WorldWideScience

Sample records for intelligence based methods

  1. Cyclotron operating mode determination based on intelligent methods

    International Nuclear Information System (INIS)

    Ouda, M.M.E.M.

    2011-01-01

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

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

    OpenAIRE

    Bo Sun; Qiang Feng; Songjie Li

    2012-01-01

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

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

    Science.gov (United States)

    Zhou, Jian; Xue, Qian

    2018-05-01

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

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

    Science.gov (United States)

    Qiu, Feng; Dai, Guang; Zhang, Ying

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

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

    Science.gov (United States)

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

    2015-12-09

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

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

    Directory of Open Access Journals (Sweden)

    Fengmei Li

    2015-12-01

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

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

    DEFF Research Database (Denmark)

    Beczkowski, Szymon

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

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

    Directory of Open Access Journals (Sweden)

    Bo Sun

    2012-01-01

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

  9. Discrete simulation system based on artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Futo, I; Szeredi, J

    1982-01-01

    A discrete event simulation system based on the AI language Prolog is presented. The system called t-Prolog extends the traditional possibilities of simulation languages toward automatic problem solving by using backtrack in time and automatic model modification depending on logical deductions. As t-Prolog is an interactive tool, the user has the possibility to interrupt the simulation run to modify the model or to force it to return to a previous state for trying possible alternatives. It admits the construction of goal-oriented or goal-seeking models with variable structure. Models are defined in a restricted version of the first order predicate calculus using Horn clauses. 21 references.

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

    OpenAIRE

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

    2016-01-01

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

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

    NARCIS (Netherlands)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Linhui Li

    2015-01-01

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

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

    Science.gov (United States)

    Hongzhi, Zhao; Jian, Zhang

    2018-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Karel Octavianus Bachri

    2017-07-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-07-15

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

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

    International Nuclear Information System (INIS)

    Anghel, Calin I.

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Li Wei

    2017-11-01

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

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

    International Nuclear Information System (INIS)

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

    1996-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Qing Song Ai

    2013-01-01

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

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

    Science.gov (United States)

    Wang, Qiang; Cheng, Tao

    2018-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Dengpan Ye

    2011-10-01

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

  3. Intelligent methods for cyber warfare

    CERN Document Server

    Reformat, Marek; Alajlan, Naif

    2015-01-01

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

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

    Science.gov (United States)

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

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

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

    Institute of Scientific and Technical Information of China (English)

    桂劲松; 刘红; 康海贵

    2004-01-01

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

  6. A New Dimension of Business Intelligence: Location-based Intelligence

    OpenAIRE

    Zeljko Panian

    2012-01-01

    Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

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

    Energy Technology Data Exchange (ETDEWEB)

    Marshall, S.; Kajl, S.

    1999-07-01

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

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

    Science.gov (United States)

    Doaei, Marjan; Tavallali, M. Sadegh

    2018-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Kwang Baek Kim

    2015-01-01

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

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

    International Nuclear Information System (INIS)

    Jiang Li; Shi Tielin; Xuan Jianping

    2012-01-01

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

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

    Science.gov (United States)

    Hortos, William S.

    2006-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Daniel Garcia-Pozuelo

    2017-02-01

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

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

    Science.gov (United States)

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

    2006-12-01

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

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-12-20

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

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

    Directory of Open Access Journals (Sweden)

    Chien-Ming Hung

    2017-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Mostefa RAHLI

    2006-07-01

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

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

    Science.gov (United States)

    Xin, L.

    2018-04-01

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

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  20. 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.  .

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

    International Nuclear Information System (INIS)

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

    2007-01-01

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

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

    Science.gov (United States)

    Yan, Xuesong; Zhu, Zhixin; Wu, Qinghua

    2018-01-01

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

  3. COMPETITIVE INTELLIGENCE ANALYSIS - SCENARIOS METHOD

    Directory of Open Access Journals (Sweden)

    Ivan Valeriu

    2014-07-01

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

  4. Artificial intelligence methods for diagnostic

    International Nuclear Information System (INIS)

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

    1996-01-01

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

  5. Constructing an Intelligent Patent Network Analysis Method

    Directory of Open Access Journals (Sweden)

    Chao-Chan Wu

    2012-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Feng Qiang

    2014-04-01

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

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

    OpenAIRE

    Feng, Qiang; Li, Songjie; Sun, Bo

    2014-01-01

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

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

    Science.gov (United States)

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

    2016-01-08

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

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

    Directory of Open Access Journals (Sweden)

    Ke Li

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jinshuan Peng

    2018-01-01

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

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

    Science.gov (United States)

    Schmidt, Uwe

    2005-10-01

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

  15. Machine intelligence and knowledge bases

    Energy Technology Data Exchange (ETDEWEB)

    Furukawa, K

    1981-09-01

    The basic functions necessary in machine intelligence are a knowledge base and a logic programming language such as PROLOG using deductive reasoning. Recently inductive reasoning based on meta knowledge and default reasoning have been developed. The creative thought model of Lenit is reviewed and the concept of knowledge engineering is introduced. 17 references.

  16. Intelligent structural optimization: Concept, Model and Methods

    International Nuclear Information System (INIS)

    Lu, Dagang; Wang, Guangyuan; Peng, Zhang

    2002-01-01

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

  17. 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.

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

    Science.gov (United States)

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

    2017-08-09

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

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

    Directory of Open Access Journals (Sweden)

    Liang Xiaodan

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jin-Woo Jung

    2005-04-01

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

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

    Science.gov (United States)

    Osipov, Gennady

    2013-04-01

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

  2. Students’ thinking level based on intrapersonal intelligence

    Science.gov (United States)

    Sholikhati, Rahadian; Mardiyana; Retno Sari Saputro, Dewi

    2017-12-01

    This research aims to determine the students’ thinking level based on bloom taxonomy guidance and reviewed from students' Intrapersonal Intelligence. Taxonomy bloom is a taxonomy that classifies the students' thinking level into six, ie the remembering, understanding, applying, analyzing, creating, and evaluating levels. Students' Intrapersonal Intelligence is the intelligence associated with awareness and knowledge of oneself. The type of this research is descriptive research with qualitative approach. The research subject were taken by one student in each Intrapersonal Intelligence category (high, moderate, and low) which then given the problem solving test and the result was triangulated by interview. From this research, it is found that high Intrapersonal Intelligence students can achieve analyzing thinking level, subject with moderate Intrapersonal Intelligence being able to reach the level of applying thinking, and subject with low Intrapersonal Intelligence able to reach understanding level.

  3. Mathematics creative thinking levels based on interpersonal intelligence

    Science.gov (United States)

    Kuncorowati, R. H.; Mardiyana; Saputro, D. R. S.

    2017-12-01

    Creative thinking ability was one of student’s ability to determine various alternative solutions toward mathematics problem. One of indicators related to creative thinking ability was interpersonal intelligence. Student’s interpersonal intelligence would influence to student’s creativity. This research aimed to analyze creative thinking ability level of junior high school students in Karanganyar using descriptive method. Data was collected by test, questionnaire, interview, and documentation. The result showed that students with high interpersonal intelligence achieved third and fourth level in creative thinking ability. Students with moderate interpersonal intelligence achieved second level in creative thinking ability and students with low interpersonal intelligence achieved first and zero level in creative thinking ability. Hence, students with high, moderate, and low interpersonal intelligence could solve mathematics problem based on their mathematics creative thinking ability.

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

    Directory of Open Access Journals (Sweden)

    Kisielnicki Jerzy

    2017-10-01

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

  5. Computing Nash equilibria through computational intelligence methods

    Science.gov (United States)

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

    2005-03-01

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

  6. A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

    Directory of Open Access Journals (Sweden)

    Shan Li

    2014-01-01

    Full Text Available With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

  7. Intelligent Transportation Control based on Proactive Complex Event Processing

    Directory of Open Access Journals (Sweden)

    Wang Yongheng

    2016-01-01

    Full Text Available Complex Event Processing (CEP has become the key part of Internet of Things (IoT. Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is proposed as sequential decision model. A Q-learning method is proposed for this model. The experimental evaluations show that this method works well when used to control congestion in in intelligent transportation systems.

  8. Delamination detection using methods of computational intelligence

    Science.gov (United States)

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

    2012-11-01

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

  9. ORTHO IMAGE AND DTM GENERATION WITH INTELLIGENT METHODS

    Directory of Open Access Journals (Sweden)

    H. Bagheri

    2013-10-01

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

  10. Intelligent interaction based on holographic personalized portal

    Directory of Open Access Journals (Sweden)

    Yadong Huang

    2017-06-01

    Full Text Available Purpose – The purpose of this paper is to study the architecture of holographic personalized portal, user modeling, commodity modeling and intelligent interaction. Design/methodology/approach – In this paper, the authors propose crowd-science industrial ecological system based on holographic personalized portal and its interaction. The holographic personality portal is based on holographic enterprises, commodities and consumers, and the personalized portal consists of accurate ontology, reliable supply, intelligent demand and smart cyberspace. Findings – The personalized portal can realize the information acquisition, characteristic analysis and holographic presentation. Then, the intelligent interaction, e.g. demand decomposition, personalized search, personalized presentation and demand prediction, will be implemented within the personalized portal. Originality/value – The authors believe that their work on intelligent interaction based on holographic personalized portal, which has been first proposed in this paper, is innovation focusing on the interaction between intelligence and convenience.

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

    Directory of Open Access Journals (Sweden)

    Marina ZHURAVSKAYA

    2014-12-01

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

  12. Speech Intelligibility Prediction Based on Mutual Information

    DEFF Research Database (Denmark)

    Jensen, Jesper; Taal, Cees H.

    2014-01-01

    This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

  13. Ability-versus skill-based assessment of emotional intelligence.

    Science.gov (United States)

    Bradberry, Travis R; Su, Lac D

    2006-01-01

    Emotional intelligence has received an intense amount of attention in leadership circles during the last decade and continuing debate exists concerning the best method for measuring this construct. This study analyzed leader emotional intelligence scores, measured via skill and ability methodologies, against leader job performance. Two hundred twelve employees from three organizations participated in this study. Scores on the Emotional Intelligence Appraisal, a skill-based assessment, were positively, though not significantly, correlated with scores on the MSCEIT, an ability-based assessment of emotional intelligence. Scores on the MSCEIT did not have a significant relationship with job performance in this study, whereas, scores on the Emotional Intelligence Appraisal had a strong link to leader job performance. The four subcomponents of the Emotional Intelligence Appraisal were examined against job performance. Relationship management was a stronger predictor of leader job performance than the other three subcomponents. Social awareness was the single emotional intelligence skill that did not have a significant link to leader job performance. Factor analyses yielded a two-component model of emotional intelligence encompassing personal and social competence, rather than confirmation of a four-part taxonomy.

  14. Ortho Image and DTM Generation with Intelligent Methods

    Science.gov (United States)

    Bagheri, H.; Sadeghian, S.

    2013-10-01

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

  15. Business intelligence and capacity planning: web-based solutions.

    Science.gov (United States)

    James, Roger

    2010-07-01

    Income (activity) and expenditure (costs) form the basis of a modern hospital's 'business intelligence'. However, clinical engagement in business intelligence is patchy. This article describes the principles of business intelligence and outlines some recent developments using web-based applications.

  16. Intelligent Transportation Control based on Proactive Complex Event Processing

    OpenAIRE

    Wang Yongheng; Geng Shaofeng; Li Qian

    2016-01-01

    Complex Event Processing (CEP) has become the key part of Internet of Things (IoT). Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is p...

  17. Interactive analysis of geodata based intelligence

    Science.gov (United States)

    Wagner, Boris; Eck, Ralf; Unmüessig, Gabriel; Peinsipp-Byma, Elisabeth

    2016-05-01

    When a spatiotemporal events happens, multi-source intelligence data is gathered to understand the problem, and strategies for solving the problem are investigated. The difficulties arising from handling spatial and temporal intelligence data represent the main problem. The map might be the bridge to visualize the data and to get the most understand model for all stakeholders. For the analysis of geodata based intelligence data, a software was developed as a working environment that combines geodata with optimized ergonomics. The interaction with the common operational picture (COP) is so essentially facilitated. The composition of the COP is based on geodata services, which are normalized by international standards of the Open Geospatial Consortium (OGC). The basic geodata are combined with intelligence data from images (IMINT) and humans (HUMINT), stored in a NATO Coalition Shared Data Server (CSD). These intelligence data can be combined with further information sources, i.e., live sensors. As a result a COP is generated and an interaction suitable for the specific workspace is added. This allows the users to work interactively with the COP, i.e., searching with an on board CSD client for suitable intelligence data and integrate them into the COP. Furthermore, users can enrich the scenario with findings out of the data of interactive live sensors and add data from other sources. This allows intelligence services to contribute effectively to the process by what military and disaster management are organized.

  18. Hybrid intelligent optimization methods for engineering problems

    Science.gov (United States)

    Pehlivanoglu, Yasin Volkan

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

  19. Classification of Children Intelligence with Fuzzy Logic Method

    Science.gov (United States)

    Syahminan; ika Hidayati, Permata

    2018-04-01

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

  20. Expectation-based intelligent control

    International Nuclear Information System (INIS)

    Zak, Michail

    2006-01-01

    New dynamics paradigms-negative diffusion and terminal attractors-are introduced to control noise and chaos. The applied control forces are composed of expectations governed by the associated Fokker-Planck and Liouville equations. The approach is expanded to a general concept of intelligent control via expectations. Relevance to control in livings is emphasized and illustrated by neural nets with mirror neurons

  1. Multiple Intelligences - Based Planning of EFL Classes

    Directory of Open Access Journals (Sweden)

    Sanan Shero Malo Zebari

    2018-04-01

    Full Text Available The present study aimed to set a plan for teaching EFL classes based on the identification of university students’ dominant multiple intelligences in EFL classes, and the differences in the types of intelligence between female and male students in terms of their gender. The problem the present study aimed to address is that the traditional concept that “one size fits all” is still adopted by many EFL teachers, and that EFL students’ differences and preferences are noticeably unheeded. It is believed that identifying students’ dominant intelligences is a sound remedial solution for such a problem before embarking on any teaching program. Moreover, getting students aware of their different types of intelligence will motivate and encourage them in the classroom. The researchers used a questionnaire as a research instrument for data collection.  The results arrived at showed that there were no significant differences in the types of intelligence between female and male students in terms of their gender, except for bodily- kinesthetic intelligence. They also showed that the dominant intelligences were ranked from the highest to the lowest as follows interpersonal, linguistic, spatial, logical-mathematical, bodily kinesthetic, intrapersonal, musical, and naturalistic.

  2. Method of dynamic fuzzy symptom vector in intelligent diagnosis

    International Nuclear Information System (INIS)

    Sun Hongyan; Jiang Xuefeng

    2010-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1999-02-01

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

  4. A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network

    Directory of Open Access Journals (Sweden)

    Deyu Cui

    2018-04-01

    Full Text Available State of charge (SOC estimation is becoming increasingly important, along with electric vehicle (EV rapid development, while SOC is one of the most significant parameters for the battery management system, indicating remaining energy and ensuring the safety and reliability of EV. In this paper, a hybrid wavelet neural network (WNN model combining the discrete wavelet transform (DWT method and adaptive WNN is proposed to estimate the SOC of lithium-ion batteries. The WNN model is trained by Levenberg-Marquardt (L-M algorithm, whose inputs are processed by discrete wavelet decomposition and reconstitution. Compared with back-propagation neural network (BPNN, L-M based BPNN (LMBPNN, L-M based WNN (LMWNN, DWT with L-M based BPNN (DWTLMBPNN and extend Kalman filter (EKF, the proposed intelligent SOC estimation method is validated and proved to be effective. Under the New European Driving Cycle (NEDC, the mean absolute error and maximum error can be reduced to 0.59% and 3.13%, respectively. The characteristics of high accuracy and strong robustness of the proposed method are verified by comparison study and robustness evaluation results (e.g., measurement noise test and untrained driving cycle test.

  5. 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

  6. 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

  7. Development and validity of mathematical learning assessment instruments based on multiple intelligence

    Directory of Open Access Journals (Sweden)

    Helmiah Suryani

    2017-06-01

    Full Text Available This study was aimed to develop and produce an assessment instrument of mathematical learning results based on multiple intelligence. The methods in this study used Borg & Gall-Research and Development approach (Research & Development. The subject of research was 289 students. The results of research: (1 Result of Aiken Analysis showed 58 valid items were between 0,714 to 0,952. (2 Result of the Exploratory on factor analysis indicated the instrument consist of three factors i.e. mathematical logical intelligence-spatial intelligence-and linguistic intelligence. KMO value was 0.661 df 0.780 sig. 0.000 with valid category. This research succeeded to developing the assessment instrument of mathematical learning results based on multiple intelligence of second grade in elementary school with characteristics of logical intelligence of mathematics, spatial intelligence, and linguistic intelligence.

  8. 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 ...

  9. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2000-07-01

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

  11. Evaluation of Intelligent Grouping Based on Learners' Collaboration Competence Level in Online Collaborative Learning Environment

    Science.gov (United States)

    Muuro, Maina Elizaphan; Oboko, Robert; Wagacha, Waiganjo Peter

    2016-01-01

    In this paper we explore the impact of an intelligent grouping algorithm based on learners' collaborative competency when compared with (a) instructor based Grade Point Average (GPA) method level and (b) random method, on group outcomes and group collaboration problems in an online collaborative learning environment. An intelligent grouping…

  12. Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

    Science.gov (United States)

    Li, Mengshan; Zhang, Huaijing; Chen, Bingsheng; Wu, Yan; Guan, Lixin

    2018-03-05

    The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the population entropy was higher than the set maximum threshold, the convergence strategy was adopted; when the population entropy was lower than the set minimum threshold the divergence strategy was adopted; when the population entropy was between the maximum and minimum threshold, the self-adaptive adjustment strategy was maintained. The improved PSO algorithm was applied in the training of radial basis function artificial neural network (RBF ANN) model and the selection of molecular descriptors. A quantitative structure-activity relationship model based on RBF ANN trained by the improved PSO algorithm was proposed to predict the pKa values of 74 kinds of neutral and basic drugs and then validated by another database containing 20 molecules. The validation results showed that the model had a good prediction performance. The absolute average relative error, root mean square error, and squared correlation coefficient were 0.3105, 0.0411, and 0.9685, respectively. The model can be used as a reference for exploring other quantitative structure-activity relationships.

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    Jorge Yunta

    2018-02-01

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

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

    Science.gov (United States)

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

    2018-02-06

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

  16. 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...

  17. Implementation of Multiple Intelligences Supported Project-Based Learning in EFL/ESL Classrooms

    Science.gov (United States)

    Bas, Gokhan

    2008-01-01

    This article deals with the implementation of Multiple Intelligences supported Project-Based learning in EFL/ESL Classrooms. In this study, after Multiple Intelligences supported Project-based learning was presented shortly, the implementation of this learning method into English classrooms. Implementation process of MI supported Project-based…

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

    Science.gov (United States)

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

    2018-03-01

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

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

    Science.gov (United States)

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

    2014-09-01

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

  20. Applying intelligent statistical methods on biometric systems

    OpenAIRE

    Betschart, Willie

    2005-01-01

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

  1. [Control of intelligent car based on electroencephalogram and neurofeedback].

    Science.gov (United States)

    Li, Song; Xiong, Xin; Fu, Yunfa

    2018-02-01

    To improve the performance of brain-controlled intelligent car based on motor imagery (MI), a method based on neurofeedback (NF) with electroencephalogram (EEG) for controlling intelligent car is proposed. A mental strategy of MI in which the energy column diagram of EEG features related to the mental activity is presented to subjects with visual feedback in real time to train them to quickly master the skills of MI and regulate their EEG activity, and combination of multi-features fusion of MI and multi-classifiers decision were used to control the intelligent car online. The average, maximum and minimum accuracy of identifying instructions achieved by the trained group (trained by the designed feedback system before the experiment) were 85.71%, 90.47% and 76.19%, respectively and the corresponding accuracy achieved by the control group (untrained) were 73.32%, 80.95% and 66.67%, respectively. For the trained group, the average, longest and shortest time consuming were 92 s, 101 s, and 85 s, respectively, while for the control group the corresponding time were 115.7 s, 120 s, and 110 s, respectively. According to the results described above, it is expected that this study may provide a new idea for the follow-up development of brain-controlled intelligent robot by the neurofeedback with EEG related to MI.

  2. Data transfer based on intelligent ethernet card

    International Nuclear Information System (INIS)

    Zhu Haitao; Chinese Academy of Sciences, Beijing; Chu Yuanping; Zhao Jingwei

    2007-01-01

    Intelligent Ethernet Cards are widely used in systems where the network throughout is very large, such as the DAQ systems for modern high energy physics experiments, web service. With the example of a commercial intelligent Ethernet card, this paper introduces the architecture, the principle and the process of intelligent Ethernet cards. In addition, the results of several experiments showing the differences between intelligent Ethernet cards and general ones are also presented. (authors)

  3. Comparison of methods for estimating premorbid intelligence

    OpenAIRE

    Bright, Peter; van der Linde, Ian

    2018-01-01

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

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

    DEFF Research Database (Denmark)

    Taal, Cees H.; Jensen, Jesper

    2013-01-01

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

  5. Intelligent methods for data retrieval in fusion databases

    International Nuclear Information System (INIS)

    Vega, J.

    2008-01-01

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

  6. Artificial neural network intelligent method for prediction

    Science.gov (United States)

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

    2017-09-01

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

  7. Artificial Intelligence based technique for BTS placement

    Science.gov (United States)

    Alenoghena, C. O.; Emagbetere, J. O.; Aibinu, A. M.

    2013-12-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out.

  8. Knowledge based systems for intelligent robotics

    Science.gov (United States)

    Rajaram, N. S.

    1982-01-01

    It is pointed out that the construction of large space platforms, such as space stations, has to be carried out in the outer space environment. As it is extremely expensive to support human workers in space for large periods, the only feasible solution appears to be related to the development and deployment of highly capable robots for most of the tasks. Robots for space applications will have to possess characteristics which are very different from those needed by robots in industry. The present investigation is concerned with the needs of space robotics and the technologies which can be of assistance to meet these needs, giving particular attention to knowledge bases. 'Intelligent' robots are required for the solution of arising problems. The collection of facts and rules needed for accomplishing such solutions form the 'knowledge base' of the system.

  9. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    Alenoghena, C O; Emagbetere, J O; 1 Minna (Nigeria))" data-affiliation=" (Department of Telecommunications Engineering, Federal University of Techn.1 Minna (Nigeria))" >Aibinu, A M

    2013-01-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out

  10. Memory Based Machine Intelligence Techniques in VLSI hardware

    OpenAIRE

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

  11. Intelligent model-based diagnostics for vehicle health management

    Science.gov (United States)

    Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

    2003-08-01

    The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

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

    OpenAIRE

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

    2013-01-01

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

  13. Internet-based intelligent information processing systems

    CERN Document Server

    Tonfoni, G; Ichalkaranje, N S

    2003-01-01

    The Internet/WWW has made it possible to easily access quantities of information never available before. However, both the amount of information and the variation in quality pose obstacles to the efficient use of the medium. Artificial intelligence techniques can be useful tools in this context. Intelligent systems can be applied to searching the Internet and data-mining, interpreting Internet-derived material, the human-Web interface, remote condition monitoring and many other areas. This volume presents the latest research on the interaction between intelligent systems (neural networks, adap

  14. Intelligent monitoring-based safety system of massage robot

    Institute of Scientific and Technical Information of China (English)

    胡宁; 李长胜; 王利峰; 胡磊; 徐晓军; 邹雲鹏; 胡玥; 沈晨

    2016-01-01

    As an important attribute of robots, safety is involved in each link of the full life cycle of robots, including the design, manufacturing, operation and maintenance. The present study on robot safety is a systematic project. Traditionally, robot safety is defined as follows: robots should not collide with humans, or robots should not harm humans when they collide. Based on this definition of robot safety, researchers have proposed ex ante and ex post safety standards and safety strategies and used the risk index and risk level as the evaluation indexes for safety methods. A massage robot realizes its massage therapy function through applying a rhythmic force on the massage object. Therefore, the traditional definition of safety, safety strategies, and safety realization methods cannot satisfy the function and safety requirements of massage robots. Based on the descriptions of the environment of massage robots and the tasks of massage robots, the present study analyzes the safety requirements of massage robots; analyzes the potential safety dangers of massage robots using the fault tree tool; proposes an error monitoring-based intelligent safety system for massage robots through monitoring and evaluating potential safety danger states, as well as decision making based on potential safety danger states; and verifies the feasibility of the intelligent safety system through an experiment.

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

    Science.gov (United States)

    Hao, Ruizhe; Huang, Jian

    2017-08-01

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

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

    International Nuclear Information System (INIS)

    Reifman, J.

    1997-01-01

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

  17. Robust Bio-Signal Based Control of an Intelligent Wheelchair

    Directory of Open Access Journals (Sweden)

    Dongyi Chen

    2013-09-01

    Full Text Available In this paper, an adaptive human-machine interaction (HMI method that is based on surface electromyography (sEMG signals is proposed for the hands-free control of an intelligent wheelchair. sEMG signals generated by the facial movements are obtained by a convenient dry electrodes sensing device. After the signals features are extracted from the autoregressive model, control data samples are updated and trained by an incremental online learning algorithm in real-time. Experimental results show that the proposed method can significantly improve the classification accuracy and training speed. Moreover, this method can effectively reduce the influence of muscle fatigue during a long time operation of sEMG-based HMI.

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

    Science.gov (United States)

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

    1996-12-01

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

  19. Intelligent numerical methods applications to fractional calculus

    CERN Document Server

    Anastassiou, George A

    2016-01-01

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

  20. Beyond fluid intelligence and personality traits in social support: the role of ability based emotional intelligence.

    Science.gov (United States)

    Fabio, Annamaria Di

    2015-01-01

    Social support represents an important individual resource that has been associated with multiple indices of adaptive functioning and resiliency. Existing research has also identified an association between emotional intelligence (EI) and social support. The present study builds on prior research by investigating the contributions of ability based EI to social support, beyond the effects of fluid intelligence and personality traits. The Advanced Progressive Matrices, the Big Five Questionnaire, the Mayer Salovey Caruso EI test (MSCEIT), and the Multidimensional Scale of Perceived Social Support were administered to 149 Italian high school students. The results showed that ability based EI added significant incremental variance in explaining perceived social support, beyond the variance due to fluid intelligence and personality traits. The results underline the role of ability based EI in relation to perceived social support. Since ability based EI can be increased through specific training, the results of the present study highlight new possibilities for research and intervention in a preventive framework.

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

    Science.gov (United States)

    Musen, M A

    1998-01-01

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

  2. An Integrated Conceptual Environment based on Collective Intelligence and Distributed Artificial Intelligence for Connecting People on Problem Solving

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2012-12-01

    Full Text Available This paper aims to analyze the different forms of intelligence within organizations in a systemic and inclusive vision, in order to conceptualize an integrated environment based on Distributed Artificial Intelligence (DAI and Collective Intelligence (CI. In this way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. The best way to use collective intelligence is based on knowledge mobilization and semantic technologies. We must not let computers to imitate people but to support people think and develop their ideas within a group. CI helps people to think together, while DAI tries to support people so as to limit human error. Within an organization, to manage CI is to combine instruments like Semantic Technologies (STs, knowledge mobilization methods for developing Knowledge Management (KM strategies, and the processes that promote connection and collaboration between individual minds in order to achieve collective objectives, to perform a task or to solve increasingly economic complex problems.

  3. An Artificial Intelligence-Based Environment Quality Analysis System

    OpenAIRE

    Oprea , Mihaela; Iliadis , Lazaros

    2011-01-01

    Part 20: Informatics and Intelligent Systems Applications for Quality of Life information Services (ISQLIS) Workshop; International audience; The paper describes an environment quality analysis system based on a combination of some artificial intelligence techniques, artificial neural networks and rule-based expert systems. Two case studies of the system use are discussed: air pollution analysis and flood forecasting with their impact on the environment and on the population health. The syste...

  4. Intelligent Traffic Light Based on PLC Control

    Science.gov (United States)

    Mei, Lin; Zhang, Lijian; Wang, Lingling

    2017-11-01

    The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

  5. FPGA Based Intelligent Co-operative Processor in Memory Architecture

    DEFF Research Database (Denmark)

    Ahmed, Zaki; Sotudeh, Reza; Hussain, Dil Muhammad Akbar

    2011-01-01

    benefits of PIM, a concept of Co-operative Intelligent Memory (CIM) was developed by the intelligent system group of University of Hertfordshire, based on the previously developed Co-operative Pseudo Intelligent Memory (CPIM). This paper provides an overview on previous works (CPIM, CIM) and realization......In a continuing effort to improve computer system performance, Processor-In-Memory (PIM) architecture has emerged as an alternative solution. PIM architecture incorporates computational units and control logic directly on the memory to provide immediate access to the data. To exploit the potential...

  6. A Survey of Formal Methods for Intelligent Swarms

    Science.gov (United States)

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

    2004-01-01

    cutting edge in system correctness, and requires higher levels of assurance than other (traditional) missions that use a single or small number of spacecraft that are deterministic in nature and have near continuous communication access. One of the highest possible levels of assurance comes from the application of formal methods. Formal methods are mathematics-based tools and techniques for specifying and verifying (software and hardware) systems. They are particularly useful for specifying complex parallel systems, such as exemplified by the ANTS mission, where the entire system is difficult for a single person to fully understand, a problem that is multiplied with multiple developers. Once written, a formal specification can be used to prove properties of a system (e.g., the underlying system will go from one state to another or not into a specific state) and check for particular types of errors (e.g., race or livelock conditions). A formal specification can also be used as input to a model checker for further validation. This report gives the results of a survey of formal methods techniques for verification and validation of space missions that use swarm technology. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft using the ANTS mission as an example system. This report is the first result of the project to determine formal approaches that are promising for formally specifying swarm-based systems. From this survey, the most promising approaches were selected and are discussed relative to their possible application to the ANTS mission. Future work will include the application of an integrated approach, based on the selected approaches identified in this report, to the formal specification of the ANTS mission.

  7. The design of remote intelligent terminal based on ARM

    International Nuclear Information System (INIS)

    Zhang Bin; Liu Zixin

    2014-01-01

    This paper introduces the function and principle of the remote intelligent terminal. It was designed on SmartARM 2200, uses uC/OS-II operating system and MiniGUI. And then,it gives a method to realize it. Introduces the work flow of remote intelligent terminal, and the function module of the system are analyzed in detail, and then the terminal of the principle has carried on the preliminary study. (authors)

  8. 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

  9. 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.

  10. Fixed Point Learning Based Intelligent Traffic Control System

    Science.gov (United States)

    Zongyao, Wang; Cong, Sui; Cheng, Shao

    2017-10-01

    Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

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

    Energy Technology Data Exchange (ETDEWEB)

    Cristensen, D.L.

    1986-01-01

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

  12. Greenhouse intelligent control system based on microcontroller

    Science.gov (United States)

    Zhang, Congwei

    2018-04-01

    As one of the hallmarks of agricultural modernization, intelligent greenhouse has the advantages of high yield, excellent quality, no pollution and continuous planting. Taking AT89S52 microcontroller as the main controller, the greenhouse intelligent control system uses soil moisture sensor, temperature and humidity sensors, light intensity sensor and CO2 concentration sensor to collect measurements and display them on the 12864 LCD screen real-time. Meantime, climate parameter values can be manually set online. The collected measured values are compared with the set standard values, and then the lighting, ventilation fans, warming lamps, water pumps and other facilities automatically start to adjust the climate such as light intensity, CO2 concentration, temperature, air humidity and soil moisture of the greenhouse parameter. So, the state of the environment in the greenhouse Stabilizes and the crop grows in a suitable environment.

  13. Multiple intelligences and outcomes based education

    Directory of Open Access Journals (Sweden)

    Elaine Ridge

    2008-08-01

    Full Text Available This article explores the reasons that make it advantageous to develop learning programmes which draw on the theory of multiple intelligences (MI. A unitary view of intelligence privileges analytic/linguisticallygifted learners. The theory of MI, on the other hand, takes account of the diversity of learners and challenges educators to provide opportunities for them to use their varied intelligences.The outline of each of the eight intelligences demonstratesthe many ways in which learners can demonstrate their ability to excel. Application of these insights can complement the kind of transformatoryeducation envisaged in the Department of Education policy documents. MI translated into school practice has taken a variety of forms: project-basedapproaches, interdisciplinarycurriculums, entry points to lesson plans and complex assessments are only some of these. Ordinary classroom teachers can create diverse opportunities for all learners to enjoy a high measure of success.Hierdie artikel ondersoek die redes waarom dit voordelig is om leerprogramme te ontwikkel wal gebaseer is op idees uit die leorie van meervoudige intelligensies (MI.'n Unitêre siening van intelligensiebevoordeel analities- en taalbegaafde-leerders.Die MI-teorie, daarenleen neem die ongelyksoortigheidvan die leerders in ag en daag opvoeders uit om geleenthede te skep vir die leerlinge om verskeie van hulle intelligensies te gebruik. Die omskrywing van elk van die agt soorte intelligensies demonstreer die talryke-maniere waarop leerders hulle vermoë om uit te blink kan bewys.Die toepassing van hierdie insigte kan bydra tot die transformerendeaard van die opvoeding wat met die Departmentvan Opvoedkunde se beleidsdokumentebeoog word.MI toegepas in skoolpraktykneem verskillendevorms aan: projek-gebaseerdebenaderinge;interdissiplinêrekurrikulums; loelreepunte vir lesplanne en veelsydige assessering, om maar 'n paar te noem.Gewone klas-onderwysers kan 'n verskeidenheid geleenthede skep

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

    OpenAIRE

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Grover Zurita

    2016-09-01

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

  16. Advances in Reasoning-Based Image Processing Intelligent Systems Conventional and Intelligent Paradigms

    CERN Document Server

    Nakamatsu, Kazumi

    2012-01-01

    The book puts special stress on the contemporary techniques for reasoning-based image processing and analysis: learning based image representation and advanced video coding; intelligent image processing and analysis in medical vision systems; similarity learning models for image reconstruction; visual perception for mobile robot motion control, simulation of human brain activity in the analysis of video sequences; shape-based invariant features extraction; essential of paraconsistent neural networks, creativity and intelligent representation in computational systems. The book comprises 14 chapters. Each chapter is a small monograph, representing resent investigations of authors in the area. The topics of the chapters cover wide scientific and application areas and complement each-other very well. The chapters’ content is based on fundamental theoretical presentations, followed by experimental results and comparison with similar techniques. The size of the chapters is well-ballanced which permits a thorough ...

  17. Intelligent perception control based on a blackboard architecture

    International Nuclear Information System (INIS)

    Taibi, I.; Koenig, A.; Vacherand, F.

    1991-01-01

    In this paper, is described the intelligent perception control system GESPER which is presently equipped with a set of three cameras, a telemeter and a camera associated with a structured strip light. This system is of great interest for all our robotic applications as it is capable of autonomously planning, triggering acquisitions, integrating and interpreting multisensory data. The GESPER architecture, based on the blackboard model, provides a generic development method for indoor and outdoor perception. The modularity and the independence of the knowledge sources make the software evolving easily without breaking down the architecture. New sensors and/or new data processing can be integrated by the addition of new knowledge sources that modelize them. At present, first results are obtained in our testbed hall which simulates the nuclear plant as gives similar experimental conditions. Our ongoing research concerns the improvement of fusion algorithms and the embedding of the whole system (hardware and software) on target robots and distributed architecture

  18. Subspace methods for pattern recognition in intelligent environment

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

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

  19. Intelligent Hydraulic Actuator and Exp-based Modelling of Losses in Pumps and .

    DEFF Research Database (Denmark)

    Zhang, Muzhi

    A intelligent fuzzy logic self-organising PD+I controller for a gearrotor hydraulic motor was developed and evaluated. Furthermore, a experimental-based modelling methods with a new software tool 'Dynamodata' for modelling of losses in hydraulic motors and pumps was developed.......A intelligent fuzzy logic self-organising PD+I controller for a gearrotor hydraulic motor was developed and evaluated. Furthermore, a experimental-based modelling methods with a new software tool 'Dynamodata' for modelling of losses in hydraulic motors and pumps was developed....

  20. Autonomous entropy-based intelligent experimental design

    Science.gov (United States)

    Malakar, Nabin Kumar

    2011-07-01

    The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner. Present day scientific frontiers involve data collection at an ever-increasing rate. This requires that we find a way to collect the most relevant data in an automated fashion. By following the logic of the scientific method, we couple an inference engine with an inquiry engine to automate the iterative process of scientific learning. The inference engine involves Bayesian machine learning techniques to estimate model parameters based upon both prior information and previously collected data, while the inquiry engine implements data-driven exploration. By choosing an experiment whose distribution of expected results has the maximum entropy, the inquiry engine selects the experiment that maximizes the expected information gain. The coupled inference and inquiry engines constitute an autonomous learning method for scientific exploration. We apply it to a robotic arm to demonstrate the efficacy of the method. Optimizing inquiry involves searching for an experiment that promises, on average, to be maximally informative. If the set of potential experiments is described by many parameters, the search involves a high-dimensional entropy space. In such cases, a brute force search method will be slow and computationally expensive. We develop an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment. This helps to reduce the number of computations necessary to find the optimal experiment. We also extended the method of maximizing entropy, and developed a method of maximizing joint entropy so that it could be used as a principle of collaboration between two robots. This is a major achievement of this thesis, as it allows the information-based collaboration between two robotic units towards a same

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

    Science.gov (United States)

    Mehdizadeh, Saeid; Behmanesh, Javad; Khalili, Keivan

    2016-08-01

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

  2. T-Spline Based Unifying Registration Procedure for Free-Form Surface Workpieces in Intelligent CMM

    Directory of Open Access Journals (Sweden)

    Zhenhua Han

    2017-10-01

    Full Text Available With the development of the modern manufacturing industry, the free-form surface is widely used in various fields, and the automatic detection of a free-form surface is an important function of future intelligent three-coordinate measuring machines (CMMs. To improve the intelligence of CMMs, a new visual system is designed based on the characteristics of CMMs. A unified model of the free-form surface is proposed based on T-splines. A discretization method of the T-spline surface formula model is proposed. Under this discretization, the position and orientation of the workpiece would be recognized by point cloud registration. A high accuracy evaluation method is proposed between the measured point cloud and the T-spline surface formula. The experimental results demonstrate that the proposed method has the potential to realize the automatic detection of different free-form surfaces and improve the intelligence of CMMs.

  3. SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    V. Panteleev Andrei

    2017-01-01

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

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

    Science.gov (United States)

    Becker, John Darrell

    2012-01-01

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

  5. Fault diagnosis of an intelligent hydraulic pump based on a nonlinear unknown input observer

    Directory of Open Access Journals (Sweden)

    Zhonghai MA

    2018-02-01

    Full Text Available Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system (IHPS based on a nonlinear unknown input observer (NUIO is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS. Keywords: Fault diagnosis, Hydraulic piston pump, Model-based, Nonlinear unknown input observer (NUIO, Residual error

  6. A novel AIDS/HIV intelligent medical consulting system based on expert systems.

    Science.gov (United States)

    Ebrahimi, Alireza Pour; Toloui Ashlaghi, Abbas; Mahdavy Rad, Maryam

    2013-01-01

    The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV. In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs' ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed. The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%. AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical.

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

    Directory of Open Access Journals (Sweden)

    Svetlana V. Kulikova

    2018-01-01

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

  8. Sensorless speed control of switched reluctance motor using brain emotional learning based intelligent controller

    International Nuclear Information System (INIS)

    Dehkordi, Behzad Mirzaeian; Parsapoor, Amir; Moallem, Mehdi; Lucas, Caro

    2011-01-01

    In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.

  9. Sensorless speed control of switched reluctance motor using brain emotional learning based intelligent controller

    Energy Technology Data Exchange (ETDEWEB)

    Dehkordi, Behzad Mirzaeian, E-mail: mirzaeian@eng.ui.ac.i [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Parsapoor, Amir, E-mail: amirparsapoor@yahoo.co [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Moallem, Mehdi, E-mail: moallem@cc.iut.ac.i [Department of Electrical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of); Lucas, Caro, E-mail: lucas@ut.ac.i [Centre of Excellence for Control and Intelligent Processing, Electrical and Computer Engineering Faculty, College of Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

    2011-01-15

    In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.

  10. Design of intelligent house system based on Yeelink

    Directory of Open Access Journals (Sweden)

    Lin Zhi-Huang

    2016-01-01

    Full Text Available In order to monitor the security situation of house in real time, an intelligent house remote monitoring system is designed based on Yeelink cloud services and ZigBee wireless communication technology. This system includes three parts, ZigBee wireless sensor networks, intelligent house gateway and Yeelink Cloud Services. Users can access Yeelink website or APP to get real time information in the house, receiving information including gas concentration, temperature. Also, remote commands can be sent from mobile devices to control the household appliances. The user who can monitor and control the house effectively through a simple and convenient user interface, will feel much more safe and comfortable.

  11. Intelligent Shutter Speech Control System Based on DSP

    Directory of Open Access Journals (Sweden)

    Yonghong Deng

    2017-01-01

    Full Text Available Based on TMS320F28035 DSP, this paper designed a smart shutters voice control system, which realized the functions of opening and closing shutters, intelligent switching of lighting mode and solar power supply through voice control. The traditional control mode is converted to voice control at the same time with automatic lighting and solar power supply function. In the convenience of people’s lives at the same time more satisfied with today’s people on the intelligent and environmental protection of the two concepts of the pursuit. The whole system is simple, low cost, safe and reliable.

  12. Machine Learning-based Intelligent Formal Reasoning and Proving System

    Science.gov (United States)

    Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

    2018-03-01

    The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

  13. Personalized E- learning System Based on Intelligent Agent

    Science.gov (United States)

    Duo, Sun; Ying, Zhou Cai

    Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

  14. Active Probing Feedback based Self Configurable Intelligent Distributed Antenna System

    DEFF Research Database (Denmark)

    Kumar, Ambuj

    collectively as Place Time Coverage & Capacity (PTC2). The dissertation proves through the concept of the PTC2 that the network performance can severely be degraded by the excessive and unrealistic site demands, the network management inefficiency, and the consequence of the accumulation of subscribers...... challenge through a viable solution that is based on injecting intelligence and services in parallel layers through a Distributed Antenna Systems (DAS) network. This approach would enable the remote sites to acquire intelligence and a resource pool at the same time, thereby managing the network dynamics...... promptly and aptly to absorb the PTC2 wobble. An Active Probing Management System (APMS) is proposed as a supporting architecture, to assist the intelligent system to keep a check on the variations at each and every site by either deploying the additional antenna or by utilising the service antenna...

  15. [Artificial intelligence--the knowledge base applied to nephrology].

    Science.gov (United States)

    Sancipriano, G P

    2005-01-01

    The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

  16. Feature-based tolerancing for intelligent inspection process definition

    International Nuclear Information System (INIS)

    Brown, C.W.

    1993-07-01

    This paper describes a feature-based tolerancing capability that complements a geometric solid model with an explicit representation of conventional and geometric tolerances. This capability is focused on supporting an intelligent inspection process definition system. The feature-based tolerance model's benefits include advancing complete product definition initiatives (e.g., STEP -- Standard for Exchange of Product model dam), suppling computer-integrated manufacturing applications (e.g., generative process planning and automated part programming) with product definition information, and assisting in the solution of measurement performance issues. A feature-based tolerance information model was developed based upon the notion of a feature's toleranceable aspects and describes an object-oriented scheme for representing and relating tolerance features, tolerances, and datum reference frames. For easy incorporation, the tolerance feature entities are interconnected with STEP solid model entities. This schema will explicitly represent the tolerance specification for mechanical products, support advanced dimensional measurement applications, and assist in tolerance-related methods divergence issues

  17. Enhancing reliable online transaction with intelligent rule-based ...

    African Journals Online (AJOL)

    Enhancing reliable online transaction with intelligent rule-based fraud detection technique. ... These are with a bid to reducing amongst other things the cost of production and also dissuade the poor handling of Nigeria currency. The CBN pronouncement has necessitated the upsurge in transactions completed with credit ...

  18. Towards an Intelligent Planning Knowledge Base Development Environment

    Science.gov (United States)

    Chien, S.

    1994-01-01

    ract describes work in developing knowledge base editing and debugging tools for the Multimission VICAR Planner (MVP) system. MVP uses artificial intelligence planning techniques to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing requests made to the JPL Multimission Image Processing Laboratory.

  19. A generic model for camera based intelligent road crowd control ...

    African Journals Online (AJOL)

    This research proposes a model for intelligent traffic flow control by implementing camera based surveillance and feedback system. A series of cameras are set minimum three signals ahead from the target junction. The complete software system is developed to help integrating the multiple camera on road as feedback to ...

  20. Intelligent Web-Based English Instruction in Middle Schools

    Science.gov (United States)

    Jia, Jiyou

    2015-01-01

    The integration of technology into educational environments has become more prominent over the years. The combination of technology and face-to-face interaction with instructors allows for a thorough, more valuable educational experience. "Intelligent Web-Based English Instruction in Middle Schools" addresses the concerns associated with…

  1. Ontology-based intelligent fuzzy agent for diabetes application

    NARCIS (Netherlands)

    Acampora, G.; Lee, C.-S.; Wang, M.-H.; Hsu, C.-Y.; Loia, V.

    2009-01-01

    It is widely pointed out that classical ontologies are not sufficient to deal with imprecise and vague knowledge for some real world applications, but the fuzzy ontology can effectively solve data and knowledge with uncertainty. In this paper, an ontology-based intelligent fuzzy agent (OIFA),

  2. An Artificial Intelligence-Based Distance Education System: Artimat

    Science.gov (United States)

    Nabiyev, Vasif; Karal, Hasan; Arslan, Selahattin; Erumit, Ali Kursat; Cebi, Ayca

    2013-01-01

    The purpose of this study is to evaluate the artificial intelligence-based distance education system called ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed…

  3. Crack identification based on synthetic artificial intelligent technique

    International Nuclear Information System (INIS)

    Shim, Mun Bo; Suh, Myung Won

    2001-01-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising

  4. Advanced intelligent systems

    CERN Document Server

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

    2014-01-01

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

  5. Design of embedded hardware platform in intelligent γ-spectrometry instrument based on ARM9

    International Nuclear Information System (INIS)

    Hong Tianqi; Fang Fang

    2008-01-01

    This paper described the design of embedded hardware platform based on ARM9 S3C2410A, emphases are focused on analyzing the methods of design the circuits of memory, LCD and keyboard ports. It presented a new solution of hardware platform in intelligent portable instrument for γ measurement. (authors)

  6. Design of an intelligent materials data base for the IFR

    International Nuclear Information System (INIS)

    Mikaili, R.; Lambert, J.D.B.; Orth, T.D.

    1992-01-01

    In the development of the integral fast reactor (IFR) concept, there is a consensus that materials considerations are an important part of the reactor design, operation, and maintenance and that materials performance is central to liquid-metal reactor reliability and safety. In the design of the IRF materials data base, artificial intelligence techniques are being used to ensure efficient control of information. Intelligent control will provide for the selection of menus to be displayed, efficient data-base searches, and application-dependent guidance through the data base. The development of the IRF data base has progressed to the point of (a) completing the design of the data-base architecture and tables, (b) installing computer hardware for storing large amounts of data, (c) outlining strategies for data transferal, and (d) identifying ways to validate and secure the integrity of data

  7. Reviewing the development of an artificial intelligence based risk program

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    A successful application of nonconventional programming methods has been achieved in computer-assisted probabilistic risk assessment (PRA). The event tree sequence importance calculator, SQUIMP, provides for prompted data entry, generic expansion, on-line pruning, boolean reductions, and importance factor selection. SQUIMP employs constructs typically found in artificial intelligence (AI) programs. The development history of SQUIMP is outlined and its internal structure described as background for a discussion on the applicability of symbolic programming methods in PRA

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

    OpenAIRE

    Marina ZHURAVSKAYA; Vladimir TARASYAN

    2014-01-01

    In the modern world the alternative energy sources, which considerably depend on a region, play more and more significant role. However, the transition of regions to new energy sources lead to the change of transport and logistic network configuration. The formation of optimal core transport network today is a guarantee of the successful economic development of a region tomorrow. The present article studies the issue of advanced core transport network development in a region based on the ...

  9. Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems

    OpenAIRE

    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...

  10. Artificial Intelligence (AI) Based Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1990-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches, including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance of a prototype concurrent TDG system are presented.

  11. An Intelligent Agent based Architecture for Visual Data Mining

    OpenAIRE

    Hamdi Ellouzi; Hela Ltifi; Mounir Ben Ayed

    2016-01-01

    the aim of this paper is to present an intelligent architecture of Decision Support System (DSS) based on visual data mining. This architecture applies the multi-agent technology to facilitate the design and development of DSS in complex and dynamic environment. Multi-Agent Systems add a high level of abstraction. To validate the proposed architecture, it is implemented to develop a distributed visual data mining based DSS to predict nosocomial infectionsoccurrence in intensive care units. Th...

  12. Study of intelligent building system based on the internet of things

    Science.gov (United States)

    Wan, Liyong; Xu, Renbo

    2017-03-01

    In accordance with the problem such as isolated subsystems, weak system linkage and expansibility of the bus type buildings management system, this paper based on the modern intelligent buildings has studied some related technologies of the intelligent buildings and internet of things, and designed system architecture of the intelligent buildings based on the Internet of Things. Meanwhile, this paper has also analyzed wireless networking modes, wireless communication protocol and wireless routing protocol of the intelligent buildings based on the Internet of Things.

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

    Directory of Open Access Journals (Sweden)

    Vitaliy PAVLENKO

    2017-06-01

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

  14. Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

    International Nuclear Information System (INIS)

    Laghari, J.A.; Mokhlis, H.; Karimi, M.; Bakar, A.H.A.; Mohamad, Hasmaini

    2014-01-01

    Highlights: • Unintentional and intentional islanding, their causes, and solutions are presented. • Remote, passive, active and hybrid islanding detection techniques are discussed. • The limitation of these techniques in accurately detect islanding are discussed. • Computational intelligence techniques ability in detecting islanding is discussed. • Review of ANN, fuzzy logic control, ANFIS, Decision tree techniques is provided. - Abstract: Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system

  15. Intelligent traffic lights based on MATLAB

    Science.gov (United States)

    Nie, Ying

    2018-04-01

    In this paper, I describes the traffic lights system and it has some. Through analysis, I used MATLAB technology, transformed the camera photographs into digital signals. Than divided the road vehicle is into three methods: very congestion, congestion, a little congestion. Through the MCU programming, solved the different roads have different delay time, and Used this method, saving time and resources, so as to reduce road congestion.

  16. A Model of Intelligent Fault Diagnosis of Power Equipment Based on CBR

    Directory of Open Access Journals (Sweden)

    Gang Ma

    2015-01-01

    Full Text Available Nowadays the demand of power supply reliability has been strongly increased as the development within power industry grows rapidly. Nevertheless such large demand requires substantial power grid to sustain. Therefore power equipment’s running and testing data which contains vast information underpins online monitoring and fault diagnosis to finally achieve state maintenance. In this paper, an intelligent fault diagnosis model for power equipment based on case-based reasoning (IFDCBR will be proposed. The model intends to discover the potential rules of equipment fault by data mining. The intelligent model constructs a condition case base of equipment by analyzing the following four categories of data: online recording data, history data, basic test data, and environmental data. SVM regression analysis was also applied in mining the case base so as to further establish the equipment condition fingerprint. The running data of equipment can be diagnosed by such condition fingerprint to detect whether there is a fault or not. Finally, this paper verifies the intelligent model and three-ratio method based on a set of practical data. The resulting research demonstrates that this intelligent model is more effective and accurate in fault diagnosis.

  17. Intelligent Agent Based Semantic Web in Cloud Computing Environment

    OpenAIRE

    Mukhopadhyay, Debajyoti; Sharma, Manoj; Joshi, Gajanan; Pagare, Trupti; Palwe, Adarsha

    2013-01-01

    Considering today's web scenario, there is a need of effective and meaningful search over the web which is provided by Semantic Web. Existing search engines are keyword based. They are vulnerable in answering intelligent queries from the user due to the dependence of their results on information available in web pages. While semantic search engines provides efficient and relevant results as the semantic web is an extension of the current web in which information is given well defined meaning....

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

    Science.gov (United States)

    Kong, Changduk; Lim, Semyeong

    2011-12-01

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

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

    Science.gov (United States)

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

    2018-04-01

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

  20. Using artificial intelligence methods to design new conducting polymers

    Directory of Open Access Journals (Sweden)

    Ronaldo Giro

    2003-12-01

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

  1. Intelligent judgements over health risks in a spatial agent-based model.

    Science.gov (United States)

    Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

    2018-03-20

    Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

  2. ANALYSIS AND CONCEPTION DEVELOPMENT OF INFORMATION DEFENSE CID AND CLOUD PLATFORM ON THE BASE OF INTELLIGENCE TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    V. A. Vishniakov

    2014-01-01

    Full Text Available Two problems the use of intelligence technologies in information defense (ITID – creating specialized knowledge bases with threats simulation and high the security level in corporative nets and cloud computing are presented. The analysis of t wo directions of the second ITID problem: the intelligence decision support systems and the malt y-agent system use are given. As trends and conception development of intelligence technologies are the perfection of methods. models, architectures, and hard-sot ware tools for ITID in corporative systems and cloud computing.

  3. Ontology-Based Information Extraction for Business Intelligence

    Science.gov (United States)

    Saggion, Horacio; Funk, Adam; Maynard, Diana; Bontcheva, Kalina

    Business Intelligence (BI) requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers or feed statistical BI models and tools. The massive amount of information available to business analysts makes information extraction and other natural language processing tools key enablers for the acquisition and use of that semantic information. We describe the application of ontology-based extraction and merging in the context of a practical e-business application for the EU MUSING Project where the goal is to gather international company intelligence and country/region information. The results of our experiments so far are very promising and we are now in the process of building a complete end-to-end solution.

  4. Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction

    Directory of Open Access Journals (Sweden)

    Aleksandar Sabljic

    2004-12-01

    Full Text Available This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.

  5. An Innovative Thinking-Based Intelligent Information Fusion Algorithm

    Directory of Open Access Journals (Sweden)

    Huimin Lu

    2013-01-01

    Full Text Available This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information.

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

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

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

  7. Intelligent image retrieval based on radiology reports

    Energy Technology Data Exchange (ETDEWEB)

    Gerstmair, Axel; Langer, Mathias; Kotter, Elmar [University Medical Center Freiburg, Department of Diagnostic Radiology, Freiburg (Germany); Daumke, Philipp; Simon, Kai [Averbis GmbH, Freiburg (Germany)

    2012-12-15

    To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

  8. Intelligent Adaptation Process for Case Based Systems

    International Nuclear Information System (INIS)

    Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

    2014-01-01

    Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

  9. Intelligent image retrieval based on radiology reports

    International Nuclear Information System (INIS)

    Gerstmair, Axel; Langer, Mathias; Kotter, Elmar; Daumke, Philipp; Simon, Kai

    2012-01-01

    To create an advanced image retrieval and data-mining system based on in-house radiology reports. Radiology reports are semantically analysed using natural language processing (NLP) techniques and stored in a state-of-the-art search engine. Images referenced by sequence and image number in the reports are retrieved from the picture archiving and communication system (PACS) and stored for later viewing. A web-based front end is used as an interface to query for images and show the results with the retrieved images and report text. Using a comprehensive radiological lexicon for the underlying terminology, the search algorithm also finds results for synonyms, abbreviations and related topics. The test set was 108 manually annotated reports analysed by different system configurations. Best results were achieved using full syntactic and semantic analysis with a precision of 0.929 and recall of 0.952. Operating successfully since October 2010, 258,824 reports have been indexed and a total of 405,146 preview images are stored in the database. Data-mining and NLP techniques provide quick access to a vast repository of images and radiology reports with both high precision and recall values. Consequently, the system has become a valuable tool in daily clinical routine, education and research. (orig.)

  10. Tablet based distributed intelligent load management

    Science.gov (United States)

    Lu, Yan; Zhou, Siyuan

    2018-01-09

    A facility is connected to an electricity utility and is responsive to Demand Response Events. A plurality of devices is each individually connected to the electricity grid via an addressable switch connected to a secure network that is enabled to be individually switched off by a server. An occupant of a room in control of the plurality of devices provides via a Human Machine Interface on a tablet a preferred order of switching off the plurality of devices in case of a Demand Response Event. A configuration file based at least partially on the preferred order and on a severity of the Demand Response Events determines which devices which of the plurality devices will be switched off. The server accesses the configuration file and switches off the devices included in the configuration file.

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

    Directory of Open Access Journals (Sweden)

    Shin Young Heo

    2015-10-01

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

  12. STEM-based science learning implementation to identify student’s personal intelligences profiles

    Science.gov (United States)

    Wiguna, B. J. P. K.; Suwarma, I. R.; Liliawati, W.

    2018-05-01

    Science and technology are rapidly developing needs to be balanced with the human resources that have the qualified ability. Not only cognitive ability, but also have the soft skills that support 21st century skills. Science, Technology, Engineering, and Mathematics (STEM) Education is a solution to improve the quality of learning and prepare students may be able to trained 21st century skills. This study aims to analyse the implementation of STEM-based science learning on Newton’s law of motion by identifying the personal intelligences profile junior high school students. The method used in this research is pre experiment with the design of the study one group pre-test post-test. Samples in this study were 26 junior high school students taken using Convenience Sampling. Students personal intelligences profile after learning STEM-based science uses two instruments, self-assessment and peer assessment. Intrapersonal intelligence profile based self-assessment and peer assessment are respectively 69.38; and 64.08. As for interpersonal intelligence for self-assessment instrument is 73 and the peer assessment is 60.23.

  13. Intelligent-based Structural Damage Detection Model

    International Nuclear Information System (INIS)

    Lee, Eric Wai Ming; Yu, K.F.

    2010-01-01

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  14. Intelligent-based Structural Damage Detection Model

    Science.gov (United States)

    Lee, Eric Wai Ming; Yu, Kin Fung

    2010-05-01

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  15. Experiments with microcomputer-based artificial intelligence environments

    Science.gov (United States)

    Summers, E.G.; MacDonald, R.A.

    1988-01-01

    The U.S. Geological Survey (USGS) has been experimenting with the use of relatively inexpensive microcomputers as artificial intelligence (AI) development environments. Several AI languages are available that perform fairly well on desk-top personal computers, as are low-to-medium cost expert system packages. Although performance of these systems is respectable, their speed and capacity limitations are questionable for serious earth science applications foreseen by the USGS. The most capable artificial intelligence applications currently are concentrated on what is known as the "artificial intelligence computer," and include Xerox D-series, Tektronix 4400 series, Symbolics 3600, VAX, LMI, and Texas Instruments Explorer. The artificial intelligence computer runs expert system shells and Lisp, Prolog, and Smalltalk programming languages. However, these AI environments are expensive. Recently, inexpensive 32-bit hardware has become available for the IBM/AT microcomputer. USGS has acquired and recently completed Beta-testing of the Gold Hill Systems 80386 Hummingboard, which runs Common Lisp on an IBM/AT microcomputer. Hummingboard appears to have the potential to overcome many of the speed/capacity limitations observed with AI-applications on standard personal computers. USGS is a Beta-test site for the Gold Hill Systems GoldWorks expert system. GoldWorks combines some high-end expert system shell capabilities in a medium-cost package. This shell is developed in Common Lisp, runs on the 80386 Hummingboard, and provides some expert system features formerly available only on AI-computers including frame and rule-based reasoning, on-line tutorial, multiple inheritance, and object-programming. ?? 1988 International Association for Mathematical Geology.

  16. The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

    Science.gov (United States)

    Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

    2017-05-01

    This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

  17. Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization

    International Nuclear Information System (INIS)

    Zhou, Quan; Zhang, Wei; Cash, Scott; Olatunbosun, Oluremi; Xu, Hongming; Lu, Guoxiang

    2017-01-01

    Highlights: • A novel algorithm for hybrid electric powertrain intelligent sizing is introduced and applied. • The proposed CAPSO algorithm is capable of finding the real optimal result with much higher reputation. • Logistic mapping is the most effective strategy to build CAPSO. • The CAPSO gave more reliable results and increased the efficiency by 1.71%. - Abstract: This paper firstly proposed a novel HEV sizing method using the Chaos-enhanced Accelerated Particle Swarm Optimization (CAPSO) algorithm and secondly provided a demonstration on sizing a series hybrid electric powertrain with investigations of chaotic mapping strategies to achieve the global optimization. In this paper, the intelligent sizing of a series hybrid electric powertrain is formulated as an integer multi-objective optimization issue by modelling the powertrain system. The intelligent sizing mechanism based on APSO is then introduced, and 4 types of the most effective chaotic mapping strategy are investigated to upgrade the standard APSO into CAPSO algorithms for intelligent sizing. The evaluation of the intelligent sizing systems based on standard APSO and CAPSOs are then performed. The Monte Carlo analysis and reputation evaluation indicate that the CAPSO outperforms the standard APSO for finding the real optimal sizing result with much higher reputation, and CAPSO with logistic mapping strategy is the most effective algorithm for HEV powertrain components intelligent sizing. In addition, this paper also performs the sensitivity analysis and Pareto analysis to help engineers customize the intelligent sizing system.

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

    Directory of Open Access Journals (Sweden)

    George Karavokiros

    2016-09-01

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

  19. 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.

  20. Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

    Science.gov (United States)

    Ganapathy, S.; Yogesh, P.; Kannan, A.

    2012-01-01

    Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

  1. Hot complaint intelligent classification based on text mining

    Directory of Open Access Journals (Sweden)

    XIA Haifeng

    2013-10-01

    Full Text Available The complaint recognizer system plays an important role in making sure the correct classification of the hot complaint,improving the service quantity of telecommunications industry.The customers’ complaint in telecommunications industry has its special particularity which should be done in limited time,which cause the error in classification of hot complaint.The paper presents a model of complaint hot intelligent classification based on text mining,which can classify the hot complaint in the correct level of the complaint navigation.The examples show that the model can be efficient to classify the text of the complaint.

  2. Smart Waste Collection System Based on Location Intelligence

    DEFF Research Database (Denmark)

    Lopez, Jose Manuel Guterrez Lopez; Jensen, Michael; Andreasen, Morten Henius

    2015-01-01

    (IoT) integration with data access networks, Geographic Information Systems (GIS), combinatorial optimization, and electronic engineering can contribute to improve cities’ management systems. We present a waste collection solution based on providing intelligence to trashcans, by using an IoT prototype...... to contribute and develop Smart city solutions.......Cities around the world are on the run to become smarter. Some of these have seen an opportunity on deploying dedicated municipal access networks to support all types of city management and maintenance services requiring a data connection. This paper practically demonstrates how Internet of Things...

  3. ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

    Institute of Scientific and Technical Information of China (English)

    X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

    2003-01-01

    An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

  4. Knowledge-based dialogue in Intelligent Decision Support Systems

    International Nuclear Information System (INIS)

    Hollnagel, E.

    1987-01-01

    The overall goal for the design of Intelligent Decision Support Systems (IDSS) is to enhance understanding of the process under all operating conditions. For an IDSS to be effective, it must: select or generate the right information; produce reliable and consistent information; allow flexible and effective operator interaction; relate information presentation to current plant status and problems; and make the presentation at the right time. Several ongoing R and D programs try to design and build IDSSs. A particular example is the ESPRIT project Graphics and Knowledge Based Diaglogue for Dynamic Systems (GRADIENT). This project, the problems it addresses, and its uses, are discussed here

  5. A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems

    Directory of Open Access Journals (Sweden)

    Yiming Jiang

    2016-01-01

    Full Text Available Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC and neural network (NN control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area.

  6. 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)

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Nima Farajian

    2013-10-01

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

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

    International Nuclear Information System (INIS)

    Medhat, M.E.

    2012-01-01

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

  10. Utility and potential of rapid epidemic intelligence from internet-based sources.

    Science.gov (United States)

    Yan, S J; Chughtai, A A; Macintyre, C R

    2017-10-01

    Rapid epidemic detection is an important objective of surveillance to enable timely intervention, but traditional validated surveillance data may not be available in the required timeframe for acute epidemic control. Increasing volumes of data on the Internet have prompted interest in methods that could use unstructured sources to enhance traditional disease surveillance and gain rapid epidemic intelligence. We aimed to summarise Internet-based methods that use freely-accessible, unstructured data for epidemic surveillance and explore their timeliness and accuracy outcomes. Steps outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist were used to guide a systematic review of research related to the use of informal or unstructured data by Internet-based intelligence methods for surveillance. We identified 84 articles published between 2006-2016 relating to Internet-based public health surveillance methods. Studies used search queries, social media posts and approaches derived from existing Internet-based systems for early epidemic alerts and real-time monitoring. Most studies noted improved timeliness compared to official reporting, such as in the 2014 Ebola epidemic where epidemic alerts were generated first from ProMED-mail. Internet-based methods showed variable correlation strength with official datasets, with some methods showing reasonable accuracy. The proliferation of publicly available information on the Internet provided a new avenue for epidemic intelligence. Methodologies have been developed to collect Internet data and some systems are already used to enhance the timeliness of traditional surveillance systems. To improve the utility of Internet-based systems, the key attributes of timeliness and data accuracy should be included in future evaluations of surveillance systems. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-31

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

  12. Realization of Intelligent Household Appliance Wireless Monitoring Network Based on LEACH Protocol

    Directory of Open Access Journals (Sweden)

    Weilong ZHOU

    2014-06-01

    Full Text Available The intelligent household appliance wireless monitoring network can real-time monitor the apparent power and power factor of various household appliances in different indoor regions, and can realize the real-time monitoring on the household appliance working status and performance. The household appliance wireless monitoring network based on LEACH protocol is designed in the paper. Firstly, the basic idea of LEACH routing algorithm is proposed. Aiming at the node-distribution feature of intelligent home, the selection of cluster head in the routing algorithm and the data transmission method at the stable communication phase is modified. Moreover, the hardware circuit of power acquisition and power factor measurement is designed. The realization of wireless monitoring network based on CC2530 is described, each module and the whole system were conducted the on-line debugging. Finally, the system is proved to meet the practical requirement through the networking test.

  13. Auto-correlation based intelligent technique for complex waveform presentation and measurement

    International Nuclear Information System (INIS)

    Rana, K P S; Singh, R; Sayann, K S

    2009-01-01

    Waveform acquisition and presentation forms the heart of many measurement systems. Particularly, data acquisition and presentation of repeating complex signals like sine sweep and frequency-modulated signals introduces the challenge of waveform time period estimation and live waveform presentation. This paper presents an intelligent technique, for waveform period estimation of both the complex and simple waveforms, based on the normalized auto-correlation method. The proposed technique is demonstrated using LabVIEW based intensive simulations on several simple and complex waveforms. Implementation of the technique is successfully demonstrated using LabVIEW based virtual instrumentation. Sine sweep vibration waveforms are successfully presented and measured for electrodynamic shaker system generated vibrations. The proposed method is also suitable for digital storage oscilloscope (DSO) triggering, for complex signals acquisition and presentation. This intelligence can be embodied into the DSO, making it an intelligent measurement system, catering wide varieties of the waveforms. The proposed technique, simulation results, robustness study and implementation results are presented in this paper.

  14. Development of Android Based Powered Intelligent Wheelchair for Quadriplegic Persons

    Science.gov (United States)

    Gupta, Ashutosh; Ghosh, Tathagata; Kumar, Pradeep; Bhawna, Shruthi. S.

    2017-08-01

    Several surveys give us the view that both children and adults benefit substantially from access towards independent mobility. With the inventions of technology, no individuals are satisfied with traditional manual operated machines. To accommodate population, researchers are using technology, originally developed for mobile robots to create ‘intelligent wheelchairs’. It’s a major challenge for quadriplegic persons as they really find it difficult to manipulate powered wheelchair during the activities of their daily living. As the Smartphone era has evolved with innovative android based applications, engineers are improving and trying to make such machines simple and cheap to the next level. In this paper, we present a development of android based powered intelligent wheelchair to assist the quadriplegic person by making them self sufficient in controlling the wheelchair. The wheels of the chair can be controlled by the voice or gesture movement or by touching the screen of the android app by the challenged persons. The system uses the Bluetooth communication to interface the microcontroller and the inbuilt sensors in the android Smartphone. According to the commands received from android phone, the kinematics of the wheels are controlled.

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

    Directory of Open Access Journals (Sweden)

    Rojek G.

    2016-06-01

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

  16. Self-Calibration and Optimal Response in Intelligent Sensors Design Based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Gilberto Bojorquez

    2007-08-01

    Full Text Available The development of smart sensors involves the design of reconfigurable systemscapable of working with different input sensors. Reconfigurable systems ideally shouldspend the least possible amount of time in their calibration. An autocalibration algorithmfor intelligent sensors should be able to fix major problems such as offset, variation of gainand lack of linearity, as accurately as possible. This paper describes a new autocalibrationmethodology for nonlinear intelligent sensors based on artificial neural networks, ANN.The methodology involves analysis of several network topologies and training algorithms.The proposed method was compared against the piecewise and polynomial linearizationmethods. Method comparison was achieved using different number of calibration points,and several nonlinear levels of the input signal. This paper also shows that the proposedmethod turned out to have a better overall accuracy than the other two methods. Besides,experimentation results and analysis of the complete study, the paper describes theimplementation of the ANN in a microcontroller unit, MCU. In order to illustrate themethod capability to build autocalibration and reconfigurable systems, a temperaturemeasurement system was designed and tested. The proposed method is an improvement over the classic autocalibration methodologies, because it impacts on the design process of intelligent sensors, autocalibration methodologies and their associated factors, like time and cost.

  17. The Construction of Intelligent English Teaching Model Based on Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Xiaoguang Li

    2017-12-01

    Full Text Available In order to build a modernized tool platform that can help students improve their English learning efficiency according to their mastery of knowledge and personality, this paper develops an online intelligent English learning system that uses Java and artificial intelligence language Prolog as the software system. This system is a creative reflection of the thoughts of expert system in artificial intelligence. Established on the Struts Spring Hibernate lightweight JavaEE framework, the system modules are coupled with each other in a much lower degree, which is convenient to future function extension. Combined with the idea of expert system in artificial intelligence, the system developed appropriate learning strategies to help students double the learning effect with half the effort; Finally, the system takes into account the forgetting curve of memory, on which basis the knowledge that has been learned will be tested periodically, intending to spare students’ efforts to do a sea of exercises and obtain better learning results.

  18. 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)

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

    Science.gov (United States)

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

    2017-12-12

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

  20. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

  1. DIAGNOSIS WINDOWS PROBLEMS BASED ON HYBRID INTELLIGENCE SYSTEMS

    Directory of Open Access Journals (Sweden)

    SAFWAN O. HASOON

    2013-10-01

    Full Text Available This paper describes the artificial intelligence technologies by integrating Radial Basis Function networks with expert systems to construct a robust hybrid system. The purpose of building the hybrid system is to give recommendations to repair the operating system (Windows problems and troubleshoot the problems that can be repaired. The neural network has unique characteristics which it can complete the uncompleted data, the expert system can't deal with data that is incomplete, but using the neural network individually has some disadvantages which it can't give explanations and recommendations to the problems. The expert system has the ability to explain and give recommendations by using the rules and the human expert in some conditions. Therefore, we have combined the two technologies. The paper will explain the integration methods between the two technologies and which method is suitable to be used in the proposed hybrid system.

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

    Directory of Open Access Journals (Sweden)

    Habibollah Bazdar

    2017-11-01

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

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  4. AN ARTIFICIAL INTELLIGENCE-BASED DISTANCE EDUCATION SYSTEM: Artimat

    Directory of Open Access Journals (Sweden)

    Vasif NABIYEV

    2013-04-01

    Full Text Available The purpose of this study is to evaluate the artificial intelligence-based distance education system called as ARTIMAT, which has been prepared in order to improve mathematical problem solving skills of the students, in terms of conceptual proficiency and ease of use with the opinions of teachers and students. The implementation has been performed with 4 teachers and 59 students in 10th grade in an Anatolian High School in Trabzon. Many institutions and organizations in the world approach seriously to distance education besides traditional education. It is inevitable to use the distance education in teaching the problem solving skills in this different dimension of the education. In the studies in Turkey and abroad in the field of mathematics teaching, problem solving skills are generally stated not to be at the desired level and often expressed to have difficulty in teaching. For this reason, difficulties of the students in problem solving have initially been evaluated and the system has been prepared utilizing artificial intelligence algorithms according to the obtained results. In the evaluation of the findings obtained from the application, it has been concluded that the system is responsive to the needs of the students and is successful in general, but that conceptual changes should be made in order that students adapt to the system quickly.

  5. Intelligent community management system based on the devicenet fieldbus

    Science.gov (United States)

    Wang, Yulan; Wang, Jianxiong; Liu, Jiwen

    2013-03-01

    With the rapid development of the national economy and the improvement of people's living standards, people are making higher demands on the living environment. And the estate management content, management efficiency and service quality have been higher required. This paper in-depth analyzes about the intelligent community of the structure and composition. According to the users' requirements and related specifications, it achieves the district management systems, which includes Basic Information Management: the management level of housing, household information management, administrator-level management, password management, etc. Service Management: standard property costs, property charges collecting, the history of arrears and other property expenses. Security Management: household gas, water, electricity and security and other security management, security management district and other public places. Systems Management: backup database, restore database, log management. This article also carries out on the Intelligent Community System analysis, proposes an architecture which is based on B / S technology system. And it has achieved a global network device management with friendly, easy to use, unified human - machine interface.

  6. Intelligent Chiral Sensing Based on Supramolecular and Interfacial Concepts

    Directory of Open Access Journals (Sweden)

    Hironori Izawa

    2010-07-01

    Full Text Available Of the known intelligently-operating systems, the majority can undoubtedly be classed as being of biological origin. One of the notable differences between biological and artificial systems is the important fact that biological materials consist mostly of chiral molecules. While most biochemical processes routinely discriminate chiral molecules, differentiation between chiral molecules in artificial systems is currently one of the challenging subjects in the field of molecular recognition. Therefore, one of the important challenges for intelligent man-made sensors is to prepare a sensing system that can discriminate chiral molecules. Because intermolecular interactions and detection at surfaces are respectively parts of supramolecular chemistry and interfacial science, chiral sensing based on supramolecular and interfacial concepts is a significant topic. In this review, we briefly summarize recent advances in these fields, including supramolecular hosts for color detection on chiral sensing, indicator-displacement assays, kinetic resolution in supramolecular reactions with analyses by mass spectrometry, use of chiral shape-defined polymers, such as dynamic helical polymers, molecular imprinting, thin films on surfaces of devices such as QCM, functional electrodes, FET, and SPR, the combined technique of magnetic resonance imaging and immunoassay, and chiral detection using scanning tunneling microscopy and cantilever technology. In addition, we will discuss novel concepts in recent research including the use of achiral reagents for chiral sensing with NMR, and mechanical control of chiral sensing. The importance of integration of chiral sensing systems with rapidly developing nanotechnology and nanomaterials is also emphasized.

  7. Price Comparisons on the Internet Based on Computational Intelligence

    Science.gov (United States)

    Kim, Jun Woo; Ha, Sung Ho

    2014-01-01

    Information-intensive Web services such as price comparison sites have recently been gaining popularity. However, most users including novice shoppers have difficulty in browsing such sites because of the massive amount of information gathered and the uncertainty surrounding Web environments. Even conventional price comparison sites face various problems, which suggests the necessity of a new approach to address these problems. Therefore, for this study, an intelligent product search system was developed that enables price comparisons for online shoppers in a more effective manner. In particular, the developed system adopts linguistic price ratings based on fuzzy logic to accommodate user-defined price ranges, and personalizes product recommendations based on linguistic product clusters, which help online shoppers find desired items in a convenient manner. PMID:25268901

  8. Intelligent Home Control System Based on Single Chip Microcomputer

    Science.gov (United States)

    Yang, Libo

    2017-12-01

    Intelligent home as a way to achieve the realization of the family information has become an important part of the development of social information, Internet of Things because of its huge application prospects, will be smart home industry in the development process of a more realistic breakthrough in the smart home industry development has great significance. This article is based on easy to implement, easy to operate, close to the use of the design concept, the use of STC89C52 microcontroller as the control core for the control terminal, and including infrared remote control, buttons, Web interface, including multiple control sources to control household appliances. The second chapter of this paper describes the design of the hardware and software part of the specific implementation, the fifth chapter is based on the design of a good function to build a specific example of the environment.

  9. Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

    Directory of Open Access Journals (Sweden)

    Yuanpeng Tan

    2018-01-01

    Full Text Available Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

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

    Institute of Scientific and Technical Information of China (English)

    KIM Jongwoo; LEE Hongjoo; PARK Sungjoo

    2004-01-01

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

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

    OpenAIRE

    中島, 正世; Nakajima, Masayo

    2015-01-01

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

  12. Monocular-Based 6-Degree of Freedom Pose Estimation Technology for Robotic Intelligent Grasping Systems

    Directory of Open Access Journals (Sweden)

    Tao Liu

    2017-02-01

    Full Text Available Industrial robots are expected to undertake ever more advanced tasks in the modern manufacturing industry, such as intelligent grasping, in which robots should be capable of recognizing the position and orientation of a part before grasping it. In this paper, a monocular-based 6-degree of freedom (DOF pose estimation technology to enable robots to grasp large-size parts at informal poses is proposed. A camera was mounted on the robot end-flange and oriented to measure several featured points on the part before the robot moved to grasp it. In order to estimate the part pose, a nonlinear optimization model based on the camera object space collinearity error in different poses is established, and the initial iteration value is estimated with the differential transformation. Measuring poses of the camera are optimized based on uncertainty analysis. Also, the principle of the robotic intelligent grasping system was developed, with which the robot could adjust its pose to grasp the part. In experimental tests, the part poses estimated with the method described in this paper were compared with those produced by a laser tracker, and results show the RMS angle and position error are about 0.0228° and 0.4603 mm. Robotic intelligent grasping tests were also successfully performed in the experiments.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-12-31

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

  14. Effects of multiple intelligences supported project-based learning on students’ achievement levels and attitudes towards English lesson

    Directory of Open Access Journals (Sweden)

    Gökhan BAŞ

    2010-07-01

    Full Text Available The aim of the research was to investigate the effects of multiple intelligences supported project-based learning and traditional foreign language-teaching environment on students' achievement and their attitude towards English lesson. The research was carried out in 2009 – 2010 education-instruction year in Karatli Sehit Sahin Yilmaz Elementary School, Nigde, Turkey. Totally 50 students in two different classes in the 5th grade of this school participated in the study. The results of the research showed a significant difference between the attitude scores of the experiment group and the control group. It was also found out that the multiple intelligences approach activities were more effective in thepositive development of the students’ attitudes. At the end of the research, it is revealed that the students who are educated by multiple intelligences supported project-based learning method are more successful and have a higher motivation level than the studentswho are educated by the traditional instructional methods.

  15. Intelligent Aggregation Based on Content Routing Scheme for Cloud Computing

    Directory of Open Access Journals (Sweden)

    Jiachen Xu

    2017-10-01

    Full Text Available Cloud computing has emerged as today’s most exciting computing paradigm for providing services using a shared framework, which opens a new door for solving the problems of the explosive growth of digital resource demands and their corresponding convenience. With the exponential growth of the number of data types and data size in so-called big data work, the backbone network is under great pressure due to its transmission capacity, which is lower than the growth of the data size and would seriously hinder the development of the network without an effective approach to solve this problem. In this paper, an Intelligent Aggregation based on a Content Routing (IACR scheme for cloud computing, which could reduce the amount of data in the network effectively and play a basic supporting role in the development of cloud computing, is first put forward. All in all, the main innovations in this paper are: (1 A framework for intelligent aggregation based on content routing is proposed, which can support aggregation based content routing; (2 The proposed IACR scheme could effectively route the high aggregation ratio data to the data center through the same routing path so as to effectively reduce the amount of data that the network transmits. The theoretical analyses experiments and results show that, compared with the previous original routing scheme, the IACR scheme can balance the load of the whole network, reduce the amount of data transmitted in the network by 41.8%, and reduce the transmission time by 31.6% in the same network with a more balanced network load.

  16. How People Interact with Technology based on Natural and Artificial Intelligence

    OpenAIRE

    Vasile MAZILESCU

    2017-01-01

    This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI) and Collective Intelligence (CI). This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow), of connecting people with...

  17. Intelligent Growth Automaton of Virtual Plant Based on Physiological Engine

    Science.gov (United States)

    Zhu, Qingsheng; Guo, Mingwei; Qu, Hongchun; Deng, Qingqing

    In this paper, a novel intelligent growth automaton of virtual plant is proposed. Initially, this intelligent growth automaton analyzes the branching pattern which is controlled by genes and then builds plant; moreover, it stores the information of plant growth, provides the interface between virtual plant and environment, and controls the growth and development of plant on the basis of environment and the function of plant organs. This intelligent growth automaton can simulate that the plant growth is controlled by genetic information system, and the information of environment and the function of plant organs. The experimental results show that the intelligent growth automaton can simulate the growth of plant conveniently and vividly.

  18. Joint Dictionary Learning-Based Non-Negative Matrix Factorization for Voice Conversion to Improve Speech Intelligibility After Oral Surgery.

    Science.gov (United States)

    Fu, Szu-Wei; Li, Pei-Chun; Lai, Ying-Hui; Yang, Cheng-Chien; Hsieh, Li-Chun; Tsao, Yu

    2017-11-01

    Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients. Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient

  19. Machine learning based Intelligent cognitive network using fog computing

    Science.gov (United States)

    Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

    2017-05-01

    In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

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

    Science.gov (United States)

    Lee, Oi Sun; Gu, Mee Ock

    2014-12-01

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

  1. JOYO operation support system 'JOYCAT' based on intelligent alarm handling

    International Nuclear Information System (INIS)

    Tamaoki, Tetsuo; Yamamoto, Hiroki; Sato, Masuo; Yoshida, Megumu; Kaneko, Tomoko; Terunuma, Seiichi; Takatsuto, Hiroshi; Morimoto, Makoto.

    1992-01-01

    An operation support system for the experimental fast reactor 'JOYO' was developed based on an intelligent alarm-handling. A specific feature of this system, called JOYCAT (JOYO Consulting and Analyzing Tool), is in its sequential processing structure that a uniform treatment by using design knowledge base is firstly applied for all activated alarms, and an exceptional treatment by using heuristic knowledge base is then applied only for the former results. This enables us to achieve real-time and flexible alarm-handling. The first alarm-handling determines the candidates of causal alarms, important alarms with which the operator should firstly cope, through identifying the cause-consequence relations among alarms based on the design knowledge base in which importance and activating conditions are described for each of 640 alarms in a frame format. The second alarm-handling makes the final judgement with the candidates by using the heuristic knowledge base described as production rules. Then, operation manuals concerning the most important alarms are displayed to operators. JOYCAT has been in commission since September of 1990, after a wide scope of validation tests by using an on-site full-scope training simulator. (author)

  2. Developing energy forecasting model using hybrid artificial intelligence method

    Institute of Scientific and Technical Information of China (English)

    Shahram Mollaiy-Berneti

    2015-01-01

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

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

    Science.gov (United States)

    Sundararajan, Subashini; Gopichandran, Vijayaprasad

    2018-05-04

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

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

    Directory of Open Access Journals (Sweden)

    Tomasz Wójcicki

    2014-12-01

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

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

    Science.gov (United States)

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

    2017-03-01

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

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

    NARCIS (Netherlands)

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

    2001-01-01

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

  7. Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation.

    Science.gov (United States)

    Cheng, Yu-Huei

    2014-12-01

    Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

  8. Intelligent control and maintenance of management integrated system based on multi-agents for coal preparation plant

    Energy Technology Data Exchange (ETDEWEB)

    Meng, F.; Wang, Y. [China University of Mining and technology, Xuzhou (China). School of Information and Electrical Engineering

    2006-06-15

    This paper discusses the progress of computer integrated processing (CIPS) of coal preparation and then presents an intelligence controlled production process, device-maintenance and production-management system of coal preparation based on multi-agents (IICMMS-CP). The construction of the IICMMS-CP, the distributed network control system based on live intelligence control stations and the strategy of implementing a distributed intelligence control system are studied in order to overcome the disadvantages brought about by the wide use of the PLC system by coal preparation plants. The software frame, based on a Multi-Agent Intelligence Control and Maintenance Management integrated system, is studied and the implementation methods of IICMMS-CP are discussed. The characteristics of distributed architecture, cooperation and parallel computing meet the needs of integrated control of coal preparation plants with large-scale spatial production distribution, densely-related processes and complex systems. Its application further improves the reliability and precision of process control, accuracy of fault identification and intelligence of production adjustment, establishes a technical basis for system integration and flexible production. The main function of the system has been tested in a coal preparation plant to good effect in stabilizing product quality, improving efficiency and reducing consumption. 17 refs., 4 figs.

  9. New technology-based recruitment methods

    OpenAIRE

    Oksanen, Reija

    2018-01-01

    The transformation that recruitment might encounter due to big data analytics and artificial intelligence (AI) is particularly fascinating which is why this thesis focuses on the changes recruitment processes are and will be facing as new technological solutions are emerging. The aim and main objective of this study is to widen knowledge about new technology-based recruitment methods, focusing on how they are utilized by Finnish recruitment professionals and how the opportunities and risks th...

  10. 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...

  11. The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

    Science.gov (United States)

    Hali, Nur Ihsan

    2017-01-01

    This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…

  12. The Relationship between Emotional Intelligence and Attitudes toward Computer-Based Instruction of Postsecondary Hospitality Students

    Science.gov (United States)

    Behnke, Carl; Greenan, James P.

    2011-01-01

    This study examined the relationship between postsecondary students' emotional-social intelligence and attitudes toward computer-based instructional materials. Research indicated that emotions and emotional intelligence directly impact motivation, while instructional design has been shown to impact student attitudes and subsequent engagement with…

  13. Motorcycle Start-stop System based on Intelligent Biometric Voice Recognition

    Science.gov (United States)

    Winda, A.; E Byan, W. R.; Sofyan; Armansyah; Zariantin, D. L.; Josep, B. G.

    2017-03-01

    Current mechanical key in the motorcycle is prone to bulgary, being stolen or misplaced. Intelligent biometric voice recognition as means to replace this mechanism is proposed as an alternative. The proposed system will decide whether the voice is belong to the user or not and the word utter by the user is ‘On’ or ‘Off’. The decision voice will be sent to Arduino in order to start or stop the engine. The recorded voice is processed in order to get some features which later be used as input to the proposed system. The Mel-Frequency Ceptral Coefficient (MFCC) is adopted as a feature extraction technique. The extracted feature is the used as input to the SVM-based identifier. Experimental results confirm the effectiveness of the proposed intelligent voice recognition and word recognition system. It show that the proposed method produces a good training and testing accuracy, 99.31% and 99.43%, respectively. Moreover, the proposed system shows the performance of false rejection rate (FRR) and false acceptance rate (FAR) accuracy of 0.18% and 17.58%, respectively. In the intelligent word recognition shows that the training and testing accuracy are 100% and 96.3%, respectively.

  14. Road Vehicle Monitoring System Based on Intelligent Visual Internet of Things

    Directory of Open Access Journals (Sweden)

    Qingwu Li

    2015-01-01

    Full Text Available In recent years, with the rapid development of video surveillance infrastructure, more and more intelligent surveillance systems have employed computer vision and pattern recognition techniques. In this paper, we present a novel intelligent surveillance system used for the management of road vehicles based on Intelligent Visual Internet of Things (IVIoT. The system has the ability to extract the vehicle visual tags on the urban roads; in other words, it can label any vehicle by means of computer vision and therefore can easily recognize vehicles with visual tags. The nodes designed in the system can be installed not only on the urban roads for providing basic information but also on the mobile sensing vehicles for providing mobility support and improving sensing coverage. Visual tags mentioned in this paper consist of license plate number, vehicle color, and vehicle type and have several additional properties, such as passing spot and passing moment. Moreover, we present a fast and efficient image haze removal method to deal with haze weather condition. The experiment results show that the designed road vehicle monitoring system achieves an average real-time tracking accuracy of 85.80% under different conditions.

  15. A Crowdsensing-Based Real-Time System for Finger Interactions in Intelligent Transport System

    Directory of Open Access Journals (Sweden)

    Chengqun Song

    2017-01-01

    Full Text Available Crowdsensing leverages human intelligence/experience from the general public and social interactions to create participatory sensor networks, where context-aware and semantically complex information is gathered, processed, and shared to collaboratively solve specific problems. This paper proposes a real-time projector-camera finger system based on the crowdsensing, in which user can interact with a computer by bare hand touching on arbitrary surfaces. The interaction process of the system can be completely carried out automatically, and it can be used as an intelligent device in intelligent transport system where the driver can watch and interact with the display information while driving, without causing visual distractions. A single camera is used in the system to recover 3D information of fingertip for hand touch detection. A linear-scanning method is used in the system to determine the touch for increasing the users’ collaboration and operationality. Experiments are performed to show the feasibility of the proposed system. The system is robust to different lighting conditions. The average percentage of correct hand touch detection of the system is 92.0% and the average time of processing one video frame is 30 milliseconds.

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

    Science.gov (United States)

    Arotaritei, D.; Rotariu, C.

    2015-09-01

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

  17. Improvement of Base and Soil Construction Quality by Using Intelligent Compaction Technology : Final Report.

    Science.gov (United States)

    2017-08-01

    Intelligent Compaction (IC) technique is a fast-developing technology for base and soil compaction quality control. Proof-rolling subgrades and bases using IC rollers upon completion of compaction can identify the less stiff spots and significantly i...

  18. Gaussian process based intelligent sampling for measuring nano-structure surfaces

    Science.gov (United States)

    Sun, L. J.; Ren, M. J.; Yin, Y. H.

    2016-09-01

    Nanotechnology is the science and engineering that manipulate matters at nano scale, which can be used to create many new materials and devices with a vast range of applications. As the nanotech product increasingly enters the commercial marketplace, nanometrology becomes a stringent and enabling technology for the manipulation and the quality control of the nanotechnology. However, many measuring instruments, for instance scanning probe microscopy, are limited to relatively small area of hundreds of micrometers with very low efficiency. Therefore some intelligent sampling strategies should be required to improve the scanning efficiency for measuring large area. This paper presents a Gaussian process based intelligent sampling method to address this problem. The method makes use of Gaussian process based Bayesian regression as a mathematical foundation to represent the surface geometry, and the posterior estimation of Gaussian process is computed by combining the prior probability distribution with the maximum likelihood function. Then each sampling point is adaptively selected by determining the position which is the most likely outside of the required tolerance zone among the candidates and then inserted to update the model iteratively. Both simulationson the nominal surface and manufactured surface have been conducted on nano-structure surfaces to verify the validity of the proposed method. The results imply that the proposed method significantly improves the measurement efficiency in measuring large area structured surfaces.

  19. Artificial Intelligence in Civil Engineering

    OpenAIRE

    Lu, Pengzhen; Chen, Shengyong; Zheng, Yujun

    2012-01-01

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

  20. Predicting Couples’ Happiness Based on Spiritual Intelligence and Lovemaking Styles: The Mediating Role of Marital adjustment

    Directory of Open Access Journals (Sweden)

    ZAHRA KERMANI MAMAZANDI

    2017-02-01

    Full Text Available The purpose of this study was to predict couples’ happiness based on spiritual intelligence and lovemaking styles with the mediating role of marital adjustment. Therefore 360 male and female, married students living in Tehran University dormitory were randomly selected and were asked to answer the items of Sternberg’s Love Questionnaire, King’s Spiritual Intelligence Scale, Oxford’s Happiness Questionnaire and Spanier’s Marital Adjustment Questionnaire. Structural equation modeling (path analysis was used for data analysis. The results  of path analysis showed  that spiritual intelligence and lovemaking styles have direct effects on couples’ happiness, and the spiritual intelligence did not have an indirect effect on couples’ happiness whereas lovemaking styles had indirect effects on couples’ happiness through martial satisfaction. Altogether the results of this research show that marital adjustment has a mediating role in predicting couples’ happiness based on spiritual intelligence and lovemaking styles.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-03-15

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

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

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  3. Home Automation System Based on Intelligent Transducer Enablers

    Science.gov (United States)

    Suárez-Albela, Manuel; Fraga-Lamas, Paula; Fernández-Caramés, Tiago M.; Dapena, Adriana; González-López, Miguel

    2016-01-01

    This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet. PMID:27690031

  4. Home Automation System Based on Intelligent Transducer Enablers.

    Science.gov (United States)

    Suárez-Albela, Manuel; Fraga-Lamas, Paula; Fernández-Caramés, Tiago M; Dapena, Adriana; González-López, Miguel

    2016-09-28

    This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet.

  5. Home Automation System Based on Intelligent Transducer Enablers

    Directory of Open Access Journals (Sweden)

    Manuel Suárez-Albela

    2016-09-01

    Full Text Available This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers, which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet.

  6. Predicting chick body mass by artificial intelligence-based models

    Directory of Open Access Journals (Sweden)

    Patricia Ferreira Ponciano Ferraz

    2014-07-01

    Full Text Available The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks - with the variables dry-bulb air temperature, duration of thermal stress (days, chick age (days, and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs and neuro-fuzzy networks (NFNs. The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

  7. Solar-Based Fuzzy Intelligent Water Sprinkle System

    Directory of Open Access Journals (Sweden)

    Riza Muhida

    2012-03-01

    Full Text Available A solar-based intelligent water sprinkler system project that has been developed to ensure the effectiveness in watering the plant is improved by making the system automated. The control system consists of an electrical capacitance soil moisture sensor installed into the ground which is interfaced to a controller unit of Motorola 68HC11 Handy board microcontroller. The microcontroller was programmed based on the decision rules made using fuzzy logic approach on when to water the lawn. The whole system is powered up by the solar energy which is then interfaced to a particular type of irrigation timer for plant fertilizing schedule and rain detector through a simple design of rain dual-collector tipping bucket. The controller unit automatically disrupted voltage signals sent to the control valves whenever irrigation was not needed. Using this system we combined the logic implementation in the area of irrigation and weather sensing equipment, and more efficient water delivery can be made possible. 

  8. 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

  9. 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...

  10. An intelligent clustering based methodology for confusable diseases ...

    African Journals Online (AJOL)

    Journal of Computer Science and Its Application ... In this paper, an intelligent system driven by fuzzy clustering algorithm and Adaptive Neuro-Fuzzy Inference System for ... Data on patients diagnosed and confirmed by laboratory tests of viral ...

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

    Science.gov (United States)

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

    2017-04-01

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

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

    Directory of Open Access Journals (Sweden)

    Massoud Tabesh

    2011-07-01

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

  13. TOWARDS MEASURES OF INTELLIGENCE BASED ON SEMIOTIC CONTROL

    Energy Technology Data Exchange (ETDEWEB)

    C. JOSLYN

    2000-08-01

    We address the question of how to identify and measure the degree of intelligence in systems. We define the presence of intelligence as equivalent to the presence of a control relation. We contrast the distinct atomic semioic definitions of models and controls, and discuss hierarchical and anticipatory control. We conclude with a suggestion about moving towards quantitative measures of the degree of such control in systems.

  14. Intelligent Home Control System Based on ARM10

    Science.gov (United States)

    Chen, G. X.; Jiang, J.; Zhong, L. H.

    2017-10-01

    Intelligent home is becoming the hot spot of social attention in the 21st century. When it is in China, it is a really new industry. However, there is no doubt that Intelligent home will become a new economic growth point of social development; it will change the life-style of human being. To develop the intelligent home, we should keep up with the development trend of technology. This is the reason why I talk about the intelligent home control system here. In this paper, intelligent home control system is designed for alarm and remote control on gas- leaking, fire disaster, earthquake prediction, etc., by examining environmental changes around house. When the Intelligent home control system has detected an accident occurs, the processor will communicate with the GSM module, informing the house keeper the occurrence of accident. User can receive and send the message to the system to cut the power by mobile phone. The system can get access to DCCthrough ARM10 JTAG interface, using DCC to send and receive messages. At the same time, the debugger on the host is mainly used to receive the user’s command and send it to the debug component in the target system. The data that returned from the target system is received and displayed to the user in a certain format.

  15. The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

    Directory of Open Access Journals (Sweden)

    Nur Ihsan Halil

    2017-10-01

    Full Text Available This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by developing and constructing an existing concept, namely the concept of linguistic intelligence, which is disseminated into a literature-based learning of verbal-linguistic intelligence. The purpose of this paper is to answer the question of how to apply the literary learning model based on the verbal-linguistic intelligence. Then, regarding Gardner's concept, the author formulated a literary learning model based on the verbal-linguistic intelligence through a story-telling learning model with five steps namely arguing, discussing, interpreting, speaking, and writing about literary works. In short, the writer draw a conclusion that learning-based models of verbal-linguistic intelligence can be designed with attention into five components namely (1 definition, (2 characteristics, (3 teaching strategy, (4 final learning outcomes, and (5 figures.

  16. New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Bio-inspired intelligence is in the spotlight in the field of international artificial intelligence,and unmanned combat aerial vehicle(UCAV),owing to its potential to perform dangerous,repetitive tasks in remote and hazardous,is very promising for the technological leadership of the nation and essential for improving the security of society.On the basis of introduction of bioinspired intelligence and UCAV,a series of new development thoughts on UCAV control are proposed,including artificial brain based high-level autonomous control for UCAV,swarm intelligence based cooperative control for multiple UCAVs,hy-brid swarm intelligence and Bayesian network based situation assessment under complicated combating environments, bio-inspired hardware based high-level autonomous control for UCAV,and meta-heuristic intelligence based heterogeneous cooperative control for multiple UCAVs and unmanned combat ground vehicles(UCGVs).The exact realization of the proposed new development thoughts can enhance the effectiveness of combat,while provide a series of novel breakthroughs for the intelligence,integration and advancement of future UCAV systems.

  17. Development of hybrid artificial intelligent based handover decision algorithm

    Directory of Open Access Journals (Sweden)

    A.M. Aibinu

    2017-04-01

    Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

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

    OpenAIRE

    Mezera, Filip; Křupka, Jiří

    2017-01-01

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

  19. The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

    Science.gov (United States)

    Han, Gaining; Fu, Weiping; Wang, Wen

    2016-01-01

    In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

  20. Implementation Of CAN Based Intelligent Driver Alert System

    Directory of Open Access Journals (Sweden)

    Yin Mar Win Kyaw Myo Maung Maung

    2015-08-01

    Full Text Available This system is an attempt to analyze Intelligent Driver Alert System Using CAN Protocol. CAN Controller Area Network offer an efficient communication protocol among sensors actuators controllers and other nodes in real-time applications and is known for its simplicity reliability and high performance. It has given an effective way by which can increase the car and driver safety. This system presents the development and implementation of a digital driving system for a semi-autonomous vehicle to improve the driver-vehicle interface using microcontroller based data acquisition system that uses ADC to bring all control data from analog to digital format. In this system the signal information like temperature LM35 sensor if the temperature increase above the 60 o C and ultrasonic sensor is adapted to measure the distance between the object and vehicle if obstacle is detected within 75cm from the vehicle the controller gives buzzer to the driver speed measure using RPM sensor if revolution increase up to 1200 per minute controller act and to avoid the maximum revolution and to check the fuel level continuously and display in the percentage if fuel level below 20 percent the controller also gives buzzer to the driver and distance fuel level and temperature continuously display on the LCD.

  1. a New Architecture for Intelligent Systems with Logic Based Languages

    Science.gov (United States)

    Saini, K. K.; Saini, Sanju

    2008-10-01

    People communicate with each other in sentences that incorporate two kinds of information: propositions about some subject, and metalevel speech acts that specify how the propositional information is used—as an assertion, a command, a question, or a promise. By means of speech acts, a group of people who have different areas of expertise can cooperate and dynamically reconfigure their social interactions to perform tasks and solve problems that would be difficult or impossible for any single individual. This paper proposes a framework for intelligent systems that consist of a variety of specialized components together with logic-based languages that can express propositions and speech acts about those propositions. The result is a system with a dynamically changing architecture that can be reconfigured in various ways: by a human knowledge engineer who specifies a script of speech acts that determine how the components interact; by a planning component that generates the speech acts to redirect the other components; or by a committee of components, which might include human assistants, whose speech acts serve to redirect one another. The components communicate by sending messages to a Linda-like blackboard, in which components accept messages that are either directed to them or that they consider themselves competent to handle.

  2. Domain-based Teaching Strategy for Intelligent Tutoring System Based on Generic Rules

    Science.gov (United States)

    Kseibat, Dawod; Mansour, Ali; Adjei, Osei; Phillips, Paul

    In this paper we present a framework for selecting the proper instructional strategy for a given teaching material based on its attributes. The new approach is based on a flexible design by means of generic rules. The framework was adapted in an Intelligent Tutoring System to teach Modern Standard Arabic language to adult English-speaking learners with no pre-knowledge of Arabic language is required.

  3. Predicting Speech Intelligibility Decline in Amyotrophic Lateral Sclerosis Based on the Deterioration of Individual Speech Subsystems

    Science.gov (United States)

    Yunusova, Yana; Wang, Jun; Zinman, Lorne; Pattee, Gary L.; Berry, James D.; Perry, Bridget; Green, Jordan R.

    2016-01-01

    Purpose To determine the mechanisms of speech intelligibility impairment due to neurologic impairments, intelligibility decline was modeled as a function of co-occurring changes in the articulatory, resonatory, phonatory, and respiratory subsystems. Method Sixty-six individuals diagnosed with amyotrophic lateral sclerosis (ALS) were studied longitudinally. The disease-related changes in articulatory, resonatory, phonatory, and respiratory subsystems were quantified using multiple instrumental measures, which were subjected to a principal component analysis and mixed effects models to derive a set of speech subsystem predictors. A stepwise approach was used to select the best set of subsystem predictors to model the overall decline in intelligibility. Results Intelligibility was modeled as a function of five predictors that corresponded to velocities of lip and jaw movements (articulatory), number of syllable repetitions in the alternating motion rate task (articulatory), nasal airflow (resonatory), maximum fundamental frequency (phonatory), and speech pauses (respiratory). The model accounted for 95.6% of the variance in intelligibility, among which the articulatory predictors showed the most substantial independent contribution (57.7%). Conclusion Articulatory impairments characterized by reduced velocities of lip and jaw movements and resonatory impairments characterized by increased nasal airflow served as the subsystem predictors of the longitudinal decline of speech intelligibility in ALS. Declines in maximum performance tasks such as the alternating motion rate preceded declines in intelligibility, thus serving as early predictors of bulbar dysfunction. Following the rapid decline in speech intelligibility, a precipitous decline in maximum performance tasks subsequently occurred. PMID:27148967

  4. Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

    Science.gov (United States)

    Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

    2016-01-01

    The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well. PMID:26861345

  5. Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges.

    Science.gov (United States)

    Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

    2016-02-06

    The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

  6. Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

    Directory of Open Access Journals (Sweden)

    Yuanfang Chen

    2016-02-01

    Full Text Available The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases is an important research issue in the industrial applications of the Internet of Things (IoT. An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

  7. [Remote intelligent Brunnstrom assessment system for upper limb rehabilitation for post-stroke based on extreme learning machine].

    Science.gov (United States)

    Wang, Yue; Yu, Lei; Fu, Jianming; Fang, Qiang

    2014-04-01

    In order to realize an individualized and specialized rehabilitation assessment of remoteness and intelligence, we set up a remote intelligent assessment system of upper limb movement function of post-stroke patients during rehabilitation. By using the remote rehabilitation training sensors and client data sampling software, we collected and uploaded the gesture data from a patient's forearm and upper arm during rehabilitation training to database of the server. Then a remote intelligent assessment system, which had been developed based on the extreme learning machine (ELM) algorithm and Brunnstrom stage assessment standard, was used to evaluate the gesture data. To evaluate the reliability of the proposed method, a group of 23 stroke patients, whose upper limb movement functions were in different recovery stages, and 4 healthy people, whose upper limb movement functions were normal, were recruited to finish the same training task. The results showed that, compared to that of the experienced rehabilitation expert who used the Brunnstrom stage standard table, the accuracy of the proposed remote Brunnstrom intelligent assessment system can reach a higher level, as 92.1%. The practical effects of surgery have proved that the proposed system could realize the intelligent assessment of upper limb movement function of post-stroke patients remotely, and it could also make the rehabilitation of the post-stroke patients at home or in a community care center possible.

  8. The Effectiveness of learning materials based on multiple intelligence on the understanding of global warming

    Science.gov (United States)

    Liliawati, W.; Purwanto; Zulfikar, A.; Kamal, R. N.

    2018-05-01

    This study aims to examine the effectiveness of the use of teaching materials based on multiple intelligences on the understanding of high school students’ material on the theme of global warming. The research method used is static-group pretest-posttest design. Participants of the study were 60 high school students of XI class in one of the high schools in Bandung. Participants were divided into two classes of 30 students each for the experimental class and control class. The experimental class uses compound-based teaching materials while the experimental class does not use a compound intelligence-based teaching material. The instrument used is a test of understanding of the concept of global warming with multiple choices form amounted to 15 questions and 5 essay items. The test is given before and after it is applied to both classes. Data analysis using N-gain and effect size. The results obtained that the N-gain for both classes is in the medium category and the effectiveness of the use of teaching materials based on the results of effect-size test results obtained in the high category.

  9. Intelligent Security IT System for Detecting Intruders Based on Received Signal Strength Indicators

    Directory of Open Access Journals (Sweden)

    Yunsick Sung

    2016-10-01

    Full Text Available Given that entropy-based IT technology has been applied in homes, office buildings and elsewhere for IT security systems, diverse kinds of intelligent services are currently provided. In particular, IT security systems have become more robust and varied. However, access control systems still depend on tags held by building entrants. Since tags can be obtained by intruders, an approach to counter the disadvantages of tags is required. For example, it is possible to track the movement of tags in intelligent buildings in order to detect intruders. Therefore, each tag owner can be judged by analyzing the movements of their tags. This paper proposes a security approach based on the received signal strength indicators (RSSIs of beacon-based tags to detect intruders. The normal RSSI patterns of moving entrants are obtained and analyzed. Intruders can be detected when abnormal RSSIs are measured in comparison to normal RSSI patterns. In the experiments, one normal and one abnormal scenario are defined for collecting the RSSIs of a Bluetooth-based beacon in order to validate the proposed method. When the RSSIs of both scenarios are compared to pre-collected RSSIs, the RSSIs of the abnormal scenario are about 61% more different compared to the RSSIs of the normal scenario. Therefore, intruders in buildings can be detected by considering RSSI differences.

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

    Science.gov (United States)

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

    2018-05-01

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

  11. Artificial intelligence-based speed control of DTC induction motor drives - A comparative study

    Energy Technology Data Exchange (ETDEWEB)

    Gadoue, S.M.; Giaouris, D.; Finch, J.W. [School of Electrical, Electronic and Computer Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

    2009-01-15

    The design of the speed controller greatly affects the performance of an electric drive. A common strategy to control an induction machine is to use direct torque control combined with a PI speed controller. These schemes require proper and continuous tuning and therefore adaptive controllers are proposed to replace conventional PI controllers to improve the drive's performance. This paper presents a comparison between four different speed controller design strategies based on artificial intelligence techniques; two are based on tuning of conventional PI controllers, the third makes use of a fuzzy logic controller and the last is based on hybrid fuzzy sliding mode control theory. To provide a numerical comparison between different controllers, a performance index based on speed error is assigned. All methods are applied to the direct torque control scheme and each control strategy has been tested for its robustness and disturbance rejection ability. (author)

  12. 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)

  13. Intelligent IPv6 based iot network monitoring and altering system on ...

    African Journals Online (AJOL)

    Intelligent IPv6 based iot network monitoring and altering system on Cooja framework. ... Journal of Fundamental and Applied Sciences. Journal Home · ABOUT THIS ... Keywords: IoT; Cooja framework; Contiki OS; packet monitoring.

  14. Intelligent vehicle based traffic monitoring – exploring application in South Africa

    CSIR Research Space (South Africa)

    Labuschagne, FJJ

    2010-08-01

    Full Text Available The paper details the anticipated benefits of an intelligent vehicle based traffic monitoring approach holds. The approach utilises advanced technology with the potential to reduce crashes and includes the monitor of vehicle speeds and flows...

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

    Science.gov (United States)

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

    2018-03-01

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

  16. 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.

  17. Security analysis - from analytical methods to intelligent systems

    Energy Technology Data Exchange (ETDEWEB)

    Lambert-Torres, G; Silva, A.P. Alves da; Ferreira, C [Escola Federal de Engenharia de Itajuba, MG (Brazil); Mattos dos Reis, L O [Taubate Univ., SP (Brazil)

    1994-12-31

    This paper presents an alternative approach to Security Analysis based on Artificial Neural Network (ANN) techniques. This new technique tries to imitate the human brain and is based on neurons and synopses. A critical review of the ANN used in Power System Operation problem solving is made, while structures to solve the Security Analysis problems are proposed. (author) 7 refs., 4 figs.

  18. Three IQs of AI Systems and their Testing Methods

    OpenAIRE

    Liu, Feng; Shi, Yong; Liu, Ying

    2017-01-01

    The rapid development of artificial intelligence has brought the artificial intelligence threat theory as well as the problem about how to evaluate the intelligence level of intelligent products. Both need to find a quantitative method to evaluate the intelligence level of intelligence systems, including human intelligence. Based on the standard intelligence system and the extended Von Neumann architecture, this paper proposes General IQ, Service IQ and Value IQ evaluation methods for intelli...

  19. Challenges facing the distribution of an artificial-intelligence-based system for nursing.

    Science.gov (United States)

    Evans, S

    1985-04-01

    The marketing and successful distribution of artificial-intelligence-based decision-support systems for nursing face special barriers and challenges. Issues that must be confronted arise particularly from the present culture of the nursing profession as well as the typical organizational structures in which nurses predominantly work. Generalizations in the literature based on the limited experience of physician-oriented artificial intelligence applications (predominantly in diagnosis and pharmacologic treatment) must be modified for applicability to other health professions.

  20. Network-based modeling and intelligent data mining of social media for improving care.

    Science.gov (United States)

    Akay, Altug; Dragomir, Andrei; Erlandsson, Bjorn-Erik

    2015-01-01

    Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative sentiment, as well as the side effects of treatment, in users' forum posts, and identifies user communities (modules) and influential users for the purpose of ascertaining user opinion of cancer treatment. We used a self-organizing map to analyze word frequency data derived from users' forum posts. We then introduced a novel network-based approach for modeling users' forum interactions and employed a network partitioning method based on optimizing a stability quality measure. This allowed us to determine consumer opinion and identify influential users within the retrieved modules using information derived from both word-frequency data and network-based properties. Our approach can expand research into intelligently mining social media data for consumer opinion of various treatments to provide rapid, up-to-date information for the pharmaceutical industry, hospitals, and medical staff, on the effectiveness (or ineffectiveness) of future treatments.

  1. Informatics in radiology: automated Web-based graphical dashboard for radiology operational business intelligence.

    Science.gov (United States)

    Nagy, Paul G; Warnock, Max J; Daly, Mark; Toland, Christopher; Meenan, Christopher D; Mezrich, Reuben S

    2009-11-01

    Radiology departments today are faced with many challenges to improve operational efficiency, performance, and quality. Many organizations rely on antiquated, paper-based methods to review their historical performance and understand their operations. With increased workloads, geographically dispersed image acquisition and reading sites, and rapidly changing technologies, this approach is increasingly untenable. A Web-based dashboard was constructed to automate the extraction, processing, and display of indicators and thereby provide useful and current data for twice-monthly departmental operational meetings. The feasibility of extracting specific metrics from clinical information systems was evaluated as part of a longer-term effort to build a radiology business intelligence architecture. Operational data were extracted from clinical information systems and stored in a centralized data warehouse. Higher-level analytics were performed on the centralized data, a process that generated indicators in a dynamic Web-based graphical environment that proved valuable in discussion and root cause analysis. Results aggregated over a 24-month period since implementation suggest that this operational business intelligence reporting system has provided significant data for driving more effective management decisions to improve productivity, performance, and quality of service in the department.

  2. A test sheet generating algorithm based on intelligent genetic algorithm and hierarchical planning

    Science.gov (United States)

    Gu, Peipei; Niu, Zhendong; Chen, Xuting; Chen, Wei

    2013-03-01

    In recent years, computer-based testing has become an effective method to evaluate students' overall learning progress so that appropriate guiding strategies can be recommended. Research has been done to develop intelligent test assembling systems which can automatically generate test sheets based on given parameters of test items. A good multisubject test sheet depends on not only the quality of the test items but also the construction of the sheet. Effective and efficient construction of test sheets according to multiple subjects and criteria is a challenging problem. In this paper, a multi-subject test sheet generation problem is formulated and a test sheet generating approach based on intelligent genetic algorithm and hierarchical planning (GAHP) is proposed to tackle this problem. The proposed approach utilizes hierarchical planning to simplify the multi-subject testing problem and adopts genetic algorithm to process the layered criteria, enabling the construction of good test sheets according to multiple test item requirements. Experiments are conducted and the results show that the proposed approach is capable of effectively generating multi-subject test sheets that meet specified requirements and achieve good performance.

  3. An intelligent switch with back-propagation neural network based hybrid power system

    Science.gov (United States)

    Perdana, R. H. Y.; Fibriana, F.

    2018-03-01

    The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

  4. Visual and intelligent transients and accidents analyzer based on thermal-hydraulic system code

    International Nuclear Information System (INIS)

    Meng Lin; Rui Hu; Yun Su; Ronghua Zhang; Yanhua Yang

    2005-01-01

    Full text of publication follows: Many thermal-hydraulic system codes were developed in the past twenty years, such as RELAP5, RETRAN, ATHLET, etc. Because of their general and advanced features in thermal-hydraulic computation, they are widely used in the world to analyze transients and accidents. But there are following disadvantages for most of these original thermal-hydraulic system codes. Firstly, because models are built through input decks, so the input files are complex and non-figurative, and the style of input decks is various for different users and models. Secondly, results are shown in off-line data file form. It is not convenient for analysts who may pay more attention to dynamic parameters trend and changing. Thirdly, there are few interfaces with other program in these original thermal-hydraulic system codes. This restricts the codes expanding. The subject of this paper is to develop a powerful analyzer based on these thermal-hydraulic system codes to analyze transients and accidents more simply, accurately and fleetly. Firstly, modeling is visual and intelligent. Users build the thermalhydraulic system model using component objects according to their needs, and it is not necessary for them to face bald input decks. The style of input decks created automatically by the analyzer is unified and can be accepted easily by other people. Secondly, parameters concerned by analyst can be dynamically communicated to show or even change. Thirdly, the analyzer provide interface with other programs for the thermal-hydraulic system code. Thus parallel computation between thermal-hydraulic system code and other programs become possible. In conclusion, through visual and intelligent method, the analyzer based on general and advanced thermal-hydraulic system codes can be used to analysis transients and accidents more effectively. The main purpose of this paper is to present developmental activities, assessment and application results of the visual and intelligent

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

    Directory of Open Access Journals (Sweden)

    Salman Afan

    2014-03-01

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

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

    Science.gov (United States)

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

    2009-08-01

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

  7. Design and realization of intelligent tourism service system based on voice interaction

    Science.gov (United States)

    Hu, Lei-di; Long, Yi; Qian, Cheng-yang; Zhang, Ling; Lv, Guo-nian

    2008-10-01

    Voice technology is one of the important contents to improve the intelligence and humanization of tourism service system. Combining voice technology, the paper concentrates on application needs and the composition of system to present an overall intelligent tourism service system's framework consisting of presentation layer, Web services layer, and tourism application service layer. On the basis, the paper further elaborated the implementation of the system and its key technologies, including intelligent voice interactive technology, seamless integration technology of multiple data sources, location-perception-based guides' services technology, and tourism safety control technology. Finally, according to the situation of Nanjing tourism, a prototype of Tourism Services System is realized.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Abdul Kadir Ritonga

    2017-01-01

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

  10. Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

    CERN Document Server

    Khan, Samee; Burczy´nski, Tadeusz

    2012-01-01

    One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

  11. Simulation Study of Swarm Intelligence Based on Life Evolution Behavior

    Directory of Open Access Journals (Sweden)

    Yanmin Liu

    2015-01-01

    Full Text Available Swarm intelligence (SI is a new evolutionary computation technology, and its performance efficacy is usually affected by each individual behavior in the swarm. According to the genetic and sociological theory, the life evolution behavior process is influenced by the external and internal factors, so the mechanisms of external and internal environment change must be analyzed and explored. Therefore, in this paper, we used the thought of the famous American genetic biologist Morgan, “life = DNA + environment + interaction of environment + gene,” to propose the mutation and crossover operation of DNA fragments by the environmental change to improve the performance efficiency of intelligence algorithms. Additionally, PSO is a random swarm intelligence algorithm with the genetic and sociological property, so we embed the improved mutation and crossover operation to particle swarm optimization (PSO and designed DNA-PSO algorithm to optimize single and multiobjective optimization problems. Simulation experiments in single and multiobjective optimization problems show that the proposed strategies can effectively improve the performance of swarm intelligence.

  12. Improving General Intelligence with a Nutrient-Based Pharmacological Intervention

    Science.gov (United States)

    Stough, Con; Camfield, David; Kure, Christina; Tarasuik, Joanne; Downey, Luke; Lloyd, Jenny; Zangara, Andrea; Scholey, Andrew; Reynolds, Josh

    2011-01-01

    Cognitive enhancing substances such as amphetamine and modafinil have become popular in recent years to improve acute cognitive performance particularly in environments in which enhanced cognition or intelligence is required. Nutraceutical nootropics, which are natural substances that have the ability to bring about acute or chronic changes in…

  13. Artificial intelligence based decision support for trumpeter swan management

    Science.gov (United States)

    Sojda, Richard S.

    2002-01-01

    The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

  14. Fast DCNN based on FWT, intelligent dropout and layer skipping for image retrieval.

    Science.gov (United States)

    ElAdel, Asma; Zaied, Mourad; Amar, Chokri Ben

    2017-11-01

    Deep Convolutional Neural Network (DCNN) can be marked as a powerful tool for object and image classification and retrieval. However, the training stage of such networks is highly consuming in terms of storage space and time. Also, the optimization is still a challenging subject. In this paper, we propose a fast DCNN based on Fast Wavelet Transform (FWT), intelligent dropout and layer skipping. The proposed approach led to improve the image retrieval accuracy as well as the searching time. This was possible thanks to three key advantages: First, the rapid way to compute the features using FWT. Second, the proposed intelligent dropout method is based on whether or not a unit is efficiently and not randomly selected. Third, it is possible to classify the image using efficient units of earlier layer(s) and skipping all the subsequent hidden layers directly to the output layer. Our experiments were performed on CIFAR-10 and MNIST datasets and the obtained results are very promising. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. LEARNING STYLES BASED ADAPTIVE INTELLIGENT TUTORING SYSTEMS: DOCUMENT ANALYSIS OF ARTICLES PUBLISHED BETWEEN 2001. AND 2016.

    Directory of Open Access Journals (Sweden)

    Amit Kumar

    2017-12-01

    Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

  16. Identification of Age, Temperature and Radiation Effect on Ferritic Steel Microstructure Based on Artificial Intelligence

    International Nuclear Information System (INIS)

    Mike Susmikanti; Entin Hartini; Antonius Sitompul

    2008-01-01

    In the construction of nuclear installation, it is important to know the material condition used on it. Considering mechanical properties of these materials, there are some material change affected by ageing, temperature and radiation. For some years, austenitic stainless steel are used as a fuel cladding in fast breeder reactor. However this material will not sufficiently competitive from economic point of view for the next year. Experiment result on ferritic steel gave information of stronger structural properties compared to austenitic stainless steel. Modeling and simulation will support further identification of this material changing caused by such effects. Pattern recognition of these changes base on artificial intelligence is expected to support the research and development activities on nuclear structure materials. Material structure pattern of these materials, observed by SEM, are converted using image processing system. Its characteristic is then analyzed with principal component using perception method, which usually used on identifying and learning neural network system based on artificial intelligence. Specific design and input are needed to identify the change of material structure pattern before and after any applied effect. In this paper, simulation of changing identification on three types ferritic steel F17(17 Cr), EM 12 (9 CR-2 MoNbV), and EMI 0 (9 Cr-I Mo) were done. The microstructure data before and after effect are taken from some references. The whole pattern recognition process are done using MATLAB software package. (author)

  17. An intelligent anticorrosion coating based on pH-responsive supramolecular nanocontainers

    International Nuclear Information System (INIS)

    Chen Tao; Fu Jiajun

    2012-01-01

    The hollow mesoporous silica nanoparticles (HMSNs), which have been used as the nanocontainers for the corrosion inhibitor, benzotriazole, were fabricated using the hard-template method. Alkaline-responsive HMSNs based on cucurbit[6]uril (CB[6])/bisammonium supramolecular complex and acid-responsive HMSNs based on α-cyclodextrin (α-CD)/aniline supramolecular complex, which operate in water, have been achieved and characterized by solid-state NMR, thermogravimetry analysis, scanning electron microscopy, transmission electron microscopy and N 2 adsorption-desorption analysis. The two elaborately designed nanocontainers show the pH-controlled encapsulation/release behaviors for benzotriazole molecules. Equal amounts of the alkaline- and acid-responsive nanocontainers were uniformly distributed in the hybrid zirconia-silica sol–gel coating and thus formed the intelligent anticorrosion coating. The self-healing property of AA2024 alloy coated with the intelligent anticorrosion coating is evaluated by electrochemical impedance spectroscopy (EIS). The sol–gel coating doped with the pH-responsive nanocontainers clearly demonstrates long-term corrosion protection performances when compared to the undoped sol–gel coating, which is attributed to the release of corrosion inhibitor from the nanocontainers after feeling the changes of environmental pH values near the corroded areas. (paper)

  18. 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...

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

    Science.gov (United States)

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

    2018-02-07

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

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

    Science.gov (United States)

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

    2018-04-01

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

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

    CERN Document Server

    Marwala, Tshilidzi

    2012-01-01

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

  2. Assessing the accuracy of perceptions of intelligence based on heritable facial features

    OpenAIRE

    Lee, Anthony J.; Hibbs, Courtney; Wright, Margaret J.; Martin, Nicholas G.; Keller, Matthew C.; Zietsch, Brendan P.

    2017-01-01

    Perceptions of intelligence based on facial features can have a profound impact on many social situations, but findings have been mixed as to whether these judgements are accurate. Even if such perceptions were accurate, the underlying mechanism is unclear. Several possibilities have been proposed, including evolutionary explanations where certain morphological facial features are associated with fitness-related traits (including cognitive development), or that intelligence judgements are ove...

  3. Intelligent harmonic load model based on neural networks

    Science.gov (United States)

    Ji, Pyeong-Shik; Lee, Dae-Jong; Lee, Jong-Pil; Park, Jae-Won; Lim, Jae-Yoon

    2007-12-01

    In this study, we developed a RBFNs(Radial Basis Function Networks) based load modeling method with harmonic components. The developed method implemented by using harmonic information as well as fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. The RBFNs have certain advantage such as simple structure and rapid computation ability compared with multilayer perceptron which is extensively applied for load modeling. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with conventional methods such as polynominal 2nd equation method, MLP and RBF without considering harmonic components.

  4. Study on robot motion control for intelligent welding processes based on the laser tracking sensor

    Science.gov (United States)

    Zhang, Bin; Wang, Qian; Tang, Chen; Wang, Ju

    2017-06-01

    A robot motion control method is presented for intelligent welding processes of complex spatial free-form curve seams based on the laser tracking sensor. First, calculate the tip position of the welding torch according to the velocity of the torch and the seam trajectory detected by the sensor. Then, search the optimal pose of the torch under constraints using genetic algorithms. As a result, the intersection point of the weld seam and the laser plane of the sensor is within the detectable range of the sensor. Meanwhile, the angle between the axis of the welding torch and the tangent of the weld seam meets the requirements. The feasibility of the control method is proved by simulation.

  5. Long Term Solar Radiation Forecast Using Computational Intelligence Methods

    Directory of Open Access Journals (Sweden)

    João Paulo Coelho

    2014-01-01

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

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

    Science.gov (United States)

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

    2009-09-01

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

  7. 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

  8. 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

  9. 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)

  10. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    Directory of Open Access Journals (Sweden)

    Daniel-Petru GHENCEA

    2017-06-01

    Full Text Available The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic. The paper presents a prediction mode obtaining valid range of values for spindles with similar characteristics based on measured data sets from a few spindles test without additional measures being required. Extracting polynomial functions of graphs resulting from simultaneous measurements and predict the dynamics of the two features with multi-objective criterion is the main advantage of this method.

  11. Intelligent Lighting Control System

    OpenAIRE

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

    2014-01-01

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

  12. Development opportunities of emotional intelligence with reflective strategies using video-based training

    Directory of Open Access Journals (Sweden)

    Andrea Pokorná

    2015-12-01

    Full Text Available Background: Within nursing, Emotional intelligence (EI means the ability of nurses or nursing students to understand not only their own feelings and reactions, but also, and more importantly, the feelings and reactions of the patients in their care. EI plays an important part in forming successful human relationships as a part of emotional labour. Emotional labour is important in establishing therapeutic nurse–patient relationships but carries the risk of ‘burnout’ if prolonged or intense. Objective/Purpose: The assessment of students' views and perceptions of video-based training as an opportunity to develop emotional intelligence. Material and methods: Data about the video-based training in relation to EI were collected, after the completion of the reflection assignments, using semi-structured interviews and reflective sheets (ALACT model /acronym of the basic phases and steps/ - Action, Looking back on the action, Awareness of essential aspects, Creating alternative methods of action, Trial. The study included 46 students in total (post-graduate student Intensive care nurses in two sequential academic years (2012/13 n = 15 and 2013/14 n = 31. Results: The results showed that students in both cohorts considered video as an effective tool for carrying out self-evaluations and development of EI. The usefulness of video and peer-feedback for other reflection processes differed in students' view. Most students (80% appreciated the opportunity of viewing some unusual situations from clinical practice and appropriate ways of communicating. Some students (17% stated that they needed more time for similar teaching activities. Conclusion: 80% of all the students considered video-based training generally useful for all the reflection processes and improvement of EI; however they also indicated some limitations (i.e. time consuming teaching method. The study demonstrated that student-centric pedagogies and reflective activities on student learning

  13. Multimodal Detection of Music Performances for Intelligent Emotion Based Lighting

    DEFF Research Database (Denmark)

    Bonde, Esben Oxholm Skjødt; Hansen, Ellen Kathrine; Triantafyllidis, Georgios

    2016-01-01

    Playing music is about conveying emotions and the lighting at a concert can help do that. However, new and unknown bands that play at smaller venues and bands that don’t have the budget to hire a dedicated light technician have to miss out on lighting that will help them to convey the emotions...... of what they play. In this paper it is investigated whether it is possible or not to develop an intelligent system that through a multimodal input detects the intended emotions of the played music and in realtime adjusts the lighting accordingly. A concept for such an intelligent lighting system...... is developed and described. Through existing research on music and emotion, as well as on musicians’ body movements related to the emotion they want to convey, a row of cues is defined. This includes amount, speed, fluency and regularity for the visual and level, tempo, articulation and timbre for the auditory...

  14. Research Algorithm on Building Intelligent Transportation System based on RFID Technology

    Directory of Open Access Journals (Sweden)

    Chuanqi Chen

    2013-05-01

    Full Text Available Intelligent transportation system to all aspects of organic integration of human, vehicle, road and environment of the transport system, so that the operation of functional integration and intelligent vehicle, road. Intelligent transportation system (ITS to improve the efficiency of traffic system by increasing the effective use and management of traffic information is mainly composed of information collection and input, output, control strategy, implementation of the subsystems of data transmission and communication subsystem. The RFID reader to wireless communication through the antenna and RFID tag can achieve a write operation on the tag identification codes and memory read data. The paper proposes research on building intelligent transportation system based on RFID technology. Experimental results show that ITS system can effectively improve the traffic situation, improve the utilization rate of the existing road resource and save social cost.

  15. Activity-Based Intelligence prevedere il futuro osservando il presente con gli strumenti Hexagon Geospatial

    Directory of Open Access Journals (Sweden)

    Massimo Zotti

    2015-06-01

    Full Text Available The intelligence of human activities on the earth's surface, obtained through the analysis of earth observation data and other geospatial information, is vital for the planning and execution of any military action, for peacekeeping or for humanitarian emergencies. The success of these actions largely depends on the ability to analyze timely data from multiple sources. However, the proliferation of new sources of intelligence in a Geospatial big data scenario increasingly complicate the analysis of such activities by human analysts. Modern technologies solve these problems by enabling the Activity Based Intelligence, a methodology that improves the efficiency and timeliness of intelligence through the analysis of historical, current and future activity, to identify patterns, trends and relationships hidden in large data collections from different sources.

  16. Artificial intelligence-based modeling and control of fluidized bed combustion

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, E.; Leppaekoski, K. (Univ. of Oulu, Dept. of Process and Environmental Engineering (Finland)). email: enso.ikonen@oulu.fi

    2009-07-01

    AI-inspired techniques have a lot to offer when developing methods for advanced identification, monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory, e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions. Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vaguenesses in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising

  17. Simulation Study of Swarm Intelligence Based on Life Evolution Behavior

    OpenAIRE

    Yanmin Liu; Ying Bi; Changling Sui; Yuanfeng Luo; Zhuanzhou Zhang; Rui Liu

    2015-01-01

    Swarm intelligence (SI) is a new evolutionary computation technology, and its performance efficacy is usually affected by each individual behavior in the swarm. According to the genetic and sociological theory, the life evolution behavior process is influenced by the external and internal factors, so the mechanisms of external and internal environment change must be analyzed and explored. Therefore, in this paper, we used the thought of the famous American genetic biologist Morgan, “life = DN...

  18. Neuro-Based Artificial Intelligence Model for Loan Decisions

    OpenAIRE

    Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

    2010-01-01

    Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpr...

  19. Artificial intelligence based models for stream-flow forecasting: 2000-2015

    Science.gov (United States)

    Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

    2015-11-01

    The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

  20. Research on application of intelligent computation based LUCC model in urbanization process

    Science.gov (United States)

    Chen, Zemin

    2007-06-01

    Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents

  1. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

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

  2. 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

  3. Prediction of speech intelligibility based on a correlation metric in the envelope power spectrum domain

    DEFF Research Database (Denmark)

    Relano-Iborra, Helia; May, Tobias; Zaar, Johannes

    A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speechbased envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envel...

  4. The Use of Artificial-Intelligence-Based Ensembles for Intrusion Detection: A Review

    Directory of Open Access Journals (Sweden)

    Gulshan Kumar

    2012-01-01

    Full Text Available In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI- based techniques play prominent role in development of ensemble for intrusion detection (ID and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1 architecture & approach followed; (2 different methods utilized in different phases of ensemble learning; (3 other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs.

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

    Directory of Open Access Journals (Sweden)

    Олександр Павлович Кіркін

    2017-06-01

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

  6. Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

    Science.gov (United States)

    Winda, A.; Sofyan; Sthevany; Vincent, R. S.

    2017-12-01

    Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

  7. Design and research of intelligent mobile robot environment detection system based on multi-sensor technology

    International Nuclear Information System (INIS)

    Chen Yu; Wen Xinling

    2007-01-01

    The intelligent mobile robot environment detection system is researched based on SCM MC68HC908GP3 as core of control system. The four groups of detection systems constituted by ultrasonic sensors and infrared sensors gather information of forward, behind, left and right different directions, solve the problem of blind spot, and make up each other shortage. The distance measurement precision is improved rapidly and the detection precision is less than ±1% through using the way of the pulse shooting, the signal chooses circuit, and the temperature compensation. The system design method and the hardware circuit are introduced in detail. Simultaneity, the system adopts the single chip control technology, it makes the system possess favorable expansibility and gains the practicability in engineering field. (authors)

  8. A Privacy-Preserving Intelligent Medical Diagnosis System Based on Oblivious Keyword Search

    Directory of Open Access Journals (Sweden)

    Zhaowen Lin

    2017-01-01

    Full Text Available One of the concerns people have is how to get the diagnosis online without privacy being jeopardized. In this paper, we propose a privacy-preserving intelligent medical diagnosis system (IMDS, which can efficiently solve the problem. In IMDS, users submit their health examination parameters to the server in a protected form; this submitting process is based on Paillier cryptosystem and will not reveal any information about their data. And then the server retrieves the most likely disease (or multiple diseases from the database and returns it to the users. In the above search process, we use the oblivious keyword search (OKS as a basic framework, which makes the server maintain the computational ability but cannot learn any personal information over the data of users. Besides, this paper also provides a preprocessing method for data stored in the server, to make our protocol more efficient.

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

    Directory of Open Access Journals (Sweden)

    Z. Jančíková

    2008-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Jungtaek Seo

    2012-08-01

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

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

    Science.gov (United States)

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

    2017-02-01

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

  12. Wearable sensors in intelligent clothing for measuring human body temperature based on optical fiber Bragg grating.

    Science.gov (United States)

    Li, Hongqiang; Yang, Haijing; Li, Enbang; Liu, Zhihui; Wei, Kejia

    2012-05-21

    Measuring body temperature is considerably important to physiological studies as well as clinical investigations. In recent years, numerous observations have been reported and various methods of measurement have been employed. The present paper introduces a novel wearable sensor in intelligent clothing for human body temperature measurement. The objective is the integration of optical fiber Bragg grating (FBG)-based sensors into functional textiles to extend the capabilities of wearable solutions for body temperature monitoring. In addition, the temperature sensitivity is 150 pm/°C, which is almost 15 times higher than that of a bare FBG. This study combines large and small pipes during fabrication to implant FBG sensors into the fabric. The law of energy conservation of the human body is considered in determining heat transfer between the body and its clothing. The mathematical model of heat transmission between the body and clothed FBG sensors is studied, and the steady-state thermal analysis is presented. The simulation results show the capability of the material to correct the actual body temperature. Based on the skin temperature obtained by the weighted average method, this paper presents the five points weighted coefficients model using both sides of the chest, armpits, and the upper back for the intelligent clothing. The weighted coefficients of 0.0826 for the left chest, 0.3706 for the left armpit, 0.3706 for the right armpit, 0.0936 for the upper back, and 0.0826 for the right chest were obtained using Cramer's Rule. Using the weighting coefficient, the deviation of the experimental result was ± 0.18 °C, which favors the use for clinical armpit temperature monitoring. Moreover, in special cases when several FBG sensors are broken, the weighted coefficients of the other sensors could be changed to obtain accurate body temperature.

  13. Intelligence Control System for Landfills Based on Wireless Sensor Network

    Science.gov (United States)

    Zhang, Qian; Huang, Chuan; Gong, Jian

    2018-06-01

    This paper put forward an intelligence system for controlling the landfill gas in landfills to make the landfill gas (LFG) exhaust controllably and actively. The system, which is assigned by the wireless sensor network, were developed and supervised by remote applications in workshop instead of manual work. An automatic valve control depending on the sensor units embedded is installed in tube, the air pressure and concentration of LFG are detected to decide the level of the valve switch. The paper also proposed a modified algorithm to solve transmission problem, so that the system can keep a high efficiency and long service life.

  14. Intelligent Agent Based Traffic Signal Control on Isolated Intersections

    Directory of Open Access Journals (Sweden)

    Daniela Koltovska

    2014-08-01

    Full Text Available The purpose of this paper is to develop an adaptive signal control strategy on isolated urban intersections. An innovative approach to defining the set of states dependent on the actual and primarily observed parameters has been introduced. ?he Q–learning algorithm has been applied. The developed self-learning adaptive signal strategy has been tested on a re?l intersection. The intelligent agent results have been compared to those in cases of fixed-time and actuated control. Regarding the average total delay, the total number of stops and the total throughput, the best results have been obtained for unknown traffic demand and over-capacity.

  15. Intelligence Control System for Landfills Based on Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Zhang Qian

    2018-01-01

    Full Text Available This paper put forward an intelligence system for controlling the landfill gas in landfills to make the landfill gas (LFG exhaust controllably and actively. The system, which is assigned by the wireless sensor network, were developed and supervised by remote applications in workshop instead of manual work. An automatic valve control depending on the sensor units embedded is installed in tube, the air pressure and concentration of LFG are detected to decide the level of the valve switch. The paper also proposed a modified algorithm to solve transmission problem, so that the system can keep a high efficiency and long service life.

  16. Artificial Intelligence in Civil Engineering

    Directory of Open Access Journals (Sweden)

    Pengzhen Lu

    2012-01-01

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

  17. Intelligent fault recognition strategy based on adaptive optimized multiple centers

    Science.gov (United States)

    Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

    2018-06-01

    For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

  18. Artificial intelligence-based condition monitoring for practical electrical drives

    OpenAIRE

    Ashari, Djoni; Pislaru, Crinela; Ball, Andrew; Gu, Fengshou

    2012-01-01

    The main types of existing Condition Monitoring methods (MCSA, GA, IAS) for electrical drives are\\ud described. Then the steps for the design of expert systems are presented: problem identification and analysis, system specification, development tool selection, knowledge based, prototyping and testing. The employment of SOMA (Self-Organizing Migrating Algorithm) used for the optimization of ambient\\ud vibration energy harvesting is analyzed. The power electronics devices are becoming smaller ...

  19. Simulation-Based Cryosurgery Intelligent Tutoring System Prototype.

    Science.gov (United States)

    Sehrawat, Anjali; Keelan, Robert; Shimada, Kenji; Wilfong, Dona M; McCormick, James T; Rabin, Yoed

    2016-04-01

    As a part of an ongoing effort to develop computerized training tools for cryosurgery, the current study presents a proof of concept for a computerized tool for cryosurgery tutoring. The tutoring system lists geometrical constraints of cryoprobes placement, simulates cryoprobe insertion, displays a rendered shape of the prostate, enables distance measurements, simulates the corresponding thermal history, and evaluates the mismatch between the target region shape and a preselected planning isotherm. The quality of trainee planning is measured in comparison with a computer-generated planning, created for each case study by previously developed planning algorithms. The following two versions of the tutoring system have been tested in the current study: (1) an unguided version, where the trainee can practice cases in unstructured sessions and (2) an intelligent tutoring system, which forces the trainee to follow specific steps, believed by the authors to potentially shorten the learning curve. Although the tutoring level in this study aims only at geometrical constraints on cryoprobe placement and the resulting thermal histories, it creates a unique opportunity to gain insight into the process outside the operation room. Post-test results indicate that the intelligent tutoring system may be more beneficial than the nonintelligent tutoring system, but the proof of concept is demonstrated with either system. © The Author(s) 2015.

  20. A systematic profile/feature-based intelligence for spectral sensors

    International Nuclear Information System (INIS)

    Vogt, M.C.

    2000-01-01

    Argonne National Laboratory (ANL) has been creating a special-purpose software-engineering tool to support research and development of spectrum-output-type [chemical] sensors. The modular software system is called SAGE, the Sensor Algorithm Generation Environment and includes general-purpose signal conditioning algorithms (GP/SAGE) as well as intelligent classifiers, pattern recognizes, response accelerators, and sensitivity analyzers. GP/SAGE is an implementation of an approach for delivering a level of encapsulated intelligence to a wide range of sensors and instruments. It capitalizes on the genene classification and analysis needed to process most profile-type data. The GP/SAGE native data format is a generalized one-dimensional vector, signature, or spectrum. GP/SAGE modules form a computer-aided software engineering (CASE) workbench where users can experiment with various conditioning, filtering, and pattern recognition stages, then automatically generate final algorithm source code for data acquisition and analysis systems. SAGE was designed to free the [chemical] sensor developer from the signal processing allowing them to focus on understanding and improving the basic sensing mechanisms. The SAGE system's strength is its creative application of advanced neural computing techniques to response-vector and response-surface data, affording new insight and perspectives with regard to phenomena being studied for sensor development

  1. Intelligent Online Store: User Behavior Analysis based Recommender System

    Directory of Open Access Journals (Sweden)

    Mohamadreza Karimi Alavije

    2015-06-01

    Full Text Available Recommender systems provide personalised recommendations to users, helping them find their ideal items, also play a key role in encouraging users to make their purchases through websites thus leading to the success of online stores. The collaborative filtering method is one of the most successful techniques utilized in these systems facilitating the provision of recommendations close to that of the customer's taste and need. However the proliferation of both customers and products on offer, the technique faces some issues such as "cold start" and scalability. As such in this paper a new method has been introduced in which user-based collaborative filtering is used at a base method along with a weighted clustering of users based upon demographics in order to improve the results obtained from the system. The implementation of the results of the algorithms demonstrate that the presented approach has a lower RMSE, which means that the system offers improved performance and accuracy and that the resulting recommendations are closer to the taste and preferences of the users.

  2. A Vision-Based Counting and Recognition System for Flying Insects in Intelligent Agriculture

    Directory of Open Access Journals (Sweden)

    Yuanhong Zhong

    2018-05-01

    Full Text Available Rapid and accurate counting and recognition of flying insects are of great importance, especially for pest control. Traditional manual identification and counting of flying insects is labor intensive and inefficient. In this study, a vision-based counting and classification system for flying insects is designed and implemented. The system is constructed as follows: firstly, a yellow sticky trap is installed in the surveillance area to trap flying insects and a camera is set up to collect real-time images. Then the detection and coarse counting method based on You Only Look Once (YOLO object detection, the classification method and fine counting based on Support Vector Machines (SVM using global features are designed. Finally, the insect counting and recognition system is implemented on Raspberry PI. Six species of flying insects including bee, fly, mosquito, moth, chafer and fruit fly are selected to assess the effectiveness of the system. Compared with the conventional methods, the test results show promising performance. The average counting accuracy is 92.50% and average classifying accuracy is 90.18% on Raspberry PI. The proposed system is easy-to-use and provides efficient and accurate recognition data, therefore, it can be used for intelligent agriculture applications.

  3. Artificial intelligence systems based on texture descriptors for vaccine development.

    Science.gov (United States)

    Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

    2011-02-01

    The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

  4. Installation and evaluation of a nuclear power plant operator advisor based on artificial intelligence technology

    International Nuclear Information System (INIS)

    Hajek, B.K.; Miller, D.W.

    1989-01-01

    This report discusses the following topics on a Nuclear Power Plant operator advisor based on artificial Intelligence Technology; Workstation conversion; Software Conversion; V ampersand V Program Development Development; Simulator Interface Development; Knowledge Base Expansion; Dynamic Testing; Database Conversion; Installation at the Perry Simulator; Evaluation of Operator Interaction; Design of Man-Machine Interface; and Design of Maintenance Facility

  5. Application of instrument platform based embedded Linux system on intelligent scaler

    International Nuclear Information System (INIS)

    Wang Jikun; Yang Run'an; Xia Minjian; Yang Zhijun; Li Lianfang; Yang Binhua

    2011-01-01

    It designs a instrument platform based on embedded Linux system and peripheral circuit, by designing Linux device driver and application program based on QT Embedded, various functions of the intelligent scaler are realized. The system architecture is very reasonable, so the stability and the expansibility and the integration level are increased, the development cycle is shorten greatly. (authors)

  6. Research on human physiological parameters intelligent clothing based on distributed Fiber Bragg Grating

    Science.gov (United States)

    Miao, Changyun; Shi, Boya; Li, Hongqiang

    2008-12-01

    A human physiological parameters intelligent clothing is researched with FBG sensor technology. In this paper, the principles and methods of measuring human physiological parameters including body temperature and heart rate in intelligent clothing with distributed FBG are studied, the mathematical models of human physiological parameters measurement are built; the processing method of body temperature and heart rate detection signals is presented; human physiological parameters detection module is designed, the interference signals are filtered out, and the measurement accuracy is improved; the integration of the intelligent clothing is given. The intelligent clothing can implement real-time measurement, processing, storage and output of body temperature and heart rate. It has accurate measurement, portability, low cost, real-time monitoring, and other advantages. The intelligent clothing can realize the non-contact monitoring between doctors and patients, timely find the diseases such as cancer and infectious diseases, and make patients get timely treatment. It has great significance and value for ensuring the health of the elders and the children with language dysfunction.

  7. Effects of multiple intelligences supported project-based learning on students’ achievement levels and attitudes towards English lesson

    Directory of Open Access Journals (Sweden)

    Gökhan Baş

    2007-07-01

    Full Text Available The aim of the research was to investigate the effects of multiple intelligences supported project-based learning and traditional foreign language-teaching environment on students’ achievement and their attitude towards English lesson. The research was carried out in 2009 – 2010 education-instruction year in Karatli Sehit Sahin Yilmaz Elementary School, Nigde, Turkey. Totally 50 students in two different classes in the 5th grade of this school participated in the study. The results of the research showed a significant difference between the attitude scores of the experiment group and the control group. It was also found out that the multiple intelligences approach activities were more effective in the positive development of the students’ attitudes. At the end of the research, it is revealed that the students who are educated by multiple intelligences supported project-based learning method are more successful and have a higher motivation level than the students who are educated by the traditional instructional methods.

  8. Modelling intelligent behavior

    Science.gov (United States)

    Green, H. S.; Triffet, T.

    1993-01-01

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

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

    International Nuclear Information System (INIS)

    Erdogan, A.

    2001-01-01

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

  10. Exploring the role of emotional intelligence in behavior-based safety coaching.

    Science.gov (United States)

    Wiegand, Douglas M

    2007-01-01

    Safety coaching is an applied behavior analysis technique that involves interpersonal interaction to understand and manipulate environmental conditions that are directing (i.e., antecedent to) and motivating (i.e., consequences of) safety-related behavior. A safety coach must be skilled in interacting with others so as to understand their perspectives, communicate a point clearly, and be persuasive with behavior-based feedback. This article discusses the evidence-based "ability model" of emotional intelligence and its relevance to the interpersonal aspect of the safety coaching process. Emotional intelligence has potential for improving safety-related efforts and other aspects of individuals' work and personal lives. Safety researchers and practitioners are therefore encouraged to gain an understanding of emotional intelligence and conduct and support research applying this construct toward injury prevention.

  11. 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.

  12. Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

    Directory of Open Access Journals (Sweden)

    Ajay Kumar Saxena

    2002-05-01

    Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

  13. Material quality assessment of silk nanofibers based on swarm intelligence

    Science.gov (United States)

    Brandoli Machado, Bruno; Nunes Gonçalves, Wesley; Martinez Bruno, Odemir

    2013-02-01

    In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.

  14. a Novel 3d Intelligent Fuzzy Algorithm Based on Minkowski-Clustering

    Science.gov (United States)

    Toori, S.; Esmaeily, A.

    2017-09-01

    Assessing and monitoring the state of the earth surface is a key requirement for global change research. In this paper, we propose a new consensus fuzzy clustering algorithm that is based on the Minkowski distance. This research concentrates on Tehran's vegetation mass and its changes during 29 years using remote sensing technology. The main purpose of this research is to evaluate the changes in vegetation mass using a new process by combination of intelligent NDVI fuzzy clustering and Minkowski distance operation. The dataset includes the images of Landsat8 and Landsat TM, from 1989 to 2016. For each year three images of three continuous days were used to identify vegetation impact and recovery. The result was a 3D NDVI image, with one dimension for each day NDVI. The next step was the classification procedure which is a complicated process of categorizing pixels into a finite number of separate classes, based on their data values. If a pixel satisfies a certain set of standards, the pixel is allocated to the class that corresponds to those criteria. This method is less sensitive to noise and can integrate solutions from multiple samples of data or attributes for processing data in the processing industry. The result was a fuzzy one dimensional image. This image was also computed for the next 28 years. The classification was done in both specified urban and natural park areas of Tehran. Experiments showed that our method worked better in classifying image pixels in comparison with the standard classification methods.

  15. In the Context of Multiple Intelligences Theory, Intelligent Data Analysis of Learning Styles Was Based on Rough Set Theory

    Science.gov (United States)

    Narli, Serkan; Ozgen, Kemal; Alkan, Huseyin

    2011-01-01

    The present study aims to identify the relationship between individuals' multiple intelligence areas and their learning styles with mathematical clarity using the concept of rough sets which is used in areas such as artificial intelligence, data reduction, discovery of dependencies, prediction of data significance, and generating decision…

  16. Fractured reservoir history matching improved based on artificial intelligent

    Directory of Open Access Journals (Sweden)

    Sayyed Hadi Riazi

    2016-12-01

    Full Text Available In this paper, a new robust approach based on Least Square Support Vector Machine (LSSVM as a proxy model is used for an automatic fractured reservoir history matching. The proxy model is made to model the history match objective function (mismatch values based on the history data of the field. This model is then used to minimize the objective function through Particle Swarm Optimization (PSO and Imperialist Competitive Algorithm (ICA. In automatic history matching, sensitive analysis is often performed on full simulation model. In this work, to get new range of the uncertain parameters (matching parameters in which the objective function has a minimum value, sensitivity analysis is also performed on the proxy model. By applying the modified ranges to the optimization methods, optimization of the objective function will be faster and outputs of the optimization methods (matching parameters are produced in less time and with high precision. This procedure leads to matching of history of the field in which a set of reservoir parameters is used. The final sets of parameters are then applied for the full simulation model to validate the technique. The obtained results show that the present procedure in this work is effective for history matching process due to its robust dependability and fast convergence speed. Due to high speed and need for small data sets, LSSVM is the best tool to build a proxy model. Also the comparison of PSO and ICA shows that PSO is less time-consuming and more effective.

  17. Multi-Working Modes Product-Color Planning Based on Evolutionary Algorithms and Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Man Ding

    2010-01-01

    Full Text Available In order to assist designer in color planning during product development, a novel synthesized evaluation method is presented to evaluate color-combination schemes of multi-working modes products (MMPs. The proposed evaluation method considers color-combination images in different working modes as evaluating attributes, to which the corresponding weights are assigned for synthesized evaluation. Then a mathematical model is developed to search for optimal color-combination schemes of MMP based on the proposed evaluation method and two powerful search techniques known as Evolution Algorithms (EAs and Swarm Intelligence (SI. In the experiments, we present a comparative study for two EAs, namely, Genetic Algorithm (GA and Difference Evolution (DE, and one SI algorithm, namely, Particle Swarm Optimization (PSO, on searching for color-combination schemes of MMP problem. All of the algorithms are evaluated against a test scenario, namely, an Arm-type aerial work platform, which has two working modes. The results show that the DE obtains the superior solution than the other two algorithms for color-combination scheme searching problem in terms of optimization accuracy and computation robustness. Simulation results demonstrate that the proposed method is feasible and efficient.

  18. Analysis of Students' Online Learning Readiness Based on Their Emotional Intelligence Level

    Science.gov (United States)

    Engin, Melih

    2017-01-01

    The objective of the present study is to determine whether there is a significant relationship between the students' readiness in online learning and their emotional intelligence levels. Correlational research method was used in the study. Online Learning Readiness Scale which was developed by Hung et al. (2010) has been used and Trait Emotional…

  19. Business Intelligence & Knowledge Management - Technological Support for Strategic Management in the Knowledge Based Economy

    Directory of Open Access Journals (Sweden)

    Dorel PARASCHIV

    2008-01-01

    Full Text Available The viability and success of modern enterprises are subject to the increasing dynamic of the economic environment, so they need to adjust rapidly their policies and strategies in order to respond to sophistication of competitors, customers and suppliers, globalization of business, international competition. Perhaps the most critical component for success of the modern enterprise is its ability to take advantage of all available information - both internal and external. Making sense of all this information, gaining value and competitive advantage through represents real challenges for the enterprise. The IT solutions designed to address these challenges have been developed in two different approaches: structured data management (Business Intelligence and unstructured content management (Knowledge Management. Integrating Business Intelligence and Knowledge Management in new software applications designated not only to store highly structured data and exploit it in real time but also to interpret the results and communicate them to decision factors provides real technological support for Strategic Management. Integrating Business Intelligence and Knowledge Management in order to respond to the challenges the modern enterprise has to deal with represents not only a "new trend" in IT, but a necessity in the emerging knowledge based economy. These hybrid technologies are already widely known in both scientific and practice communities as Competitive Intelligence. In the end of paper,a competitive datawarehouse design is proposed, in an attempt to apply business intelligence technologies to economic environment analysis making use of romanian public data sources.

  20. The association between intelligence and telomere length: a longitudinal population based study.

    Directory of Open Access Journals (Sweden)

    Eva M Kingma

    Full Text Available Low intelligence has been associated with poor health and mortality, but underlying mechanisms remain obscure. We hypothesized that low intelligence is associated with accelerated biological ageing as reflected by telomere length; we suggested potential mediation of this association by unhealthy behaviors and low socioeconomic position. The study was performed in a longitudinal population-based cohort study of 895 participants (46.8% males. Intelligence was measured with the Generalized Aptitude-Test Battery at mean age 52.8 years (33-79 years, SD=11.3. Leukocyte telomere length was measured by PCR. Lifestyle and socioeconomic factors were assessed using written self-report measures. Linear regression analyses, adjusted for age, sex, and telomere length measured at the first assessment wave (T1, showed that low intelligence was associated with shorter leukocyte telomere length at approximately 2 years follow-up (beta= .081, t=2.160, p= .031. Nearly 40% of this association was explained by an unhealthy lifestyle, while low socioeconomic position did not add any significant mediation. Low intelligence may be a risk factor for accelerated biological ageing, thereby providing an explanation for its association with poor health and mortality.

  1. Representation of Students in Solving Simultaneous Linear Equation Problems Based on Multiple Intelligence

    Science.gov (United States)

    Yanti, Y. R.; Amin, S. M.; Sulaiman, R.

    2018-01-01

    This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.

  2. “TOTTO-CHAN”: INSIGHTS INTO MULTIPLE INTELLIGENCES-BASED ENGLISH TEACHING TO YOUNG LEARNERS

    Directory of Open Access Journals (Sweden)

    K. M. Widi Hadiyanti

    2017-04-01

    Full Text Available Children are unique individuals who have their own ways to learn about the world and solve problems. It is supported by Gardner‘s ideas about multiple intelligences. Gardner (1993, 1998 suggested several kinds of intelligences. In their attempt to learn about the world, children make use of all resources, including their multiple intelligences. The application of multiple intelligences in teaching young learner seems to be apparent in Tetsuko Kuroyanagi‘s autobiographical memoir, ―Totto-chan: The Little Girl at the Window‖. This study identified and analyzed the techniques used to apply multiple intelligences in teaching young learners in Totto-chan‘s elementary school, Tomoe Gakuen. Based on the identification and analysis conducted in ―Totto-chan‖, this study elaborated the techniques in teaching English for young learners. In particular, this study proposed teaching techniques for four language skills. This study will be of great benefit for English teachers for young learners to enrich their teaching techniques that accord with the children nature of development.

  3. Metacognitive experience of mathematics education students in open start problem solving based on intrapersonal intelligence

    Science.gov (United States)

    Sari, D. P.; Usodo, B.; Subanti, S.

    2018-04-01

    This research aims to describe metacognitive experience of mathematics education students with strong, average, and weak intrapersonal intelligence in open start problem solving. Type of this research was qualitative research. The research subject was mathematics education students in Muhammadiyah University of Surakarta in academic year 2017/2018. The selected students consisted of 6 students with details of two students in each intrapersonal intelligence category. The research instruments were questionnaire, open start problem solving task, and interview guidelines. Data validity used time triangulation. Data analyses were done through data collection, data reduction, data presentation, and drawing conclusion. Based on findings, subjects with strong intrapersonal intelligence had high self confidence that they were able to solve problem correctly, able to do planning steps and able to solve the problem appropriately. Subjects with average intrapersonal intelligence had high self-assessment that they were able to solve the problem, able to do planning steps appropriately but they had not maximized in carrying out the plan so that it resulted incorrectness answer. Subjects with weak intrapersonal intelligence had high self confidence in capability of solving math problem, lack of precision in taking plans so their task results incorrectness answer.

  4. The Prediction of Mental Quality of Life Based on Defectiveness/Shame Schema with Mediating Role of Emotional Intelligence and Coping Strategies by Means of Structural Equations Modeling

    Directory of Open Access Journals (Sweden)

    S. Dehghani

    2014-06-01

    Full Text Available Early maladaptive schema is assumed to be a disrupting factor for quality of life. Yet, the mechanism of this vulnerability is not well known. The purpose of this study was to investigate the characteristic of emotional intelligence and coping strategy with stress as a mediator between early maladaptive defectiveness/ shame and mental quality of life. Participants were 245 men and women in Isfahan who were selected as the sample by availability sampling method. They completed the Petrides and Furnham's Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF, Coping Inventory for stressful situation (CISS and WHO Quality of Life-BREF (WHOQOL-BREF and Young Schema Questionnaire-Short Form (YSQ-SF. Data was analyzed by means of structural equation modeling. The results indicated that the suggested model of study needs modification and only emotional intelligence was the mediator. Standard path coefficient of defectiveness/shame schema to emotional intelligence was -0.55 and emotional intelligence to problem focused coping, emotion focused coping and mental quality of life were 0.49, -0.59 and 0.78 (p<0.05. Based on results, emotional intelligence training can improve mental quality of life and coping strategies in people who have early defectiveness/shame maladaptive schema.

  5. Intelligence system based classification approach for medical disease diagnosis

    Science.gov (United States)

    Sagir, Abdu Masanawa; Sathasivam, Saratha

    2017-08-01

    The prediction of breast cancer in women who have no signs or symptoms of the disease as well as survivability after undergone certain surgery has been a challenging problem for medical researchers. The decision about presence or absence of diseases depends on the physician's intuition, experience and skill for comparing current indicators with previous one than on knowledge rich data hidden in a database. This measure is a very crucial and challenging task. The goal is to predict patient condition by using an adaptive neuro fuzzy inference system (ANFIS) pre-processed by grid partitioning. To achieve an accurate diagnosis at this complex stage of symptom analysis, the physician may need efficient diagnosis system. A framework describes methodology for designing and evaluation of classification performances of two discrete ANFIS systems of hybrid learning algorithms least square estimates with Modified Levenberg-Marquardt and Gradient descent algorithms that can be used by physicians to accelerate diagnosis process. The proposed method's performance was evaluated based on training and test datasets with mammographic mass and Haberman's survival Datasets obtained from benchmarked datasets of University of California at Irvine's (UCI) machine learning repository. The robustness of the performance measuring total accuracy, sensitivity and specificity is examined. In comparison, the proposed method achieves superior performance when compared to conventional ANFIS based gradient descent algorithm and some related existing methods. The software used for the implementation is MATLAB R2014a (version 8.3) and executed in PC Intel Pentium IV E7400 processor with 2.80 GHz speed and 2.0 GB of RAM.

  6. Impact of emotional intelligence and flexibility on the tendency of employees to leave the organization in project based organizations

    Directory of Open Access Journals (Sweden)

    Hossein Mohammadi

    2017-12-01

    Full Text Available Sentiment is a powerful psychological force that can significantly affect employee behavior and performance. However, workplace emotions are still an issue to be studied, especially in the field of sales management in project based organizations. The purpose of this study is to investigate the effect of emotional intelligence and flexibility on the tendency of employees to leave the organization. The method of this research is descriptive correlational and in a survey method and it is a practical purpose. The statistical population of this study includes all 108 employees of the representatives of selected insurance firms in city of Zanjan, Iran. Using Cochran formula, 84 people were selected as the statistical sample. The results have indicated that while there was a positive and meaningful relationship between emotional intelligence and flexibility (r = 0.534, Sig. = 0.000, there were negative and meaningful relationships between flexibility and emotion-al intelligence on one side and intend to leave an organization on the other side.

  7. Eye gaze in intelligent user interfaces gaze-based analyses, models and applications

    CERN Document Server

    Nakano, Yukiko I; Bader, Thomas

    2013-01-01

    Remarkable progress in eye-tracking technologies opened the way to design novel attention-based intelligent user interfaces, and highlighted the importance of better understanding of eye-gaze in human-computer interaction and human-human communication. For instance, a user's focus of attention is useful in interpreting the user's intentions, their understanding of the conversation, and their attitude towards the conversation. In human face-to-face communication, eye gaze plays an important role in floor management, grounding, and engagement in conversation.Eye Gaze in Intelligent User Interfac

  8. A mircocontroller MC68HC908GP32 based intelligent scalar

    International Nuclear Information System (INIS)

    Liu Huiying

    2001-01-01

    A Mircocontroller MC68HC908GP32 based intelligent scalar is presented. By replacing traditional IC modular with Mircocontroller, the new type scalar can provide new functions, such as countering rate measurement, control signal output, LCD display, PC control, etc., in addition to traditional functions of normal scalar. This intelligent scalar achieved comprehensive technical innovation to the traditional nuclear electronic instrument, with regard to the design methodology, structure and functions. In this way, the overall technical performance of the new type scalar, such as counting rate, accuracy, volume, cost and operation, etc., has been improved obviously, with bright prospects for application and dissemination

  9. System Design and Implementation of Intelligent Fire Engine Path Planning based on SAT Algorithm

    Institute of Scientific and Technical Information of China (English)

    CAI Li-sha[1; ZENG Wei-peng[1; HAN Bao-ru[1

    2016-01-01

    In this paper, in order to make intelligent fi re car complete autonomy path planning in simulation map. Proposed system design of intelligent fi re car path planning based on SAT. The system includes a planning module, a communication module, a control module. Control module via the communication module upload the initial state and the goal state to planning module. Planning module solve this planning solution,and then download planning solution to control module, control the movement of the car fi re. Experiments show this the system is tracking short time, higher planning effi ciency.

  10. The Application Research of Modern Intelligent Cold Chain Distribution System Based on Internet of Things Technology

    Science.gov (United States)

    Fan, Dehui; Gao, Shan

    This paper implemented an intelligent cold chain distribution system based on the technology of Internet of things, and took the protoplasmic beer logistics transport system as example. It realized the remote real-time monitoring material status, recorded the distribution information, dynamically adjusted the distribution tasks and other functions. At the same time, the system combined the Internet of things technology with weighted filtering algorithm, realized the real-time query of condition curve, emergency alarming, distribution data retrieval, intelligent distribution task arrangement, etc. According to the actual test, it can realize the optimization of inventory structure, and improve the efficiency of cold chain distribution.

  11. A Novel Architecture of Metadata Management System Based on Intelligent Cache

    Institute of Scientific and Technical Information of China (English)

    SONG Baoyan; ZHAO Hongwei; WANG Yan; GAO Nan; XU Jin

    2006-01-01

    This paper introduces a novel architecture of metadata management system based on intelligent cache called Metadata Intelligent Cache Controller (MICC). By using an intelligent cache to control the metadata system, MICC can deal with different scenarios such as splitting and merging of queries into sub-queries for available metadata sets in local, in order to reduce access time of remote queries. Application can find results patially from local cache and the remaining portion of the metadata that can be fetched from remote locations. Using the existing metadata, it can not only enhance the fault tolerance and load balancing of system effectively, but also improve the efficiency of access while ensuring the access quality.

  12. Structural invariance of multiple intelligences, based on the level of execution.

    Science.gov (United States)

    Almeida, Leandro S; Prieto, María Dolores; Ferreira, Arístides; Ferrando, Mercedes; Ferrandiz, Carmen; Bermejo, Rosario; Hernández, Daniel

    2011-11-01

    The independence of multiple intelligences (MI) of Gardner's theory has been debated since its conception. This article examines whether the one- factor structure of the MI theory tested in previous studies is invariant for low and high ability students. Two hundred ninety-four children (aged 5 to 7) participated in this study. A set of Gardner's Multiple Intelligence assessment tasks based on the Spectrum Project was used. To analyze the invariance of a general dimension of intelligence, the different models of behaviours were studied in samples of participants with different performance on the Spectrum Project tasks with Multi-Group Confirmatory Factor Analysis (MGCFA). Results suggest an absence of structural invariance in Gardner's tasks. Exploratory analyses suggest a three-factor structure for individuals with higher performance levels and a two-factor structure for individuals with lower performance levels.

  13. Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

    Institute of Scientific and Technical Information of China (English)

    谭冠政; 曾庆冬; 李文斌

    2004-01-01

    A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

  14. The effectiveness of discourse-based intervention on personal narrative of school-aged children with borderline intelligence quotient

    Directory of Open Access Journals (Sweden)

    Belghis Rovshan

    2014-04-01

    Full Text Available Background and Aim: Discourse-based interventions were studied less in speech therapy. This study aimed to investigate the effects of discourse-based intervention on language disabilities in school-aged children with borderline intelligence quotient (IQ.Methods: In an experimental study, 33 students at the age of 6-13 years with borderline intelligence quotient (17 students for intervention and 16 students for control group were selected with available sampling. The intervention lasted 14 sessions (every session: 45 minutes that focused on the structure and content of discourse. Personal narrative was elicited with explanation of the same topic (go to a trip for pre- and post-test.Results: Mean scores of intelligence quotient, age and education had no difference between the two groups. The intervention caused the increase of compound sentences (p=0.038, types of cohesive conjunctions (p=0.003, and related information (p=0.008 and decrease of ungrammatical sentences (p=0.031.Conclusion: Our findings indicate that participation in the intervention program has a clinically significant effect on the participants' abilities to produce personal narrative.

  15. Impacts of Intelligent Automated Quality Control on a Small Animal APD-Based Digital PET Scanner

    Science.gov (United States)

    Charest, Jonathan; Beaudoin, Jean-François; Bergeron, Mélanie; Cadorette, Jules; Arpin, Louis; Lecomte, Roger; Brunet, Charles-Antoine; Fontaine, Réjean

    2016-10-01

    Stable system performance is mandatory to warrant the accuracy and reliability of biological results relying on small animal positron emission tomography (PET) imaging studies. This simple requirement sets the ground for imposing routine quality control (QC) procedures to keep PET scanners at a reliable optimal performance level. However, such procedures can become burdensome to implement for scanner operators, especially taking into account the increasing number of data acquisition channels in newer generation PET scanners. In systems using pixel detectors to achieve enhanced spatial resolution and contrast-to-noise ratio (CNR), the QC workload rapidly increases to unmanageable levels due to the number of independent channels involved. An artificial intelligence based QC system, referred to as Scanner Intelligent Diagnosis for Optimal Performance (SIDOP), was proposed to help reducing the QC workload by performing automatic channel fault detection and diagnosis. SIDOP consists of four high-level modules that employ machine learning methods to perform their tasks: Parameter Extraction, Channel Fault Detection, Fault Prioritization, and Fault Diagnosis. Ultimately, SIDOP submits a prioritized faulty channel list to the operator and proposes actions to correct them. To validate that SIDOP can perform QC procedures adequately, it was deployed on a LabPET™ scanner and multiple performance metrics were extracted. After multiple corrections on sub-optimal scanner settings, a 8.5% (with a 95% confidence interval (CI) of [7.6, 9.3]) improvement in the CNR, a 17.0% (CI: [15.3, 18.7]) decrease of the uniformity percentage standard deviation, and a 6.8% gain in global sensitivity were observed. These results confirm that SIDOP can indeed be of assistance in performing QC procedures and restore performance to optimal figures.

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

    Science.gov (United States)

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

    2014-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Shahoo Maleki

    2014-06-01

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

  18. Knowledge Based Artificial Augmentation Intelligence Technology: Next Step in Academic Instructional Tools for Distance Learning

    Science.gov (United States)

    Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh

    2017-01-01

    With augmented intelligence/knowledge based system (KBS) it is now possible to develop distance learning applications to support both curriculum and administrative tasks. Instructional designers and information technology (IT) professionals are now moving from the programmable systems era that started in the 1950s to the cognitive computing era.…

  19. A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

    Science.gov (United States)

    de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

    2017-01-01

    Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

  20. The Effect of Teaching Strategy Based on Multiple Intelligences on Students' Academic Achievement in Science Course

    Science.gov (United States)

    Abdi, Ali; Laei, Susan; Ahmadyan, Hamze

    2013-01-01

    The purpose of this study was to investigate the effects of Teaching Strategy based on Multiple Intelligences on students' academic achievement in sciences course. Totally 40 students from two different classes (Experimental N = 20 and Control N = 20) participated in the study. They were in the fifth grade of elementary school and were selected…

  1. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    Science.gov (United States)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  2. Predicting speech intelligibility based on a correlation metric in the envelope power spectrum domain

    DEFF Research Database (Denmark)

    Relaño-Iborra, Helia; May, Tobias; Zaar, Johannes

    2016-01-01

    A speech intelligibility prediction model is proposed that combines the auditory processing front end of the multi-resolution speech-based envelope power spectrum model [mr-sEPSM; Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134(1), 436–446] with a correlation back end inspired by the sh...

  3. MamMoeT : An intelligent agent-based communication support platform for multimodal transport

    NARCIS (Netherlands)

    Dullaert, Wout; Neutens, Tijs; Vanden Berghe, Greet; Vermeulen, Tijs; Vernimmen, Bert; Witlox, Frank

    In this paper, an intelligent agent-based communication support platform for multimodal transport is developed. The rationale for doing so is found in the potential of such a system to increase cost efficiency, service and safety for different transport-related actors. Although, at present several

  4. An Autonomous Learning System of Bengali Characters Using Web-Based Intelligent Handwriting Recognition

    Science.gov (United States)

    Khatun, Nazma; Miwa, Jouji

    2016-01-01

    This research project was aimed to develop an intelligent Bengali handwriting education system to improve the literacy level in Bangladesh. Due to the socio-economical limitation, all of the population does not have the chance to go to school. Here, we developed a prototype of web-based (iPhone/smartphone or computer browser) intelligent…

  5. Vedic Science Based Education and Nonverbal Intelligence: A Preliminary Longitudinal Study in Cambodia.

    Science.gov (United States)

    Fergusson, Lee C.; And Others

    1996-01-01

    A study investigated the effects on students' nonverbal intelligence of implementing an approach to higher education based on Vedic science, developed by Maharishi Mahesh Yogi and including transcendental meditation. The approach was implemented in two Cambodian universities and its effects assessed in 70 undergraduate students. An increase in…

  6. Effects of an Intelligent Web-Based English Instruction System on Students' Academic Performance

    Science.gov (United States)

    Jia, J.; Chen, Y.; Ding, Z.; Bai, Y.; Yang, B.; Li, M.; Qi, J.

    2013-01-01

    This research conducted quasi-experiments in four middle schools to evaluate the long-term effects of an intelligent web-based English instruction system, Computer Simulation in Educational Communication (CSIEC), on students' academic attainment. The analysis of regular examination scores and vocabulary test validates the positive impact of CSIEC,…

  7. An Agent-Based Model for the Development of Intelligent Mobile Services

    NARCIS (Netherlands)

    Koch, F.L.

    2009-01-01

    The next generation of mobile services must invisible, convenient, and useful. It requires new techniques to design and develop mobile computing applications, based on user-centred, environment-aware, adaptive behaviour. I propose an alternative technology for the development of intelligent mobile

  8. Outcome measures based on classification performance fail to predict the intelligibility of binary-masked speech

    DEFF Research Database (Denmark)

    Kressner, Abigail Anne; May, Tobias; Rozell, Christopher J.

    2016-01-01

    To date, the most commonly used outcome measure for assessing ideal binary mask estimation algorithms is based on the difference between the hit rate and the false alarm rate (H-FA). Recently, the error distribution has been shown to substantially affect intelligibility. However, H-FA treats each...... evaluations should not be made solely on the basis of these metrics....

  9. Game Algorithm for Resource Allocation Based on Intelligent Gradient in HetNet

    Directory of Open Access Journals (Sweden)

    Fang Ye

    2017-02-01

    Full Text Available In order to improve system performance such as throughput, heterogeneous network (HetNet has become an effective solution in Long Term Evolution-Advanced (LET-A. However, co-channel interference leads to degradation of the HetNet throughput, because femtocells are always arranged to share the spectrum with the macro base station. In this paper, in view of the serious cross-layer interference in double layer HetNet, the Stackelberg game model is adopted to analyze the resource allocation methods of the network. Unlike the traditional system models only focusing on macro base station performance improvement, we take into account the overall system performance and build a revenue function with convexity. System utility functions are defined as the average throughput, which does not adopt frequency spectrum trading method, so as to avoid excessive signaling overhead. Due to the value scope of continuous Nash equilibrium of the built game model, the gradient iterative algorithm is introduced to reduce the computational complexity. As for the solution of Nash equilibrium, one kind of gradient iterative algorithm is proposed, which is able to intelligently choose adjustment factors. The Nash equilibrium can be quickly solved; meanwhile, the step of presetting adjustment factors is avoided according to network parameters in traditional linear iterative model. Simulation results show that the proposed algorithm enhances the overall performance of the system.

  10. Simulation-Based Cryosurgery Intelligent Tutoring System (ITS) Prototype

    Science.gov (United States)

    Sehrawat, Anjali; Keelan, Robert; Shimada, Kenji; Wilfong, Dona M.; McCormick, James T.; Rabin, Yoed

    2015-01-01

    As a part of an ongoing effort to develop computerized training tools for cryosurgery, the current study presents a proof-of-concept for a computerized tool for cryosurgery tutoring. The tutoring system lists geometrical constraints of cryoprobes placement, simulates cryoprobe insertion, displays a rendered shape of the prostate, enables distance measurements, simulates the corresponding thermal history, and evaluates the mismatch between the target region shape and a pre-selected planning isotherm. The quality of trainee planning is measured in comparison with a computer-generated planning, created for each case study by previously developed planning algorithms. Two versions of the tutoring system have been tested in the current study: (i) an unguided version, where the trainee can practice cases in unstructured sessions, and (ii) an intelligent tutoring system (ITS), which forces the trainee to follow specific steps, believed by the authors to potentially shorten the learning curve. While the tutoring level in this study aims only at geometrical constraints on cryoprobe placement and the resulting thermal histories, it creates a unique opportunity to gain insight into the process outside of the operation room. Posttest results indicate that the ITS system maybe more beneficial than the non-ITS system, but the proof-of-concept is demonstrated with either system. PMID:25941163

  11. Intelligent energy buildings based on RES and nanotechnology

    Energy Technology Data Exchange (ETDEWEB)

    Kaplanis, S., E-mail: kaplanis@teipat.gr; Kaplani, E. [R.E.S. Laboratory, Mechanical Engineering Dept., Technological Educational Institute of Western Greece M. Alexandrou 1, Koukouli 26 334, Patra (Greece)

    2015-12-31

    The paper presents the design features, the energy modelling and optical performance details of two pilot Intelligent Energy Buildings, (IEB). Both are evolution of the Zero Energy Building (ZEB) concept. RES innovations backed up by signal processing, simulation models and ICT tools were embedded into the building structures in order to implement a new predictive energy management concept. In addition, nano-coatings, produced by TiO2 and ITO nano-particles, were deposited on the IEB structural elements and especially on the window panes and the PV glass covers. They exhibited promising SSP values which lowered the cooling loads and increased the PV modules yield. Both pilot IEB units were equipped with an on-line dynamic hourly solar radiation prediction model, implemented by sensors and the related software to manage effectively the energy source, the loads and the storage or the backup system. The IEB energy sources covered the thermal loads via a south façade embedded in the wall and a solar roof which consists of a specially designed solar collector type, while a PV generator is part of the solar roof, like a compact BIPV in hybrid configuration to a small wind turbine.

  12. Understanding the Relationship between School-Based Management, Emotional Intelligence and Performance of Religious Upper Secondary School Principals in Banten Province

    Science.gov (United States)

    Muslihah, Oleh Eneng

    2015-01-01

    The research examines the correlation between the understanding of school-based management, emotional intelligences and headmaster performance. Data was collected, using quantitative methods. The statistical analysis used was the Pearson Correlation, and multivariate regression analysis. The results of this research suggest firstly that there is…

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

    Science.gov (United States)

    Goodarzi, Mohammad; dos Santos Coelho, Leandro

    2014-12-10

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

  14. Development and evaluation of intelligent machine tools based on knowledge evolution in M2M environment

    International Nuclear Information System (INIS)

    Kim, Dong Hoon; Song, Jun Yeob; Lee, Jong Hyun; Cha, Suk Keun

    2009-01-01

    In the near future, the foreseen improvement in machine tools will be in the form of a knowledge evolution-based intelligent device. The goal of this study is to develop intelligent machine tools having knowledge-evolution capability in Machine to Machine (M2M) wired and wireless environment. The knowledge evolution-based intelligent machine tools are expected to be capable of gathering knowledge autonomously, producing knowledge, understanding knowledge, applying reasoning to knowledge, making new decisions, dialoguing with other machines, etc. The concept of the knowledge-evolution intelligent machine originated from the process of machine control operation by the sense, dialogue and decision of a human expert. The structure of knowledge evolution in M2M and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, and work-offset compensation from thermal change and recommendation of cutting condition are performed on-line for knowledge-evolution verification

  15. Quality control of intelligence research

    International Nuclear Information System (INIS)

    Lu Yan; Xin Pingping; Wu Jian

    2014-01-01

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

  16. Study on virtual instrument developing system based on intelligent virtual control

    International Nuclear Information System (INIS)

    Tang Baoping; Cheng Fabin; Qin Shuren

    2005-01-01

    The paper introduces a non-programming developing system of a virtual instrument (VI), i.e., a virtual measurement instrument developing system (VMIDS) based on intelligent virtual control (IVC). The background of the IVC-based VMIDS is described briefly, and the hierarchical message bus (HMB)-based software architecture of VMIDS is discussed in detail. The three parts and functions of VMIDS are introduced, and the process of non-programming developing VI is further described

  17. Study on virtual instrument developing system based on intelligent virtual control

    Energy Technology Data Exchange (ETDEWEB)

    Tang Baoping; Cheng Fabin; Qin Shuren [Test Center, College of Mechanical Engineering, Chongqing University , Chongqing 400030 (China)

    2005-01-01

    The paper introduces a non-programming developing system of a virtual instrument (VI), i.e., a virtual measurement instrument developing system (VMIDS) based on intelligent virtual control (IVC). The background of the IVC-based VMIDS is described briefly, and the hierarchical message bus (HMB)-based software architecture of VMIDS is discussed in detail. The three parts and functions of VMIDS are introduced, and the process of non-programming developing VI is further described.

  18. Swarm intelligence based on modified PSO algorithm for the optimization of axial-flow pump impeller

    International Nuclear Information System (INIS)

    Miao, Fuqing; Kim, Chol Min; Ahn, Seok Young; Park, Hong Seok

    2015-01-01

    This paper presents a multi-objective optimization of the impeller shape of an axial-flow pump based on the Modified particle swarm optimization (MPSO) algorithm. At first, an impeller shape was designed and used as a reference in the optimization process then NPSHr and η of the axial flow pump were numerically investigated by using the commercial software ANSYS with the design variables concerning hub angle β_h, chord angle β_c, cascade solidity of chord σ_c and maximum thickness of blade H. By using the Group method of data handling (GMDH) type neural networks in commercial software DTREG, the corresponding polynomial representation for NPSHr and η with respect to the design variables were obtained. A benchmark test was employed to evaluate the performance of the MPSO algorithm in comparison with other particle swarm algorithms. Later the MPSO approach was used for Pareto based optimization. Finally, the MPSO optimization result and CFD simulation result were compared in a re-evaluation process. By using swarm intelligence based on the modified PSO algorithm, better performance pump with higher efficiency and lower NPSHr could be obtained. This novel algorithm was successfully applied for the optimization of axial-flow pump impeller shape design

  19. Swarm intelligence based on modified PSO algorithm for the optimization of axial-flow pump impeller

    Energy Technology Data Exchange (ETDEWEB)

    Miao, Fuqing; Kim, Chol Min; Ahn, Seok Young [Pusan National University, Busan (Korea, Republic of); Park, Hong Seok [Ulsan University, Ulsan (Korea, Republic of)

    2015-11-15

    This paper presents a multi-objective optimization of the impeller shape of an axial-flow pump based on the Modified particle swarm optimization (MPSO) algorithm. At first, an impeller shape was designed and used as a reference in the optimization process then NPSHr and η of the axial flow pump were numerically investigated by using the commercial software ANSYS with the design variables concerning hub angle β{sub h}, chord angle β{sub c}, cascade solidity of chord σ{sub c} and maximum thickness of blade H. By using the Group method of data handling (GMDH) type neural networks in commercial software DTREG, the corresponding polynomial representation for NPSHr and η with respect to the design variables were obtained. A benchmark test was employed to evaluate the performance of the MPSO algorithm in comparison with other particle swarm algorithms. Later the MPSO approach was used for Pareto based optimization. Finally, the MPSO optimization result and CFD simulation result were compared in a re-evaluation process. By using swarm intelligence based on the modified PSO algorithm, better performance pump with higher efficiency and lower NPSHr could be obtained. This novel algorithm was successfully applied for the optimization of axial-flow pump impeller shape design.

  20. 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

  1. 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.

  2. A Novel Biometric Identification Based on a User's Input Pattern Analysis for Intelligent Mobile Devices

    Directory of Open Access Journals (Sweden)

    Hojin Seo

    2012-07-01

    Full Text Available As intelligent mobile devices become more popular, security threats targeting them are increasing. The resource constraints of mobile devices, such as battery life and computing power, however, make it harder to handle such threats effectively. The existing physical and behavioural biometric identification methods - looked upon as good alternatives - are unsuitable for the current mobile environment. This paper proposes a specially designed biometric identification method for intelligent mobile devices by analysing the user's input patterns, such as a finger's touch duration, pressure level and the touching width of the finger on the touch screen. We collected the input pattern data of individuals to empirically test our method. Our testing results show that this method effectively identifies users with near a 100% rate of accuracy.

  3. Wireless Intelligent Monitoring and Control System of Greenhouse Temperature Based on Fuzzy-PID

    Directory of Open Access Journals (Sweden)

    Mei ZHAN

    2014-03-01

    Full Text Available Control effect is not ideal for traditional control method and wired control system, since greenhouse temperature has such characteristics as nonlinear and longtime lag. Therefore, Fuzzy- PID control method was introduced and radio frequency chip CC1110 was applied to design greenhouse wireless intelligent monitoring and control system. The design of the system, the component of nodes and the developed intelligent management software system were explained in this paper. Then describe the design of the control algorithm Fuzzy-PID. By simulating the new method in Matlab software, the results showed that Fuzzy-PID method small overshoot and better dynamic performance compared with general PID control. It has shorter settling time and no steady-state error compared with fuzzy control. It can meet requirements in greenhouse production.

  4. Applying of Content Analysis Method in Business Online Advertising Intelligence Extraction --Based on Advertising of China Three Telecom Operators%内容分析法在商业网络广告情报萃取中的运用——以中国三大电信运营商为例

    Institute of Scientific and Technical Information of China (English)

    黄晓斌; 钟辉新

    2012-01-01

    This paper applies the content analysis method combined with visualization tools UCINET to extract the marketing strategies and corporate strategic intelligence from banner advertising of three China telecom operators' online business hall. The results show that the content analysis method can effectively extract the marketing strategy and corporate strategic intelligence of telecom operators. Moreover, the strategies extracted from advertising are in good agreement with the company' s real strategies. Therefore, the content analysis method is an effective method for extracting business online advertising intelligence.%运用内容分析法,借助可视化工具UCINET,分析中国三大电信运营商网络营业厅横幅广告中隐含的营销战略和企业战略情报。结果表明:通过网络广告内容分析法能有效地萃取电信运营商的营销战略和企业战略情报,而且萃取出的企业战略情报与企业的真实战略有较好的一致性,说明内容分析法是一种行之有效的商业网络广告情报萃取的方法。

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

    Science.gov (United States)

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

    2017-12-01

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

  6. How People Interact with Technology based on Natural and Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2017-04-01

    Full Text Available This paper aims to analyse the different forms of intelligence within organizations in a systemic and inclusive vision, in order to design an integrated environment based on Artificial Intelligence (AI and Collective Intelligence (CI. This way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow, of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals, to the current approaches of connecting people on the use (automatic of operational knowledge to solve problems and make decisions based on intellectual cooperation. Few technologies have the big potential to review how we live, move, and work. Artificial intelligence (AI is nowdays equivalent of electricity and the Internet. AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans.

  7. Facile preparation of luminescent and intelligent gold nanodots based on supramolecular self-assembly

    International Nuclear Information System (INIS)

    Shi Yunfeng; Li Sujuan; Zhou Yahui; Zhai Qingpan; Hu Mengyue; Cai Fensha; Du Jimin; Liang Jiamiao; Zhu Xinyuan

    2012-01-01

    A new strategy for preparing luminescent and intelligent gold nanodots based on supramolecular self-assembly is described in this paper. The supramolecular self-assembly was initiated through electrostatic interactions and ion pairing between palmitic acid and hyperbranched poly(ethylenimine). The resulting structures not only have the dynamic reversible properties of supramolecules but also possess torispherical and highly branched architectures. Thus they can be regarded as a new kind of ideal nanoreactor for preparing intelligent Au nanodots. By preparing Au nanodots within this kind of supramolecular self-assembly, the environmental sensitivity of intelligent polymers and the optical, electrical properties of Au nanodots can be combined, endowing the Au nanodots with intelligence. In this paper, a supramolecular self-assembly process based on dendritic poly(ethylenimine) and palmitic acid was designed and then applied to prepare fluorescent and size-controlled Au nanodots. The pH response of Au nanodots embodied by phase transfer from oil phase to water phase was also investigated. (paper)

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

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

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

  9. Data driven model generation based on computational intelligence

    Science.gov (United States)

    Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

    2010-05-01

    The simulation of discharges at a local gauge or the modeling of large scale river catchments are effectively involved in estimation and decision tasks of hydrological research and practical applications like flood prediction or water resource management. However, modeling such processes using analytical or conceptual approaches is made difficult by both complexity of process relations and heterogeneity of processes. It was shown manifold that unknown or assumed process relations can principally be described by computational methods, and that system models can automatically be derived from observed behavior or measured process data. This study describes the development of hydrological process models using computational methods including Fuzzy logic and artificial neural networks (ANN) in a comprehensive and automated manner. Methods We consider a closed concept for data driven development of hydrological models based on measured (experimental) data. The concept is centered on a Fuzzy system using rules of Takagi-Sugeno-Kang type which formulate the input-output relation in a generic structure like Ri : IFq(t) = lowAND...THENq(t+Δt) = ai0 +ai1q(t)+ai2p(t-Δti1)+ai3p(t+Δti2)+.... The rule's premise part (IF) describes process states involving available process information, e.g. actual outlet q(t) is low where low is one of several Fuzzy sets defined over variable q(t). The rule's conclusion (THEN) estimates expected outlet q(t + Δt) by a linear function over selected system variables, e.g. actual outlet q(t), previous and/or forecasted precipitation p(t ?Δtik). In case of river catchment modeling we use head gauges, tributary and upriver gauges in the conclusion part as well. In addition, we consider temperature and temporal (season) information in the premise part. By creating a set of rules R = {Ri|(i = 1,...,N)} the space of process states can be covered as concise as necessary. Model adaptation is achieved by finding on optimal set A = (aij) of conclusion

  10. A development framework for artificial intelligence based distributed operations support systems

    Science.gov (United States)

    Adler, Richard M.; Cottman, Bruce H.

    1990-01-01

    Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

  11. A Multi-Agent-Based Intelligent Sensor and Actuator Network Design for Smart House and Home Automation

    Directory of Open Access Journals (Sweden)

    Fei Hu

    2013-08-01

    Full Text Available The smart-house technology aims to increase home automation and security with reduced energy consumption. A smart house consists of various intelligent sensors and actuators operating on different platforms with conflicting objectives. This paper proposes a multi-agent system (MAS design framework to achieve smart house automation. The novelties of this work include the developments of (1 belief, desire and intention (BDI agent behavior models; (2 a regulation policy-based multi-agent collaboration mechanism; and (3 a set of metrics for MAS performance evaluation. Simulations of case studies are performed using the Java Agent Development Environment (JADE to demonstrate the advantages of the proposed method.

  12. A Workflow-based Intelligent Network Data Movement Advisor with End-to-end Performance Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Michelle M. [Southern Illinois Univ., Carbondale, IL (United States); Wu, Chase Q. [Univ. of Memphis, TN (United States)

    2013-11-07

    Next-generation eScience applications often generate large amounts of simulation, experimental, or observational data that must be shared and managed by collaborative organizations. Advanced networking technologies and services have been rapidly developed and deployed to facilitate such massive data transfer. However, these technologies and services have not been fully utilized mainly because their use typically requires significant domain knowledge and in many cases application users are even not aware of their existence. By leveraging the functionalities of an existing Network-Aware Data Movement Advisor (NADMA) utility, we propose a new Workflow-based Intelligent Network Data Movement Advisor (WINDMA) with end-to-end performance optimization for this DOE funded project. This WINDMA system integrates three major components: resource discovery, data movement, and status monitoring, and supports the sharing of common data movement workflows through account and database management. This system provides a web interface and interacts with existing data/space management and discovery services such as Storage Resource Management, transport methods such as GridFTP and GlobusOnline, and network resource provisioning brokers such as ION and OSCARS. We demonstrate the efficacy of the proposed transport-support workflow system in several use cases based on its implementation and deployment in DOE wide-area networks.

  13. An Intelligent FPGA Based Anti-Sweating System for Bed Sore Prevention in a Clinical Environment

    Directory of Open Access Journals (Sweden)

    K. S. Jaichandar

    2011-01-01

    Full Text Available Bed sores, a common problem among immobile patients occur as a result of continuous sweating due to increase in skin to bed surface temperature in patients lying on same posture for prolonged period. If left untreated, the skin can break open and become infected. Currently adopted methods for bed sores prevention include: use of two hourly flip chat for repositioning patient or use of air fluidized beds. However, the setbacks of these preventive measures include either use of costly equipment or wastage of human resources. This paper introduces an intelligent low cost FPGA based anti-sweating system for bed sores prevention in a clinical environment. The developed system consists of bed surface implanted temperature sensors interfaced with an FPGA chip for sensing the temperature change in patient’s skin to bed surface. Based on the temperature change, the FPGA chip select the - mode (heater/cooler and speed of the fan module. Furthermore, an alarm module was implemented to alert the nurse to reposition the patient only if patient’s skin to bed surface temperature exceeds a predefined threshold thereby saving human resources. By integrating the whole system into a single FPGA chip, we were able to build a low cost compact system without sacrificing processing power and flexibility.

  14. Epileptic seizure predictors based on computational intelligence techniques: a comparative study with 278 patients.

    Science.gov (United States)

    Alexandre Teixeira, César; Direito, Bruno; Bandarabadi, Mojtaba; Le Van Quyen, Michel; Valderrama, Mario; Schelter, Bjoern; Schulze-Bonhage, Andreas; Navarro, Vincent; Sales, Francisco; Dourado, António

    2014-05-01

    The ability of computational intelligence methods to predict epileptic seizures is evaluated in long-term EEG recordings of 278 patients suffering from pharmaco-resistant partial epilepsy, also known as refractory epilepsy. This extensive study in seizure prediction considers the 278 patients from the European Epilepsy Database, collected in three epilepsy centres: Hôpital Pitié-là-Salpêtrière, Paris, France; Universitätsklinikum Freiburg, Germany; Centro Hospitalar e Universitário de Coimbra, Portugal. For a considerable number of patients it was possible to find a patient specific predictor with an acceptable performance, as for example predictors that anticipate at least half of the seizures with a rate of false alarms of no more than 1 in 6 h (0.15 h⁻¹). We observed that the epileptic focus localization, data sampling frequency, testing duration, number of seizures in testing, type of machine learning, and preictal time influence significantly the prediction performance. The results allow to face optimistically the feasibility of a patient specific prospective alarming system, based on machine learning techniques by considering the combination of several univariate (single-channel) electroencephalogram features. We envisage that this work will serve as benchmark data that will be of valuable importance for future studies based on the European Epilepsy Database. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. Automated waste canister docking and emplacement using a sensor-based intelligent controller

    International Nuclear Information System (INIS)

    Drotning, W.D.

    1992-08-01

    A sensor-based intelligent control system is described that utilizes a multiple degree-of-freedom robotic system for the automated remote manipulation and precision docking of large payloads such as waste canisters. Computer vision and ultrasonic proximity sensing are used to control the automated precision docking of a large object with a passive target cavity. Real-time sensor processing and model-based analysis are used to control payload position to a precision of ± 0.5 millimeter

  16. A cyber kill chain based taxonomy of banking Trojans for evolutionary computational intelligence

    OpenAIRE

    Kiwia, D; Dehghantanha, A; Choo, K-KR; Slaughter, J

    2017-01-01

    Malware such as banking Trojans are popular with financially-motivated cybercriminals. Detection of banking Trojans remains a challenging task, due to the constant evolution of techniques used to obfuscate and circumvent existing detection and security solutions. Having a malware taxonomy can facilitate the design of mitigation strategies such as those based on evolutionary computational intelligence. Specifically, in this paper, we propose a cyber kill chain based taxonomy of banking Trojans...

  17. 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 ...

  18. Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The ...... process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America.......A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data....... The model estimates the speech-to-noise envelope power ratio, SNR env, at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech...

  19. The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

    Science.gov (United States)

    Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

    2017-05-30

    The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

  20. The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

    Directory of Open Access Journals (Sweden)

    Gaining Han

    2017-05-01

    Full Text Available The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS, the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

  1. Optimization of chemical composition in the manufacturing process of flotation balls based on intelligent soft sensing

    Directory of Open Access Journals (Sweden)

    Dučić Nedeljko

    2016-01-01

    Full Text Available This paper presents an application of computational intelligence in modeling and optimization of parameters of two related production processes - ore flotation and production of balls for ore flotation. It is proposed that desired chemical composition of flotation balls (Mn=0.69%; Cr=2.247%; C=3.79%; Si=0.5%, which ensures minimum wear rate (0.47 g/kg during copper milling is determined by combining artificial neural network (ANN and genetic algorithm (GA. Based on the results provided by neuro-genetic combination, a second neural network was derived as an ‘intelligent soft sensor’ in the process of white cast iron production. The proposed ANN 12-16-12-4 model demonstrated favourable prediction capacity, and can be recommended as a ‘intelligent soft sensor’ in the alloying process intended for obtaining favourable chemical composition of white cast iron for production of flotation balls. In the development of intelligent soft sensor data from the two real production processes was used. [Projekat Ministarstva nauke Republike Srbije, br. TR35037 i br. TR35015

  2. Novel Rock Detection Intelligence for Space Exploration Based on Non-Symbolic Algorithms and Concepts

    Science.gov (United States)

    Yildirim, Sule; Beachell, Ronald L.; Veflingstad, Henning

    2007-01-01

    Future space exploration can utilize artificial intelligence as an integral part of next generation space rover technology to make the rovers more autonomous in performing mission objectives. The main advantage of the increased autonomy through a higher degree of intelligence is that it allows for greater utilization of rover resources by reducing the frequency of time consuming communications between rover and earth. In this paper, we propose a space exploration application of our research on a non-symbolic algorithm and concepts model. This model is based on one of the most recent approaches of cognitive science and artificial intelligence research, a parallel distributed processing approach. We use the Mars rovers. Sprit and Opportunity, as a starting point for proposing what rovers in the future could do if the presented model of non-symbolic algorithms and concepts is embedded in a future space rover. The chosen space exploration application for this paper, novel rock detection, is only one of many potential space exploration applications which can be optimized (through reduction of the frequency of rover-earth communications. collection and transmission of only data that is distinctive/novel) through the use of artificial intelligence technology compared to existing approaches.

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

    Science.gov (United States)

    Petrini, Maira; Pozzebon, Marlei

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

  4. An intelligent human-machine system based on an ecological interface design concept

    International Nuclear Information System (INIS)

    Naito, N.

    1995-01-01

    It seems both necessary and promising to develop an intelligent human-machine system, considering the objective of the human-machine system and the recent advance in cognitive engineering and artificial intelligence together with the ever-increasing importance of human factor issues in nuclear power plant operation and maintenance. It should support human operators in their knowledge-based behaviour and allow them to cope with unanticipated abnormal events, including recovery from erroneous human actions. A top-down design approach has been adopted based on cognitive work analysis, and (1) an ecological interface, (2) a cognitive model-based advisor and (3) a robust automatic sequence controller have been established. These functions have been integrated into an experimental control room. A validation test was carried out by the participation of experienced operators and engineers. The results showed the usefulness of this system in supporting the operator's supervisory plant control tasks. ((orig.))

  5. Attribute-Based Methods

    Science.gov (United States)

    Thomas P. Holmes; Wiktor L. Adamowicz

    2003-01-01

    Stated preference methods of environmental valuation have been used by economists for decades where behavioral data have limitations. The contingent valuation method (Chapter 5) is the oldest stated preference approach, and hundreds of contingent valuation studies have been conducted. More recently, and especially over the last decade, a class of stated preference...

  6. A Solution-Based Intelligent Tutoring System Integrated with an Online Game-Based Formative Assessment: Development and Evaluation

    Science.gov (United States)

    Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Abdollahi, Abbas; Horng, Shi-Jinn; Lim, Heuiseok

    2016-01-01

    Nowadays, intelligent tutoring systems are considered an effective research tool for learning systems and problem-solving skill improvement. Nonetheless, such individualized systems may cause students to lose learning motivation when interaction and timely guidance are lacking. In order to address this problem, a solution-based intelligent…

  7. Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence

    Science.gov (United States)

    Poonamallee, Latha; Harrington, Alex M.; Nagpal, Manisha; Musial, Alec

    2018-01-01

    Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI). The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies. PMID:29527182

  8. Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence

    Directory of Open Access Journals (Sweden)

    Latha Poonamallee

    2018-02-01

    Full Text Available Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI. The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies.

  9. Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence.

    Science.gov (United States)

    Poonamallee, Latha; Harrington, Alex M; Nagpal, Manisha; Musial, Alec

    2018-01-01

    Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI). The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies.

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

    Science.gov (United States)

    Li, Ke; Chen, Peng

    2011-01-01

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

  11. Detection of cyst using image segmentation and building knowledge-based intelligent decision support system as an aid to telemedicine

    Science.gov (United States)

    Janet, J.; Natesan, T. R.; Santhosh, Ramamurthy; Ibramsha, Mohideen

    2005-02-01

    An intelligent decision support tool to the Radiologist in telemedicine is described. Medical prescriptions are given based on the images of cyst that has been transmitted over computer networks to the remote medical center. The digital image, acquired by sonography, is converted into an intensity image. This image is then subjected to image preprocessing which involves correction methods to eliminate specific artifacts. The image is resized into a 256 x 256 matrix by using bilinear interpolation method. The background area is detected using distinct block operation. The area of the cyst is calculated by removing the background area from the original image. Boundary enhancement and morphological operations are done to remove unrelated pixels. This gives us the cyst volume. This segmented image of the cyst is sent to the remote medical center for analysis by Knowledge based artificial Intelligent Decision Support System (KIDSS). The type of cyst is detected and reported to the control mechanism of KIDSS. Then the inference engine compares this with the knowledge base and gives appropriate medical prescriptions or treatment recommendations by applying reasoning mechanisms at the remote medical center.

  12. [Research on demodulation system for human body temperature measurement of intelligent clothing based on arrayed waveguide grating].

    Science.gov (United States)

    Yu, Xiao-gang; Miao, Chang-yun; Li, Hong-qiang; Li, En-bang; Liu, Zhi-hui; Wei, Ke-jia

    2012-08-01

    A system for demodulating distributed fiber Bragg grating sensors of the intelligent clothing was researched and realized, which is based on arrayed waveguide grating. The principle of demodulation method based on arrayed waveguide grating was analyzed, intensity--demodulating method was used to interrogate the wavelength of the fiber Bragg grating based on the building up of an experimental platform, and demodulation experiment of pre and post series of fiber Bragg grating was completed. The results show that the wavelength demodulation of the system has high linearity for fiber Bragg grating, the system gives a wavelength accuracy of 0.001 nm, and demodulation error caused by crosstalk between different sensors is 0.0005 nm. The measurement error of human body temperature is +/- 0.16 degrees C. It can be applied to the human body temperature measurement.

  13. Intelligent Tools for Planning Knowledge base Development and Verification

    Science.gov (United States)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

  14. The Effect of Multiple Intelligence-Based Instruction on Critical Thinking of Full Day Islamic Elementary Schools Students

    Directory of Open Access Journals (Sweden)

    Alhamuddin Alhamuddin

    2016-09-01

    Full Text Available Lack of critical thinking skills of elementary schools’ students was influenced by teachers’ domination in instructional activities; meanwhile students did not play independently as the learners. Theoretically, multiple intelligences based instruction is an appropriate solution. For that reason, this research aims to know the impact of multiple intelligences based instruction on students' critical thinking skills. The research was conducted at Al-Amanah and Buahati Islamic Elementary Schools by using a quantitative approach with case study method. Data collected through critical thinking tests was analyzed by using independent sample t-test to examine the impact of instruction on students' critical thinking skills. The results showed that the implementation of multiple intelligences based intruction had significant effect on students’ critical thinking skills. From the finding, some recommendations are given as follows: 1 The teacher’s role is not only for transferring knowledge based on his/her competencies but also students’ characteristics reflecting their instruction styles; and 2 for further researcher, it is suggested to investigate this issues more specifically and comprehensively.   Kurangnya keterampilan berpikir kritis dari siswa sekolah dasar dipengaruhi oleh dominasi guru dalam kegiatan pembelajaran; Sementara itu siswa tidak bermain secara independen sebagai peserta didik. Secara teoritis, pendekatan berbasis kecerdasan ganda merupakan solusi yang tepat. Untuk itu, penelitian ini bertujuan untuk mengetahui dampak pendekatan berbasis kecerdasan ganda pada keterampilan berpikir kritis siswa. Penelitian ini dilakukan di Sekolah Dasar Islam Al-Amanah dan Buahati dengan menggunakan pendekatan kuantitatif dengan metode studi kasus. Data dikumpulkan melalui tes berpikir kritis dianalisis dengan menggunakan sampel independent t-test untuk menguji dampak dari pendekatan pada keterampilan berpikir kritis siswa. Hasil penelitian

  15. Distributed and Collaborative Requirements Elicitation Based on Social Intelligence

    NARCIS (Netherlands)

    Wen, Bin; Luo, Z.; Liang, P.

    2012-01-01

    Requirements is the formal expression of user's needs. Also, requirements elicitation is the process of activity focusing on requirements collection. Traditional acquisition methods, such as interview, observation and prototype, are unsuited for the service-oriented software development featuring in

  16. Intelligent Furniture Design in the Elderly Based on the Cognitive Situation

    Directory of Open Access Journals (Sweden)

    Lu Xinhui

    2017-01-01

    Full Text Available This paper analyzes the present situation of Chinese elderly furniture and the elderly has cognitive characteristics that consciousness experiences and recognitions recede, cognitive fuzzy from Information processing. Expounds the elderly intelligent furniture design elements: functional elements required the elderly furniture is easy and simple to handle; Size and shape elements should be biased towards low, light type, reduce multifunction or fold function; colour collocation should use low lightness and low purity natural materials; Emotional elements design should meet the demand of the elderly social emotion. Introduction of intelligent furniture make up the cognitive decline in the elderly, Furniture judge the elderly demand by the inductor, Supplement by hardware control module to solve the special needs of the elderly life. Build design thinking based on the cognitive process and explore the elderly intelligent furniture design. This paper discusses the design process, for example and concludes the design rules: 1.The Operating Experience Pleasure. It is the height matching of user expectation and furniture function. Pleasure in the design of the operating parts mainly embodies in two aspects. Firstly, the Fitts Law; Secondly, it’s The Movement Optimization. 2.”Unconscious” Design. Intelligent furniture need to delete unnecessary operation module, make it easy to understand, furniture function and cognitive scene match with each other. 3. Modularity Design. Modularization can indirectly regulate the scale and specification of the design. Under the premise of individual character, customization, the compression of the cost, Designer should make the elderly intelligent furniture consistent with the user action.4.Design Consistency. The consistency principle reflected in the appearance, color and operation way consistency.

  17. Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study

    Science.gov (United States)

    Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

    The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they typically rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this chapter we present a semantically enabled image annotation and retrieval engine that is designed to satisfy the requirements of commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as presenting our initial thoughts on exploiting lexical databases for explicit semantic-based query expansion.

  18. Design of intelligent locks based on the triple KeeLoq algorithm

    Directory of Open Access Journals (Sweden)

    Huibin Chen

    2016-04-01

    Full Text Available KeeLoq algorithm with high security was usually used in wireless codec. Its security lack is indicated in this article according to the detailed rationale and the introduction of previous attack researches. Taking examples from Triple Data Encryption Standard algorithm, the triple KeeLoq codec algorithm was first proposed. Experimental results showed that the algorithm would not reduce powerful rolling effect and in consideration of limited computing power of embedded microcontroller three 64-bit keys were suitable to increase the crack difficulties and further improved its security. The method was applied to intelligent door access system for experimental verification. 16F690 extended Bluetooth or WiFi interface was employed to design the lock system on door. Key application was constructed on Android platform. The wireless communication between the lock on door and Android key application employed triple KeeLoq algorithm to ensure the higher security. Due to flexibility and multiformity (an Android key application with various keys of software-based keys, the solution owned overwhelmed advantages of low cost, high security, humanity, and green environmental protection.

  19. Development of 3D online contact measurement system for intelligent manufacturing based on stereo vision

    Science.gov (United States)

    Li, Peng; Chong, Wenyan; Ma, Yongjun

    2017-10-01

    In order to avoid shortcomings of low efficiency and restricted measuring range exsited in traditional 3D on-line contact measurement method for workpiece size, the development of a novel 3D contact measurement system is introduced, which is designed for intelligent manufacturing based on stereo vision. The developed contact measurement system is characterized with an intergarted use of a handy probe, a binocular stereo vision system, and advanced measurement software.The handy probe consists of six track markers, a touch probe and the associated elcetronics. In the process of contact measurement, the hand probe can be located by the use of the stereo vision system and track markers, and 3D coordinates of a space point on the workpiece can be mearsured by calculating the tip position of a touch probe. With the flexibility of the hand probe, the orientation, range, density of the 3D contact measurenent can be adptable to different needs. Applications of the developed contact measurement system to high-precision measurement and rapid surface digitization are experimentally demonstrated.

  20. A prediction model based on an artificial intelligence system for moderate to severe obstructive sleep apnea.

    Science.gov (United States)

    Sun, Lei Ming; Chiu, Hung-Wen; Chuang, Chih Yuan; Liu, Li

    2011-09-01

    Obstructive sleep apnea (OSA) is a major concern in modern medicine; however, it is difficult to diagnose. Screening questionnaires such as the Berlin questionnaire, Rome questionnaire, and BASH'IM score are used to identify patients with OSA. However, the sensitivity and specificity of these tools are not satisfactory. We aim to introduce an artificial intelligence method to screen moderate to severe OSA patients (apnea-hypopnea index ≧15). One hundred twenty patients were asked to complete a newly developed questionnaire before undergoing an overnight polysomnography (PSG) study. One hundred ten validated questionnaires were enrolled in this study. Genetic algorithm (GA) was used to build the five best models based on these questionnaires. The same data were analyzed with logistic regression (LR) for comparison. The sensitivity of the GA models varied from 81.8% to 88.0%, with a specificity of 95% to 97%. On the other hand, the sensitivity and specificity of the LR model were 55.6% and 57.9%, respectively. GA provides a good solution to build models for screening moderate to severe OSA patients, who require PSG evaluation and medical intervention. The questionnaire did not require any special biochemistry data and was easily self-administered. The sensitivity and specificity of the GA models are satisfactory and may improve when more patients are recruited.

  1. Intelligent transportation systems 802 11-based vehicular communications

    CERN Document Server

    Hasan, Syed Faraz; Chakraborty, Shyam

    2017-01-01

    This book begins by describing a mathematical model that represents disruption in WLAN-based Vehicular Communications. Secondly, it sets out to reduce the handover latency for establishing quick connections between the mobile nodes and the roadside WLAN APs.

  2. A Swarm-Based Learning Method Inspired by Social Insects

    Science.gov (United States)

    He, Xiaoxian; Zhu, Yunlong; Hu, Kunyuan; Niu, Ben

    Inspired by cooperative transport behaviors of ants, on the basis of Q-learning, a new learning method, Neighbor-Information-Reference (NIR) learning method, is present in the paper. This is a swarm-based learning method, in which principles of swarm intelligence are strictly complied with. In NIR learning, the i-interval neighbor's information, namely its discounted reward, is referenced when an individual selects the next state, so that it can make the best decision in a computable local neighborhood. In application, different policies of NIR learning are recommended by controlling the parameters according to time-relativity of concrete tasks. NIR learning can remarkably improve individual efficiency, and make swarm more "intelligent".

  3. Research on Intelligent Agriculture Greenhouses Based on Internet of Things Technology

    OpenAIRE

    Shang Ying; Fu An-Ying

    2017-01-01

    Internet of things is a hot topic in the field of research, get a lot of attention, On behalf of the future development trend of the network, Internet of Things has a wide range of applications, because of the efficient and reliable information transmission in modern agriculture. In the greenhouse, the conditions of the Greenhouse determine the quality of crops, high yield and many other aspects. Research on Intelligent Agriculture Greenhouses based on Internet of Things, mainly Research on h...

  4. MULTI AGENT-BASED ENVIRONMENTAL LANDSCAPE (MABEL) - AN ARTIFICIAL INTELLIGENCE SIMULATION MODEL: SOME EARLY ASSESSMENTS

    OpenAIRE

    Alexandridis, Konstantinos T.; Pijanowski, Bryan C.

    2002-01-01

    The Multi Agent-Based Environmental Landscape model (MABEL) introduces a Distributed Artificial Intelligence (DAI) systemic methodology, to simulate land use and transformation changes over time and space. Computational agents represent abstract relations among geographic, environmental, human and socio-economic variables, with respect to land transformation pattern changes. A multi-agent environment is developed providing task-nonspecific problem-solving abilities, flexibility on achieving g...

  5. Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

    OpenAIRE

    Ajay Kumar Saxena; S. 0. Bhatnagar; P. K Saxena

    2002-01-01

    Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives p...

  6. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

  7. Design of Bus Protocol Intelligent Initiation System Based On RS485

    Directory of Open Access Journals (Sweden)

    Li Liming

    2017-01-01

    Full Text Available In order to design an effective and reliable RS485 bus protocol based on RS485 bus, this paper introduces the structure and transmission mode of the command frame and the response frame, and also introduce four control measures and the communication in order to process quality of this system. The communication protocol is open, tolerant, reliable and fast, and can realize ignition more reliable and accurate in the intelligent initiation system.

  8. Based on Intelligent Robot of E-business Distribution Center Operation Mode Research

    Directory of Open Access Journals (Sweden)

    Li Juntao

    2016-01-01

    Full Text Available According to E-business distribution center operation mode in domestic and advanced experience drawing lessons at home and abroad, this paper based on intelligent robot researches E-business distribution center operation mode. And it proposes the innovation logistics storage in E-business and sorting integration system, and elaborates its principle, characteristics, as well as studies its business mode and logistics process, and its parameters and working mode of AGV equipment.

  9. Research Intelligent Precision Marketing of E-commerce Based on the Big Data

    OpenAIRE

    Jianhui Zhang; Junxuan Zhu

    2014-01-01

    This paper analyzed and summarized the development path of electronic commerce marketing based on the big data; the related aspects of intelligent precision marketing framework has been designed combined with smart technology; and describes its functional structure and operational processes. Taking into account the differences between e-commerce and traditional retail industry; constructed RFMA model combined with characterizes of the electricity suppliers, by means of k-means clustering to a...

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

    Science.gov (United States)

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

    2015-12-02

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

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

    Directory of Open Access Journals (Sweden)

    Manuel Castañón–Puga

    2015-12-01

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

  12. Algorithms in ambient intelligence

    NARCIS (Netherlands)

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

    2004-01-01

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

  13. 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

  14. 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.

  15. Fuzzy Sliding Mode Lateral Control of Intelligent Vehicle Based on Vision

    Directory of Open Access Journals (Sweden)

    Linhui Li

    2013-01-01

    Full Text Available The lateral control of intelligent vehicle is studied in this paper, with the intelligent vehicle DLUIV-1 based on visual navigation as the object of research. Firstly, the lateral control model based on visual preview is established. The kinematics model based on visual preview, including speed and other factors, is used to calculate the lateral error and direction error. Secondly, according to the characteristics of lateral control, an efficient strategy of intelligent vehicle lateral mode is proposed. The integration of the vehicle current lateral error and direction error is chosen as the parameter of the sliding mode switching function to design the sliding surface. The control variables are adjusted according to the fuzzy control rules to ensure that they meet the existence and reaching condition. The sliding mode switching function is regarded as the control objective, to ensure the stability of the steering wheel rotation. Simulation results show that the lateral controller can guarantee high path-tracking accuracy and strong robustness for the change of model parameters.

  16. Development of cyberblog-based intelligent tutorial system to improve students learning ability algorithm

    Science.gov (United States)

    Wahyudin; Riza, L. S.; Putro, B. L.

    2018-05-01

    E-learning as a learning activity conducted online by the students with the usual tools is favoured by students. The use of computer media in learning provides benefits that are not owned by other learning media that is the ability of computers to interact individually with students. But the weakness of many learning media is to assume that all students have a uniform ability, when in reality this is not the case. The concept of Intelligent Tutorial System (ITS) combined with cyberblog application can overcome the weaknesses in neglecting diversity. An Intelligent Tutorial System-based Cyberblog application (ITS) is a web-based interactive application program that implements artificial intelligence which can be used as a learning and evaluation media in the learning process. The use of ITS-based Cyberblog in learning is one of the alternative learning media that is interesting and able to help students in measuring ability in understanding the material. This research will be associated with the improvement of logical thinking ability (logical thinking) of students, especially in algorithm subjects.

  17. Brain Emotional Learning Based Intelligent Decoupler for Nonlinear Multi-Input Multi-Output Distillation Columns

    Directory of Open Access Journals (Sweden)

    M. H. El-Saify

    2017-01-01

    Full Text Available The distillation process is vital in many fields of chemical industries, such as the two-coupled distillation columns that are usually highly nonlinear Multi-Input Multi-Output (MIMO coupled processes. The control of MIMO process is usually implemented via a decentralized approach using a set of Single-Input Single-Output (SISO loop controllers. Decoupling the MIMO process into group of single loops requires proper input-output pairing and development of decoupling compensator unit. This paper proposes a novel intelligent decoupling approach for MIMO processes based on new MIMO brain emotional learning architecture. A MIMO architecture of Brain Emotional Learning Based Intelligent Controller (BELBIC is developed and applied as a decoupler for 4 input/4 output highly nonlinear coupled distillation columns process. Moreover, the performance of the proposed Brain Emotional Learning Based Intelligent Decoupler (BELBID is enhanced using Particle Swarm Optimization (PSO technique. The performance is compared with the PSO optimized steady state decoupling compensation matrix. Mathematical models of the distillation columns and the decouplers are built and tested in simulation environment by applying the same inputs. The results prove remarkable success of the BELBID in minimizing the loops interactions without degrading the output that every input has been paired with.

  18. Support vector machine based diagnostic system for breast cancer using swarm intelligence.

    Science.gov (United States)

    Chen, Hui-Ling; Yang, Bo; Wang, Gang; Wang, Su-Jing; Liu, Jie; Liu, Da-You

    2012-08-01

    Breast cancer is becoming a leading cause of death among women in the whole world, meanwhile, it is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. In this paper, a swarm intelligence technique based support vector machine classifier (PSO_SVM) is proposed for breast cancer diagnosis. In the proposed PSO-SVM, the issue of model selection and feature selection in SVM is simultaneously solved under particle swarm (PSO optimization) framework. A weighted function is adopted to design the objective function of PSO, which takes into account the average accuracy rates of SVM (ACC), the number of support vectors (SVs) and the selected features simultaneously. Furthermore, time varying acceleration coefficients (TVAC) and inertia weight (TVIW) are employed to efficiently control the local and global search in PSO algorithm. The effectiveness of PSO-SVM has been rigorously evaluated against the Wisconsin Breast Cancer Dataset (WBCD), which is commonly used among researchers who use machine learning methods for breast cancer diagnosis. The proposed system is compared with the grid search method with feature selection by F-score. The experimental results demonstrate that the proposed approach not only obtains much more appropriate model parameters and discriminative feature subset, but also needs smaller set of SVs for training, giving high predictive accuracy. In addition, Compared to the existing methods in previous studies, the proposed system can also be regarded as a promising success with the excellent classification accuracy of 99.3% via 10-fold cross validation (CV) analysis. Moreover, a combination of five informative features is identified, which might provide important insights to the nature of the breast cancer disease and give an important clue for the physicians to take a closer attention. We believe the promising result can ensure that the physicians make very accurate diagnostic decision in

  19. An intelligent trust-based access control model for affective ...

    African Journals Online (AJOL)

    In this study, a fuzzy expert system Trust-Based Access Control (TBAC) model for improving the Quality of crowdsourcing using emotional affective computing is presented. This model takes into consideration a pre-processing module consisting of three inputs such as crowd-workers category, trust metric and emotional ...

  20. An Intelligent Computer-Based System for Sign Language Tutoring

    Science.gov (United States)

    Ritchings, Tim; Khadragi, Ahmed; Saeb, Magdy

    2012-01-01

    A computer-based system for sign language tutoring has been developed using a low-cost data glove and a software application that processes the movement signals for signs in real-time and uses Pattern Matching techniques to decide if a trainee has closely replicated a teacher's recorded movements. The data glove provides 17 movement signals from…

  1. A Personalised Profile-Based Intelligent and Adaptive Energy

    African Journals Online (AJOL)

    2015-05-11

    May 11, 2015 ... Increasing electronic waste has forced the mobile phone industry to move into a new era of energy ... Based on the information gathered, a mobile application, MoBateriE, was designed. ...... Thesis (PhD). Carnegie Mellon ...

  2. Roadmap to tracking based business and intelligent products

    NARCIS (Netherlands)

    Holmström, J.; Kajosaari, R.; Främling, K.; Langius, E.A.F.

    2009-01-01

    Item-centric tracking is an opportunity to increase visibility and control in different operations of a company. The economical feasibility of item-centric tracking is based on recent technological developments for monitoring the material flow on the item-level instead of the material type-level. It

  3. SmartWeld/SmartProcess - intelligent model based system for the design and validation of welding processes

    Energy Technology Data Exchange (ETDEWEB)

    Mitchner, J.

    1996-04-01

    Diagrams are presented on an intelligent model based system for the design and validation of welding processes. Key capabilities identified include `right the first time` manufacturing, continuous improvement, and on-line quality assurance.

  4. Vision based interface system for hands free control of an intelligent wheelchair

    Directory of Open Access Journals (Sweden)

    Kim Eun

    2009-08-01

    Full Text Available Abstract Background Due to the shift of the age structure in today's populations, the necessities for developing the devices or technologies to support them have been increasing. Traditionally, the wheelchair, including powered and manual ones, is the most popular and important rehabilitation/assistive device for the disabled and the elderly. However, it is still highly restricted especially for severely disabled. As a solution to this, the Intelligent Wheelchairs (IWs have received considerable attention as mobility aids. The purpose of this work is to develop the IW interface for providing more convenient and efficient interface to the people the disability in their limbs. Methods This paper proposes an intelligent wheelchair (IW control system for the people with various disabilities. To facilitate a wide variety of user abilities, the proposed system involves the use of face-inclination and mouth-shape information, where the direction of an IW is determined by the inclination of the user's face, while proceeding and stopping are determined by the shapes of the user's mouth. Our system is composed of electric powered wheelchair, data acquisition board, ultrasonic/infra-red sensors, a PC camera, and vision system. Then the vision system to analyze user's gestures is performed by three stages: detector, recognizer, and converter. In the detector, the facial region of the intended user is first obtained using Adaboost, thereafter the mouth region is detected based on edge information. The extracted features are sent to the recognizer, which recognizes the face inclination and mouth shape using statistical analysis and K-means clustering, respectively. These recognition results are then delivered to the converter to control the wheelchair. Result & conclusion The advantages of the proposed system include 1 accurate recognition of user's intention with minimal user motion and 2 robustness to a cluttered background and the time-varying illumination

  5. Intelligent DNA-based molecular diagnostics using linked genetic markers

    Energy Technology Data Exchange (ETDEWEB)

    Pathak, D.K.; Perlin, M.W.; Hoffman, E.P.

    1994-12-31

    This paper describes a knowledge-based system for molecular diagnostics, and its application to fully automated diagnosis of X-linked genetic disorders. Molecular diagnostic information is used in clinical practice for determining genetic risks, such as carrier determination and prenatal diagnosis. Initially, blood samples are obtained from related individuals, and PCR amplification is performed. Linkage-based molecular diagnosis then entails three data analysis steps. First, for every individual, the alleles (i.e., DNA composition) are determined at specified chromosomal locations. Second, the flow of genetic material among the individuals is established. Third, the probability that a given individual is either a carrier of the disease or affected by the disease is determined. The current practice is to perform each of these three steps manually, which is costly, time consuming, labor-intensive, and error-prone. As such, the knowledge-intensive data analysis and interpretation supersede the actual experimentation effort as the major bottleneck in molecular diagnostics. By examining the human problem solving for the task, we have designed and implemented a prototype knowledge-based system capable of fully automating linkage-based molecular diagnostics in X-linked genetic disorders, including Duchenne Muscular Dystrophy (DMD). Our system uses knowledge-based interpretation of gel electrophoresis images to determine individual DNA marker labels, a constraint satisfaction search for consistent genetic flow among individuals, and a blackboard-style problem solver for risk assessment. We describe the system`s successful diagnosis of DMD carrier and affected individuals from raw clinical data.

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

    Directory of Open Access Journals (Sweden)

    Anna Maria Misiak

    2016-06-01

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

  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. Intelligent fault diagnosis of rolling bearing based on kernel neighborhood rough sets and statistical features

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Xiao Ran; Zhang, You Yun; Zhu, Yong Sheng [Xi' an Jiaotong Univ., Xi' an (China)

    2012-09-15

    Intelligent fault diagnosis benefits from efficient feature selection. Neighborhood rough sets are effective in feature selection. However, determining the neighborhood value accurately remains a challenge. The wrapper feature selection algorithm is designed by combining the kernel method and neighborhood rough sets to self-adaptively select sensitive features. The combination effectively solves the shortcomings in selecting the neighborhood value in the previous application process. The statistical features of time and frequency domains are used to describe the characteristic of the rolling bearing to make the intelligent fault diagnosis approach work. Three classification algorithms, namely, classification and regression tree (CART), commercial version 4.5 (C4.5), and radial basis function support vector machines (RBFSVM), are used to test UCI datasets and 10 fault datasets of rolling bearing. The results indicate that the diagnostic approach presented could effectively select the sensitive fault features and simultaneously identify the type and degree of the fault.

  11. Intelligent fault diagnosis of rolling bearing based on kernel neighborhood rough sets and statistical features

    International Nuclear Information System (INIS)

    Zhu, Xiao Ran; Zhang, You Yun; Zhu, Yong Sheng

    2012-01-01

    Intelligent fault diagnosis benefits from efficient feature selection. Neighborhood rough sets are effective in feature selection. However, determining the neighborhood value accurately remains a challenge. The wrapper feature selection algorithm is designed by combining the kernel method and neighborhood rough sets to self-adaptively select sensitive features. The combination effectively solves the shortcomings in selecting the neighborhood value in the previous application process. The statistical features of time and frequency domains are used to describe the characteristic of the rolling bearing to make the intelligent fault diagnosis approach work. Three classification algorithms, namely, classification and regression tree (CART), commercial version 4.5 (C4.5), and radial basis function support vector machines (RBFSVM), are used to test UCI datasets and 10 fault datasets of rolling bearing. The results indicate that the diagnostic approach presented could effectively select the sensitive fault features and simultaneously identify the type and degree of the fault

  12. Wearable computer for mobile augmented-reality-based controlling of an intelligent robot

    Science.gov (United States)

    Turunen, Tuukka; Roening, Juha; Ahola, Sami; Pyssysalo, Tino

    2000-10-01

    An intelligent robot can be utilized to perform tasks that are either hazardous or unpleasant for humans. Such tasks include working in disaster areas or conditions that are, for example, too hot. An intelligent robot can work on its own to some extent, but in some cases the aid of humans will be needed. This requires means for controlling the robot from somewhere else, i.e. teleoperation. Mobile augmented reality can be utilized as a user interface to the environment, as it enhances the user's perception of the situation compared to other interfacing methods and allows the user to perform other tasks while controlling the intelligent robot. Augmented reality is a method that combines virtual objects into the user's perception of the real world. As computer technology evolves, it is possible to build very small devices that have sufficient capabilities for augmented reality applications. We have evaluated the existing wearable computers and mobile augmented reality systems to build a prototype of a future mobile terminal- the CyPhone. A wearable computer with sufficient system resources for applications, wireless communication media with sufficient throughput and enough interfaces for peripherals has been built at the University of Oulu. It is self-sustained in energy, with enough operating time for the applications to be useful, and uses accurate positioning systems.

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

    OpenAIRE

    Beczkowski, Szymon

    2012-01-01

    High power light-emitting diodes allow the creation of luminaires capable of generating saturated colour light at very high efficacies. Contrary to traditional light sources like incandescent and high-intensity discharge lamps, where colour is generated using filters, LEDs use additive light mixing, where the intensity of each primary colour diode has to be adjusted to the needed intensity to generate specified colour. The function of LED driver is to supply the diode with power needed to ach...

  14. Multiple estimation channel decoupling and optimization method based on inverse system

    Science.gov (United States)

    Wu, Peng; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng

    2018-03-01

    This paper addressed the intelligent autonomous navigation request of intelligent deformation missile, based on the intelligent deformation missile dynamics and kinematics modeling, navigation subsystem solution method and error modeling, and then focuses on the corresponding data fusion and decision fusion technology, decouples the sensitive channel of the filter input through the inverse system of design dynamics to reduce the influence of sudden change of the measurement information on the filter input. Then carrying out a series of simulation experiments, which verified the feasibility of the inverse system decoupling algorithm effectiveness.

  15. Parallel Computational Intelligence-Based Multi-Camera Surveillance System

    OpenAIRE

    Orts-Escolano, Sergio; Garcia-Rodriguez, Jose; Morell, Vicente; Cazorla, Miguel; Azorin-Lopez, Jorge; García-Chamizo, Juan Manuel

    2014-01-01

    In this work, we present a multi-camera surveillance system based on the use of self-organizing neural networks to represent events on video. The system processes several tasks in parallel using GPUs (graphic processor units). It addresses multiple vision tasks at various levels, such as segmentation, representation or characterization, analysis and monitoring of the movement. These features allow the construction of a robust representation of the environment and interpret the behavior of mob...

  16. A Proposed Intelligent Policy-Based Interface for a Mobile eHealth Environment

    Science.gov (United States)

    Tavasoli, Amir; Archer, Norm

    Users of mobile eHealth systems are often novices, and the learning process for them may be very time consuming. In order for systems to be attractive to potential adopters, it is important that the interface should be very convenient and easy to learn. However, the community of potential users of a mobile eHealth system may be quite varied in their requirements, so the system must be able to adapt easily to suit user preferences. One way to accomplish this is to have the interface driven by intelligent policies. These policies can be refined gradually, using inputs from potential users, through intelligent agents. This paper develops a framework for policy refinement for eHealth mobile interfaces, based on dynamic learning from user interactions.

  17. Visualization of suspicious lesions in breast MRI based on intelligent neural systems

    Science.gov (United States)

    Twellmann, Thorsten; Lange, Oliver; Nattkemper, Tim Wilhelm; Meyer-Bäse, Anke

    2006-05-01

    Intelligent medical systems based on supervised and unsupervised artificial neural networks are applied to the automatic visualization and classification of suspicious lesions in breast MRI. These systems represent an important component of future sophisticated computer-aided diagnosis systems and enable the extraction of spatial and temporal features of dynamic MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogenity of the cancerous tissue, these techniques reveal the malignant, benign and normal kinetic signals and and provide a regional subclassification of pathological breast tissue. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.

  18. A Web-Based Authoring Tool for Algebra-Related Intelligent Tutoring Systems

    Directory of Open Access Journals (Sweden)

    Maria Virvou

    2000-01-01

    Full Text Available This paper describes the development of a web-based authoring tool for Intelligent Tutoring Systems. The tool aims to be useful to teachers and students of domains that make use of algebraic equations. The initial input to the tool is a "description" of a specific domain given by a human teacher. In return the tool provides assistance at the construction of exercises by the human teacher and then monitors the students while they are solving the exercises and provides appropriate feedback. The tool incorporates intelligence in its diagnostic component, which performs error diagnosis to students’ errors. It also handles the teaching material in a flexible and individualised way.

  19. 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.

  20. A multi-resolution envelope-power based model for speech intelligibility

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Ewert, Stephan D.; Dau, Torsten

    2013-01-01

    The speech-based envelope power spectrum model (sEPSM) presented by Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] estimates the envelope power signal-to-noise ratio (SNRenv) after modulation-frequency selective processing. Changes in this metric were shown to account well...... to conditions with stationary interferers, due to the long-term integration of the envelope power, and cannot account for increased intelligibility typically obtained with fluctuating maskers. Here, a multi-resolution version of the sEPSM is presented where the SNRenv is estimated in temporal segments...... with a modulation-filter dependent duration. The multi-resolution sEPSM is demonstrated to account for intelligibility obtained in conditions with stationary and fluctuating interferers, and noisy speech distorted by reverberation or spectral subtraction. The results support the hypothesis that the SNRenv...