques. Nous proposons une méthode pour reconnaître les objets géologiques et un formalisme FROG(1 de représentation symbolique de ces objets. Nous utilisons pour parvenir à cette fin les méthodes et techniques de programmation d'Intelligence Artificielle. En particulier, nous substituons à la reconnaissance de formes qui n'est pas applicable dans ce cas, ce que nous appelons la reconnaissance génétique où les modèles d'objets à reconnaître sont définis non pas par leurs caractéristiques géométriques, mais leurs caractéristiques historiques, autrement dit par leur genèse. L'identification de ces caractéristiques, ainsi que la compréhension de leur signification géologique forment une partie de l'expertise d'un géologue. Le programme GROG met en oeuvre ces idées et fournit une validation de ce travail. (1 Formalisme de Représentation des Objets Géologiques. A picking of cross-section is currently represented in a numerical way. This kind of representation is not adapted to perform geological reasoning. We propose a method of recognition of geological objects and the FROG (1 symbolic representation formalism for geological objects. To achieve this goal, we use Artifical Intelligence methods and techniques. Particularly, we do not use pattern recognition methods which are hardly helpful, but what we call genetic recognition: geological models are not defined by their geometrical features, but by their historical features, i. e. by their genesis. Identification of these features and understanding of their geological meaning are a part of the geologist expertise. The GROG program provides a FROG implementation and a validation of this work. (1 Formalism for Representation of Objects in Geology.

  20. Combined time-varying forecast based on the proper scoring approach for wind power generation

    DEFF Research Database (Denmark)

    Chen, Xingying; Jiang, Yu; Yu, Kun

    2017-01-01

    Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error...... distribution, a proper scoring approach is applied to combine plausible models to form an overall time-varying model for the next day forecasts, rather than weights-based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results...... demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction....

  1. Management of advanced intracranial intradural juvenile nasopharyngeal angiofibroma: combined single-stage rhinosurgical and neurosurgical approach.

    Science.gov (United States)

    Naraghi, Mohsen; Saberi, Hooshang; Mirmohseni, Atefeh Sadat; Nikdad, Mohammad Sadegh; Afarideh, Mohsen

    2015-07-01

    Although intracranial extension of juvenile nasopharyngeal angiofibroma (JNA) occurs commonly, intradural penetration is extremely rare. Management of such tumors is a challenging issue in skull-base surgery, necessitating their removal via combined approaches. In this work, we share our experience in management of extensive intradural JNA. In a university hospital-based setting of 2 tertiary care academic centers, retrospective chart of 6 male patients (5 between 15 and 19 years old) was reviewed. Patients presented chiefly with nasal obstruction, epistaxis, and proptosis. One of them was an aggressive recurrent tumor in a 32-year-old patient. All cases underwent combined transnasal, transmaxillary, and craniotomy approaches assisted by the use of image-guided endoscopic surgery, with craniotomy preceding the rhinosurgical approach in 3 cases. Adding a transcranial approach to the transnasal and transmaxillary endoscopic approaches provided 2-sided exposure and appreciated access to the huge intradural JNAs. One postoperative cerebrospinal fluid leak and 1 postoperative recurrence at the site of infratemporal fossa were treated successfully. Otherwise, the course was uneventful in the remaining cases. Management of intracranial intradural JNA requires a multidisciplinary approach of combined open and endoscopic-assisted rhinosurgery and neurosurgery, because of greater risk for complications during the dissection. Carotid rupture and brain damage remain 2 catastrophic complications that should always be kept in mind. A combined rhinosurgical and neurosurgical approach also has the advantage of very modest cosmetic complications. © 2015 ARS-AAOA, LLC.

  2. SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients.

    Science.gov (United States)

    Mougiakakou, Stavroula G; Bartsocas, Christos S; Bozas, Evangelos; Chaniotakis, Nikos; Iliopoulou, Dimitra; Kouris, Ioannis; Pavlopoulos, Sotiris; Prountzou, Aikaterini; Skevofilakas, Marios; Tsoukalis, Alexandre; Varotsis, Kostas; Vazeou, Andrianni; Zarkogianni, Konstantia; Nikita, Konstantina S

    2010-05-01

    SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

  3. A multi-stage intelligent approach based on an ensemble of two-way interaction model for forecasting the global horizontal radiation of India

    International Nuclear Information System (INIS)

    Jiang, He; Dong, Yao; Xiao, Ling

    2017-01-01

    Highlights: • Ensemble learning system is proposed to forecast the global solar radiation. • LASSO is utilized as feature selection method for subset model. • GSO is used to select the weight vector aggregating the response of subset model. • A simple and efficient algorithm is designed based on thresholding function. • Theoretical analysis focusing on error rate is provided. - Abstract: Forecasting of effective solar irradiation has developed a huge interest in recent decades, mainly due to its various applications in grid connect photovoltaic installations. This paper develops and investigates an ensemble learning based multistage intelligent approach to forecast 5 days global horizontal radiation at four given locations of India. The two-way interaction model is considered with purpose of detecting the associated correlation between the features. The main structure of the novel method is the ensemble learning, which is based on Divide and Conquer principle, is applied to enhance the forecasting accuracy and model stability. An efficient feature selection method LASSO is performed in the input space with the regularization parameter selected by Cross-Validation. A weight vector which best represents the importance of each individual model in ensemble system is provided by glowworm swarm optimization. The combination of feature selection and parameter selection are helpful in creating the diversity of the ensemble learning. In order to illustrate the validity of the proposed method, the datasets at four different locations of the India are split into training and test datasets. The results of the real data experiments demonstrate the efficiency and efficacy of the proposed method comparing with other competitors.

  4. 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…

  5. 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…

  6. Intelligent environmental sensing

    CERN Document Server

    Mukhopadhyay, Subhas

    2015-01-01

    Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

  7. Forensic drug intelligence and the rise of cryptomarkets. Part II: Combination of data from the physical and virtual markets.

    Science.gov (United States)

    Morelato, Marie; Broséus, Julian; De Grazia, Adrian; Tahtouh, Mark; Esseiva, Pierre; Roux, Claude

    2018-05-08

    Technology provides new ways to access customers and suppliers while enhancing the security of off-line criminal activity. Since the first cryptomarket, Silk Road, in 2011, cryptomarkets have transformed the traditional drug sale by facilitating the creation of a global network of vendors and buyers. Due to the fragmented nature of traces that result from illegal activities, combining the results of concurrent processes based on traces of different nature should provide supplementary benefit to understand the drug market. This article compares the data of the Australian virtual market (in particular data extracted from cryptomarkets) to the data related to traditional market descriptors, namely national seizures and arrests, prevalence data, shipping countries of seized post shipments as well as outcomes of specific surveys targeting users' behaviour online. Results revealed the domestic nature of the online illicit drug trade in Australia which is dominated by amphetamine-type substances (ATS), in particular methylamphetamine and cannabis. These illicit drugs were also the most seized drugs on the physical market. This article shows that the combination of different information offers a broader perspective of the illicit drug market in Australia and thus provides stronger arguments for policy makers. It also highlights the links between the virtual and physical markets. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. 3D measurement using combined Gray code and dual-frequency phase-shifting approach

    Science.gov (United States)

    Yu, Shuang; Zhang, Jing; Yu, Xiaoyang; Sun, Xiaoming; Wu, Haibin; Liu, Xin

    2018-04-01

    The combined Gray code and phase-shifting approach is a commonly used 3D measurement technique. In this technique, an error that equals integer multiples of the phase-shifted fringe period, i.e. period jump error, often exists in the absolute analog code, which can lead to gross measurement errors. To overcome this problem, the present paper proposes 3D measurement using a combined Gray code and dual-frequency phase-shifting approach. Based on 3D measurement using the combined Gray code and phase-shifting approach, one set of low-frequency phase-shifted fringe patterns with an odd-numbered multiple of the original phase-shifted fringe period is added. Thus, the absolute analog code measured value can be obtained by the combined Gray code and phase-shifting approach, and the low-frequency absolute analog code measured value can also be obtained by adding low-frequency phase-shifted fringe patterns. Then, the corrected absolute analog code measured value can be obtained by correcting the former by the latter, and the period jump errors can be eliminated, resulting in reliable analog code unwrapping. For the proposed approach, we established its measurement model, analyzed its measurement principle, expounded the mechanism of eliminating period jump errors by error analysis, and determined its applicable conditions. Theoretical analysis and experimental results show that the proposed approach can effectively eliminate period jump errors, reliably perform analog code unwrapping, and improve the measurement accuracy.

  9. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  10. An intelligent operator support system for dynamic positioning

    NARCIS (Netherlands)

    Diggelen, J. van; Broek, J. van den; Schraagen, J.M.C.; Waa, J.S. van der

    2018-01-01

    This paper proposes a human-centered approach to Dynamic Position-ing systems which combines multiple technologies in an intelligent operator sup-port system (IOSS). IOSS allows the operator to be roaming and do other tasks in quiet conditions. When conditions become more demanding, the IOSS calls

  11. Engineering and management of IT-based service systems an intelligent decision-making support systems approach

    CERN Document Server

    Gomez, Jorge; Garrido, Leonardo; Perez, Francisco

    2014-01-01

    Intelligent Decision-Making Support Systems (i-DMSS) are specialized IT-based systems that support some or several phases of the individual, team, organizational or inter-organizational decision making process by deploying some or several intelligent mechanisms. This book pursues the following academic aims: (i) generate a compendium of quality theoretical and applied contributions in Intelligent Decision-Making Support Systems (i-DMSS) for engineering and management IT-based service systems (ITSS); (ii)  diffuse scarce knowledge about foundations, architectures and effective and efficient methods and strategies for successfully planning, designing, building, operating, and evaluating i-DMSS for ITSS, and (iii) create an awareness of, and a bridge between ITSS and i-DMSS academicians and practitioners in the current complex and dynamic engineering and management ITSS organizational. The book presents a collection of 11 chapters referring to relevant topics for both IT service systems and i-DMSS including: pr...

  12. 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...

  13. Liquid-phase microextraction approaches combined with atomic detection: A critical review

    International Nuclear Information System (INIS)

    Pena-Pereira, Francisco; Lavilla, Isela; Bendicho, Carlos

    2010-01-01

    Liquid-phase microextraction (LPME) displays unique characteristics such as excellent preconcentration capability, simplicity, low cost, sample cleanup and integration of steps. Even though LPME approaches have the potential to be combined with almost every analytical technique, their use in combination with atomic detection techniques has not been exploited until recently. A comprehensive review dealing with the applications of liquid-phase microextraction combined with atomic detection techniques is presented. Theoretical features, possible strategies for these combinations as well as the effect of key experimental parameters influencing method development are addressed. Finally, a critical comparison of the different LPME approaches in terms of enrichment factors achieved, extraction efficiency, precision, selectivity and simplicity of operation is provided.

  14. Nanotechnology-based combinational drug delivery: an emerging approach for cancer therapy.

    Science.gov (United States)

    Parhi, Priyambada; Mohanty, Chandana; Sahoo, Sanjeeb Kumar

    2012-09-01

    Combination therapy for the treatment of cancer is becoming more popular because it generates synergistic anticancer effects, reduces individual drug-related toxicity and suppresses multi-drug resistance through different mechanisms of action. In recent years, nanotechnology-based combination drug delivery to tumor tissues has emerged as an effective strategy by overcoming many biological, biophysical and biomedical barriers that the body stages against successful delivery of anticancer drugs. The sustained, controlled and targeted delivery of chemotherapeutic drugs in a combination approach enhanced therapeutic anticancer effects with reduced drug-associated side effects. In this article, we have reviewed the scope of various nanotechnology-based combination drug delivery approaches and also summarized the current perspective and challenges facing the successful treatment of cancer. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

    Science.gov (United States)

    Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

    2009-01-01

    The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

  16. RELAP5 simulation of surge line break accident using combined and best estimate plus uncertainty approaches

    International Nuclear Information System (INIS)

    Kristof, Marian; Kliment, Tomas; Petruzzi, Alessandro; Lipka, Jozef

    2009-01-01

    Licensing calculations in a majority of countries worldwide still rely on the application of combined approach using best estimate computer code without evaluation of the code models uncertainty and conservative assumptions on initial and boundary, availability of systems and components and additional conservative assumptions. However best estimate plus uncertainty (BEPU) approach representing the state-of-the-art in the area of safety analysis has a clear potential to replace currently used combined approach. There are several applications of BEPU approach in the area of licensing calculations, but some questions are discussed, namely from the regulatory point of view. In order to find a proper solution to these questions and to support the BEPU approach to become a standard approach for licensing calculations, a broad comparison of both approaches for various transients is necessary. Results of one of such comparisons on the example of the VVER-440/213 NPP pressurizer surge line break event are described in this paper. A Kv-scaled simulation based on PH4-SLB experiment from PMK-2 integral test facility applying its volume and power scaling factor is performed for qualitative assessment of the RELAP5 computer code calculation using the VVER-440/213 plant model. Existing hardware differences are identified and explained. The CIAU method is adopted for performing the uncertainty evaluation. Results using combined and BEPU approaches are in agreement with the experimental values in PMK-2 facility. Only minimal difference between combined and BEPU approached has been observed in the evaluation of the safety margins for the peak cladding temperature. Benefits of the CIAU uncertainty method are highlighted.

  17. 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 ...

  18. A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

    Directory of Open Access Journals (Sweden)

    Abdullah M. Iliyasu

    2017-12-01

    Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

  19. Towards Intelligent Supply Chains

    DEFF Research Database (Denmark)

    Siurdyban, Artur; Møller, Charles

    2012-01-01

    applied to the context of organizational processes can increase the success rate of business operations. The framework is created using a set of theoretical based constructs grounded in a discussion across several streams of research including psychology, pedagogy, artificial intelligence, learning...... of deploying inapt operations leading to deterioration of profits. To address this problem, we propose a unified business process design framework based on the paradigm of intelligence. Intelligence allows humans and human-designed systems cope with environmental volatility, and we argue that its principles......, business process management and supply chain management. It outlines a number of system tasks combined in four integrated management perspectives: build, execute, grow and innovate, put forward as business process design propositions for Intelligent Supply Chains....

  20. An approach to combining heuristic and qualitative reasoning in an expert system

    Science.gov (United States)

    Jiang, Wei-Si; Han, Chia Yung; Tsai, Lian Cheng; Wee, William G.

    1988-01-01

    An approach to combining the heuristic reasoning from shallow knowledge and the qualitative reasoning from deep knowledge is described. The shallow knowledge is represented in production rules and under the direct control of the inference engine. The deep knowledge is represented in frames, which may be put in a relational DataBase Management System. This approach takes advantage of both reasoning schemes and results in improved efficiency as well as expanded problem solving ability.

  1. Angular approach combined to mechanical model for tool breakage detection by eddy current sensors

    OpenAIRE

    Ritou , Mathieu; Garnier , Sébastien; Furet , Benoît; Hascoët , Jean-Yves

    2014-01-01

    International audience; The paper presents a new complete approach for Tool Condition Monitoring (TCM) in milling. The aim is the early detection of small damages so that catastrophic tool failures are prevented. A versatile in-process monitoring system is introduced for reliability concerns. The tool condition is determined by estimates of the radial eccentricity of the teeth. An adequate criterion is proposed combining mechanical model of milling and angular approach. Then, a new solution i...

  2. Critical Combinations of Radiation Dose and Volume Predict Intelligence Quotient and Academic Achievement Scores After Craniospinal Irradiation in Children With Medulloblastoma

    Energy Technology Data Exchange (ETDEWEB)

    Merchant, Thomas E., E-mail: thomas.merchant@stjude.org [Division of Radiation Oncology, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States); Schreiber, Jane E. [Department of Psychology, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States); Wu, Shengjie [Department of Biostatistcs, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States); Lukose, Renin [Division of Radiation Oncology, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States); Xiong, Xiaoping [Department of Biostatistcs, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States); Gajjar, Amar [Department of Oncology, St. Jude Children' s Research Hospital, Memphis, Tennessee (United States)

    2014-11-01

    Purpose: To prospectively follow children treated with craniospinal irradiation to determine critical combinations of radiation dose and volume that would predict for cognitive effects. Methods and Materials: Between 1996 and 2003, 58 patients (median age 8.14 years, range 3.99-20.11 years) with medulloblastoma received risk-adapted craniospinal irradiation followed by dose-intense chemotherapy and were followed longitudinally with multiple cognitive evaluations (through 5 years after treatment) that included intelligence quotient (estimated intelligence quotient, full-scale, verbal, and performance) and academic achievement (math, reading, spelling) tests. Craniospinal irradiation consisted of 23.4 Gy for average-risk patients (nonmetastatic) and 36-39.6 Gy for high-risk patients (metastatic or residual disease >1.5 cm{sup 2}). The primary site was treated using conformal or intensity modulated radiation therapy using a 2-cm clinical target volume margin. The effect of clinical variables and radiation dose to different brain volumes were modeled to estimate cognitive scores after treatment. Results: A decline with time for all test scores was observed for the entire cohort. Sex, race, and cerebrospinal fluid shunt status had a significant impact on baseline scores. Age and mean radiation dose to specific brain volumes, including the temporal lobes and hippocampi, had a significant impact on longitudinal scores. Dichotomized dose distributions at 25 Gy, 35 Gy, 45 Gy, and 55 Gy were modeled to show the impact of the high-dose volume on longitudinal test scores. The 50% risk of a below-normal cognitive test score was calculated according to mean dose and dose intervals between 25 Gy and 55 Gy at 10-Gy increments according to brain volume and age. Conclusions: The ability to predict cognitive outcomes in children with medulloblastoma using dose-effects models for different brain subvolumes will improve treatment planning, guide intervention, and help

  3. Critical Combinations of Radiation Dose and Volume Predict Intelligence Quotient and Academic Achievement Scores After Craniospinal Irradiation in Children With Medulloblastoma

    International Nuclear Information System (INIS)

    Merchant, Thomas E.; Schreiber, Jane E.; Wu, Shengjie; Lukose, Renin; Xiong, Xiaoping; Gajjar, Amar

    2014-01-01

    Purpose: To prospectively follow children treated with craniospinal irradiation to determine critical combinations of radiation dose and volume that would predict for cognitive effects. Methods and Materials: Between 1996 and 2003, 58 patients (median age 8.14 years, range 3.99-20.11 years) with medulloblastoma received risk-adapted craniospinal irradiation followed by dose-intense chemotherapy and were followed longitudinally with multiple cognitive evaluations (through 5 years after treatment) that included intelligence quotient (estimated intelligence quotient, full-scale, verbal, and performance) and academic achievement (math, reading, spelling) tests. Craniospinal irradiation consisted of 23.4 Gy for average-risk patients (nonmetastatic) and 36-39.6 Gy for high-risk patients (metastatic or residual disease >1.5 cm 2 ). The primary site was treated using conformal or intensity modulated radiation therapy using a 2-cm clinical target volume margin. The effect of clinical variables and radiation dose to different brain volumes were modeled to estimate cognitive scores after treatment. Results: A decline with time for all test scores was observed for the entire cohort. Sex, race, and cerebrospinal fluid shunt status had a significant impact on baseline scores. Age and mean radiation dose to specific brain volumes, including the temporal lobes and hippocampi, had a significant impact on longitudinal scores. Dichotomized dose distributions at 25 Gy, 35 Gy, 45 Gy, and 55 Gy were modeled to show the impact of the high-dose volume on longitudinal test scores. The 50% risk of a below-normal cognitive test score was calculated according to mean dose and dose intervals between 25 Gy and 55 Gy at 10-Gy increments according to brain volume and age. Conclusions: The ability to predict cognitive outcomes in children with medulloblastoma using dose-effects models for different brain subvolumes will improve treatment planning, guide intervention, and help estimate

  4. Combined transoral and endoscopic approach for total maxillectomy: a pioneering report.

    Science.gov (United States)

    Liu, Zhuofu; Yu, Huapeng; Wang, Dehui; Wang, Jingjing; Sun, Xicai; Liu, Juan

    2013-06-01

    Total maxillectomy is sometimes necessary especially for malignant tumors originating from the maxillary sinus. Here we describe a combined transoral and endoscopic approach for total maxillectomy for the treatment of malignant maxillary sinus tumors and evaluate its short-term outcome. This approach was evaluated in terms of the physiological function, aesthetic outcome, and complications. Six patients underwent the above-mentioned approach for resection of malignant maxillary sinus tumors from May 2010 to June 2011. This combined transoral and endoscopic approach includes five basic steps: total sphenoethmoidectomy, sublabial incision, incision of the frontal process of the maxilla, incision of the zygomaticomaxillary fissure, and hard palate osteotomy. All patients with malignant maxillary sinus tumors successfully underwent the planned total endoscopic maxillectomy without the need for facial incision or transfixion of the nasal septum; there were no significant complications. Five patients received preoperative radiation therapy. All patients were well and had no recurrence at follow-up from 13 to 27 months. The combined approach is feasible and can be performed in carefully selected patients. The benefit of the absence of facial incisions or transfixion of the nasal septum, potential improvement in hemostasis, and visual magnification may help to decrease the morbidity of traditional open approaches.

  5. COMPARISONS BETWEEN AND COMBINATIONS OF DIFFERENT APPROACHES TO ACCELERATE ENGINEERING PROJECTS

    Directory of Open Access Journals (Sweden)

    H. Steyn

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: In this article, traditional project management methods such as PERT and CPM, as well as fast-tracking and systems approaches, viz. concurrent engineering and critical chain, are reviewed with specific reference to their contribution to reducing the duration of the execution phase of engineering projects. Each of these techniques has some role to play in the acceleration of project execution. Combinations of approaches are evaluated by considering the potential of sets consisting of two different approaches each. While PERT and CPM approaches have been combined for many years in a technique called PERT/CPM, new combinations of approaches are discussed. Certain assumptions inherent to PERT and often wrong are not made by the critical chain approach.

    AFRIKAANSE OPSOMMING: In hierdie artikel word tradisionele projekbestuurbenaderings soos PERT en CPM asook projekversnelling en stelselbenaderings, naamlik gelyktydige ingenieurswese, en kritiekeketting-ondersoek met betrekking tot die bydrae wat elk tot die versnelling van die uitvoeringsfase van ingenieursprojekte kan lewer. Elk van hierdie benaderings kan ‘n spesifieke bydrae tot die versnelling van projekte lewer. Kombinasies, elk bestaande uit twee verskillende benaderings, word geëvalueer. Terwyl PERT en CPM reeds baie jare lank in kombinasie gebruik word, word nuwe kombinasies ook hier bespreek. Sekere aannames inherent aan die PERT-benadering is dikwels foutief. Hierdie aannames word nie deur die kritieke-ketting-benadering gemaak nie.

  6. From Braitenberg's Vehicles to Jansen's Beach Animals: Towards an Ecological Approach to the Design of Non-Organic Intelligence

    NARCIS (Netherlands)

    Bleeker, M.A.

    2017-01-01

    This article presents a comparison of two proposals for how to conceive of the evolution of non-organic intelligence. One is Valentino Braitenberg’s 1984 essay ‘Vehicles: Experiments in Synthetic Psychology’. The other is the Strandbeesten (beach animals) of Dutch engineer-artist Theo Jansen.

  7. Research-through-design for considering ethical implications in Ambient Intelligence system design: The Growth Plan approach

    NARCIS (Netherlands)

    Ross, P.R.; Tomico, O.

    2009-01-01

    The technologies we use transform our behaviours and experiences. Particularly Ambient Intelligent (AmI) systems, envisioned to integrate extensively, will have a profound influence on our everyday lives. Design of these systems requires considering what kind of influence is desirable. This brings

  8. Intelligently interactive combat simulation

    Science.gov (United States)

    Fogel, Lawrence J.; Porto, Vincent W.; Alexander, Steven M.

    2001-09-01

    To be fully effective, combat simulation must include an intelligently interactive enemy... one that can be calibrated. But human operated combat simulations are uncalibratable, for we learn during the engagement, there's no average enemy, and we cannot replicate their culture/personality. Rule-based combat simulations (expert systems) are not interactive. They do not take advantage of unexpected mistakes, learn, innovate, and reflect the changing mission/situation. And it is presumed that the enemy does not have a copy of the rules, that the available experts are good enough, that they know why they did what they did, that their combat experience provides a sufficient sample and that we know how to combine the rules offered by differing experts. Indeed, expert systems become increasingly complex, costly to develop, and brittle. They have face validity but may be misleading. In contrast, intelligently interactive combat simulation is purpose- driven. Each player is given a well-defined mission, reference to the available weapons/platforms, their dynamics, and the sensed environment. Optimal tactics are discovered online and in real-time by simulating phenotypic evolution in fast time. The initial behaviors are generated randomly or include hints. The process then learns without instruction. The Valuated State Space Approach provides a convenient way to represent any purpose/mission. Evolutionary programming searches the domain of possible tactics in a highly efficient manner. Coupled together, these provide a basis for cruise missile mission planning, and for driving tank warfare simulation. This approach is now being explored to benefit Air Force simulations by a shell that can enhance the original simulation.

  9. Two-stage approach for risk estimation of fetal trisomy 21 and other aneuploidies using computational intelligence systems.

    Science.gov (United States)

    Neocleous, A C; Syngelaki, A; Nicolaides, K H; Schizas, C N

    2018-04-01

    To estimate the risk of fetal trisomy 21 (T21) and other chromosomal abnormalities (OCA) at 11-13 weeks' gestation using computational intelligence classification methods. As a first step, a training dataset consisting of 72 054 euploid pregnancies, 295 cases of T21 and 305 cases of OCA was used to train an artificial neural network. Then, a two-stage approach was used for stratification of risk and diagnosis of cases of aneuploidy in the blind set. In Stage 1, using four markers, pregnancies in the blind set were classified into no risk and risk. No-risk pregnancies were not examined further, whereas the risk pregnancies were forwarded to Stage 2 for further examination. In Stage 2, using seven markers, pregnancies were classified into three types of risk, namely no risk, moderate risk and high risk. Of 36 328 unknown to the system pregnancies (blind set), 17 512 euploid, two T21 and 18 OCA were classified as no risk in Stage 1. The remaining 18 796 cases were forwarded to Stage 2, of which 7895 euploid, two T21 and two OCA cases were classified as no risk, 10 464 euploid, 83 T21 and 61 OCA as moderate risk and 187 euploid, 50 T21 and 52 OCA as high risk. The sensitivity and the specificity for T21 in Stage 2 were 97.1% and 99.5%, respectively, and the false-positive rate from Stage 1 to Stage 2 was reduced from 51.4% to ∼1%, assuming that the cell-free DNA test could identify all euploid and aneuploid cases. We propose a method for early diagnosis of chromosomal abnormalities that ensures that most T21 cases are classified as high risk at any stage. At the same time, the number of euploid cases subjected to invasive or cell-free DNA examinations was minimized through a routine procedure offered in two stages. Our method is minimally invasive and of relatively low cost, highly effective at T21 identification and it performs better than do other existing statistical methods. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd. Copyright

  10. Is Combining Child Labour and School Education the Right Approach? Investigating the Cambodian Case

    Science.gov (United States)

    Kim, Chae-Young

    2009-01-01

    The paper considers whether letting children combine work and school is a valid and effective approach in Cambodia. Policy makers' suggestions that child labour should be allowed to some extent due to household poverty appear ungrounded as no significant relation between children's work and household poverty is found while arranging school…

  11. Global Practical Stabilization and Tracking for an Underactuated Ship - A Combined Averaging and Backstepping Approach

    Directory of Open Access Journals (Sweden)

    Kristin Y. Pettersen

    1999-10-01

    Full Text Available We solve both the global practical stabilization and tracking problem for an underactuated ship, using a combined integrator backstepping and averaging approach. Exponential convergence to an arbitrarily small neighbourhood of the origin and of the reference trajectory, respectively, is proved. Simulation results are included.

  12. "Combining equity and utilitarianism"-additional insights into a novel approach

    NARCIS (Netherlands)

    Lemmen-Gerdessen, van Joke; Kanellopoulos, Argyris; Claassen, Frits

    2018-01-01

    Recently, a novel approach (to be referred to as CEU) was introduced for the frequently arising problem of combining the conflicting criteria of equity and utilitarianism. This paper provides additional insights into CEU and assesses its added value for practice by comparing it with a commonly used

  13. A simple network agreement-based approach for combining evidences in a heterogeneous sensor network

    Directory of Open Access Journals (Sweden)

    Raúl Eusebio-Grande

    2015-12-01

    Full Text Available In this research we investigate how the evidences provided by both static and mobile nodes that are part of a heterogenous sensor network can be combined to have trustworthy results. A solution relying on a network agreement-based approach was implemented and tested.

  14. Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

    Science.gov (United States)

    Yang, S; Wang, D

    2000-01-01

    This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

  15. Combination of Evidence with Different Weighting Factors: A Novel Probabilistic-Based Dissimilarity Measure Approach

    Directory of Open Access Journals (Sweden)

    Mengmeng Ma

    2015-01-01

    Full Text Available To solve the invalidation problem of Dempster-Shafer theory of evidence (DS with high conflict in multisensor data fusion, this paper presents a novel combination approach of conflict evidence with different weighting factors using a new probabilistic dissimilarity measure. Firstly, an improved probabilistic transformation function is proposed to map basic belief assignments (BBAs to probabilities. Then, a new dissimilarity measure integrating fuzzy nearness and introduced correlation coefficient is proposed to characterize not only the difference between basic belief functions (BBAs but also the divergence degree of the hypothesis that two BBAs support. Finally, the weighting factors used to reassign conflicts on BBAs are developed and Dempster’s rule is chosen to combine the discounted sources. Simple numerical examples are employed to demonstrate the merit of the proposed method. Through analysis and comparison of the results, the new combination approach can effectively solve the problem of conflict management with better convergence performance and robustness.

  16. Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging Based on a Riemannian Manifold Approach.

    Science.gov (United States)

    Baust, Maximilian; Weinmann, Andreas; Wieczorek, Matthias; Lasser, Tobias; Storath, Martin; Navab, Nassir

    2016-08-01

    In this paper, we consider combined TV denoising and diffusion tensor fitting in DTI using the affine-invariant Riemannian metric on the space of diffusion tensors. Instead of first fitting the diffusion tensors, and then denoising them, we define a suitable TV type energy functional which incorporates the measured DWIs (using an inverse problem setup) and which measures the nearness of neighboring tensors in the manifold. To approach this functional, we propose generalized forward- backward splitting algorithms which combine an explicit and several implicit steps performed on a decomposition of the functional. We validate the performance of the derived algorithms on synthetic and real DTI data. In particular, we work on real 3D data. To our knowledge, the present paper describes the first approach to TV regularization in a combined manifold and inverse problem setup.

  17. Intelligent Systems For Aerospace Engineering: An Overview

    Science.gov (United States)

    KrishnaKumar, K.

    2003-01-01

    Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

  18. Aproximación a la inteligencia para la seguridad nacional/Approach to intelligence for national security

    Directory of Open Access Journals (Sweden)

    Luis Hurtado González (España

    2009-08-01

    Full Text Available La inteligencia por ser una metodología en la que se desprenden valoración que permiten reconocer las amenazas que ponen en riesgo. Los Estados democrático requieren realizar dicha actividad, a fin de salvaguardar la seguridad nacional la producción de inteligencia se presenta como una tarea imperativa para todo estado, en especial en aquellos que muestran debilidades estructurales crónicas, este ya representa avance, ya que legitima el accionar de nuestros órganos de inteligencia. Existen algunos trabajos que analizan la importancia de la inteligencia para la seguridad nacional. La teoría democrática propone que el gobierno dispone el poder que reside originariamente en el pueblo, dentro de ciertos límites éticos y jurídicos. Se entiende por inteligencia el conocimiento obtenido a partir de la recolección procesamiento, diseminación y explotación de información, para la toma de decisiones en materia de Seguridad Nacional, el siclo de inteligencia se inicia con una operación de carácter metodológico, la cual depende de la consecuencia exitosa del proceso mismo, determina con precisión aquello que se ignora frente a un conflicto provocado por una amenaza a la seguridad nacional. Intelligence is a methodology in which evolve valuation that allow to recognize the threats that put at risk. Democratic States require such activity, in order to safeguard the national security intelligence production is presented as an imperative task for any State, especially in those who are chronic structural weaknesses, this already represents progress, since legitimate actions of our intelligence agencies. There are some studies that analyzed the importance of intelligence for national security. The democratic theory proposes that the Government has the power residing originally in the town, within ethical and legal limits. Intelligence means the knowledge gained from the collection processing, dissemination and exploitation of information for

  19. Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

    Science.gov (United States)

    Asaithambi, Sasikumar; Rajappa, Muthaiah

    2018-05-01

    In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

  20. The Effectiveness of Problem-Based Learning Approach Based on Multiple Intelligences in Terms of Student’s Achievement, Mathematical Connection Ability, and Self-Esteem

    Science.gov (United States)

    Kartikasari, A.; Widjajanti, D. B.

    2017-02-01

    The aim of this study is to explore the effectiveness of learning approach using problem-based learning based on multiple intelligences in developing student’s achievement, mathematical connection ability, and self-esteem. This study is experimental research with research sample was 30 of Grade X students of MIA III MAN Yogyakarta III. Learning materials that were implemented consisting of trigonometry and geometry. For the purpose of this study, researchers designed an achievement test made up of 44 multiple choice questions with respectively 24 questions on the concept of trigonometry and 20 questions for geometry. The researcher also designed a connection mathematical test and self-esteem questionnaire that consisted of 7 essay questions on mathematical connection test and 30 items of self-esteem questionnaire. The learning approach said that to be effective if the proportion of students who achieved KKM on achievement test, the proportion of students who achieved a minimum score of high category on the results of both mathematical connection test and self-esteem questionnaire were greater than or equal to 70%. Based on the hypothesis testing at the significance level of 5%, it can be concluded that the learning approach using problem-based learning based on multiple intelligences was effective in terms of student’s achievement, mathematical connection ability, and self-esteem.

  1. Multiport Combined Endoscopic Approach to Nonembolized Juvenile Nasopharyngeal Angiofibroma with Parapharyngeal Extension: An Emerging Concept

    Directory of Open Access Journals (Sweden)

    Tiruchy Narayanan Janakiram

    2016-01-01

    Full Text Available Background. Surgical approaches to the parapharyngeal space (PPS are challenging by virtue of deep location and neurovascular content. Juvenile Nasopharyngeal Angiofibroma (JNA is a formidable hypervascular tumor that involves multiple compartments with increase in size. In tumors with extension to parapharyngeal space, the endonasal approach was observed to be inadequate. Combined Endoscopic Endonasal Approaches and Endoscopic Transoral Surgery (EEA-ETOS approach has provided a customized alternative of multicorridor approach to access JNA for its safe and efficient resection. Methods. The study demonstrates a case series of patients of JNA with prestyloid parapharyngeal space extension operated by endoscopic endonasal and endoscopic transoral approach for tumor excision. Results. The multiport EEA-ETOS approach was used to provide wide exposure to access JNA in parapharyngeal space. No major complications were observed. No conversion to external approach was required. Postoperative morbidity was low and postoperative scans showed no residual tumor. A one-year follow-up was maintained and there was no evidence of disease recurrence. Conclusion. Although preliminary, our experience demonstrates safety and efficacy of multiport approach in providing access to multiple compartments, facilitating total excision of JNA in selected cases.

  2. 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...

  3. Competing intelligent search agents in global optimization

    Energy Technology Data Exchange (ETDEWEB)

    Streltsov, S.; Vakili, P. [Boston Univ., MA (United States); Muchnik, I. [Rutgers Univ., Piscataway, NJ (United States)

    1996-12-31

    In this paper we present a new search methodology that we view as a development of intelligent agent approach to the analysis of complex system. The main idea is to consider search process as a competition mechanism between concurrent adaptive intelligent agents. Agents cooperate in achieving a common search goal and at the same time compete with each other for computational resources. We propose a statistical selection approach to resource allocation between agents that leads to simple and efficient on average index allocation policies. We use global optimization as the most general setting that encompasses many types of search problems, and show how proposed selection policies can be used to improve and combine various global optimization methods.

  4. Computational intelligence in multi-feature visual pattern recognition hand posture and face recognition using biologically inspired approaches

    CERN Document Server

    Pisharady, Pramod Kumar; Poh, Loh Ai

    2014-01-01

    This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...

  5. Why do fearful facial expressions elicit behavioral approach? Evidence from a combined approach-avoidance implicit association test.

    Science.gov (United States)

    Hammer, Jennifer L; Marsh, Abigail A

    2015-04-01

    Despite communicating a "negative" emotion, fearful facial expressions predominantly elicit behavioral approach from perceivers. It has been hypothesized that this seemingly paradoxical effect may occur due to fearful expressions' resemblance to vulnerable, infantile faces. However, this hypothesis has not yet been tested. We used a combined approach-avoidance/implicit association test (IAT) to test this hypothesis. Participants completed an approach-avoidance lever task during which they responded to fearful and angry facial expressions as well as neutral infant and adult faces presented in an IAT format. Results demonstrated an implicit association between fearful facial expressions and infant faces and showed that both fearful expressions and infant faces primarily elicit behavioral approach. The dominance of approach responses to both fearful expressions and infant faces decreased as a function of psychopathic personality traits. Results suggest that the prosocial responses to fearful expressions observed in most individuals may stem from their associations with infantile faces. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

  6. Conventional and intelligent generalized supervisory control for combined cycle generating power stations.; Control supervisiorio generalizado convencional e inteligente para centrales de generacion de ciclo combinado

    Energy Technology Data Exchange (ETDEWEB)

    Martinez M, Miguel A; Sanchez P, Marino [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico); Gonzalez Rubio S, Jose L [Cento Nacional de Investigacion y Desarrollo Tecnologico (Cenidet), Cuernavaca, Morelos (Mexico)

    2005-07-01

    Under the expectations of expansion of electric power generation in Mexico, this work exposes the development of a conventional and intelligent generalized supervisory control (CSG) for a combined cycle generation power plant. This one allows to obtain the optimal operation of the power plant through the automatic starting of the generating units and to obtain the maximum possible amount of electrical power in automatic and safe form. For the development of the CSG a control loop by temperature was implemented for the gas turbine system and a control loop by strangled pressure for the gas turbine and a control loop by strangled pressure for the steam turbine. The design of these supervisory systems was made with base in the critical limits on the involved variables of the process: blading average temperature, for the gas turbine (GT) and strangled pressure for the steam turbine (ST) [Spanish] Bajo estas expectativas de expansion de generacion de energia en Mexico, este trabajo expone el desarrollo de un control supervisorio generalizado (CSG) para una central generacion de ciclo combinado. Este permite lograr la operacion optima de la planta a traves del arranque automatico de las unidades generadoras y obtener la maxima cantidad posible de potencia electrica en forma automatica y segura. Para el desarrollo del CSG se implanto un lazo de control por temperatura para el sistema de turbina de gas y un lazo de control por presion estrangulada para la turbina de gas y un lazo de control por presion estrangulada para la turbina de vapor. El diseno de estos sistemas supervisorio se realizo con base en los limites criticos de las variables del proceso involucradas: temperatura promedio de empaletado para la turbina de gas (TG) y presion estrangulada para la turbina de vapor (TV)

  7. Approach to the problem of combined radiation and environmental effect standardization

    International Nuclear Information System (INIS)

    Burykina, L.N.; Ajzina, N.L.; Vasil'eva, L.A.; Veselovskaya, K.A.; Likhachev, Yu.P.; Ponomareva, V.L.; Satarina, S.M.; Shmeleva, E.V.

    1978-01-01

    Rats were used to study combined forms of damage caused by radioactive substances with varioUs types of distribution ( 131 I and 147 Pm) and by external radiation sources (γ, X). Damage caused by radiation and dust factors was also studied. Synergism of the combined effect of the tolerance dose of 147 Pm introduced and preceding external general γ-irradiation was determined. The combined action of 131 I and external γ- and X-ray radiation exhibited an additional effect on rat thyroid glands. The combined action of dust and radiation factors showed that the biological effect depended on the dose abs.orbed in a critical organ (lungs). The results of the investigations point to an important role of critical organs (systems) and the degree of their radiosensitivity in response of body to combined internal and external irradiations. The facts presented show that the approach to standardizing radiation factors from the position of partial summation should be changed. This may be accomplished by using a combination factor which is determined experimentally and reflects a relative biological efficiency of the combined effects as compared to separate ones

  8. A systematic approach to the application of Automation, Robotics, and Machine Intelligence Systems /ARAMIS/ to future space projects

    Science.gov (United States)

    Smith, D. B. S.

    1982-01-01

    The potential applications of Automation, Robotics, and Machine Intelligence Systems (ARAMIS) to space projects are investigated, through a systematic method. In this method selected space projects are broken down into space project tasks, and 69 of these tasks are selected for study. Candidate ARAMIS options are defined for each task. The relative merits of these options are evaluated according to seven indices of performance. Logical sequences of ARAMIS development are also defined. Based on this data, promising applications of ARAMIS are

  9. DC Voltage Droop Control Implementation in the AC/DC Power Flow Algorithm: Combinational Approach

    DEFF Research Database (Denmark)

    Akhter, F.; Macpherson, D.E.; Harrison, G.P.

    2015-01-01

    of operational flexibility, as more than one VSC station controls the DC link voltage of the MTDC system. This model enables the study of the effects of DC droop control on the power flows of the combined AC/DC system for steady state studies after VSC station outages or transient conditions without needing...... to use its complete dynamic model. Further, the proposed approach can be extended to include multiple AC and DC grids for combined AC/DC power flow analysis. The algorithm is implemented by modifying the MATPOWER based MATACDC program and the results shows that the algorithm works efficiently....

  10. An approach for investigation of secure access processes at a combined e-learning environment

    Science.gov (United States)

    Romansky, Radi; Noninska, Irina

    2017-12-01

    The article discuses an approach to investigate processes for regulation the security and privacy control at a heterogenous e-learning environment realized as a combination of traditional and cloud means and tools. Authors' proposal for combined architecture of e-learning system is presented and main subsystems and procedures are discussed. A formalization of the processes for using different types resources (public, private internal and private external) is proposed. The apparatus of Markovian chains (MC) is used for modeling and analytical investigation of the secure access to the resources is used and some assessments are presented.

  11. A survey of approaches combining safety and security for industrial control systems

    International Nuclear Information System (INIS)

    Kriaa, Siwar; Pietre-Cambacedes, Ludovic; Bouissou, Marc; Halgand, Yoran

    2015-01-01

    The migration towards digital control systems creates new security threats that can endanger the safety of industrial infrastructures. Addressing the convergence of safety and security concerns in this context, we provide a comprehensive survey of existing approaches to industrial facility design and risk assessment that consider both safety and security. We also provide a comparative analysis of the different approaches identified in the literature. - Highlights: • We raise awareness of safety and security convergence in numerical control systems. • We highlight safety and security interdependencies for modern industrial systems. • We give a survey of approaches combining safety and security engineering. • We discuss the potential of the approaches to model safety and security interactions

  12. The combined theoretical and experimental approach to arrive at optimum parameters in friction stir welding

    Science.gov (United States)

    Jagadeesha, C. B.

    2017-12-01

    Even though friction stir welding was invented long back (1991) by TWI England, till now there has no method or procedure or approach developed, which helps to obtain quickly optimum or exact parameters yielding good or sound weld. An approach has developed in which an equation has been derived, by which approximate rpm can be obtained and by setting range of rpm ±100 or 50 rpm over approximate rpm and by setting welding speed equal to 60 mm/min or 50 mm/min one can conduct FSW experiment to reach optimum parameters; one can reach quickly to optimum parameters, i.e. desired rpm, and welding speed, which yield sound weld by the approach. This approach can be effectively used to obtain sound welds for all similar and dissimilar combinations of materials such as Steel, Al, Mg, Ti, etc.

  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. A combined segmenting and non-segmenting approach to signal quality estimation for ambulatory photoplethysmography

    International Nuclear Information System (INIS)

    Wander, J D; Morris, D

    2014-01-01

    Continuous cardiac monitoring of healthy and unhealthy patients can help us understand the progression of heart disease and enable early treatment. Optical pulse sensing is an excellent candidate for continuous mobile monitoring of cardiovascular health indicators, but optical pulse signals are susceptible to corruption from a number of noise sources, including motion artifact. Therefore, before higher-level health indicators can be reliably computed, corrupted data must be separated from valid data. This is an especially difficult task in the presence of artifact caused by ambulation (e.g. walking or jogging), which shares significant spectral energy with the true pulsatile signal. In this manuscript, we present a machine-learning-based system for automated estimation of signal quality of optical pulse signals that performs well in the presence of periodic artifact. We hypothesized that signal processing methods that identified individual heart beats (segmenting approaches) would be more error-prone than methods that did not (non-segmenting approaches) when applied to data contaminated by periodic artifact. We further hypothesized that a fusion of segmenting and non-segmenting approaches would outperform either approach alone. Therefore, we developed a novel non-segmenting approach to signal quality estimation that we then utilized in combination with a traditional segmenting approach. Using this system we were able to robustly detect differences in signal quality as labeled by expert human raters (Pearson’s r = 0.9263). We then validated our original hypotheses by demonstrating that our non-segmenting approach outperformed the segmenting approach in the presence of contaminated signal, and that the combined system outperformed either individually. Lastly, as an example, we demonstrated the utility of our signal quality estimation system in evaluating the trustworthiness of heart rate measurements derived from optical pulse signals. (paper)

  16. Non-Newtonian Aspects of Artificial Intelligence

    Science.gov (United States)

    Zak, Michail

    2016-05-01

    The challenge of this work is to connect physics with the concept of intelligence. By intelligence we understand a capability to move from disorder to order without external resources, i.e., in violation of the second law of thermodynamics. The objective is to find such a mathematical object described by ODE that possesses such a capability. The proposed approach is based upon modification of the Madelung version of the Schrodinger equation by replacing the force following from quantum potential with non-conservative forces that link to the concept of information. A mathematical formalism suggests that a hypothetical intelligent particle, besides the capability to move against the second law of thermodynamics, acquires such properties like self-image, self-awareness, self-supervision, etc. that are typical for Livings. However since this particle being a quantum-classical hybrid acquires non-Newtonian and non-quantum properties, it does not belong to the physics matter as we know it: the modern physics should be complemented with the concept of the information force that represents a bridge to intelligent particle. As a follow-up of the proposed concept, the following question is addressed: can artificial intelligence (AI) system composed only of physical components compete with a human? The answer is proven to be negative if the AI system is based only on simulations, and positive if digital devices are included. It has been demonstrated that there exists such a quantum neural net that performs simulations combined with digital punctuations. The universality of this quantum-classical hybrid is in capability to violate the second law of thermodynamics by moving from disorder to order without external resources. This advanced capability is illustrated by examples. In conclusion, a mathematical machinery of the perception that is the fundamental part of a cognition process as well as intelligence is introduced and discussed.

  17. Approaches of data combining for reliability assessments with taking into account the priority of data application

    International Nuclear Information System (INIS)

    Zelenyj, O.V.; Pecheritsa, A.V.

    2004-01-01

    Based upon the available experience on assessments of risk from Ukrainian NPP's operational events as well as on results of State review of PSA studies for pilot units it should be noted that historical information on domestic NPP's operation is not always available or used properly under implementation of mentioned activities. The several approaches for combining of available generic and specific information for reliability parameters assessment (taking into account the priority of data application) are briefly described in the article along with some recommendations how to apply those approaches

  18. Cleaner Production and Workplace Health and Safety: A combined approach. A case study from South Africa

    DEFF Research Database (Denmark)

    Hedlund, Frank Huess

    Environmental goals may be pursued narrow-mindedly with no attention paid to the workplace. This book examines combined approaches in cleaner production projects. It explores two main avenues. First, integration into the project specification. The planning tools in use by assistance agencies......, integration of management systems is an option. A study on the South African Nosa 5-Star system refutes earlier criticism of dismal performance of top-down systems. It is argued that integration at this level is viable. For small companies, less formalistic approaches are required. ILO's network concept WISE...

  19. Combined action of ionizing radiation with another factor: common rules and theoretical approach

    International Nuclear Information System (INIS)

    Kim, Jin Kyu; Roh, Changhyun; Komarova, Ludmila N.; Petin, Vladislav G.

    2013-01-01

    Two or more factors can simultaneously make their combined effects on the biological objects. This study has focused on theoretical approach to synergistic interaction due to the combined action of radiation and another factor on cell inactivation. A mathematical model for the synergistic interaction of different environmental agents was suggested for quantitative prediction of irreversibly damaged cells after combined exposures. The model takes into account the synergistic interaction of agents and based on the supposition that additional effective damages responsible for the synergy are irreversible and originated from an interaction of ineffective sub lesions. The experimental results regarding the irreversible component of radiation damage of diploid yeast cells simultaneous exposed to heat with ionizing radiation or UV light are presented. A good agreement of experimental results with model predictions was demonstrated. The importance of the results obtained for the interpretation of the mechanism of synergistic interaction of various environmental factors is discussed. (author)

  20. Combined action of ionizing radiation with another factor: common rules and theoretical approach

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jin Kyu; Roh, Changhyun, E-mail: jkkim@kaeri.re.kr [Korea Atomic Energy Research Institute, Jeongeup (Korea, Republic of); Komarova, Ludmila N.; Petin, Vladislav G., E-mail: vgpetin@yahoo.com [Medical Radiological Research Center, Obninsk (Russian Federation)

    2013-07-01

    Two or more factors can simultaneously make their combined effects on the biological objects. This study has focused on theoretical approach to synergistic interaction due to the combined action of radiation and another factor on cell inactivation. A mathematical model for the synergistic interaction of different environmental agents was suggested for quantitative prediction of irreversibly damaged cells after combined exposures. The model takes into account the synergistic interaction of agents and based on the supposition that additional effective damages responsible for the synergy are irreversible and originated from an interaction of ineffective sub lesions. The experimental results regarding the irreversible component of radiation damage of diploid yeast cells simultaneous exposed to heat with ionizing radiation or UV light are presented. A good agreement of experimental results with model predictions was demonstrated. The importance of the results obtained for the interpretation of the mechanism of synergistic interaction of various environmental factors is discussed. (author)

  1. Combined perventricular septal defect closure and patent ductus arteriosus ligation via the lower ministernotomy approach.

    Science.gov (United States)

    Voitov, Alexey; Omelchenko, Alexander; Gorbatykh, Yuriy; Bogachev-Prokophiev, Alexander; Karaskov, Alexander

    2018-02-01

    Over the past decade, minimally invasive approaches have been advocated for surgical correction of congenital defects to reduce costs related to hospitalization and for improved cosmesis. Minimal skin incisions and partial sternotomy reduce surgical trauma, however these techniques might not be successful in treating a number of congenital pathological conditions, particularly for combined congenital defects. We focused on cases with a combined presentation of ventricular septal defect and patent ductus arteriosus. We studied 12 infants who successfully underwent surgical treatment for a combined single-stage ventricular septal defect and patent ductus arteriosus closure through a lower ministernotomy without using cardiopulmonary bypass and X-rays. No intraoperative and early postoperative complications or mortality were noted. Postoperative echocardiography did not reveal residual shunts. The proposed technique is safe and reproducible in infants. © Crown copyright 2017.

  2. Combined transnasal and transoral endoscopic approach to a transsphenoidal encephalocele in an infant.

    Science.gov (United States)

    Tan, Sien Hui; Mun, Kein Seong; Chandran, Patricia Ann; Manuel, Anura Michelle; Prepageran, Narayanan; Waran, Vicknes; Ganesan, Dharmendra

    2015-07-01

    This paper reports an unusual case of a transsphenoidal encephalocele and discusses our experience with a minimally invasive management. To the best of our knowledge, we present the first case of a combined endoscopic transnasal and transoral approach to a transsphenoidal encephalocele in an infant. A 17-day-old boy, who was referred for further assessment of upper airway obstruction, presented with respiratory distress and feeding difficulties. Bronchoscopy and imaging revealed a transsphenoidal encephalocele. At the age of 48 days, he underwent a combined endoscopic transnasal and transoral excision of the nasal component of the encephalocele. This approach, with the aid of neuronavigation, allows good demarcation of the extra-cranial neck of the transsphenoidal encephalocele. We were able to cauterize and carefully dissect the sac prior to excision. The defect of the neck was clearly visualized, and Valsalva manoeuvre was performed to exclude any CSF leak. As the defect was small, it was allowed to heal by secondary intention. The patient's recovery was uneventful, and he tolerated full feeds orally on day 2. Postoperative imaging demonstrated no evidence of recurrence of the nasal encephalocele. Endoscopic follow-up showed good healing of the mucosa and no cerebrospinal fluid leak. The surgical management of transsphenoidal encephalocele in neonates and infants is challenging. We describe a safe technique with low morbidity in managing such a condition. The combined endoscopic transnasal and transoral approach with neuronavigation is a minimally invasive, safe and feasible alternative, even for children below 1 year of age.

  3. Economic intelligence of the modern state

    OpenAIRE

    Levytskyi, Valentyn

    2001-01-01

    The goal of the thesis is to explore economic intelligence. The work includes the analysis of open sources. Tile approach to the issue of economic intelligence is based on the analysis of the state's economic security. The research presents the views of politicians, intelligence professionals, and scientists. It proposes possible objectives and missions of economic intelligence. Additionally, the research investigates the usefulness and reliability of open sources of economic analysis. The se...

  4. From Braitenberg's Vehicles to Jansen's Beach Animals: Towards an Ecological Approach to the Design of Non-Organic Intelligence

    OpenAIRE

    Bleeker, M.A.

    2017-01-01

    This article presents a comparison of two proposals for how to conceive of the evolution of non-organic intelligence. One is Valentino Braitenberg’s 1984 essay ‘Vehicles: Experiments in Synthetic Psychology’. The other is the Strandbeesten (beach animals) of Dutch engineer-artist Theo Jansen. Jansen’s beach animals are not robots. Yet, as semi-autonomous non-organic agents created by humans, they are interesting in the context of the development of robots for how they present an ecological ap...

  5. Systematic approach to the application of automation, robotics, and machine intelligence systems (aramis) to future space projects

    Energy Technology Data Exchange (ETDEWEB)

    Smith, D B.S.

    1983-01-01

    The potential applications of automation, robotics and machine intelligence systems (ARAMIS) to space projects are investigated, through a systematic method. In this method selected space projects are broken down into space project tasks, and 69 of these tasks are selected for study. Candidate ARAMIS options are defined for each task. The relative merits of these options are evaluated according to seven indices of performance. Logical sequences of ARAMIS development are also defined. Based on this data, promising applications of ARAMIS are identified for space project tasks. General conclusions and recommendations for further study are also presented. 6 references.

  6. A novel combined interventional radiologic and hepatobiliary surgical approach to a complex traumatic hilar biliary stricture

    Directory of Open Access Journals (Sweden)

    Rachel E. NeMoyer

    Full Text Available Introduction: Benign strictures of the biliary system are challenging and uncommon conditions requiring a multidisciplinary team for appropriate management. Presentation of case: The patient is a 32-year-old male that developed a hilar stricture as sequelae of a gunshot wound. Due to the complex nature of the stricture and scarring at the porta hepatis a combined interventional radiologic and surgical approach was carried out to approach the hilum of the right and left hepatic ducts. The location of this stricture was found by ultrasound guidance intraoperatively using a balloon tipped catheter placed under fluoroscopy in the interventional radiology suite prior to surgery. This allowed the surgeons to select the line of parenchymal transection for best visualization of the stricture. A left hepatectomy was performed, the internal stent located and the right hepatic duct opened tangentially to allow a side-to-side Roux-en-Y hepaticojejunostomy (a Puestow-like anastomosis. Discussion: Injury to the intrahepatic biliary ductal confluence is rarely fatal, however, the associated injuries lead to severe morbidity as seen in this example. Management of these injuries poses a considerable challenge to the surgeon and treating physicians. Conclusion: Here we describe an innovative multi-disciplinary approach to the repair of this rare injury. Keywords: Combined approach, Interventional radiology, Hepatobiliary surgery, Complex traumatic hilar biliary stricture, Case report

  7. Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

    Science.gov (United States)

    Alexandridis, Konstantinos T.

    This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

  8. 赛课结合理念在智能建筑工程人才培养中的实践%Practice of Intelligent Building Engineering Talent Cultivation by Race Course Combining

    Institute of Scientific and Technical Information of China (English)

    伍银波; 施金鸿

    2014-01-01

    赛课结合的教育方式,在培养学生实践动手能力方面效果显著,电子设计类课程尤为突出。其在智能建筑工程能力培养方面亦具有良好的效果,使学生的智能建筑工程能力大大提高,所培养的学生也得到社会的认可和好评。%The way of race course combined education, has a significant effect in the aspects of cultivating students’ practical ability, especially electronic design courses. Several years education practice show that, it also has a good effect in the intelligent building engineering capability. Through the concept of education, making the students intelligent building engineering capability is greatly improved, the students get social recognition and praise.

  9. Generalized conventional and intelligent supervisory control system for combined cycle generation power plants; Sistema de control supervisorio generalizado convencional e inteligente para centrales de generacion de ciclo combinado

    Energy Technology Data Exchange (ETDEWEB)

    Martinez Morales, Miguel Angel

    2004-12-15

    The Mexican Electricity Utility (Comision Federal de Electricidad - CFE) growing program in Power Generation for the 2004 - 2008 period is based on Combined Cycle Power Plants (CCPP). In accordance with [CFE, 2000], the expected power generation capacity developed during such period will rise by the amount of 12876 MW, 10655 MW belonging to CCPP (82.75 %). With such important program for the increasing of Power Generation in Mexico, researches have to receive new technologies for CCPP, some of them not completely tested and immature, with the compromise to make then more efficient and reliable. Under such idea and looking to increase the automation level for CCPP with better control algorithms, the Supervisory Generalized Control (SGC) for CCPP was developed in this thesis, based on PID strategies and intelligent (fuzzy) control strategies. With the SGC is possible to get the best performance for the whole CCPP through the automatic starting, synchronizing and loading of the generating units (two gas turbines and one steam turbine) with a minimum participation of operators. To get the increased efficiency, the SGC generates the reference paths for both gas turbines (GT) first, and the steam turbine (ST). The SGC accelerates each unit with a minimum effort and vibrations getting the synchronizing speed in a minimum time and wasted energy. Then the SGC synchronize each unit taking minimum load quickly and loading up to the highest electric power value. All these can be done in an automated operation. The SGC employs two critical-process variable- control strategies, based on blade path temperature average (BPT Average) for Gas Turbines (GT) and the throttle steam pressure for the Steam Turbine (ST). The control algorithms designed take both units, the GT and the ST, picking up load to the highest process value avoiding the alarms activation and shutdown. This is possible only with such an automated control strategy. Test performed showed that with the SGC

  10. Combining non-invasive transcranial brain stimulation with neuroimaging and electrophysiology: Current approaches and future perspectives.

    Science.gov (United States)

    Bergmann, Til Ole; Karabanov, Anke; Hartwigsen, Gesa; Thielscher, Axel; Siebner, Hartwig Roman

    2016-10-15

    Non-invasive transcranial brain stimulation (NTBS) techniques such as transcranial magnetic stimulation (TMS) and transcranial current stimulation (TCS) are important tools in human systems and cognitive neuroscience because they are able to reveal the relevance of certain brain structures or neuronal activity patterns for a given brain function. It is nowadays feasible to combine NTBS, either consecutively or concurrently, with a variety of neuroimaging and electrophysiological techniques. Here we discuss what kind of information can be gained from combined approaches, which often are technically demanding. We argue that the benefit from this combination is twofold. Firstly, neuroimaging and electrophysiology can inform subsequent NTBS, providing the required information to optimize where, when, and how to stimulate the brain. Information can be achieved both before and during the NTBS experiment, requiring consecutive and concurrent applications, respectively. Secondly, neuroimaging and electrophysiology can provide the readout for neural changes induced by NTBS. Again, using either concurrent or consecutive applications, both "online" NTBS effects immediately following the stimulation and "offline" NTBS effects outlasting plasticity-inducing NTBS protocols can be assessed. Finally, both strategies can be combined to close the loop between measuring and modulating brain activity by means of closed-loop brain state-dependent NTBS. In this paper, we will provide a conceptual framework, emphasizing principal strategies and highlighting promising future directions to exploit the benefits of combining NTBS with neuroimaging or electrophysiology. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  11. 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...

  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. 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

  14. Phytophagous insects on native and non-native host plants: combining the community approach and the biogeographical approach.

    Directory of Open Access Journals (Sweden)

    Kim Meijer

    Full Text Available During the past centuries, humans have introduced many plant species in areas where they do not naturally occur. Some of these species establish populations and in some cases become invasive, causing economic and ecological damage. Which factors determine the success of non-native plants is still incompletely understood, but the absence of natural enemies in the invaded area (Enemy Release Hypothesis; ERH is one of the most popular explanations. One of the predictions of the ERH, a reduced herbivore load on non-native plants compared with native ones, has been repeatedly tested. However, many studies have either used a community approach (sampling from native and non-native species in the same community or a biogeographical approach (sampling from the same plant species in areas where it is native and where it is non-native. Either method can sometimes lead to inconclusive results. To resolve this, we here add to the small number of studies that combine both approaches. We do so in a single study of insect herbivory on 47 woody plant species (trees, shrubs, and vines in the Netherlands and Japan. We find higher herbivore diversity, higher herbivore load and more herbivory on native plants than on non-native plants, generating support for the enemy release hypothesis.

  15. Application of Wireless Sensor and Actuator Networks to Achieve Intelligent Microgrids: A Promising Approach towards a Global Smart Grid Deployment

    Directory of Open Access Journals (Sweden)

    Alvaro Llaria

    2016-02-01

    Full Text Available Smart Grids (SGs constitute the evolution of the traditional electrical grid towards a new paradigm, which should increase the reliability, the security and, at the same time, reduce the costs of energy generation, distribution and consumption. Electrical microgrids (MGs can be considered the first stage of this evolution of the grid, because of the intelligent management techniques that must be applied to assure their correct operation. To accomplish this task, sensors and actuators will be necessary, along with wireless communication technologies to transmit the measured data and the command messages. Wireless Sensor and Actuator Networks (WSANs are therefore a promising solution to achieve an intelligent management of MGs and, by extension, the SG. In this frame, this paper surveys several aspects concerning the application of WSANs to manage MGs and the electrical grid, as well as the communication protocols that could be applied. The main concerns regarding the SG deployment are also presented, including future scenarios where the interoperability of different generation technologies must be assured.

  16. Intelligent Buildings: Key to Achieving Total Sustainability in the Built Environment

    Directory of Open Access Journals (Sweden)

    Tulika Gadakari

    2014-01-01

    Full Text Available ‘Are intelligent buildings a pragmatic approach towards achieving a sustainable built environment?’ is the research question that this review article aims to answer. It has been argued that there is a serious need for intelligent buildings to be evaluated against the parameters of total sustainability (environmental, economic and social so as to help the agenda of living in a technologically advanced, healthy and comfortable world. This paper reviews existing theoretical concepts of intelligence and sustainability in the built environment, through an exploration of various scientific literature and U.S Green Building Council’s LEED (Leadership in Energy and Environmental Design databases. A systematic qualitative review approach has been employed to select an appropriate definition of sustainable development and use it as a theoretical framework to assess the technological impact of intelligent buildings on the environmental, economic and social front. Subsequently five case study buildings from around the world, which exemplify the use of intelligent technologies to achieve sustainable gains were chosen and analyzed to further validate the literature findings. Outputs from the study highlight the various benefits of intelligent buildings, which include decrease in energy and water consumption, operational costs, as well as increase in productivity and investments. Additionally the analysis of the case studies revealed that the use of intelligent building technologies has contributed significantly towards a higher sustainability rating on the LEED rating scale. Moreover, the comparison of the attributes of intelligent buildings and sustainable practices in buildings, illustrates the fact that there is a considerable overlap between the two and intelligence can aid sustainability in the built environment. Thus the research suggests that green technologies and intelligence in combination may be a pragmatic approach towards the sustainability

  17. Benefits of collective intelligence: Swarm intelligent foraging, an ethnographic research

    Directory of Open Access Journals (Sweden)

    Sivave Mashingaidze

    2014-12-01

    Full Text Available Wisdom of crowds; bees, colonies of ants, schools of fish, flocks of birds, and fireflies flashing synchronously are all examples of highly coordinated behaviors that emerge from collective, decentralized intelligence. This article is an ethnographic study of swarm intelligence foraging of swarms and the benefits derived from collective decision making. The author used using secondary data analysis to look at the benefits of swarm intelligence in decision making to achieve intended goals. Concepts like combined decision making and consensus were discussed and four principles of swarm intelligence were also discussed viz; coordination, cooperation, deliberation and collaboration. The research found out that collective decision making in swarms is the touchstone of achieving their goals. The research further recommended corporate to adopt collective intelligence for business sustainability.

  18. Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

    Science.gov (United States)

    Li, Tongwen; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Xuechen; Zhang, Liangpei

    2017-12-01

    Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

  19. 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.

  20. Modified Lip Repositioning with Esthetic Crown Lengthening: A Combined Approach to Treating Excessive Gingival Display.

    Science.gov (United States)

    Sánchez, Isis M; Gaud-Quintana, Sadja; Stern, Jacob K

    Lip repositioning surgery to address excessive gingival display induced by different etiologies has received major attention recently. Several techniques and variations have been reported, including myotomy or repositioning of the levator labii superioris muscle, Le Fort impaction, maxillary gingivectomies, botulinum toxin injections, and lip stabilization. This study reports a case of excessive gingival display treated by a modified combined approach. A 25-year-old woman with a 4- to 8-mm gingival display when smiling caused by a combination of short clinical crowns induced by an altered passive eruption and hypermobility of the upper lip underwent a staged esthetic crown-lengthening procedure followed by a modified lip repositioning technique. A description of the technique and a comparison with other modes of therapy is discussed. This modified approach for treating the hypermobile lip included a bilateral removal of a partial-thickness strip of mucosa from the maxillary buccal vestibule without severing the muscle, leaving the midline frenum intact and suturing the lip mucosa to the mucogingival line. The narrower vestibule and increased tooth length resulted in a symmetric and pleasing gingival display when smiling that remained stable over time. With proper diagnosis and sequence of therapy, modified lip repositioning surgery combined with esthetic crown lengthening can be used predictably to treat excessive gingival display and enhance smile esthetics.

  1. Attitudes Toward Combining Psychological, Mind-Body Therapies and Nutritional Approaches for the Enhancement of Mood.

    Science.gov (United States)

    Lores, Taryn Jade; Henke, Miriam; Chur-Hansen, Anna

    2016-01-01

    Context • Interest has been rising in the use of complementary and alternative medicine (CAM) for the promotion of health and treatment of disease. To date, the majority of CAM research has focused on exploring the demographic characteristics, attitudes, and motivations of CAM users and on the efficacy of different therapies and products. Less is known with respect to the psychological characteristics of people who use CAM. Previous research has not investigated the usefulness of integrating mind-body therapies with natural products in a combined mood intervention. Objective • The study intended to investigate attitudes toward a proposed new approach to the treatment of mood, one that integrates psychological mind-body therapies and natural nutritional products. Design • Participants completed an online survey covering demographics, personality traits, locus of control, use of CAM, attitudes toward the proposed psychonutritional approach, and mood. Setting • This study was conducted at the University of Adelaide School of Psychology (Adelaide, SA, Australia). Participants • Participants were 333 members of the Australian general public, who were recruited online via the social-media platform Facebook. The majority were women (83.2%), aged between 18 and 81 y. Outcome Measures • Measures included the Multidimensional Health Locus of Control Scale Form B, the Ten-Item Personality Inventory, and the Depression, Anxiety and Stress Scale. Results • Participants were positive about the proposed approach and were likely to try it to enhance their moods. The likeliness of use of the combined approach was significantly higher in the female participants and was associated with higher levels of the personality trait openness and an internal health locus of control, after controlling for all other variables. Conclusions • Interest exists for an intervention for mood that incorporates both psychological and nutritional approaches. Further research into the

  2. Prognostic factors in invasive bladder carcinoma treated by combined modality protocol (organ-sparing approach)

    International Nuclear Information System (INIS)

    Matos, Tadeja; Cufer, Tanja; Cervek, Jozica; Borstnar, Simona; Kragelj, Borut; Zumer-Pregelj, Mirjana

    2000-01-01

    Purpose: The results of bladder sparing approach for the treatment of muscle-invasive bladder cancer, using a combination of transurethral resection (TUR), chemotherapy, and radiotherapy, are encouraging. The survival of patients treated by this method is similar to the survival of patients treated by radical cystectomy. The aim of our study was to find out which pretreatment characteristics influence the survival of patients treated by organ sparing approach that would enable us to identify the patients most suitable for this type of treatment. Methods and Materials: The prognostic value of different factors, such as age, gender, performance status, hemoglobin level, clinical stage, histologic grade, presence of obstructive uropathy, and completeness of TUR, has been studied in 105 patients with invasive bladder cancer, who received a bladder sparing treatment in the period from 1988 to 1995. They were treated with a combination of TUR, followed by 2-4 cycles of methotrexate, cisplatinum, and vinblastine polychemotherapy. In complete responders the treatment was completed by radiotherapy (50 Gy to the bladder and 40 Gy to the regional lymph nodes), whereas nonresponders underwent cystectomy whenever feasible. Results: Our study has confirmed an independent prognostic value of performance status, histologic grade, and obstructive uropathy, for the disease-specific survival (DSS) of bladder cancer patients treated by a conservative approach. We believe that performance status best reflects the extent of disease and exerts significant influence on the extent and course of treatment, while obstructive uropathy is a good indicator of local spread of the disease, better than clinical T-stage. Our finding that histologic grade is one of the strongest prognostic factors shows that tumor biology also is a very important prognostic factor in patients treated by conservative approach. Conclusion: Patients with muscle-invasive bladder cancer who are most likely to benefit

  3. Intelligent Freigth Transport Systems

    DEFF Research Database (Denmark)

    Overø, Helene Martine; Larsen, Allan; Røpke, Stefan

    2009-01-01

    is to enhance the efficiency and lower the environmental impact in freight transport. In this paper, a pilot project involving real-time waste collection at a Danish waste collection company is described, and a solution approach is proposed. The problem corresponds to the dynamic version of the waste collection......The Danish innovation project entitled “Intelligent Freight Transport Systems” aims at developing prototype systems integrating public intelligent transport systems (ITS) with the technology in vehicles and equipment as well as the IT-systems at various transport companies. The objective...

  4. 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...

  5. 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

  6. 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.

  7. Minimization of the LCA impact of thermodynamic cycles using a combined simulation-optimization approach

    International Nuclear Information System (INIS)

    Brunet, Robert; Cortés, Daniel; Guillén-Gosálbez, Gonzalo; Jiménez, Laureano; Boer, Dieter

    2012-01-01

    This work presents a computational approach for the simultaneous minimization of the total cost and environmental impact of thermodynamic cycles. Our method combines process simulation, multi-objective optimization and life cycle assessment (LCA) within a unified framework that identifies in a systematic manner optimal design and operating conditions according to several economic and LCA impacts. Our approach takes advantages of the complementary strengths of process simulation (in which mass, energy balances and thermodynamic calculations are implemented in an easy manner) and rigorous deterministic optimization tools. We demonstrate the capabilities of this strategy by means of two case studies in which we address the design of a 10 MW Rankine cycle modeled in Aspen Hysys, and a 90 kW ammonia-water absorption cooling cycle implemented in Aspen Plus. Numerical results show that it is possible to achieve environmental and cost savings using our rigorous approach. - Highlights: ► Novel framework for the optimal design of thermdoynamic cycles. ► Combined use of simulation and optimization tools. ► Optimal design and operating conditions according to several economic and LCA impacts. ► Design of a 10MW Rankine cycle in Aspen Hysys, and a 90kW absorption cycle in Aspen Plus.

  8. Minimization of the LCA impact of thermodynamic cycles using a combined simulation-optimization approach

    Energy Technology Data Exchange (ETDEWEB)

    Brunet, Robert; Cortes, Daniel [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Guillen-Gosalbez, Gonzalo [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Jimenez, Laureano [Departament d' Enginyeria Quimica, Escola Tecnica Superior d' Enginyeria Quimica, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007 Tarragona (Spain); Boer, Dieter [Departament d' Enginyeria Mecanica, Escola Tecnica Superior d' Enginyeria, Universitat Rovira i Virgili, Campus Sescelades, Avinguda Paisos Catalans 26, 43007, Tarragona (Spain)

    2012-12-15

    This work presents a computational approach for the simultaneous minimization of the total cost and environmental impact of thermodynamic cycles. Our method combines process simulation, multi-objective optimization and life cycle assessment (LCA) within a unified framework that identifies in a systematic manner optimal design and operating conditions according to several economic and LCA impacts. Our approach takes advantages of the complementary strengths of process simulation (in which mass, energy balances and thermodynamic calculations are implemented in an easy manner) and rigorous deterministic optimization tools. We demonstrate the capabilities of this strategy by means of two case studies in which we address the design of a 10 MW Rankine cycle modeled in Aspen Hysys, and a 90 kW ammonia-water absorption cooling cycle implemented in Aspen Plus. Numerical results show that it is possible to achieve environmental and cost savings using our rigorous approach. - Highlights: Black-Right-Pointing-Pointer Novel framework for the optimal design of thermdoynamic cycles. Black-Right-Pointing-Pointer Combined use of simulation and optimization tools. Black-Right-Pointing-Pointer Optimal design and operating conditions according to several economic and LCA impacts. Black-Right-Pointing-Pointer Design of a 10MW Rankine cycle in Aspen Hysys, and a 90kW absorption cycle in Aspen Plus.

  9. Artificial intelligence based approach to forecast PM2.5 during haze episodes: A case study of Delhi, India

    Science.gov (United States)

    Mishra, Dhirendra; Goyal, P.; Upadhyay, Abhishek

    2015-02-01

    Delhi has been listed as the worst performer across the world with respect to the presence of alarmingly high level of haze episodes, exposing the residents here to a host of diseases including respiratory disease, chronic obstructive pulmonary disorder and lung cancer. This study aimed to analyze the haze episodes in a year and to develop the forecasting methodologies for it. The air pollutants, e.g., CO, O3, NO2, SO2, PM2.5 as well as meteorological parameters (pressure, temperature, wind speed, wind direction index, relative humidity, visibility, dew point temperature, etc.) have been used in the present study to analyze the haze episodes in Delhi urban area. The nature of these episodes, their possible causes, and their major features are discussed in terms of fine particulate matter (PM2.5) and relative humidity. The correlation matrix shows that temperature, pressure, wind speed, O3, and dew point temperature are the dominating variables for PM2.5 concentrations in Delhi. The hour-by-hour analysis of past data pattern at different monitoring stations suggest that the haze hours were occurred approximately 48% of the total observed hours in the year, 2012 over Delhi urban area. The haze hour forecasting models in terms of PM2.5 concentrations (more than 50 μg/m3) and relative humidity (less than 90%) have been developed through artificial intelligence based Neuro-Fuzzy (NF) techniques and compared with the other modeling techniques e.g., multiple linear regression (MLR), and artificial neural network (ANN). The haze hour's data for nine months, i.e. from January to September have been chosen for training and remaining three months, i.e., October to December in the year 2012 are chosen for validation of the developed models. The forecasted results are compared with the observed values with different statistical measures, e.g., correlation coefficients (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA). The performed

  10. Minilaparoscopic technique for inguinal hernia repair combining transabdominal pre-peritoneal and totally extraperitoneal approaches.

    Science.gov (United States)

    Carvalho, Gustavo L; Loureiro, Marcelo P; Bonin, Eduardo A; Claus, Christiano P; Silva, Frederico W; Cury, Antonio M; Fernandes, Flavio A M

    2012-01-01

    Endoscopic surgical repair of inguinal hernia is currently conducted using 2 techniques: the totally extraperitoneal (TEP) and the transabdominal (TAPP) hernia repair. The TEP procedure is technically advantageous, because of the use of no mesh fixation and the elimination of the peritoneal flap, leading to less postoperative pain and faster recovery. The drawback is that TEP is not performed as frequently, because of its complexity and longer learning curve. In this study, we propose a hybrid technique that could potentially become the gold standard of minimally invasive inguinal hernia surgery. This will be achieved by combining established advantages of TEP and TAPP associated with the precision and cosmetics of minilaparoscopy (MINI). Between January and July 2011, 22 patients were admitted for endoscopic inguinal hernia repair. The combined technique was initiated with TAPP inspection and direct visualization of a minilaparoscopic trocar dissection of the preperitoneum space. A10-mm trocar was then placed inside the previously dissected preperitoneal space, using the same umbilical TAPP skin incision. Minilaparoscopic retroperitoneal dissection was completed by TEP, and the surgical procedure was finalized with intraperitoneal review and correction of the preperitoneal work. The minilaparoscopic TEP-TAPP combined approach for inguinal hernia is feasible, safe, and allows a simple endoscopic repair. This is achieved by combining features and advantages of both TAPP and TEP techniques using precise and sophisticated MINI instruments. Minilaparoscopic preperitoneal dissection allows a faster and easier creation of the preperitoneal space for the TEP component of the procedure.

  11. Constructed Wetlands for Combined Sewer Overflow Treatment—Comparison of German, French and Italian Approaches

    Directory of Open Access Journals (Sweden)

    Daniel Meyer

    2012-12-01

    Full Text Available Combined sewer systems are designed to transport stormwater surface run off in addition to the dry weather flows up to defined limits. In most European countries, hydraulic loads greater than the design flow are discharged directly into receiving water bodies, with minimal treatment (screening, sedimentation, or with no treatment at all. One feasible solution to prevent receiving waters from strong negative impacts seems to be the application of vertical flow constructed wetlands. In Germany, first attempts to use this ecological technology were recognized in early 1990s. Since then, further development continued until a high level of treatment performance was reached. During recent years the national “state-of-the-art” (defined in 2005 was adapted in other European countries, including France and Italy. Against the background of differing national requirements in combined sewer system design, substantial developmental steps were taken. The use of coarser filter media in combination with alternating loadings of separated filter beds allows direct feedings with untreated combined runoff. Permanent water storage in deep layers of the wetland improves the system’s robustness against extended dry periods, but contains operational risks. Besides similar functions (but different designs and layouts, correct dimensioning of all approaches suffers from uncertainties in long-term rainfall predictions as well as inside sewer system simulation tools.

  12. 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 ...

  13. Ensemble approach combining multiple methods improves human transcription start site prediction

    LENUS (Irish Health Repository)

    Dineen, David G

    2010-11-30

    Abstract Background The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets. Results We demonstrate the heterogeneity of current prediction sets, and take advantage of this heterogeneity to construct a two-level classifier (\\'Profisi Ensemble\\') using predictions from 7 programs, along with 2 other data sources. Support vector machines using \\'full\\' and \\'reduced\\' data sets are combined in an either\\/or approach. We achieve a 14% increase in performance over the current state-of-the-art, as benchmarked by a third-party tool. Conclusions Supervised learning methods are a useful way to combine predictions from diverse sources.

  14. Combining Upper Limb Robotic Rehabilitation with Other Therapeutic Approaches after Stroke: Current Status, Rationale, and Challenges

    Directory of Open Access Journals (Sweden)

    Stefano Mazzoleni

    2017-01-01

    Full Text Available A better understanding of the neural substrates that underlie motor recovery after stroke has led to the development of innovative rehabilitation strategies and tools that incorporate key elements of motor skill relearning, that is, intensive motor training involving goal-oriented repeated movements. Robotic devices for the upper limb are increasingly used in rehabilitation. Studies have demonstrated the effectiveness of these devices in reducing motor impairments, but less so for the improvement of upper limb function. Other studies have begun to investigate the benefits of combined approaches that target muscle function (functional electrical stimulation and botulinum toxin injections, modulate neural activity (noninvasive brain stimulation, and enhance motivation (virtual reality in an attempt to potentialize the benefits of robot-mediated training. The aim of this paper is to overview the current status of such combined treatments and to analyze the rationale behind them.

  15. Advanced strategies for end-stage heart failure: combining regenerative approaches with LVAD, a new horizon?

    Directory of Open Access Journals (Sweden)

    Cheyenne eTseng

    2015-04-01

    Full Text Available Despite the improved treatment of cardiovascular diseases the population with end-stage heart failure is progressively growing. The scarcity of the gold standard therapy, heart transplantation, demands novel therapeutic approaches. For patients awaiting transplantation ventricular assist devices have been of great benefit on survival. To allow explantation of the assist device and obviate heart transplantation, sufficient and durable myocardial recovery is necessary. However, explant rates so far are low. Combining mechanical circulatory support with regenerative therapies such as cell(-based therapy and biomaterials might give rise to improved long-term results. Although synergistic effects are suggested with mechanical support and stem cell therapy, evidence in both preclinical and clinical setting is lacking. This review focuses on advanced and innovative strategies for the treatment of end-stage heart failure and furthermore appraises clinical experience with combined strategies.

  16. Artificial intelligence in nanotechnology.

    Science.gov (United States)

    Sacha, G M; Varona, P

    2013-11-15

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  17. Artificial intelligence in nanotechnology

    Science.gov (United States)

    Sacha, G. M.; Varona, P.

    2013-11-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  18. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

    Sacha, G M; Varona, P

    2013-01-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

  19. A genetic-neural artificial intelligence approach to resins optimization; Uma metodologia baseada em inteligencia artificial para otimizacao de resinas

    Energy Technology Data Exchange (ETDEWEB)

    Cabral, Denise C.; Barros, Marcio P.; Lapa, Celso M.F.; Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: lapa@ien.gov.br; mbarros@ien.gov.br

    2005-07-01

    This work presents a preliminary study about the viability and adequacy of a new methodology for the definition of one of the main properties of ion exchange resins used for isotopic separation. Basically, the main problem is the definition of pelicule diameter in case of pelicular ion exchange resins, in order to achieve the best performance in the shortest time. In order to achieve this, a methodology was developed, based in two classic techniques of Artificial Intelligence (AI). At first, an artificial neural network (NN) was trained to map the existing relations between the nucleus radius and the resin's efficiency associated with the exchange time. Later on, a genetic algorithm (GA) was developed in order to find the best pelicule dimension. Preliminary results seem to confirm the potential of the method, and this can be used in any chemical process employing ion exchange resins. (author)

  20. A Benders decomposition approach for a combined heat and power economic dispatch

    International Nuclear Information System (INIS)

    Abdolmohammadi, Hamid Reza; Kazemi, Ahad

    2013-01-01

    Highlights: • Benders decomposition algorithm to solve combined heat and power economic dispatch. • Decomposing the CHPED problem into master problem and subproblem. • Considering non-convex heat-power feasible region efficiently. • Solving 4 units and 5 units system with 2 and 3 co-generation units, respectively. • Obtaining better or as well results in terms of objective values. - Abstract: Recently, cogeneration units have played an increasingly important role in the utility industry. Therefore the optimal utilization of multiple combined heat and power (CHP) systems is an important optimization task in power system operation. Unlike power economic dispatch, which has a single equality constraint, two equality constraints must be met in combined heat and power economic dispatch (CHPED) problem. Moreover, in the cogeneration units, the power capacity limits are functions of the unit heat productions and the heat capacity limits are functions of the unit power generations. Thus, CHPED is a complicated optimization problem. In this paper, an algorithm based on Benders decomposition (BD) is proposed to solve the economic dispatch (ED) problem for cogeneration systems. In the proposed method, combined heat and power economic dispatch problem is decomposed into a master problem and subproblem. The subproblem generates the Benders cuts and master problem uses them as a new inequality constraint which is added to the previous constraints. The iterative process will continue until upper and lower bounds of the objective function optimal values are close enough and a converged optimal solution is found. Benders decomposition based approach is able to provide a good framework to consider the non-convex feasible operation regions of cogeneration units efficiently. In this paper, a four-unit system with two cogeneration units and a five-unit system with three cogeneration units are analyzed to exhibit the effectiveness of the proposed approach. In all cases, the