WorldWideScience

Sample records for integrating model-based artificial

  1. Integration of model-based control systems with artificial intelligence and workstations

    International Nuclear Information System (INIS)

    Lee, M.; Clearwater, S.

    1987-01-01

    Experience with model based accelerator control started at SPEAR. Since that SPEAR. Since that time nearly all accelerator beam lines have been controlled using model-based application programs, for example, PEP and SLC at SLAC. In order to take advantage of state-of-the-art hardware and software technology, the design and implementation of the accelerator control programs have undergone radical changes with time. Consequently, SPEAR, PEP, and SLC all use different control programs. Since many of these application programs are imbedded deep into the control system, they had to be rewritten each time. Each time this rewriting has occurred a great deal of time and effort has been spent on training physicists and programmers to do the job. Now, these application programs have been developed for a fourth time. This time, however, the programs being developed are generic so that they will not have to be done again. An integrated system called GOLD (Generic Orbit ampersand Lattice Debugger) has been developed for debugging and correcting trajectory errors in accelerator lattices. The system consists of a lattice modeling program (COMFORT), a beam simulator (PLUS), a graphical workstation environment (micro-VAX) and an expert system (ABLE). This paper will describe some of the features and applications of our integrated system with emphasis on the automation offered by expert systems. 5 refs., 4 figs

  2. GOLD: Integration of model-based control systems with artificial intelligence and workstations

    International Nuclear Information System (INIS)

    Lee, M.; Clearwater, S.

    1987-08-01

    Our experience with model-based accelerator control started at SPEAR. Since that time nearly all accelerator beamlines have been controlled using model-based application programs, for example, PEP and SLC at SLAC. In order to take advantage of state-of-the-art hardware and software technology, the design and implementation of the accelerator control programs have undergone radical changes with time. Consequently, SPEAR, PEP and SLC all use different control programs. Since many of these application programs are embedded deep into the control system, they had to be rewritten each time. Each time this rewriting has occurred a great deal of time and effort has been spent on training physicists and programmers to do the job. Now, we have developed an integrated system called GOLD (Genetic Orbit and Lattice Debugger) for debugging and correcting trajectory errors in accelerator lattices. The system consists of a lattice modeling program (COMFORT), a beam simulator (PLUS), a graphical workstation environment (micro-VAX) and an expert system (ABLE). This paper will describe some of the features and applications of our integrated system with emphasis on the automation offered by expert systems. 5 refs

  3. GOLD: Integration of model-based control systems with artificial intelligence and workstations

    International Nuclear Information System (INIS)

    Lee, M.; Clearwater, S.

    1987-08-01

    Our experience with model based accelerator control started at SPEAR. Since that time nearly all accelerator beam lines have been controlled using model-based application programs, for example, PEP and SLC at SLAC. In order to take advantage of state-of-the-art hardware and software technology, the design and implementation of the accelerator control programs have undergone radical change with time. Consequently, SPEAR, PEP, and SLC all use different control programs. Since many of these application programs are imbedded deep into the control system, they had to be rewritten each time. Each time this rewriting has occurred a great deal of time and effort has been spent on training physicists and programmers to do the job. Now, we have developed these application programs for a fourth time. This time, however, the programs we are developing are generic so that we will not have to do it again. We have developed an integrated system called GOLD (Generic Orbit and Lattice Debugger) for debugging and correcting trajectory errors in accelerator lattices. The system consists of a lattice modeling program (COMFORT), a beam simulator (PLUS), a graphical workstation environment (micro-VAX) and an expert system (ABLE). This paper will describe some of the features and applications of our integrated system with emphasis on the automation offered by expert systems. 5 refs

  4. Artificial emotional model based on finite state machine

    Institute of Scientific and Technical Information of China (English)

    MENG Qing-mei; WU Wei-guo

    2008-01-01

    According to the basic emotional theory, the artificial emotional model based on the finite state machine(FSM) was presented. In finite state machine model of emotion, the emotional space included the basic emotional space and the multiple emotional spaces. The emotion-switching diagram was defined and transition function was developed using Markov chain and linear interpolation algorithm. The simulation model was built using Stateflow toolbox and Simulink toolbox based on the Matlab platform.And the model included three subsystems: the input one, the emotion one and the behavior one. In the emotional subsystem, the responses of different personalities to the external stimuli were described by defining personal space. This model takes states from an emotional space and updates its state depending on its current state and a state of its input (also a state-emotion). The simulation model realizes the process of switching the emotion from the neutral state to other basic emotions. The simulation result is proved to correspond to emotion-switching law of human beings.

  5. Model-Based Integration and Interpretation of Data

    DEFF Research Database (Denmark)

    Petersen, Johannes

    2004-01-01

    Data integration and interpretation plays a crucial role in supervisory control. The paper defines a set of generic inference steps for the data integration and interpretation process based on a three-layer model of system representations. The three-layer model is used to clarify the combination...... of constraint and object-centered representations of the work domain throwing new light on the basic principles underlying the data integration and interpretation process of Rasmussen's abstraction hierarchy as well as other model-based approaches combining constraint and object-centered representations. Based...

  6. Modular Architecture for Integrated Model-Based Decision Support.

    Science.gov (United States)

    Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

    2018-01-01

    Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

  7. Improved prediction of higher heating value of biomass using an artificial neural network model based on proximate analysis.

    Science.gov (United States)

    Uzun, Harun; Yıldız, Zeynep; Goldfarb, Jillian L; Ceylan, Selim

    2017-06-01

    As biomass becomes more integrated into our energy feedstocks, the ability to predict its combustion enthalpies from routine data such as carbon, ash, and moisture content enables rapid decisions about utilization. The present work constructs a novel artificial neural network model with a 3-3-1 tangent sigmoid architecture to predict biomasses' higher heating values from only their proximate analyses, requiring minimal specificity as compared to models based on elemental composition. The model presented has a considerably higher correlation coefficient (0.963) and lower root mean square (0.375), mean absolute (0.328), and mean bias errors (0.010) than other models presented in the literature which, at least when applied to the present data set, tend to under-predict the combustion enthalpy. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Integrated optimization of temperature, CO2, screen use and artificial lighting in greenhouse crops

    DEFF Research Database (Denmark)

    Aaslyng, J.M.; Körner, O.; Andreassen, A.U.

    2005-01-01

    A leaf photosynthesis model is suggested for integrated optimization of temperature, CO2, screen use and artificial lighting in greenhouse crops. Three different approaches for the optimization are presented. First, results from greenhouse experiments with model based optimization are presented....... Second, a model-based analysis of a commercial grower's production possibility is shown. Third, results from a simulation of the effect of a new lighting strategy are demonstrated. The results demonstrate that it is possible to optimize plant production by using a model-based integrated optimization...... of temperature, CO2, and light in the greenhouse...

  9. Medical Device Integration Model Based on the Internet of Things

    Science.gov (United States)

    Hao, Aiyu; Wang, Ling

    2015-01-01

    At present, hospitals in our country have basically established the HIS system, which manages registration, treatment, and charge, among many others, of patients. During treatment, patients need to use medical devices repeatedly to acquire all sorts of inspection data. Currently, the output data of the medical devices are often manually input into information system, which is easy to get wrong or easy to cause mismatches between inspection reports and patients. For some small hospitals of which information construction is still relatively weak, the information generated by the devices is still presented in the form of paper reports. When doctors or patients want to have access to the data at a given time again, they can only look at the paper files. Data integration between medical devices has long been a difficult problem for the medical information system, because the data from medical devices are lack of mandatory unified global standards and have outstanding heterogeneity of devices. In order to protect their own interests, manufacturers use special protocols, etc., thus causing medical decices to still be the "lonely island" of hospital information system. Besides, unfocused application of the data will lead to failure to achieve a reasonable distribution of medical resources. With the deepening of IT construction in hospitals, medical information systems will be bound to develop towards mobile applications, intelligent analysis, and interconnection and interworking, on the premise that there is an effective medical device integration (MDI) technology. To this end, this paper presents a MDI model based on the Internet of Things (IoT). Through abstract classification, this model is able to extract the common characteristics of the devices, resolve the heterogeneous differences between them, and employ a unified protocol to integrate data between devices. And by the IoT technology, it realizes interconnection network of devices and conducts associate matching

  10. 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.

  11. Model-Based Fault Diagnosis in Electric Drive Inverters Using Artificial Neural Network

    National Research Council Canada - National Science Library

    Masrur, Abul; Chen, ZhiHang; Zhang, Baifang; Jia, Hongbin; Murphey, Yi-Lu

    2006-01-01

    .... A normal model and various faulted models of the inverter-motor combination were developed, and voltages and current signals were generated from those models to train an artificial neural network for fault diagnosis...

  12. 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.

  13. Integrating Design Decision Management with Model-based Software Development

    DEFF Research Database (Denmark)

    Könemann, Patrick

    Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts...... of the system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design decisions is often manual and tedious work on design models. Moreover, keeping design models consistent......, or by ignoring the causes. This substitutes manual reviews to some extent. The concepts, implemented in a tool, have been validated with design patterns, refactorings, and domain level tests that comprise a replay of a real project. This proves the applicability of the solution to realistic examples...

  14. Log-linear model based behavior selection method for artificial fish swarm algorithm.

    Science.gov (United States)

    Huang, Zhehuang; Chen, Yidong

    2015-01-01

    Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

  15. Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

    Directory of Open Access Journals (Sweden)

    Zhehuang Huang

    2015-01-01

    Full Text Available Artificial fish swarm algorithm (AFSA is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

  16. Integrated Artificial Intelligence Approaches for Disease Diagnostics.

    Science.gov (United States)

    Vashistha, Rajat; Chhabra, Deepak; Shukla, Pratyoosh

    2018-06-01

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

  17. Design of model based LQG control for integrated building systems

    NARCIS (Netherlands)

    Yahiaoui, A.; Hensen, J.L.M.; Soethout, L.L.; Paassen, van A.H.C.

    2006-01-01

    The automation of the operation of integrated building systems requires using modern control techniques to enhance the quality of the building indoor environments. This paper describes the theatrical base and practical application of an optimal dynamic regulator using modelbased Linear Quadratic

  18. Adaptive integration of daylight and artificial lighting

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve

    2016-01-01

    Daylight is dynamic and dependent upon weather conditions; unfolding with both subtle and dramatic variations in qualities of light. Through a building’s apertures, daylight creates a connection between the space inside and the world outside. The aperture or window itself constitutes the frame...... with the world. In contrast to fluctuating daylight, a specific distinctive feature of artificial light has been – until very recently – its constancy in colour and intensity. However, by virtue of the technological convertibility of LEDs in concert with digital control systems, LEDs are capable of dynamically...... producing variations in colour and intensity in ways that correspond to our experiences of the daylight. Daylight and artificial lighting are thus positioned in a new relationship to one another. Metaphorically, one can think of the adaptive software as ‘digital weather’ – as a self-generating and shifting...

  19. Integrated model-based retargeting and optical proximity correction

    Science.gov (United States)

    Agarwal, Kanak B.; Banerjee, Shayak

    2011-04-01

    Conventional resolution enhancement techniques (RET) are becoming increasingly inadequate at addressing the challenges of subwavelength lithography. In particular, features show high sensitivity to process variation in low-k1 lithography. Process variation aware RETs such as process-window OPC are becoming increasingly important to guarantee high lithographic yield, but such techniques suffer from high runtime impact. An alternative to PWOPC is to perform retargeting, which is a rule-assisted modification of target layout shapes to improve their process window. However, rule-based retargeting is not a scalable technique since rules cannot cover the entire search space of two-dimensional shape configurations, especially with technology scaling. In this paper, we propose to integrate the processes of retargeting and optical proximity correction (OPC). We utilize the normalized image log slope (NILS) metric, which is available at no extra computational cost during OPC. We use NILS to guide dynamic target modification between iterations of OPC. We utilize the NILS tagging capabilities of Calibre TCL scripting to identify fragments with low NILS. We then perform NILS binning to assign different magnitude of retargeting to different NILS bins. NILS is determined both for width, to identify regions of pinching, and space, to locate regions of potential bridging. We develop an integrated flow for 1x metal lines (M1) which exhibits lesser lithographic hotspots compared to a flow with just OPC and no retargeting. We also observe cases where hotspots that existed in the rule-based retargeting flow are fixed using our methodology. We finally also demonstrate that such a retargeting methodology does not significantly alter design properties by electrically simulating a latch layout before and after retargeting. We observe less than 1% impact on latch Clk-Q and D-Q delays post-retargeting, which makes this methodology an attractive one for use in improving shape process windows

  20. Comparison of Groundwater Level Models Based on Artificial Neural Networks and ANFIS.

    Science.gov (United States)

    Djurovic, Nevenka; Domazet, Milka; Stricevic, Ruzica; Pocuca, Vesna; Spalevic, Velibor; Pivic, Radmila; Gregoric, Enika; Domazet, Uros

    2015-01-01

    Water table forecasting plays an important role in the management of groundwater resources in agricultural regions where there are drainage systems in river valleys. The results presented in this paper pertain to an area along the left bank of the Danube River, in the Province of Vojvodina, which is the northern part of Serbia. Two soft computing techniques were used in this research: an adaptive neurofuzzy inference system (ANFIS) and an artificial neural network (ANN) model for one-month water table forecasts at several wells located at different distances from the river. The results suggest that both these techniques represent useful tools for modeling hydrological processes in agriculture, with similar computing and memory capabilities, such that they constitute an exceptionally good numerical framework for generating high-quality models.

  1. Parameter identification of piezoelectric hysteresis model based on improved artificial bee colony algorithm

    Science.gov (United States)

    Wang, Geng; Zhou, Kexin; Zhang, Yeming

    2018-04-01

    The widely used Bouc-Wen hysteresis model can be utilized to accurately simulate the voltage-displacement curves of piezoelectric actuators. In order to identify the unknown parameters of the Bouc-Wen model, an improved artificial bee colony (IABC) algorithm is proposed in this paper. A guiding strategy for searching the current optimal position of the food source is proposed in the method, which can help balance the local search ability and global exploitation capability. And the formula for the scout bees to search for the food source is modified to increase the convergence speed. Some experiments were conducted to verify the effectiveness of the IABC algorithm. The results show that the identified hysteresis model agreed well with the actual actuator response. Moreover, the identification results were compared with the standard particle swarm optimization (PSO) method, and it can be seen that the search performance in convergence rate of the IABC algorithm is better than that of the standard PSO method.

  2. Comparison of Groundwater Level Models Based on Artificial Neural Networks and ANFIS

    Directory of Open Access Journals (Sweden)

    Nevenka Djurovic

    2015-01-01

    Full Text Available Water table forecasting plays an important role in the management of groundwater resources in agricultural regions where there are drainage systems in river valleys. The results presented in this paper pertain to an area along the left bank of the Danube River, in the Province of Vojvodina, which is the northern part of Serbia. Two soft computing techniques were used in this research: an adaptive neurofuzzy inference system (ANFIS and an artificial neural network (ANN model for one-month water table forecasts at several wells located at different distances from the river. The results suggest that both these techniques represent useful tools for modeling hydrological processes in agriculture, with similar computing and memory capabilities, such that they constitute an exceptionally good numerical framework for generating high-quality models.

  3. A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

    Science.gov (United States)

    Othman, Zulaiha Ali

    2014-01-01

    Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition. PMID:25165748

  4. Short-Term Solar Irradiance Forecasting Model Based on Artificial Neural Network Using Statistical Feature Parameters

    Directory of Open Access Journals (Sweden)

    Hongshan Zhao

    2012-05-01

    Full Text Available Short-term solar irradiance forecasting (STSIF is of great significance for the optimal operation and power predication of grid-connected photovoltaic (PV plants. However, STSIF is very complex to handle due to the random and nonlinear characteristics of solar irradiance under changeable weather conditions. Artificial Neural Network (ANN is suitable for STSIF modeling and many research works on this topic are presented, but the conciseness and robustness of the existing models still need to be improved. After discussing the relation between weather variations and irradiance, the characteristics of the statistical feature parameters of irradiance under different weather conditions are figured out. A novel ANN model using statistical feature parameters (ANN-SFP for STSIF is proposed in this paper. The input vector is reconstructed with several statistical feature parameters of irradiance and ambient temperature. Thus sufficient information can be effectively extracted from relatively few inputs and the model complexity is reduced. The model structure is determined by cross-validation (CV, and the Levenberg-Marquardt algorithm (LMA is used for the network training. Simulations are carried out to validate and compare the proposed model with the conventional ANN model using historical data series (ANN-HDS, and the results indicated that the forecast accuracy is obviously improved under variable weather conditions.

  5. Artificial bee colony in neuro - Symbolic integration

    Science.gov (United States)

    Kasihmuddin, Mohd Shareduwan Mohd; Sathasivam, Saratha; Mansor, Mohd. Asyraf

    2017-08-01

    Swarm intelligence is a research area that models the population of the swarm based on natural computation. Artificial bee colony (ABC) algorithm is a swarm based metaheuristic algorithm introduced by Karaboga to optimize numerical problem. Pattern-SAT is a pattern reconstruction paradigm that utilized 2SAT logical rule in representing the behavior of the desired pattern. The information of the desired pattern in terms of 2SAT logic is embedded to Hopfield neural network (HNN-P2SAT) and the desired pattern is reconstructed during the retrieval phase. Since the performance of HNN-P2SAT in Pattern-SAT deteriorates when the number of 2SAT clause increased, newly improved ABC is used to reduce the computation burden during the learning phase of HNN-P2SAT (HNN-P2SATABC). The aim of this study is to investigate the performance of Pattern-SAT produced by ABC incorporated with HNN-P2SAT and compare it with conventional standalone HNN. The comparison is examined by using Microsoft Visual Basic C++ 2013 software. The detailed comparison in doing Pattern-SAT is discussed based on global Pattern-SAT, ratio of activated clauses and computation time. The result obtained from computer simulation indicates the beneficial features of HNN-P2SATABC in doing Pattern-SAT. This finding is expected to result in a significant implication on the choice of searching method used to do Pattern-SAT.

  6. Integration of supervisory control synthesis in model-based systems engineering

    NARCIS (Netherlands)

    Baeten, J.C.M.; van de Mortel - Fronczak, J.M.; Rooda, J.E.

    2016-01-01

    Increasing system complexity, time to market and development costs reduction place higher demands on engineering processes. Formal models play an important role here because they enable the use of various model-based analyses and early integration techniques and tools. Engineering processes based on

  7. Methodology for Developing Hydrological Models Based on an Artificial Neural Network to Establish an Early Warning System in Small Catchments

    Directory of Open Access Journals (Sweden)

    Ivana Sušanj

    2016-01-01

    Full Text Available In some situations, there is no possibility of hazard mitigation, especially if the hazard is induced by water. Thus, it is important to prevent consequences via an early warning system (EWS to announce the possible occurrence of a hazard. The aim and objective of this paper are to investigate the possibility of implementing an EWS in a small-scale catchment and to develop a methodology for developing a hydrological prediction model based on an artificial neural network (ANN as an essential part of the EWS. The methodology is implemented in the case study of the Slani Potok catchment, which is historically recognized as a hazard-prone area, by establishing continuous monitoring of meteorological and hydrological parameters to collect data for the training, validation, and evaluation of the prediction capabilities of the ANN model. The model is validated and evaluated by visual and common calculation approaches and a new evaluation for the assessment. This new evaluation is proposed based on the separation of the observed data into classes based on the mean data value and the percentages of classes above or below the mean data value as well as on the performance of the mean absolute error.

  8. Securing Digital Images Integrity using Artificial Neural Networks

    Science.gov (United States)

    Hajji, Tarik; Itahriouan, Zakaria; Ouazzani Jamil, Mohammed

    2018-05-01

    Digital image signature is a technique used to protect the image integrity. The application of this technique can serve several areas of imaging applied to smart cities. The objective of this work is to propose two methods to protect digital image integrity. We present a description of two approaches using artificial neural networks (ANN) to digitally sign an image. The first one is “Direct Signature without learning” and the second is “Direct Signature with learning”. This paper presents the theory of proposed approaches and an experimental study to test their effectiveness.

  9. State of the Art : Integrated Management of Requirements in Model-Based Software Engineering

    OpenAIRE

    Thörn, Christer

    2006-01-01

    This report describes the background and future of research concerning integrated management of requirements in model-based software engineering. The focus is on describing the relevant topics and existing theoretical backgrounds that form the basis for the research. The report describes the fundamental difficulties of requirements engineering for software projects, and proposes that the results and methods of models in software engineering can help leverage those problems. Taking inspiration...

  10. An integrated artificial neural networks approach for predicting global radiation

    International Nuclear Information System (INIS)

    Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

    2009-01-01

    This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

  11. Anti-logic or common sense that can hinder machine’s energy performance: Energy and comfort control models based on artificial intelligence responding to abnormal indoor environments

    International Nuclear Information System (INIS)

    Ahn, Jonghoon; Cho, Soolyeon

    2017-01-01

    Highlights: •Integrated energy control model improves thermal comfort and mitigates an increase of energy consumption. •Communication between heating and cooling, thermal comfort, and decision making models optimizes energy supply. •PMV model effectively rectifies set-point temperature to reduce thermal dissatisfaction in various conditions. •Five-step decision making model properly responds to abnormal situations derived from human anti-logic or common sense. •Integrated model can be extended for managing risks caused by fire or disasters. -- Abstract: In spite of the remarkable development of technology, most studies for building energy controls to evaluate or estimate the energy performance have not accurately reflected actual building’s energy consumption patterns. For this issue, several techniques, such as simulation and calibration, comprehensive survey system, smart metering, and commissioning, have been attempted. However, in most studies, some factors in thermal systems derived from occupant behavior were perceived as fixed objects, and the factors were converted into simple numbers as parts of inputs into simulation templates. There was lack of studies on considerations that unpredictable responses derived from human anti-logic or common sense could deteriorate energy efficiency in theoretical analyses even though the systems were properly operated. This research proposes integrated energy supply models based on artificial intelligence responding to anti-logic or common sense that can reduce machine’s energy saving effects. By use of design scenarios assuming some unusual situations, a decision making model determines the extent to which the cause of the abnormal situations are associated with the occupant behavior. After the five-step phases in the decision making model, the actual outputs of the energy supply model for the buildings are determined, and the reciprocal communication between the thermal and decision making models mitigates

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

    Science.gov (United States)

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

    2004-10-01

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

  13. Towards An Intelligent Model-Based Decision Support System For An Integrated Oil Company (EGPC)

    International Nuclear Information System (INIS)

    Khorshid, M.; Hassan, H.; Abdel Latife, M.A.

    2004-01-01

    Decision Support System (DSS) is an interactive, flexible and adaptable computer-based support system specially developed for supporting the solution of unstructured management problems [31] DSS has become widespread for oil industry domain in recent years. The computer-based DSS, which were developed and implemented in oil industry, are used to address the complex short-term planning and operational issues associated with downstream industry. Most of these applications concentrate on the data-centered tools, while the model-centered applications of DSS are still very limited up till now [20]. This study develops an Intelligent Model-Based DSS for an integrated oil company, to help policy makers and petroleum planner in improving the effectiveness of the strategic planning in oil sector. This domain basically imposes semi-structured or unstructured decisions and involves a very complex modeling process

  14. An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability

    Directory of Open Access Journals (Sweden)

    Xulin Guo

    2013-02-01

    Full Text Available Over 50% of world’s population presently resides in cities, and this number is expected to rise to ~70% by 2050. Increasing urbanization problems including population growth, urban sprawl, land use change, unemployment, and environmental degradation, have markedly impacted urban residents’ Quality of Life (QOL. Therefore, urban sustainability and its measurement have gained increasing attention from administrators, urban planners, and scientific communities throughout the world with respect to improving urban development and human well-being. The widely accepted definition of urban sustainability emphasizes the balancing development of three primary domains (urban economy, society, and environment. This article attempts to improve the aforementioned definition of urban sustainability by incorporating a human well-being dimension. Major problems identified in existing urban sustainability indicator (USI models include a weak integration of potential indicators, poor measurement and quantification, and insufficient spatial-temporal analysis. To tackle these challenges an integrated USI model based on a hierarchical indices system was established for monitoring and evaluating urban sustainability. This model can be performed by quantifying indicators using both traditional statistical approaches and advanced geomatic techniques based on satellite imagery and census data, which aims to provide a theoretical basis for a comprehensive assessment of urban sustainability from a spatial-temporal perspective.

  15. Integrating model checking with HiP-HOPS in model-based safety analysis

    International Nuclear Information System (INIS)

    Sharvia, Septavera; Papadopoulos, Yiannis

    2015-01-01

    The ability to perform an effective and robust safety analysis on the design of modern safety–critical systems is crucial. Model-based safety analysis (MBSA) has been introduced in recent years to support the assessment of complex system design by focusing on the system model as the central artefact, and by automating the synthesis and analysis of failure-extended models. Model checking and failure logic synthesis and analysis (FLSA) are two prominent MBSA paradigms. Extensive research has placed emphasis on the development of these techniques, but discussion on their integration remains limited. In this paper, we propose a technique in which model checking and Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) – an advanced FLSA technique – can be applied synergistically with benefit for the MBSA process. The application of the technique is illustrated through an example of a brake-by-wire system. - Highlights: • We propose technique to integrate HiP-HOPS and model checking. • State machines can be systematically constructed from HiP-HOPS. • The strengths of different MBSA techniques are combined. • Demonstrated through modeling and analysis of brake-by-wire system. • Root cause analysis is automated and system dynamic behaviors analyzed and verified

  16. Model Based Optimization of Integrated Low Voltage DC-DC Converter for Energy Harvesting Applications

    Science.gov (United States)

    Jayaweera, H. M. P. C.; Muhtaroğlu, Ali

    2016-11-01

    A novel model based methodology is presented to determine optimal device parameters for the fully integrated ultra low voltage DC-DC converter for energy harvesting applications. The proposed model feasibly contributes to determine the maximum efficient number of charge pump stages to fulfill the voltage requirement of the energy harvester application. The proposed DC-DC converter based power consumption model enables the analytical derivation of the charge pump efficiency when utilized simultaneously with the known LC tank oscillator behavior under resonant conditions, and voltage step up characteristics of the cross-coupled charge pump topology. The verification of the model has been done using a circuit simulator. The optimized system through the established model achieves more than 40% maximum efficiency yielding 0.45 V output with single stage, 0.75 V output with two stages, and 0.9 V with three stages for 2.5 kΩ, 3.5 kΩ and 5 kΩ loads respectively using 0.2 V input.

  17. Energy savings due to daylight and artificial lighting integration in office buildings in hot climate

    Energy Technology Data Exchange (ETDEWEB)

    Al-Ashwal, Nagib T. [Sana' a University, Sana' a (Yemen); Budaiwi, Ismail M. [King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia)

    2011-07-01

    Reducing energy consumption while maintaining acceptable environmental quality in buildings has been a challenging task for building professionals. In office buildings, artificial lighting systems are a major consumer of energy and can significantly contribute to building cooling load. Furthermore, although reliable, artificial lighting does not necessarily provide the required quality of lighting. Significant improvement in lighting quality and energy consumption can be achieved by proper integration of daylight and artificial lighting. The objective of this study is to investigate the energy performance of office buildings resulting from daylight and artificial lighting integration in hot climates. A parametric analysis is conducted to find the impact of different window design parameters, including window area, height and glazing type, on building energy performance. Results have shown that as much as 35% reduction in lighting energy consumption and 13% reduction in total energy consumption can be obtained when proper daylighting and artificial lighting integration is achieved.

  18. Integration of supervisory control synthesis in model-based systems engineering

    NARCIS (Netherlands)

    Baeten, J.C.M.; Mortel - Fronczak, van de J.M.; Rooda, J.E.

    2011-01-01

    Due to increasing system complexity, time-to-market and development costs reduction, there are higher demands on engineering processes. Model-based engineering can play a role here because it supports system development by enabling the use of various model-based analysis techniques and tools. As a

  19. Model-based identification and use of task complexity factors of human integrated systems

    International Nuclear Information System (INIS)

    Ham, Dong-Han; Park, Jinkyun; Jung, Wondea

    2012-01-01

    Task complexity is one of the conceptual constructs that are critical to explain and predict human performance in human integrated systems. A basic approach to evaluating the complexity of tasks is to identify task complexity factors and measure them. Although a great deal of task complexity factors have been studied, there is still a lack of conceptual frameworks for identifying and organizing them analytically, which can be generally used irrespective of the types of domains and tasks. This study proposes a model-based approach to identifying and using task complexity factors, which has two facets—the design aspects of a task and complexity dimensions. Three levels of design abstraction, which are functional, behavioral, and structural aspects of a task, characterize the design aspect of a task. The behavioral aspect is further classified into five cognitive processing activity types. The complexity dimensions explain a task complexity from different perspectives, which are size, variety, and order/organization. Twenty-one task complexity factors are identified by the combination of the attributes of each facet. Identification and evaluation of task complexity factors based on this model is believed to give insights for improving the design quality of tasks. This model for complexity factors can also be used as a referential framework for allocating tasks and designing information aids. The proposed approach is applied to procedure-based tasks of nuclear power plants (NPPs) as a case study to demonstrate its use. Last, we compare the proposed approach with other studies and then suggest some future research directions.

  20. Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques

    Science.gov (United States)

    Jain, Ashu; Srinivasulu, Sanaga

    2006-02-01

    This paper presents the findings of a study aimed at decomposing a flow hydrograph into different segments based on physical concepts in a catchment, and modelling different segments using different technique viz. conceptual and artificial neural networks (ANNs). An integrated modelling framework is proposed capable of modelling infiltration, base flow, evapotranspiration, soil moisture accounting, and certain segments of the decomposed flow hydrograph using conceptual techniques and the complex, non-linear, and dynamic rainfall-runoff process using ANN technique. Specifically, five different multi-layer perceptron (MLP) and two self-organizing map (SOM) models have been developed. The rainfall and streamflow data derived from the Kentucky River catchment were employed to test the proposed methodology and develop all the models. The performance of all the models was evaluated using seven different standard statistical measures. The results obtained in this study indicate that (a) the rainfall-runoff relationship in a large catchment consists of at least three or four different mappings corresponding to different dynamics of the underlying physical processes, (b) an integrated approach that models the different segments of the decomposed flow hydrograph using different techniques is better than a single ANN in modelling the complex, dynamic, non-linear, and fragmented rainfall runoff process, (c) a simple model based on the concept of flow recession is better than an ANN to model the falling limb of a flow hydrograph, and (d) decomposing a flow hydrograph into the different segments corresponding to the different dynamics based on the physical concepts is better than using the soft decomposition employed using SOM.

  1. Model-Based Design and Integration of Large Li-ion Battery Systems

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Kandler; Kim, Gi-Heon; Santhanagopalan, Shriram; Shi, Ying; Pesaran, Ahmad; Mukherjee, Partha; Barai, Pallab; Maute, Kurt; Behrou, Reza; Patil, Chinmaya

    2015-11-17

    This presentation introduces physics-based models of batteries and software toolsets, including those developed by the U.S. Department of Energy's (DOE) Computer-Aided Engineering for Electric-Drive Vehicle Batteries Program (CAEBAT). The presentation highlights achievements and gaps in model-based tools for materials-to-systems design, lifetime prediction and control.

  2. INTEGRATING ARTIFICIAL NEURAL NETWORKS FOR DEVELOPING TELEMEDICINE SOLUTION

    Directory of Open Access Journals (Sweden)

    Mihaela GHEORGHE

    2015-06-01

    Full Text Available Artificial intelligence is assuming an increasing important role in the telemedicine field, especially neural networks with their ability to achieve meaning from large sets of data characterized by lacking exactness and accuracy. These can be used for assisting physicians or other clinical staff in the process of taking decisions under uncertainty. Thus, machine learning methods which are specific to this technology are offering an approach for prediction based on pattern classification. This paper aims to present the importance of neural networks in detecting trends and extracting patterns which can be used within telemedicine domains, particularly for taking medical diagnosis decisions.

  3. The use of artificial intelligence techniques to improve the multiple payload integration process

    Science.gov (United States)

    Cutts, Dannie E.; Widgren, Brian K.

    1992-01-01

    A maximum return of science and products with a minimum expenditure of time and resources is a major goal of mission payload integration. A critical component then, in successful mission payload integration is the acquisition and analysis of experiment requirements from the principal investigator and payload element developer teams. One effort to use artificial intelligence techniques to improve the acquisition and analysis of experiment requirements within the payload integration process is described.

  4. A Framework for Sharing and Integrating Remote Sensing and GIS Models Based on Web Service

    Science.gov (United States)

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a “black box” and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users. PMID:24901016

  5. A framework for sharing and integrating remote sensing and GIS models based on Web service.

    Science.gov (United States)

    Chen, Zeqiang; Lin, Hui; Chen, Min; Liu, Deer; Bao, Ying; Ding, Yulin

    2014-01-01

    Sharing and integrating Remote Sensing (RS) and Geographic Information System/Science (GIS) models are critical for developing practical application systems. Facilitating model sharing and model integration is a problem for model publishers and model users, respectively. To address this problem, a framework based on a Web service for sharing and integrating RS and GIS models is proposed in this paper. The fundamental idea of the framework is to publish heterogeneous RS and GIS models into standard Web services for sharing and interoperation and then to integrate the RS and GIS models using Web services. For the former, a "black box" and a visual method are employed to facilitate the publishing of the models as Web services. For the latter, model integration based on the geospatial workflow and semantic supported marching method is introduced. Under this framework, model sharing and integration is applied for developing the Pearl River Delta water environment monitoring system. The results show that the framework can facilitate model sharing and model integration for model publishers and model users.

  6. Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics

    OpenAIRE

    Lechevalier , David; Narayanan , Anantha; Rachuri , Sudarsan; Foufou , Sebti; Lee , Y Tina

    2016-01-01

    Part 3: Interoperability and Systems Integration; International audience; To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformatio...

  7. Model-Based Data Integration and Process Standardization Techniques for Fault Management: A Feasibility Study

    Science.gov (United States)

    Haste, Deepak; Ghoshal, Sudipto; Johnson, Stephen B.; Moore, Craig

    2018-01-01

    This paper describes the theory and considerations in the application of model-based techniques to assimilate information from disjoint knowledge sources for performing NASA's Fault Management (FM)-related activities using the TEAMS® toolset. FM consists of the operational mitigation of existing and impending spacecraft failures. NASA's FM directives have both design-phase and operational-phase goals. This paper highlights recent studies by QSI and DST of the capabilities required in the TEAMS® toolset for conducting FM activities with the aim of reducing operating costs, increasing autonomy, and conforming to time schedules. These studies use and extend the analytic capabilities of QSI's TEAMS® toolset to conduct a range of FM activities within a centralized platform.

  8. Integrating artificial and human intelligence into tablet production process.

    Science.gov (United States)

    Gams, Matjaž; Horvat, Matej; Ožek, Matej; Luštrek, Mitja; Gradišek, Anton

    2014-12-01

    We developed a new machine learning-based method in order to facilitate the manufacturing processes of pharmaceutical products, such as tablets, in accordance with the Process Analytical Technology (PAT) and Quality by Design (QbD) initiatives. Our approach combines the data, available from prior production runs, with machine learning algorithms that are assisted by a human operator with expert knowledge of the production process. The process parameters encompass those that relate to the attributes of the precursor raw materials and those that relate to the manufacturing process itself. During manufacturing, our method allows production operator to inspect the impacts of various settings of process parameters within their proven acceptable range with the purpose of choosing the most promising values in advance of the actual batch manufacture. The interaction between the human operator and the artificial intelligence system provides improved performance and quality. We successfully implemented the method on data provided by a pharmaceutical company for a particular product, a tablet, under development. We tested the accuracy of the method in comparison with some other machine learning approaches. The method is especially suitable for analyzing manufacturing processes characterized by a limited amount of data.

  9. An Exploration into Integrating Daylight and Artificial Light via an Observational Instrument

    DEFF Research Database (Denmark)

    Petersen, Kjell Yngve; Søndergaard, Karin

    2015-01-01

    An Exploration into Integrating Daylight and Artificial Light via an Observational Instrument Daylight is dynamic and dependent upon weather conditions; unfolding with both subtle and dramatic variations in qualities of light. Through a building’s apertures, daylight creates a connection between...... abstract and blurred phenomena, these diffused luminous reflections rouse us into interactions with the world. In this book we are interested in identifying the qualitative parameters involved in the integration of dynamic artificial lighting and daylight; the latter being already highly dynamic by nature...... that examine how the dynamic artificial lighting in the observational instrument unfolds during the changing of the daylight situations that are generated by the weather outside. This research employs the concept of coupling between interior and exterior, in order to identify a spectrum of design parameters...

  10. Model-based integration and testing : bridging the gap between academic theory and industrial practice

    NARCIS (Netherlands)

    Braspenning, N.C.W.M.

    2008-01-01

    For manufacturers of high-tech multi-disciplinary systems such as semiconductor equipment, the effort required for integration and system testing is ever increasing, while customers demand a shorter time-to-market.This book describes how executable models can replace unavailable component

  11. Evaluation Of Model Based Systems Engineering Processes For Integration Into Rapid Acquisition Programs

    Science.gov (United States)

    2016-09-01

    for the required simulation allowed the MK6LE project to avoid the risk of having lower level model components not integrating together. The initial...that programs that applied MBSE at the lower levels, in particular the MK54 Torpedo program, expressed regrets of limiting the re-architecture to the

  12. A Model-Based Methodology for Integrated Design and Operation of Reactive Distillation Processes

    DEFF Research Database (Denmark)

    Mansouri, Seyed Soheil; Sales-Cruz, Mauricio; Huusom, Jakob Kjøbsted

    2015-01-01

    and resolved. A new approach isto tackle process intensification and controllability issues in an integrated manner, in the early stages of process design. This integrated and simultaneous synthesis approach provides optimal operation and moreefficient control of complex intensified systems that suffice...... calculation of reactive bubble points. For an energy-efficient design, the driving-forc eapproach (to determine the optimal feed location) for a reactive system has been employed. For both thereactive McCabe-Thiele and driving force method, vapor-liquid equilibrium data are based on elements. Thereactive...... system of compounds (methanol, isobutene and MTBE) to a binary system ofelements (elements A and B). For a binary element system, a simple reactive McCabe-Thiele-type method (to determine the number of reactive stages) has been used. The reactive equilibrium curve is constructed through sequential...

  13. [Psychotherapy of patients with brain lesions: an integrative model based on neuropsychological and psychodynamic perspectives].

    Science.gov (United States)

    Ouss-Ryngaert, Lisa

    2010-12-01

    Our model of psychotherapy for patients with brain lesions is based on an integrative approach of psychobehavioral symptoms, especially from the neuropsychological and psychodynamic perspectives. Adjustment of technical modalities and aims of psychoanalytical therapy is required for these patients. The analysis of the influence of cognitive disorders on transference and contre-transference plays a major role, including the role of procedural processes in changes in the intersubjective relationship between the patient and the therapist. Two vignettes are presented to illustrate our model, which respects the integrity of the cognitive and psychodynamic approaches and can be implemented by only one therapist, using alternatively each lecture, or by a working team bringing to light the different aspects of the same symptom.

  14. Complex Behavior in an Integrate-and-Fire Neuron Model Based on Small World Networks

    International Nuclear Information System (INIS)

    Lin Min; Chen Tianlun

    2005-01-01

    Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the complex behavior of electroencephalographic (EEG)-like activities produced by such a model. We find EEG-like activities have obvious chaotic characteristics. We also analyze the complex behaviors of EEG-like signals, such as spectral analysis, reconstruction of the phase space, the correlation dimension, and so on.

  15. Integrated Experimental and Model-based Analysis Reveals the Spatial Aspects of EGFR Activation Dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Shankaran, Harish; Zhang, Yi; Chrisler, William B.; Ewald, Jonathan A.; Wiley, H. S.; Resat, Haluk

    2012-10-02

    The epidermal growth factor receptor (EGFR) belongs to the ErbB family of receptor tyrosine kinases, and controls a diverse set of cellular responses relevant to development and tumorigenesis. ErbB activation is a complex process involving receptor-ligand binding, receptor dimerization, phosphorylation, and trafficking (internalization, recycling and degradation), which together dictate the spatio-temporal distribution of active receptors within the cell. The ability to predict this distribution, and elucidation of the factors regulating it, would help to establish a mechanistic link between ErbB expression levels and the cellular response. Towards this end, we constructed mathematical models for deconvolving the contributions of receptor dimerization and phosphorylation to EGFR activation, and to examine the dependence of these processes on sub-cellular location. We collected experimental datasets for EGFR activation dynamics in human mammary epithelial cells, with the specific goal of model parameterization, and used the data to estimate parameters for several alternate models. Model-based analysis indicated that: 1) signal termination via receptor dephosphorylation in late endosomes, prior to degradation, is an important component of the response, 2) less than 40% of the receptors in the cell are phosphorylated at any given time, even at saturating ligand doses, and 3) receptor dephosphorylation rates at the cell surface and early endosomes are comparable. We validated the last finding by measuring EGFR dephosphorylation rates at various times following ligand addition both in whole cells, and in endosomes using ELISAs and fluorescent imaging. Overall, our results provide important information on how EGFR phosphorylation levels are regulated within cells. Further, the mathematical model described here can be extended to determine receptor dimer abundances in cells co-expressing various levels of ErbB receptors. This study demonstrates that an iterative cycle of

  16. Quantitative geological modeling based on probabilistic integration of geological and geophysical data

    DEFF Research Database (Denmark)

    Gulbrandsen, Mats Lundh

    In order to obtain an adequate geological model of any kind, proper integration of geophysical data, borehole logs and geological expert knowledge is important. Geophysical data provide indirect information about geology, borehole logs provide sparse point wise direct information about geology...... entitled Smart Interpretation is developed. This semi-automatic method learns the relation between a set of data attributes extracted from deterministically inverted airborne electromagnetic data and a set of interpretations of a geological layer that is manually picked by a geological expert...

  17. Gaps Analysis of Integrating Product Design, Manufacturing, and Quality Data in The Supply Chain Using Model-Based Definition.

    Science.gov (United States)

    Trainer, Asa; Hedberg, Thomas; Feeney, Allison Barnard; Fischer, Kevin; Rosche, Phil

    2016-01-01

    MBE vision. Finally, it also seeks to explore the interaction between CAD and CMM processes and determine if the concept of feedback from CAM and CMM back to CAD is feasible. The main goal of our study is to test the hypothesis that model-based-data interoperability from CAD-to-CAM and CAD-to-CMM is feasible through standards-based integration. This paper presents several barriers to model-based-data interoperability. Overall, the project team demonstrated the exchange of product definition data between CAD, CAM, and CMM systems using standards-based methods. While gaps in standards coverage were identified, the gaps should not stop industry's progress toward MBE. The results of our study provide evidence in support of an open-standards method to model-based-data interoperability, which would provide maximum value and impact to industry.

  18. Model-based sensorimotor integration for multi-joint control: development of a virtual arm model.

    Science.gov (United States)

    Song, D; Lan, N; Loeb, G E; Gordon, J

    2008-06-01

    An integrated, sensorimotor virtual arm (VA) model has been developed and validated for simulation studies of control of human arm movements. Realistic anatomical features of shoulder, elbow and forearm joints were captured with a graphic modeling environment, SIMM. The model included 15 musculotendon elements acting at the shoulder, elbow and forearm. Muscle actions on joints were evaluated by SIMM generated moment arms that were matched to experimentally measured profiles. The Virtual Muscle (VM) model contained appropriate admixture of slow and fast twitch fibers with realistic physiological properties for force production. A realistic spindle model was embedded in each VM with inputs of fascicle length, gamma static (gamma(stat)) and dynamic (gamma(dyn)) controls and outputs of primary (I(a)) and secondary (II) afferents. A piecewise linear model of Golgi Tendon Organ (GTO) represented the ensemble sampling (I(b)) of the total muscle force at the tendon. All model components were integrated into a Simulink block using a special software tool. The complete VA model was validated with open-loop simulation at discrete hand positions within the full range of alpha and gamma drives to extrafusal and intrafusal muscle fibers. The model behaviors were consistent with a wide variety of physiological phenomena. Spindle afferents were effectively modulated by fusimotor drives and hand positions of the arm. These simulations validated the VA model as a computational tool for studying arm movement control. The VA model is available to researchers at website http://pt.usc.edu/cel .

  19. Model-Based Integrated Process Design and Controller Design of Chemical Processes

    DEFF Research Database (Denmark)

    Abd Hamid, Mohd Kamaruddin Bin

    that is typically formulated as a mathematical programming (optimization with constraints) problem is solved by the so-called reverse approach by decomposing it into four sequential hierarchical sub-problems: (i) pre-analysis, (ii) design analysis, (iii) controller design analysis, and (iv) final selection......This thesis describes the development and application of a new systematic modelbased methodology for performing integrated process design and controller design (IPDC) of chemical processes. The new methodology is simple to apply, easy to visualize and efficient to solve. Here, the IPDC problem...... are ordered according to the defined performance criteria (objective function). The final selected design is then verified through rigorous simulation. In the pre-analysis sub-problem, the concepts of attainable region and driving force are used to locate the optimal process-controller design solution...

  20. Model-based Integration of Past & Future in TimeTravel

    DEFF Research Database (Denmark)

    Khalefa, Mohamed E.; Fischer, Ulrike; Pedersen, Torben Bach

    2012-01-01

    We demonstrate TimeTravel, an efficient DBMS system for seamless integrated querying of past and (forecasted) future values of time series, allowing the user to view past and future values as one joint time series. This functionality is important for advanced application domain like energy....... The main idea is to compactly represent time series as models. By using models, the TimeTravel system answers queries approximately on past and future data with error guarantees (absolute error and confidence) one order of magnitude faster than when accessing the time series directly. In addition...... it to answer approximate and exact queries. TimeTravel is implemented into PostgreSQL, thus achieving complete user transparency at the query level. In the demo, we show the easy building of a hierarchical model index for a real-world time series and the effect of varying the error guarantees on the speed up...

  1. Functional integration of automated system databases by means of artificial intelligence

    Science.gov (United States)

    Dubovoi, Volodymyr M.; Nikitenko, Olena D.; Kalimoldayev, Maksat; Kotyra, Andrzej; Gromaszek, Konrad; Iskakova, Aigul

    2017-08-01

    The paper presents approaches for functional integration of automated system databases by means of artificial intelligence. The peculiarities of turning to account the database in the systems with the usage of a fuzzy implementation of functions were analyzed. Requirements for the normalization of such databases were defined. The question of data equivalence in conditions of uncertainty and collisions in the presence of the databases functional integration is considered and the model to reveal their possible occurrence is devised. The paper also presents evaluation method of standardization of integrated database normalization.

  2. A Data-Driven, Integrated Flare Model Based on Self-Organized Criticality

    Science.gov (United States)

    Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M.

    2013-09-01

    We interpret solar flares as events originating in solar active regions having reached the self-organized critical state, by alternatively using two versions of an "integrated flare model" - one static and one dynamic. In both versions the initial conditions are derived from observations aiming to investigate whether well-known scaling laws observed in the distribution functions of characteristic flare parameters are reproduced after the self-organized critical state has been reached. In the static model, we first apply a nonlinear force-free extrapolation that reconstructs the three-dimensional magnetic fields from two-dimensional vector magnetograms. We then locate magnetic discontinuities exceeding a threshold in the Laplacian of the magnetic field. These discontinuities are relaxed in local diffusion events, implemented in the form of cellular-automaton evolution rules. Subsequent loading and relaxation steps lead the system to self-organized criticality, after which the statistical properties of the simulated events are examined. In the dynamic version we deploy an enhanced driving mechanism, which utilizes the observed evolution of active regions, making use of sequential vector magnetograms. We first apply the static cellular automaton model to consecutive solar vector magnetograms until the self-organized critical state is reached. We then evolve the magnetic field inbetween these processed snapshots through spline interpolation, acting as a natural driver in the dynamic model. The identification of magnetically unstable sites as well as their relaxation follow the same rules as in the static model after each interpolation step. Subsequent interpolation/driving and relaxation steps cover all transitions until the end of the sequence. Physical requirements, such as the divergence-free condition for the magnetic field vector, are approximately satisfied in both versions of the model. We obtain robust power laws in the distribution functions of the modelled

  3. Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes.

    Science.gov (United States)

    Martinez-Millana, Antonio; Bayo-Monton, Jose-Luis; Argente-Pla, María; Fernandez-Llatas, Carlos; Merino-Torres, Juan Francisco; Traver-Salcedo, Vicente

    2017-12-29

    Life expectancy is increasing and, so, the years that patients have to live with chronic diseases and co-morbidities. Type 2 diabetes is one of the most prevalent chronic diseases, specifically linked to being overweight and ages over sixty. Recent studies have demonstrated the effectiveness of new strategies to delay and even prevent the onset of type 2 diabetes by a combination of active and healthy lifestyle on cohorts of mid to high risk subjects. Prospective research has been driven on large groups of the population to build risk scores that aim to obtain a rule for the classification of patients according to the odds for developing the disease. Currently, there are more than two hundred models and risk scores for doing this, but a few have been properly evaluated in external groups and integrated into a clinical application for decision support. In this paper, we present a novel system architecture based on service choreography and hybrid modeling, which enables a distributed integration of clinical databases, statistical and mathematical engines and web interfaces to be deployed in a clinical setting. The system was assessed during an eight-week continuous period with eight endocrinologists of a hospital who evaluated up to 8080 patients with seven different type 2 diabetes risk models implemented in two mathematical engines. Throughput was assessed as a matter of technical key performance indicators, confirming the reliability and efficiency of the proposed architecture to integrate hybrid artificial intelligence tools into daily clinical routine to identify high risk subjects.

  4. Integrated Model-Based Decisions for Water, Energy and Food Nexus

    Science.gov (United States)

    Zhang, X.; Vesselinov, V. V.

    2015-12-01

    Energy, water and food are critical resources for sustaining social development and human lives; human beings cannot survive without any one of them. Energy crises, water shortages and food security are crucial worldwide problems. The nexus of energy, water and food has received more and more attention in the past decade. Energy, water and food are closely interrelated; water is required in energy development such as electricity generation; energy is indispensable for collecting, treating, and transporting water; both energy and water are crucial inputs for food production. Changes of either of them can lead to substantial impacts on other two resources, and vice versa. Effective decisions should be based on thorough research efforts for better understanding of their complex nexus. Rapid increase of population has significantly intensified the pressures on energy, water and food. Addressing and quantifying their interactive relationships are important for making robust and cost-effective strategies for managing the three resources simultaneously. In addition, greenhouse gases (GHGs) are emitted in energy, water, food production, consequently making contributions to growing climate change. Reflecting environmental impacts of GHGs is also desired (especially, on the quality and quantity of fresh water resources). Thus, a socio-economic model is developed in this study to quantitatively address the complex connections among energy, water and food production. A synthetic problem is proposed to demonstrate the model's applicability and feasibility. Preliminary results related to integrated decisions on energy supply management, water use planning, electricity generation planning, energy facility capacity expansion, food production, and associated GHG emission control are generated for providing cost-effective supports for decision makers.

  5. Dynamic data-driven integrated flare model based on self-organized criticality

    Science.gov (United States)

    Dimitropoulou, M.; Isliker, H.; Vlahos, L.; Georgoulis, M. K.

    2013-05-01

    Context. We interpret solar flares as events originating in active regions that have reached the self-organized critical state. We describe them with a dynamic integrated flare model whose initial conditions and driving mechanism are derived from observations. Aims: We investigate whether well-known scaling laws observed in the distribution functions of characteristic flare parameters are reproduced after the self-organized critical state has been reached. Methods: To investigate whether the distribution functions of total energy, peak energy, and event duration follow the expected scaling laws, we first applied the previously reported static cellular automaton model to a time series of seven solar vector magnetograms of the NOAA active region 8210 recorded by the Imaging Vector Magnetograph on May 1 1998 between 18:59 UT and 23:16 UT until the self-organized critical state was reached. We then evolved the magnetic field between these processed snapshots through spline interpolation, mimicking a natural driver in our dynamic model. We identified magnetic discontinuities that exceeded a threshold in the Laplacian of the magnetic field after each interpolation step. These discontinuities were relaxed in local diffusion events, implemented in the form of cellular automaton evolution rules. Subsequent interpolation and relaxation steps covered all transitions until the end of the processed magnetograms' sequence. We additionally advanced each magnetic configuration that has reached the self-organized critical state (SOC configuration) by the static model until 50 more flares were triggered, applied the dynamic model again to the new sequence, and repeated the same process sufficiently often to generate adequate statistics. Physical requirements, such as the divergence-free condition for the magnetic field, were approximately imposed. Results: We obtain robust power laws in the distribution functions of the modeled flaring events with scaling indices that agree well

  6. Integrating Molecular Computation and Material Production in an Artificial Subcellular Matrix

    DEFF Research Database (Denmark)

    Fellermann, Harold; Hadorn, Maik; Bönzli, Eva

    Living systems are unique in that they integrate molecular recognition and information processing with material production on the molecular scale. Pre- dominant locus of this integration is the cellular matrix, where a multitude of biochemical reactions proceed simultaneously in highly compartmen......Living systems are unique in that they integrate molecular recognition and information processing with material production on the molecular scale. Pre- dominant locus of this integration is the cellular matrix, where a multitude of biochemical reactions proceed simultaneously in highly...... compartmentalized re- action compartments that interact and get delivered through vesicle trafficking. The European Commission funded project MatchIT (Matrix for Chemical IT) aims at creating an artificial cellular matrix that seamlessly integrates infor- mation processing and material production in much the same...

  7. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M. L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project ;The Hand Embodied; (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

  8. Tissue engineering and cell-based therapy toward integrated strategy with artificial organs.

    Science.gov (United States)

    Gojo, Satoshi; Toyoda, Masashi; Umezawa, Akihiro

    2011-09-01

    Research in order that artificial organs can supplement or completely replace the functions of impaired or damaged tissues and internal organs has been underway for many years. The recent clinical development of implantable left ventricular assist devices has revolutionized the treatment of patients with heart failure. The emerging field of regenerative medicine, which uses human cells and tissues to regenerate internal organs, is now advancing from basic and clinical research to clinical application. In this review, we focus on the novel biomaterials, i.e., fusion protein, and approaches such as three-dimensional and whole-organ tissue engineering. We also compare induced pluripotent stem cells, directly reprogrammed cardiomyocytes, and somatic stem cells for cell source of future cell-based therapy. Integrated strategy of artificial organ and tissue engineering/regenerative medicine should give rise to a new era of medical treatment to organ failure.

  9. PATIENT WITH DAMAGED ESPONTANEOUS VENTILATION: AN INTEGRATING REVIEW IN NURSING INTERVENTIONS ON USAGE OF ARTIFICIAL BREATHING

    Directory of Open Access Journals (Sweden)

    Luiz Augusto de Oliveira Antonucci

    2013-10-01

    Full Text Available This study aimed to analyze the nursing interventions given to patients with a diagnosis of spontaneous ventilation in impaired use of artificial respiration. It is an integrative literature review, the databases SciELO, LILACS, BIREME and MEDLINE. We used the key words: Nursing Care; Respiration, Artificial; Intensive Care; Nursing Diagnosis. The sample consisted of 11 items. Of these, ten were equivalent to the care of nursing interventions and suggested priority and/or optional. This study demonstrated that, despite the importance of interventions applied to patients on mechanical ventilation, many are not present in the literature, since this type of patient requires intensive nursing care, extensive and complex. Therefore, we need to encourage nurses to seek evidence to substantiate their clinical practice, providing support for implementation of appropriate interventions, providing the qualification of care.

  10. Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

    Energy Technology Data Exchange (ETDEWEB)

    Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

    2015-12-22

    health and disease.

    IMPORTANCEStudies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

  11. Employing Model-Based Reasoning in Interdisciplinary Research Teams: Evidence-Based Practices for Integrating Knowledge Across Systems

    Science.gov (United States)

    Pennington, D. D.; Vincent, S.

    2017-12-01

    The NSF-funded project "Employing Model-Based Reasoning in Socio-Environmental Synthesis (EMBeRS)" has developed a generic model for exchanging knowledge across disciplines that is based on findings from the cognitive, learning, social, and organizational sciences addressing teamwork in complex problem solving situations. Two ten-day summer workshops for PhD students from large, NSF-funded interdisciplinary projects working on a variety of water issues were conducted in 2016 and 2017, testing the model by collecting a variety of data, including surveys, interviews, audio/video recordings, material artifacts and documents, and photographs. This presentation will introduce the EMBeRS model, the design of workshop activities based on the model, and results from surveys and interviews with the participating students. Findings suggest that this approach is very effective for developing a shared, integrated research vision across disciplines, compared with activities typically provided by most large research projects, and that students believe the skills developed in the EMBeRS workshops are unique and highly desireable.

  12. Handling equipment Selection in open pit mines by using an integrated model based on group decision making

    Directory of Open Access Journals (Sweden)

    Abdolreza Yazdani-Chamzini

    2012-10-01

    Full Text Available Process of handling equipment selection is one of the most important and basic parts in the project planning, particularly mining projects due to holding a high charge of the total project's cost. Different criteria impact on the handling equipment selection, while these criteria often are in conflicting with each other. Therefore, the process of handling equipment selection is a complex and multi criteria decision making problem. There are a variety of methods for selecting the most appropriate equipment among a set of alternatives. Likewise, according to the sophisticated structure of the problem, imprecise data, less of information, and inherent uncertainty, the usage of the fuzzy sets can be useful. In this study a new integrated model based on fuzzy analytic hierarchy process (FAHP and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS is proposed, which uses group decision making to reduce individual errors. In order to calculate the weights of the evaluation criteria, FAHP is utilized in the process of handling equipment selection, and then these weights are inserted to the FTOPSIS computations to select the most appropriate handling system among a pool of alternatives. The results of this study demonstrate the potential application and effectiveness of the proposed model, which can be applied to different types of sophisticated problems in real problems.

  13. Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics.

    Science.gov (United States)

    de Lange, Elizabeth C M; van den Brink, Willem; Yamamoto, Yumi; de Witte, Wilhelmus E A; Wong, Yin Cheong

    2017-12-01

    CNS drug development has been hampered by inadequate consideration of CNS pharmacokinetic (PK), pharmacodynamics (PD) and disease complexity (reductionist approach). Improvement is required via integrative model-based approaches. Areas covered: The authors summarize factors that have played a role in the high attrition rate of CNS compounds. Recent advances in CNS research and drug discovery are presented, especially with regard to assessment of relevant neuro-PK parameters. Suggestions for further improvements are also discussed. Expert opinion: Understanding time- and condition dependent interrelationships between neuro-PK and neuro-PD processes is key to predictions in different conditions. As a first screen, it is suggested to use in silico/in vitro derived molecular properties of candidate compounds and predict concentration-time profiles of compounds in multiple compartments of the human CNS, using time-course based physiology-based (PB) PK models. Then, for selected compounds, one can include in vitro drug-target binding kinetics to predict target occupancy (TO)-time profiles in humans. This will improve neuro-PD prediction. Furthermore, a pharmaco-omics approach is suggested, providing multilevel and paralleled data on systems processes from individuals in a systems-wide manner. Thus, clinical trials will be better informed, using fewer animals, while also, needing fewer individuals and samples per individual for proof of concept in humans.

  14. A review on the integration of artificial intelligence into coastal modeling.

    Science.gov (United States)

    Chau, Kwokwing

    2006-07-01

    With the development of computing technology, mechanistic models are often employed to simulate processes in coastal environments. However, these predictive tools are inevitably highly specialized, involving certain assumptions and/or limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the underlying theories. This results in significant constraints on their manipulation as well as large gaps in understanding and expectations between the developers and practitioners of a model. The recent advancements in artificial intelligence (AI) technologies are making it possible to integrate machine learning capabilities into numerical modeling systems in order to bridge the gaps and lessen the demands on human experts. The objective of this paper is to review the state-of-the-art in the integration of different AI technologies into coastal modeling. The algorithms and methods studied include knowledge-based systems, genetic algorithms, artificial neural networks, and fuzzy inference systems. More focus is given to knowledge-based systems, which have apparent advantages over the others in allowing more transparent transfers of knowledge in the use of models and in furnishing the intelligent manipulation of calibration parameters. Of course, the other AI methods also have their individual contributions towards accurate and reliable predictions of coastal processes. The integrated model might be very powerful, since the advantages of each technique can be combined.

  15. A review on integration of artificial intelligence into water quality modelling.

    Science.gov (United States)

    Chau, Kwok-wing

    2006-07-01

    With the development of computing technology, numerical models are often employed to simulate flow and water quality processes in coastal environments. However, the emphasis has conventionally been placed on algorithmic procedures to solve specific problems. These numerical models, being insufficiently user-friendly, lack knowledge transfers in model interpretation. This results in significant constraints on model uses and large gaps between model developers and practitioners. It is a difficult task for novice application users to select an appropriate numerical model. It is desirable to incorporate the existing heuristic knowledge about model manipulation and to furnish intelligent manipulation of calibration parameters. The advancement in artificial intelligence (AI) during the past decade rendered it possible to integrate the technologies into numerical modelling systems in order to bridge the gaps. The objective of this paper is to review the current state-of-the-art of the integration of AI into water quality modelling. Algorithms and methods studied include knowledge-based system, genetic algorithm, artificial neural network, and fuzzy inference system. These techniques can contribute to the integrated model in different aspects and may not be mutually exclusive to one another. Some future directions for further development and their potentials are explored and presented.

  16. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M.L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2017-01-01

    The term ‘synergy’ – from the Greek synergia – means ‘working together’. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project “The Hand Embodied” (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies. PMID:26923030

  17. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands.

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M L; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Petr Maca

    2016-01-01

    Full Text Available The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI and the standardized precipitation evaporation index (SPEI and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

  19. The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

    Science.gov (United States)

    Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

    2016-02-01

    Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

  20. Integrated control of the cooling system and surface openings using the artificial neural networks

    International Nuclear Information System (INIS)

    Moon, Jin Woo

    2015-01-01

    This study aimed at suggesting an indoor temperature control method that can provide a comfortable thermal environment through the integrated control of the cooling system and the surface openings. Four control logic were developed, employing different application levels of rules and artificial neural network models. Rule-based control methods represented the conventional approach while ANN-based methods were applied for the predictive and adaptive controls. Comparative performance tests for the conventional- and ANN-based methods were numerically conducted for the double-skin-facade building, using the MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation) software, after proving the validity by comparing the simulation and field measurement results. Analysis revealed that the ANN-based controls of the cooling system and surface openings improved the indoor temperature conditions with increased comfortable temperature periods and decreased standard deviation of the indoor temperature from the center of the comfortable range. In addition, the proposed ANN-based logic effectively reduced the number of operating condition changes of the cooling system and surface openings, which can prevent system failure. The ANN-based logic, however, did not show superiority in energy efficiency over the conventional logic. Instead, they have increased the amount of heat removal by the cooling system. From the analysis, it can be concluded that the ANN-based temperature control logic was able to keep the indoor temperature more comfortably and stably within the comfortable range due to its predictive and adaptive features. - Highlights: • Integrated rule-based and artificial neural network based logics were developed. • A cooling device and surface openings were controlled in an integrated manner. • Computer simulation method was employed for comparative performance tests. • ANN-based logics showed the advanced features of thermal environment. • Rule

  1. Interactions of artificial lakes with groundwater applying an integrated MODFLOW solution

    Science.gov (United States)

    El-Zehairy, A. A.; Lubczynski, M. W.; Gurwin, J.

    2018-02-01

    Artificial lakes (reservoirs) are regulated water bodies with large stage fluctuations and different interactions with groundwater compared with natural lakes. A novel modelling study characterizing the dynamics of these interactions is presented for artificial Lake Turawa, Poland. The integrated surface-water/groundwater MODFLOW-NWT transient model, applying SFR7, UZF1 and LAK7 packages to account for variably-saturated flow and temporally variable lake area extent and volume, was calibrated throughout 5 years (1-year warm-up, 4-year simulation), applying daily lake stages, heads and discharges as control variables. The water budget results showed that, in contrast to natural lakes, the reservoir interactions with groundwater were primarily dependent on the balance between lake inflow and regulated outflow, while influences of precipitation and evapotranspiration played secondary roles. Also, the spatio-temporal lakebed-seepage pattern was different compared with natural lakes. The large and fast-changing stages had large influence on lakebed-seepage and water table depth and also influenced groundwater evapotranspiration and groundwater exfiltration, as their maxima coincided not with rainfall peaks but with highest stages. The mean lakebed-seepage ranged from 0.6 mm day-1 during lowest stages (lake-water gain) to 1.0 mm day-1 during highest stages (lake-water loss) with largest losses up to 4.6 mm day-1 in the peripheral zone. The lakebed-seepage of this study was generally low because of low lakebed leakance (0.0007-0.0015 day-1) and prevailing upward regional groundwater flow moderating it. This study discloses the complexity of artificial lake interactions with groundwater, while the proposed front-line modelling methodology can be applied to any reservoir, and also to natural lake interactions with groundwater.

  2. The Virtual UNICOS Process Expert: integration of Artificial Intelligence tools in Control Systems

    CERN Multimedia

    Vilches Calvo, I; Barillere, R

    2009-01-01

    UNICOS is a CERN framework to produce control applications. It provides operators with ways to interact with all process items from the most simple (e.g. I/O channels) to the most abstract objects (e.g. a part of the plant). This possibility of fine grain operation is particularly useful to recover from abnormal situations if operators have the required knowledge. The Virtual UNICOS Process Expert project aims at providing operators with means to handle difficult operation cases for which the intervention of process experts is usually requested. The main idea of project is to use the openness of the UNICOS-based applications to integrate tools (e.g. Artificial Intelligence tools) which will act as Process Experts to analyze complex situations, to propose and to execute smooth recovery procedures.

  3. Integration of artificial intelligence systems for nuclear power plants surveillance and diagnostics

    International Nuclear Information System (INIS)

    Chetry, Moon K.

    2012-01-01

    The objective of this program is to design, construct operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feed water venture flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant heat rate, d) diagnosis of nuclear power plant transients

  4. A Hybrid Forecasting Model Based on Bivariate Division and a Backpropagation Artificial Neural Network Optimized by Chaos Particle Swarm Optimization for Day-Ahead Electricity Price

    Directory of Open Access Journals (Sweden)

    Zhilong Wang

    2014-01-01

    Full Text Available In the electricity market, the electricity price plays an inevitable role. Nevertheless, accurate price forecasting, a vital factor affecting both government regulatory agencies and public power companies, remains a huge challenge and a critical problem. Determining how to address the accurate forecasting problem becomes an even more significant task in an era in which electricity is increasingly important. Based on the chaos particle swarm optimization (CPSO, the backpropagation artificial neural network (BPANN, and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN method and the CPSO-BD-BPANN method for forecasting electricity price. The former method creatively transforms the electricity demand and price to be a new variable, named DV, which is calculated using the division principle, to forecast the day-ahead electricity by multiplying the forecasted values of the DVs and forecasted values of the demand. Next, to improve the accuracy of BD-BPANN, chaos particle swarm optimization and BD-BPANN are synthesized to form a novel model, CPSO-BD-BPANN. In this study, CPSO is utilized to optimize the initial parameters of BD-BPANN to make its output more stable than the original model. Finally, two forecasting strategies are proposed regarding different situations.

  5. Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM and Artificial Neural Network (ANN

    Directory of Open Access Journals (Sweden)

    Maria Grazia De Giorgi

    2014-08-01

    Full Text Available A high penetration of wind energy into the electricity market requires a parallel development of efficient wind power forecasting models. Different hybrid forecasting methods were applied to wind power prediction, using historical data and numerical weather predictions (NWP. A comparative study was carried out for the prediction of the power production of a wind farm located in complex terrain. The performances of Least-Squares Support Vector Machine (LS-SVM with Wavelet Decomposition (WD were evaluated at different time horizons and compared to hybrid Artificial Neural Network (ANN-based methods. It is acknowledged that hybrid methods based on LS-SVM with WD mostly outperform other methods. A decomposition of the commonly known root mean square error was beneficial for a better understanding of the origin of the differences between prediction and measurement and to compare the accuracy of the different models. A sensitivity analysis was also carried out in order to underline the impact that each input had in the network training process for ANN. In the case of ANN with the WD technique, the sensitivity analysis was repeated on each component obtained by the decomposition.

  6. Fouling resistance prediction using artificial neural network nonlinear auto-regressive with exogenous input model based on operating conditions and fluid properties correlations

    Energy Technology Data Exchange (ETDEWEB)

    Biyanto, Totok R. [Department of Engineering Physics, Institute Technology of Sepuluh Nopember Surabaya, Surabaya, Indonesia 60111 (Indonesia)

    2016-06-03

    Fouling in a heat exchanger in Crude Preheat Train (CPT) refinery is an unsolved problem that reduces the plant efficiency, increases fuel consumption and CO{sub 2} emission. The fouling resistance behavior is very complex. It is difficult to develop a model using first principle equation to predict the fouling resistance due to different operating conditions and different crude blends. In this paper, Artificial Neural Networks (ANN) MultiLayer Perceptron (MLP) with input structure using Nonlinear Auto-Regressive with eXogenous (NARX) is utilized to build the fouling resistance model in shell and tube heat exchanger (STHX). The input data of the model are flow rates and temperatures of the streams of the heat exchanger, physical properties of product and crude blend data. This model serves as a predicting tool to optimize operating conditions and preventive maintenance of STHX. The results show that the model can capture the complexity of fouling characteristics in heat exchanger due to thermodynamic conditions and variations in crude oil properties (blends). It was found that the Root Mean Square Error (RMSE) are suitable to capture the nonlinearity and complexity of the STHX fouling resistance during phases of training and validation.

  7. Tower of London test: a comparison between conventional statistic approach and modelling based on artificial neural network in differentiating fronto-temporal dementia from Alzheimer's disease.

    Science.gov (United States)

    Franceschi, Massimo; Caffarra, Paolo; Savarè, Rita; Cerutti, Renata; Grossi, Enzo

    2011-01-01

    The early differentiation of Alzheimer's disease (AD) from frontotemporal dementia (FTD) may be difficult. The Tower of London (ToL), thought to assess executive functions such as planning and visuo-spatial working memory, could help in this purpose. Twentytwo Dementia Centers consecutively recruited patients with early FTD or AD. ToL performances of these groups were analyzed using both the conventional statistical approaches and the Artificial Neural Networks (ANNs) modelling. Ninety-four non aphasic FTD and 160 AD patients were recruited. ToL Accuracy Score (AS) significantly (p advanced ANNs developed by Semeion Institute. The best ANNs were selected and submitted to ROC curves. The non-linear model was able to discriminate FTD from AD with an average AUC for 7 independent trials of 0.82. The use of hidden information contained in the different items of ToL and the non linear processing of the data through ANNs allows a high discrimination between FTD and AD in individual patients.

  8. A Novel Combined Model Based on an Artificial Intelligence Algorithm—A Case Study on Wind Speed Forecasting in Penglai, China

    Directory of Open Access Journals (Sweden)

    Feiyu Zhang

    2016-06-01

    Full Text Available Wind speed forecasting plays a key role in wind-related engineering studies and is important in the management of wind farms. Current forecasting models based on different optimization algorithms can be adapted to various wind speed time series data. However, these methodologies cannot aggregate different hybrid forecasting methods and take advantage of the component models. To avoid these limitations, we propose a novel combined forecasting model called SSA-PSO-DWCM, i.e., particle swarm optimization (PSO determined weight coefficients model. This model consisted of three main steps: one is the decomposition of the original wind speed signals to discard the noise, the second is the parameter optimization of the forecasting method, and the last is the combination of different models in a nonlinear way. The proposed combined model is examined by forecasting the wind speed (10-min intervals of wind turbine 5 located in the Penglai region of China. The simulations reveal that the proposed combined model demonstrates a more reliable forecast than the component forecasting engines and the traditional combined method, which is based on a linear method.

  9. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-01-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  10. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-07-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  11. Artificial Post mining lakes - a challenge for the integration in natural hydrography and river basin management

    Science.gov (United States)

    Fleischhammel, Petra; Schoenheinz, Dagmar; Grünewald, Uwe

    2010-05-01

    In terms of the European Water Framework Directive (WFD), post mining lakes are artificial water bodies (AWB). The sustainable integration of post mining lakes in the groundwater and surface water landscape and their consideration in river basin management plans have to be linked with various (geo)hydrological, hydro(geo)chemical, technological and socioeconomic issues. The Lower Lusatian lignite mining district in eastern Germany is part of the major river basins of river Elbe and river Oder. Regionally, the mining area is situated in the sub-basins of river Spree and Schwarze Elster. After the cessation of mining activities and thereby of the artificially created groundwater drawdown in numerous mining pits, a large number of post mining lakes are evolving as consequence of natural groundwater table recovery. The lakes' designated uses vary from water reservoirs to landscape, recreation or fish farming lakes. Groundwater raise is not only substantial for the lake filling, but also for the area rehabilitation and a largely self regulated water balance in post mining landscapes. Since the groundwater flow through soil and dump sites being affected by the former mining activities, groundwater experiences various changes in its hydrochemical properties as e.g. mineralization and acidification. Consequently, downstream located groundwater fed running and standing water bodies will be affected too. Respective the European Water Framework Directive, artificial post mining lakes are not allowed to cause significant adverse impacts on the good ecological status/potential of downstream groundwater and surface water bodies. The high sulphate concentrations of groundwater fed mining lakes which reach partly more than 1,000 mg/l are e.g. damaging concrete constructures in downstream water bodies thereby representing threats for hydraulic facilities and drinking water supply. Due to small amounts of nutrients, the lakes are characterised by oligo¬trophic to slightly

  12. Vertical integration and market power: A model-based analysis of restructuring in the Korean electricity market

    International Nuclear Information System (INIS)

    Bunn, Derek W.; Martoccia, Maria; Ochoa, Patricia; Kim, Haein; Ahn, Nam-Sung; Yoon, Yong-Beom

    2010-01-01

    An agent-based simulation model is developed using computational learning to investigate the impact of vertical integration between electricity generators and retailers on market power in a competitive wholesale market setting. It is observed that if partial vertical integration creates some market foreclosure, whether this leads to an increase or decrease in market power is situation specific. A detailed application to the Korean market structure reveals this to be the case. We find that in various cases, whilst vertical integration generally reduces spot prices, it can increase or decrease the market power of other market generators, depending upon the market share and the technology segment of the market, which is integrated, as well as the market concentrations before and after the integration.

  13. Vertical integration and market power. A model-based analysis of restructuring in the Korean electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Bunn, Derek W.; Martoccia, Maria; Ochoa, Patricia [London Business School, London (United Kingdom); Kim, Haein; Ahn, Nam-Sung; Yoon, Yong-Beom [Korean Electric Power Corporation, Seoul (Korea)

    2010-07-15

    An agent-based simulation model is developed using computational learning to investigate the impact of vertical integration between electricity generators and retailers on market power in a competitive wholesale market setting. It is observed that if partial vertical integration creates some market foreclosure, whether this leads to an increase or decrease in market power is situation specific. A detailed application to the Korean market structure reveals this to be the case. We find that in various cases, whilst vertical integration generally reduces spot prices, it can increase or decrease the market power of other market generators, depending upon the market share and the technology segment of the market, which is integrated, as well as the market concentrations before and after the integration. (author)

  14. Vertical integration and market power: A model-based analysis of restructuring in the Korean electricity market

    Energy Technology Data Exchange (ETDEWEB)

    Bunn, Derek W., E-mail: dbunn@london.ed [London Business School, London (United Kingdom); Martoccia, Maria; Ochoa, Patricia [London Business School, London (United Kingdom); Kim, Haein; Ahn, Nam-Sung; Yoon, Yong-Beom [Korean Electric Power Corporation, Seoul (Korea, Republic of)

    2010-07-15

    An agent-based simulation model is developed using computational learning to investigate the impact of vertical integration between electricity generators and retailers on market power in a competitive wholesale market setting. It is observed that if partial vertical integration creates some market foreclosure, whether this leads to an increase or decrease in market power is situation specific. A detailed application to the Korean market structure reveals this to be the case. We find that in various cases, whilst vertical integration generally reduces spot prices, it can increase or decrease the market power of other market generators, depending upon the market share and the technology segment of the market, which is integrated, as well as the market concentrations before and after the integration.

  15. Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

    International Nuclear Information System (INIS)

    Ahmadi, Rouhollah; Khamehchi, Ehsan

    2013-01-01

    Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data

  16. Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

    Energy Technology Data Exchange (ETDEWEB)

    Ahmadi, Rouhollah, E-mail: rouhollahahmadi@yahoo.com [Amirkabir University of Technology, PhD Student at Reservoir Engineering, Department of Petroleum Engineering (Iran, Islamic Republic of); Khamehchi, Ehsan [Amirkabir University of Technology, Faculty of Petroleum Engineering (Iran, Islamic Republic of)

    2013-12-15

    Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.

  17. Integrating Artificial Neural Networks into the VIC Model for Rainfall-Runoff Modeling

    Directory of Open Access Journals (Sweden)

    Changqing Meng

    2016-09-01

    Full Text Available A hybrid rainfall-runoff model was developed in this study by integrating the variable infiltration capacity (VIC model with artificial neural networks (ANNs. In the proposed model, the prediction interval of the ANN replaces separate, individual simulation (i.e., single simulation. The spatial heterogeneity of horizontal resolution, subgrid-scale features and their influence on the streamflow can be assessed according to the VIC model. In the routing module, instead of a simple linear superposition of the streamflow generated from each subbasin, ANNs facilitate nonlinear mappings of the streamflow produced from each subbasin into the total streamflow at the basin outlet. A total of three subbasins were delineated and calibrated independently via the VIC model; daily runoff errors were simulated for each subbasin, then corrected by an ANN bias-correction model. The initial streamflow and corrected runoff from the simulation for individual subbasins serve as inputs to the ANN routing model. The feasibility of this proposed method was confirmed according to the performance of its application to a case study on rainfall-runoff prediction in the Jinshajiang River Basin, the headwater area of the Yangtze River.

  18. MosquitoNet: investigating the use of UAV and artificial neural networks for integrated mosquito management

    Science.gov (United States)

    Case, E.; Ren, Y.; Shragai, T.; Erickson, D.

    2017-12-01

    Integrated mosquito control is expensive and resource intensive, and changing climatic factors are predicted to expand the habitable range of disease-carrying mosquitoes into new regions in the United States. Of particular concern in the northeastern United States are aedes albopictus, an aggressive, invasive species of mosquito that can transmit both native and exotic disease. Ae. albopictus prefer to live near human populations and breed in artificial containers with as little as two millimeters of standing water, exponentially increasing the difficulty of source control in suburban and urban areas. However, low-cost unmanned aerial vehicles (UAVs) can be used to photograph large regions at centimeter-resolution, and can image containers of interest in suburban neighborhoods. While proofs-of-concepts have been shown using UAVs to identify naturally occurring bodies of water, they have not been used to identify mosquito habitat in more populated areas. One of the primary challenges is that post-processing high-resolution aerial imagery is still time intensive, often labelled by hand or with programs built for satellite imagery. Artificial neural networks have been highly successful at image recognition tasks; in the past five years, convolutional neural networks (CNN) have surpassed or aided trained humans in identification of skin cancer, agricultural crops, and poverty levels from satellite imagery. MosquitoNet, a dual classifier built from the Single Shot Multibox Detector and VGG16 architectures, was trained on UAV­­­­­ aerial imagery taken during a larval study in Westchester County in southern New York State in July and August 2017. MosquitoNet was designed to assess the habitat risk of suburban properties by automating the identification and counting of containers like tires, toys, garbage bins, flower pots, etc. The SSD-based architecture marked small containers and other habitat indicators while the VGG16-based architecture classified the type of

  19. Comparative analysis of the influence of creep of concrete composite beams of steel - concrete model based on Volterra integral equation

    Directory of Open Access Journals (Sweden)

    Partov Doncho

    2017-01-01

    Full Text Available The paper presents analysis of the stress-strain behaviour and deflection changes due to creep in statically determinate composite steel-concrete beam according to EUROCODE 2, ACI209R-92 and Gardner&Lockman models. The mathematical model involves the equation of equilibrium, compatibility and constitutive relationship, i.e. an elastic law for the steel part and an integral-type creep law of Boltzmann - Volterra for the concrete part considering the above mentioned models. On the basis of the theory of viscoelastic body of Maslov-Arutyunian-Trost-Zerna-Bažant for determining the redistribution of stresses in beam section between concrete plate and steel beam with respect to time 't', two independent Volterra integral equations of the second kind have been derived. Numerical method based on linear approximation of the singular kernel function in the integral equation is presented. Example with the model proposed is investigated.

  20. Artificial groundwater recharge as integral part of a water resources system in a humid environment

    Science.gov (United States)

    Kupfersberger, Hans; Stadler, Hermann

    2010-05-01

    In Graz, Austria, artificial groundwater recharge has been operated as an integral part of the drinking water supply system for more than thirty years. About 180 l/s of high quality water from pristine creeks (i.e. no pre-treatment necessary) are infiltrated via sand and lawn basins and infiltration trenches into two phreatic aquifers to sustain the extraction of approximately 400 l/s. The remaining third of drinking water for roughly 300.000 people is provided by a remote supply line from the East alpine karst region Hochschwab. By this threefold model the water supply system is less vulnerable to external conditions. In the early 1980's the infiltration devices were also designed as a hydraulic barrier against riverbank infiltration from the river Mur, which at that time showed seriously impaired water quality due to upstream paper mills. This resulted into high iron and manganese groundwater concentrations which lead to clogging of the pumping wells. These problems have been eliminated in the meantime due to the onsite purification of paper mill effluents and the construction of many waste water treatment plants. The recharge system has recently been thoroughly examined to optimize the operation of groundwater recharge and to provide a basis for further extension. The investigations included (i) field experiments and laboratory analyses to improve the trade off between infiltration rate and elimination capacities of the sand filter basins' top layer, (ii) numerical groundwater modelling to compute the recovery rate of the recharged water, the composition of the origin of the pumped water, emergency scenarios due to the failure of system parts, the transient capture zones of the withdrawal wells and the coordination of recharge and withdrawal and (iii) development of an online monitoring setup combined with a decision support system to guarantee reliable functioning of the entire structure. Additionally, the depreciation, maintenance and operation costs of the

  1. Integrating public demands into model-based design for multifunctional agriculture: An application to intensive dutch dairy landscapes

    NARCIS (Netherlands)

    Parra-López, C.; Groot, J.C.J.; Carmona-Torres, C.; Rossing, W.A.H.

    2008-01-01

    The contribution of agriculture to the welfare of society is determined by its economic, social and environmental performance. Although theoretical discussions can be found in the literature, few reports exist that integrate the social demand for multifunctional agriculture in the evaluation of the

  2. An interval-valued 2-tuple linguistic group decision-making model based on the Choquet integral operator

    Science.gov (United States)

    Liu, Bingsheng; Fu, Meiqing; Zhang, Shuibo; Xue, Bin; Zhou, Qi; Zhang, Shiruo

    2018-01-01

    The Choquet integral (IL) operator is an effective approach for handling interdependence among decision attributes in complex decision-making problems. However, the fuzzy measures of attributes and attribute sets required by IL are difficult to achieve directly, which limits the application of IL. This paper proposes a new method for determining fuzzy measures of attributes by extending Marichal's concept of entropy for fuzzy measure. To well represent the assessment information, interval-valued 2-tuple linguistic context is utilised to represent information. Then, we propose a Choquet integral operator in an interval-valued 2-tuple linguistic environment, which can effectively handle the correlation between attributes. In addition, we apply these methods to solve multi-attribute group decision-making problems. The feasibility and validity of the proposed operator is demonstrated by comparisons with other models in illustrative example part.

  3. Designing an integrated model based on the indicators Quality and Earned Value for risk management in Information Technology Projects

    OpenAIRE

    TATLARI, Mohammad Reza; KAZEMİPOOR, Hamed

    2015-01-01

    There are two effective factors on Information Technology (IT) projects risk including quality and earned value so that by controlling these two factors and their increased level in IT projects, the corresponding risk can be decreased. Therefore in present study, an integrated model was designed based on quality and earned value indicators for risk management in IT projects on a new and efficient approach. The proposed algorithm included the steps such as preparing a list of several indicator...

  4. Integrated Sensing and Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier and Syngas Cooler

    Energy Technology Data Exchange (ETDEWEB)

    Aditya Kumar

    2010-12-30

    This report summarizes the achievements and final results of this program. The objective of this program is to develop a comprehensive systems approach to integrated design of sensing and control systems for an Integrated Gasification Combined Cycle (IGCC) plant, using advanced model-based techniques. In particular, this program is focused on the model-based sensing and control system design for the core gasification section of an IGCC plant. The overall approach consists of (i) developing a first-principles physics-based dynamic model of the gasification section, (ii) performing model-reduction where needed to derive low-order models suitable for controls analysis and design, (iii) developing a sensing system solution combining online sensors with model-based estimation for important process variables not measured directly, and (iv) optimizing the steady-state and transient operation of the plant for normal operation as well as for startup using model predictive controls (MPC). Initially, available process unit models were implemented in a common platform using Matlab/Simulink{reg_sign}, and appropriate model reduction and model updates were performed to obtain the overall gasification section dynamic model. Also, a set of sensor packages were developed through extensive lab testing and implemented in the Tampa Electric Company IGCC plant at Polk power station in 2009, to measure temperature and strain in the radiant syngas cooler (RSC). Plant operation data was also used to validate the overall gasification section model. The overall dynamic model was then used to develop a sensing solution including a set of online sensors coupled with model-based estimation using nonlinear extended Kalman filter (EKF). Its performance in terms of estimating key unmeasured variables like gasifier temperature, carbon conversion, etc., was studied through extensive simulations in the presence sensing errors (noise and bias) and modeling errors (e.g. unknown gasifier kinetics, RSC

  5. 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...

  6. Artificial Material Integrated Ultra-wideband Tapered Slot Antenna for Gain Enhancement with Band Notch Characteristics

    Directory of Open Access Journals (Sweden)

    R. Singha

    2018-04-01

    Full Text Available The gain of the ultra-wideband tapered slot antenna (TSA is enhanced by using broadband artificial material with band notch characteristics. The proposed artificial material unit cell is designed by fabricating non-resonant three S-shaped parallel metallic line on single side of the dielectric substrate which provides a longer current path compared to the parallel-line structure. The proposed S-shaped structure is printed on the top side of the tapered slot antenna in the extended substrate periodically. The effective refractive index of the artificial material is lower than antenna substrate and phase velocity in the region of artificial material is much higher than the other region. Therefore, the proposed artificial material acts like a beam focusing lens. The band notch at 5.5 GHz is achieved by creating a split ring resonator (SRR slot near the balun. The basic and artificial material loaded TSAs are fabricated and the measurement results show that the gain of the basic antenna has been increased by 1.6 dBi. At the same time, the proposed antenna achieves a VSWR below 2 from 3 to 11 GHz except at 5.5 GHz with a notch band from 5.1 to 5.8 GHz for band rejection of wireless local area network (WLAN application.

  7. Using high-order polynomial basis in 3-D EM forward modeling based on volume integral equation method

    Science.gov (United States)

    Kruglyakov, Mikhail; Kuvshinov, Alexey

    2018-05-01

    3-D interpretation of electromagnetic (EM) data of different origin and scale becomes a common practice worldwide. However, 3-D EM numerical simulations (modeling)—a key part of any 3-D EM data analysis—with realistic levels of complexity, accuracy and spatial detail still remains challenging from the computational point of view. We present a novel, efficient 3-D numerical solver based on a volume integral equation (IE) method. The efficiency is achieved by using a high-order polynomial (HOP) basis instead of the zero-order (piecewise constant) basis that is invoked in all routinely used IE-based solvers. We demonstrate that usage of the HOP basis allows us to decrease substantially the number of unknowns (preserving the same accuracy), with corresponding speed increase and memory saving.

  8. Model-based Impact Assessment of an Integrated Water Management Strategy on Ecosystem Services relevant to Food Security in Namibia

    Science.gov (United States)

    Luetkemeier, R.; Liehr, S.

    2012-04-01

    North-central Namibia is characterized by seasonal alterations of drought and heavy rainfall, mostly saline groundwater resources and a lack of perennial rivers. Water scarcity poses a great challenge for freshwater supply, harvest and food security against the background of high population growth and climate change. CuveWaters project aims at poverty reduction and livelihood improvement on a long term basis by introducing a multi-resource-mix as part of an integrated water resources management (IWRM) approach. Herein, creating water buffers by rainwater harvesting (RWH) and subsurface water storage as well as reuse of treated wastewater facilitates micro-scale gardening activities. This link constitutes a major component of a sustainable adaptation strategy by contributing to the conservation and improvement of basic food and freshwater resources in order to reduce drought vulnerability. This paper presents main findings of an impact assessment carried out on the effect of integrated water resources management on ecosystem services (ESS) relevant to food security within the framework of CuveWaters project. North-central Namibia is perceived as a social-ecological system characterized by a strong mutual dependence between natural environment and anthropogenic system. This fundamental reliance on natural resources highlights the key role of ESS in semi-arid environments to sustain human livelihoods. Among other services, food provision was chosen for quantification as one of the most fundamental ESS in north-central Namibia. Different nutritional values were utilized as indicators to adopt a demand-supply approach (Ecosystem Service Profile) to illustrate the ability of the ecosystem to meet people's nutritional requirements. Calculations have been conducted using both Bayesian networks to incorporate uncertainty introduced by the variability of monthly precipitation and the application of plant specific water production functions. Results show that improving the

  9. The Artificial Hamiltonian, First Integrals, and Closed-Form Solutions of Dynamical Systems for Epidemics

    Science.gov (United States)

    Naz, Rehana; Naeem, Imran

    2018-03-01

    The non-standard Hamiltonian system, also referred to as a partial Hamiltonian system in the literature, of the form {\\dot q^i} = {partial H}/{partial {p_i}},\\dot p^i = - {partial H}/{partial {q_i}} + {Γ ^i}(t,{q^i},{p_i}) appears widely in economics, physics, mechanics, and other fields. The non-standard (partial) Hamiltonian systems arise from physical Hamiltonian structures as well as from artificial Hamiltonian structures. We introduce the term `artificial Hamiltonian' for the Hamiltonian of a model having no physical structure. We provide here explicitly the notion of an artificial Hamiltonian for dynamical systems of ordinary differential equations (ODEs). Also, we show that every system of second-order ODEs can be expressed as a non-standard (partial) Hamiltonian system of first-order ODEs by introducing an artificial Hamiltonian. This notion of an artificial Hamiltonian gives a new way to solve dynamical systems of first-order ODEs and systems of second-order ODEs that can be expressed as a non-standard (partial) Hamiltonian system by using the known techniques applicable to the non-standard Hamiltonian systems. We employ the proposed notion to solve dynamical systems of first-order ODEs arising in epidemics.

  10. Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

    Science.gov (United States)

    He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

    2016-03-01

    In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  11. TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

    Energy Technology Data Exchange (ETDEWEB)

    Preusser, T. [Fraunhofer MEVIS & Jacobs University (Germany)

    2015-06-15

    Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such as the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)

  12. TU-G-210-02: TRANS-FUSIMO - An Integrative Approach to Model-Based Treatment Planning of Liver FUS

    International Nuclear Information System (INIS)

    Preusser, T.

    2015-01-01

    Modeling can play a vital role in predicting, optimizing and analyzing the results of therapeutic ultrasound treatments. Simulating the propagating acoustic beam in various targeted regions of the body allows for the prediction of the resulting power deposition and temperature profiles. In this session we will apply various modeling approaches to breast, abdominal organ and brain treatments. Of particular interest is the effectiveness of procedures for correcting for phase aberrations caused by intervening irregular tissues, such as the skull in transcranial applications or inhomogeneous breast tissues. Also described are methods to compensate for motion in targeted abdominal organs such as the liver or kidney. Douglas Christensen – Modeling for Breast and Brain HIFU Treatment Planning Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Tobias Preusser – TRANS-FUSIMO – An Integrative Approach to Model-Based Treatment Planning of Liver FUS Learning Objectives: Understand the role of acoustic beam modeling for predicting the effectiveness of therapeutic ultrasound treatments. Apply acoustic modeling to specific breast, liver, kidney and transcranial anatomies. Determine how to obtain appropriate acoustic modeling parameters from clinical images. Understand the separate role of absorption and scattering in energy delivery to tissues. See how organ motion can be compensated for in ultrasound therapies. Compare simulated data with clinical temperature measurements in transcranial applications. Supported by NIH R01 HL172787 and R01 EB013433 (DC); EU Seventh Framework Programme (FP7/2007-2013) under 270186 (FUSIMO) and 611889 (TRANS-FUSIMO)(TP); and P01 CA159992, GE, FUSF and InSightec (UV)

  13. A 3D visible evaluation of landslide risk degree under integration of GIS and artificial intelligence

    Institute of Scientific and Technical Information of China (English)

    QIAO; Jianping; ZHU; Axing; CHEN; Yongbo; WANG; Rongxun

    2003-01-01

    Artificial intelligence has been used to obtain background factors (basic environmental factors) from landslide specialists. A 3D visible evaluation map may be charted by fuzzy evaluation, and the traditional plane map may be decoded into a 3D map by using factor weight from specialists system and technology of RS and GIS for quantitative sampling of these factors.

  14. Robust and Accurate Closed-Loop Control of McKibben Artificial Muscle Contraction with a Linear Single Integral Action

    Directory of Open Access Journals (Sweden)

    Bertrand Tondu

    2014-06-01

    Full Text Available We analyze the possibility of taking advantage of artificial muscle’s own stiffness and damping, and substituting it for a classic proportional-integral-derivative controller (PID controller an I controller. The advantages are that there would only be one parameter to tune and no need for a dynamic model. A stability analysis is proposed from a simple phenomenological artificial muscle model. Step and sinus-wave tracking responses performed with pneumatic McKibben muscles are reported showing the practical efficiency of the method to combine accuracy and load robustness. In the particular case of the McKibben artificial muscle technology, we suggest that the dynamic performances in stability and load robustness would result from the textile nature of its braided sleeve and its internal friction which do not obey Coulomb’s third law, as verified by preliminary reported original friction experiments. Comparisons are reported between three kinds of braided sleeves made of rayon yarns, plastic, and thin metal wires, whose similar closed-loop dynamic performances are highlighted. It is also experimentally shown that a sleeve braided with thin metal wires can give high accuracy performance, in step as in tracking response. This would be due to a low static friction coefficient combined with a kinetic friction exponentially increasing with speed in accordance with hydrodynamic lubrication theory applied to textile physics.

  15. 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.

  16. Rapid Integration of Artificial Sensory Feedback during Operant Conditioning of Motor Cortex Neurons.

    Science.gov (United States)

    Prsa, Mario; Galiñanes, Gregorio L; Huber, Daniel

    2017-02-22

    Neuronal motor commands, whether generating real or neuroprosthetic movements, are shaped by ongoing sensory feedback from the displacement being produced. Here we asked if cortical stimulation could provide artificial feedback during operant conditioning of cortical neurons. Simultaneous two-photon imaging and real-time optogenetic stimulation were used to train mice to activate a single neuron in motor cortex (M1), while continuous feedback of its activity level was provided by proportionally stimulating somatosensory cortex. This artificial signal was necessary to rapidly learn to increase the conditioned activity, detect correct performance, and maintain the learned behavior. Population imaging in M1 revealed that learning-related activity changes are observed in the conditioned cell only, which highlights the functional potential of individual neurons in the neocortex. Our findings demonstrate the capacity of animals to use an artificially induced cortical channel in a behaviorally relevant way and reveal the remarkable speed and specificity at which this can occur. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  17. An Integrated Start-Up Method for Pumped Storage Units Based on a Novel Artificial Sheep Algorithm

    Directory of Open Access Journals (Sweden)

    Zanbin Wang

    2018-01-01

    Full Text Available Pumped storage units (PSUs are an important storage tool for power systems containing large-scale renewable energy, and the merit of rapid start-up enable PSUs to modulate and stabilize the power system. In this paper, PSU start-up strategies have been studied and a new integrated start-up method has been proposed for the purpose of achieving swift and smooth start-up. A two-phase closed-loop startup strategy, composed of switching Proportion Integration (PI and Proportion Integration Differentiation (PID controller is designed, and an integrated optimization scheme is proposed for a synchronous optimization of the parameters in the strategy. To enhance the optimization performance, a novel meta-heuristic called Artificial Sheep Algorithm (ASA is proposed and applied to solve the optimization task after a sufficient verification with seven popular meta-heuristic algorithms and 13 typical benchmark functions. Simulation model has been built for a China’s PSU and comparative experiments are conducted to evaluate the proposed integrated method. Results show that the start-up performance could be significantly improved on both indices on overshoot and start-up, and up to 34%-time consumption has been reduced under different working condition. The significant improvements on start-up of PSU is interesting and meaning for further application on real unit.

  18. Artificial intelligence, neural network, and Internet tool integration in a pathology workstation to improve information access

    Science.gov (United States)

    Sargis, J. C.; Gray, W. A.

    1999-03-01

    The APWS allows user friendly access to several legacy systems which would normally each demand domain expertise for proper utilization. The generalized model, including objects, classes, strategies and patterns is presented. The core components of the APWS are the Microsoft Windows 95 Operating System, Oracle, Oracle Power Objects, Artificial Intelligence tools, a medical hyperlibrary and a web site. The paper includes a discussion of how could be automated by taking advantage of the expert system, object oriented programming and intelligent relational database tools within the APWS.

  19. Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems

    International Nuclear Information System (INIS)

    Tong, S.S.; Powell, D.; Goel, S.

    1992-02-01

    A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs

  20. Integrated control of sun shades, daylight and artificial light; Integreret regulering af solafskaermning, dagslys og kunstlys

    Energy Technology Data Exchange (ETDEWEB)

    Johnsen, K.; Christoffersen, J.; Soerensen, Henrik; Jessen, G.

    2011-07-01

    The project established a basis of calculation and a practical basis for optimum choice of solar shading and integrated control strategies for both new buildings and for office, commercial and institutional buildings to be renovated with new calculation models for controlling solar shading integrated in the BSim program. A complete and applicable model for optimum, integrated solar shading control was established, focusing on thermal and visual comfort criteria towards energy consumption for heating, cooling and lighting. A prototype was tested in the daylight laboratory at Danish Building Research Institute-Aalborg University and at University of Southern Denmark. (LN)

  1. Artificial intelligent decision support for low-cost launch vehicle integrated mission operations

    Science.gov (United States)

    Szatkowski, Gerard P.; Schultz, Roger

    1988-01-01

    The feasibility, benefits, and risks associated with Artificial Intelligence (AI) Expert Systems applied to low cost space expendable launch vehicle systems are reviewed. This study is in support of the joint USAF/NASA effort to define the next generation of a heavy-lift Advanced Launch System (ALS) which will provide economical and routine access to space. The significant technical goals of the ALS program include: a 10 fold reduction in cost per pound to orbit, launch processing in under 3 weeks, and higher reliability and safety standards than current expendables. Knowledge-based system techniques are being explored for the purpose of automating decision support processes in onboard and ground systems for pre-launch checkout and in-flight operations. Issues such as: satisfying real-time requirements, providing safety validation, hardware and Data Base Management System (DBMS) interfacing, system synergistic effects, human interfaces, and ease of maintainability, have an effect on the viability of expert systems as a useful tool.

  2. Development of an artificial neural network model integrated with constitutive and FEM models

    International Nuclear Information System (INIS)

    Kong, L.X.; Hodgson, P.D.

    2000-01-01

    Although the standard error of IPANN model developed by Kong and Hodgson is lower than the constitutive model, it is found that the prediction of reaction force and torque during rolling with FEM is less accurate for IPANN model in some deformation regions. It is the summation of the product of the strain and stress in the deformation range, which contributes most to the precise prediction. An ANN model is therefore, developed in this work by integrating both the IPANN and FEM models. It is found that the integrated IPANN and FEM model is the most accurate model. (author)

  3. Integrating human factors and artificial intelligence in the development of human-machine cooperation

    NARCIS (Netherlands)

    Maanen, P.P. van; Lindenberg, J.; Neericx, M.A.

    2005-01-01

    Increasing machine intelligence leads to a shift from a mere interactive to a much more complex cooperative human-machine relation requiring a multidisciplinary development approach. This paper presents a generic multidisciplinary cognitive engineering method CE+ for the integration of human factors

  4. A Alternative Analog Circuit Design Methodology Employing Integrated Artificial Intelligence Techniques

    Science.gov (United States)

    Tuttle, Jeffery L.

    In consideration of the computer processing power now available to the designer, an alternative analog circuit design methodology is proposed. Computer memory capacities no longer require the reduction of the transistor operational characteristics to an imprecise formulation. Therefore, it is proposed that transistor modelling be abandoned in favor of fully characterized transistor data libraries. Secondly, availability of the transistor libraries would facilitate an automated selection of the most appropriate device(s) for the circuit being designed. More specifically, a preprocessor computer program to a more sophisticated circuit simulator (e.g. SPICE) is developed to assist the designer in developing the basic circuit topology and the selection of the most appropriate transistor. Once this is achieved, the circuit topology and selected transistor data library would be downloaded to the simulator for full circuit operational characterization and subsequent design modifications. It is recognized that the design process is enhanced by the use of heuristics as applied to iterative design results. Accordingly, an artificial intelligence (AI) interface is developed to assist the designer in applying the preprocessor results. To demonstrate the retrofitability of the AI interface to established programs, the interface is specifically designed to be as non-intrusive to the host code as possible. Implementation of the proposed methodology offers the potential to speed the design process, since the preprocessor both minimizes the required number of simulator runs and provides a higher acceptance potential of the initial and subsequent simulator runs. Secondly, part count reductions may be realizable since the circuit topologies are not as strongly driven by transistor limitations. Thirdly, the predicted results should more closely match actual circuit operations since the inadequacies of the transistor models have been virtually eliminated. Finally, the AI interface

  5. Integrated Assessment to Evaluate the Artificial Recharge in a Small Portion of the Aquifer of Puebla, Mexico

    Science.gov (United States)

    Arango-Galván, C.; Flores-Marquez, L. E.; Martínez-Serrano, R.

    2009-12-01

    New policies on the use of water resources in Mexico have led to implement some alternative measures to optimize water management. In particular, water regulation entities have recommended some tools to preserve and protect the groundwater supplies. One of these tools is the artificial recharge by injecting water directly into the aquifer. The main goal of this study is to assess if it is suitable to inject rainwater and surface water in a small portion of the aquifer of the city of Puebla, in central Mexico. Artificial aquifer recharging was evaluated using a numeric model, which simulated the physical properties of the system. The model setup was inferred from an integrated study taking into account hydraulic, geological and geophysical data. The geoelectrical model was computed using electric resistivity tomography (ERT) and time domain electromagnetic data (TDEM). The aquifer geological structure inferred from geophysics depicts the presence of a shallower layer composed of sand and clay deposits with low saturation and permeability. This layer contains silt lenses that can be controlling the persistence of small water bodies on surface. Some water surficial bodies seem to be isolated from the main aquifer system. The intermediate layer shows lower electrical resistivity and higher permeability. Underlying this horizon, it is a deeper layer that reaches 200 m depth, according to information obtained from borehole in the zone. This layer shows an electrical resistivity even lower than intermediate layer but low permeability, caused by the higher content of silts. Both of these layers are the shallower aquifer exploited in the area. Once the numeric model was built we proceeded to simulate scenarios that include the continued extraction and recharge of water in wells located in strategic areas of the study zone. The results suggest that the effect of infiltration is beneficial on aquifer recharge and reduces the cone of depression caused by the extraction

  6. Hierarchical hybrid control of manipulators: Artificial intelligence in large scale integrated circuits

    Science.gov (United States)

    Greene, P. H.

    1972-01-01

    Both in practical engineering and in control of muscular systems, low level subsystems automatically provide crude approximations to the proper response. Through low level tuning of these approximations, the proper response variant can emerge from standardized high level commands. Such systems are expressly suited to emerging large scale integrated circuit technology. A computer, using symbolic descriptions of subsystem responses, can select and shape responses of low level digital or analog microcircuits. A mathematical theory that reveals significant informational units in this style of control and software for realizing such information structures are formulated.

  7. Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

    Science.gov (United States)

    Merolla, Paul A; Arthur, John V; Alvarez-Icaza, Rodrigo; Cassidy, Andrew S; Sawada, Jun; Akopyan, Filipp; Jackson, Bryan L; Imam, Nabil; Guo, Chen; Nakamura, Yutaka; Brezzo, Bernard; Vo, Ivan; Esser, Steven K; Appuswamy, Rathinakumar; Taba, Brian; Amir, Arnon; Flickner, Myron D; Risk, William P; Manohar, Rajit; Modha, Dharmendra S

    2014-08-08

    Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses. Chips can be tiled in two dimensions via an interchip communication interface, seamlessly scaling the architecture to a cortexlike sheet of arbitrary size. The architecture is well suited to many applications that use complex neural networks in real time, for example, multiobject detection and classification. With 400-pixel-by-240-pixel video input at 30 frames per second, the chip consumes 63 milliwatts. Copyright © 2014, American Association for the Advancement of Science.

  8. An integrated portfolio optimisation procedure based on data envelopment analysis, artificial bee colony algorithm and genetic programming

    Science.gov (United States)

    Hsu, Chih-Ming

    2014-12-01

    Portfolio optimisation is an important issue in the field of investment/financial decision-making and has received considerable attention from both researchers and practitioners. However, besides portfolio optimisation, a complete investment procedure should also include the selection of profitable investment targets and determine the optimal timing for buying/selling the investment targets. In this study, an integrated procedure using data envelopment analysis (DEA), artificial bee colony (ABC) and genetic programming (GP) is proposed to resolve a portfolio optimisation problem. The proposed procedure is evaluated through a case study on investing in stocks in the semiconductor sub-section of the Taiwan stock market for 4 years. The potential average 6-month return on investment of 9.31% from 1 November 2007 to 31 October 2011 indicates that the proposed procedure can be considered a feasible and effective tool for making outstanding investment plans, and thus making profits in the Taiwan stock market. Moreover, it is a strategy that can help investors to make profits even when the overall stock market suffers a loss.

  9. 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.

  10. An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination.

    Science.gov (United States)

    Kuo, R J; Wu, P; Wang, C P

    2002-09-01

    Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.

  11. A Novel Multiscale Ensemble Carbon Price Prediction Model Integrating Empirical Mode Decomposition, Genetic Algorithm and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Bangzhu Zhu

    2012-02-01

    Full Text Available Due to the movement and complexity of the carbon market, traditional monoscale forecasting approaches often fail to capture its nonstationary and nonlinear properties and accurately describe its moving tendencies. In this study, a multiscale ensemble forecasting model integrating empirical mode decomposition (EMD, genetic algorithm (GA and artificial neural network (ANN is proposed to forecast carbon price. Firstly, the proposed model uses EMD to decompose carbon price data into several intrinsic mode functions (IMFs and one residue. Then, the IMFs and residue are composed into a high frequency component, a low frequency component and a trend component which have similar frequency characteristics, simple components and strong regularity using the fine-to-coarse reconstruction algorithm. Finally, those three components are predicted using an ANN trained by GA, i.e., a GAANN model, and the final forecasting results can be obtained by the sum of these three forecasting results. For verification and testing, two main carbon future prices with different maturity in the European Climate Exchange (ECX are used to test the effectiveness of the proposed multiscale ensemble forecasting model. Empirical results obtained demonstrate that the proposed multiscale ensemble forecasting model can outperform the single random walk (RW, ARIMA, ANN and GAANN models without EMD preprocessing and the ensemble ARIMA model with EMD preprocessing.

  12. Energy optimization and prediction of complex petrochemical industries using an improved artificial neural network approach integrating data envelopment analysis

    International Nuclear Information System (INIS)

    Han, Yong-Ming; Geng, Zhi-Qiang; Zhu, Qun-Xiong

    2016-01-01

    Graphical abstract: This paper proposed an energy optimization and prediction of complex petrochemical industries based on a DEA-integrated ANN approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA-ANN prediction model is effectively verified by executing a linear comparison between all DMUs and the effective DMUs through the standard data source from the UCI (University of California at Irvine) repository. Finally, the proposed model is validated through an application in a complex ethylene production system of China petrochemical industry. Meanwhile, the optimization result and the prediction value are obtained to reduce energy consumption of the ethylene production system, guide ethylene production and improve energy efficiency. - Highlights: • The DEA-integrated ANN approach is proposed. • The DEA-ANN prediction model is effectively verified through the standard data source from the UCI repository. • The energy optimization and prediction framework of complex petrochemical industries based on the proposed method is obtained. • The proposed method is valid and efficient in improvement of energy efficiency in complex petrochemical plants. - Abstract: Since the complex petrochemical data have characteristics of multi-dimension, uncertainty and noise, it is difficult to accurately optimize and predict the energy usage of complex petrochemical systems. Therefore, this paper proposes a data envelopment analysis (DEA) integrated artificial neural network (ANN) approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA

  13. Model-based security testing

    OpenAIRE

    Schieferdecker, Ina; Großmann, Jürgen; Schneider, Martin

    2012-01-01

    Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security...

  14. Self-organized Criticality and Synchronization in a Pulse-coupled Integrate-and-Fire Neuron Model Based on Small World Networks

    International Nuclear Information System (INIS)

    Lin Min; Chen Tianlun

    2005-01-01

    A lattice model for a set of pulse-coupled integrate-and-fire neurons with small world structure is introduced. We find that our model displays the power-law behavior accompanied with the large-scale synchronized activities among the units. And the different connectivity topologies lead to different behaviors in models of integrate-and-fire neurons.

  15. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

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

  16. Energy saving analysis and management modeling based on index decomposition analysis integrated energy saving potential method: Application to complex chemical processes

    International Nuclear Information System (INIS)

    Geng, Zhiqiang; Gao, Huachao; Wang, Yanqing; Han, Yongming; Zhu, Qunxiong

    2017-01-01

    Highlights: • The integrated framework that combines IDA with energy-saving potential method is proposed. • Energy saving analysis and management framework of complex chemical processes is obtained. • This proposed method is efficient in energy optimization and carbon emissions of complex chemical processes. - Abstract: Energy saving and management of complex chemical processes play a crucial role in the sustainable development procedure. In order to analyze the effect of the technology, management level, and production structure having on energy efficiency and energy saving potential, this paper proposed a novel integrated framework that combines index decomposition analysis (IDA) with energy saving potential method. The IDA method can obtain the level of energy activity, energy hierarchy and energy intensity effectively based on data-drive to reflect the impact of energy usage. The energy saving potential method can verify the correctness of the improvement direction proposed by the IDA method. Meanwhile, energy efficiency improvement, energy consumption reduction and energy savings can be visually discovered by the proposed framework. The demonstration analysis of ethylene production has verified the practicality of the proposed method. Moreover, we can obtain the corresponding improvement for the ethylene production based on the demonstration analysis. The energy efficiency index and the energy saving potential of these worst months can be increased by 6.7% and 7.4%, respectively. And the carbon emissions can be reduced by 7.4–8.2%.

  17. Integrated Sensing & Controls for Coal Gasification - Development of Model-Based Controls for GE's Gasifier & Syngas Cooler. Topical Rerport for Phase III

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Aditya

    2011-02-17

    This Topical Report for the final Phase III of the program summarizes the results from the Task 3 of the program. In this task, the separately designed extended Kalman Filter (EKF) and model predictive controls (MPC) with ideal sensing, developed in Phase II, were integrated to achieve the overall sensing and control system for the gasification section of an IGCC plant. The EKF and MPC algorithms were updated and re-tuned to achieve closed-loop system stability as well as good steady-state and transient control response. In particular, the performance of the integrated EKF and MPC solution was tested extensively through multiple simulation studies to achieve improved steady-state as well as transient performance, with coal as well as coal-petcoke blended fuel, in the presence of unknown modeling errors as well as sensor errors (noise and bias). The simulation studies demonstrated significant improvements in steady state and transient operation performance, similar to that achieved by MPC with ideal sensors in Phase II of the program.

  18. Artificial Intelligence.

    Science.gov (United States)

    Information Technology Quarterly, 1985

    1985-01-01

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

  19. Artificial organ engineering

    CERN Document Server

    Annesini, Maria Cristina; Piemonte, Vincenzo; Turchetti, Luca

    2017-01-01

    Artificial organs may be considered as small-scale process plants, in which heat, mass and momentum transfer operations and, possibly, chemical transformations are carried out. This book proposes a novel analysis of artificial organs based on the typical bottom-up approach used in process engineering. Starting from a description of the fundamental physico-chemical phenomena involved in the process, the whole system is rebuilt as an interconnected ensemble of elemental unit operations. Each artificial organ is presented with a short introduction provided by expert clinicians. Devices commonly used in clinical practice are reviewed and their performance is assessed and compared by using a mathematical model based approach. Whilst mathematical modelling is a fundamental tool for quantitative descriptions of clinical devices, models are kept simple to remain focused on the essential features of each process. Postgraduate students and researchers in the field of chemical and biomedical engineering will find that t...

  20. The effect of polystyrene sodium sulfonate grafting on polyethylene terephthalate artificial ligaments on in vitro mineralisation and in vivo bone tissue integration

    Science.gov (United States)

    Vaquette, Cédryck; Viateau, Véronique; Guérard, Sandra; Anagnostou, Fani; Manassero, Mathieu; Castner, David G.; Migonney, Véronique

    2013-01-01

    This study investigates the impact of polystyrene sodium sulfonate (PolyNaSS) grafting onto the osseointegration of a polyethylene terephthalate artificial ligament (Ligament Advanced Reinforcement System, LARS™) used for Anterior Cruciate Ligament (ACL). The performance of grafted and non-grafted ligaments was assessed in vitro by culturing human osteoblasts under osteogenic induction and this demonstrated that the surface modification was capable of up-regulating the secretion of ALP and induced higher level of mineralisation as measured 6 weeks post-seeding by Micro-Computed Tomography. Grafted and non-grafted LARS™ were subsequently implanted in an ovine model for ACL reconstruction and the ligament-to-bone interface was evaluated by histology and biomechanical testing 3 and 12 months post-implantation. The grafted ligaments exhibited more frequent direct ligament-to-bone contact and bone formation in the core of the ligament at the later time point than the nongrafted specimens, the grafting also significantly reduced the fibrous encapsulation of the ligament 12 months post-implantation. However, this improved osseo-integration was not translated into a significant increase in the biomechanical pull-out loads. These results provide evidences that PolyNaSS grafting improved the osseo-integration of the artificial ligament within the bone tunnels. This might positively influence the outcome of the surgical reconstructions, as higher ligament stability is believed to limit micro-movement and therefore permits earlier and enhanced healing. PMID:23790438

  1. Integrating process safety with molecular modeling-based risk assessment of chemicals within the REACH regulatory framework: benefits and future challenges.

    Science.gov (United States)

    Lewis, Amanda; Kazantzis, Nikolaos; Fishtik, Ilie; Wilcox, Jennifer

    2007-04-11

    Registration, evaluation and authorization of chemicals (REACH) represents a recent regulatory initiative by the European union commission to protect human health and the environment from potentially hazardous chemicals. Under REACH, all stakeholders must submit (thermo)physical, thermochemical, and toxicological data for certain chemicals. The commission's impact assessment studies estimate that the costs of REACH will be approximately 3-5 billion Euros. The present study advocates the systematic incorporation of computational chemistry and computer-assisted chemical risk assessment methods into REACH to reduce regulatory compliance costs. Currently powerful computer-aided ab initio techniques can be used to generate predictions of key properties of broad classes of chemicals, without resorting to costly experimentation and potentially hazardous testing. These data could be integrated into a centralized IT decision and compliance support system, and stored in a retrievable, easily communicable manner should new regulatory and/or production requirements necessitate the introduction of different uses of chemicals under different conditions. For illustration purposes, ab initio calculations are performed on heterocyclic nitrogen-containing compounds which currently serve as high energy density materials in the chemical industry. Since investigations of these compounds are still in their infancy, stability studies are imperative regarding their safe handling and storage, as well as registration under REACH.

  2. Integrating process safety with molecular modeling-based risk assessment of chemicals within the REACH regulatory framework: Benefits and future challenges

    International Nuclear Information System (INIS)

    Lewis, Amanda; Kazantzis, Nikolaos; Fishtik, Ilie; Wilcox, Jennifer

    2007-01-01

    Registration, evaluation and authorization of chemicals (REACH) represents a recent regulatory initiative by the European union commission to protect human health and the environment from potentially hazardous chemicals. Under REACH, all stakeholders must submit (thermo)physical, thermochemical, and toxicological data for certain chemicals. The commission's impact assessment studies estimate that the costs of REACH will be approximately 3-5 billion Euros. The present study advocates the systematic incorporation of computational chemistry and computer-assisted chemical risk assessment methods into REACH to reduce regulatory compliance costs. Currently powerful computer-aided ab initio techniques can be used to generate predictions of key properties of broad classes of chemicals, without resorting to costly experimentation and potentially hazardous testing. These data could be integrated into a centralized IT decision and compliance support system, and stored in a retrievable, easily communicable manner should new regulatory and/or production requirements necessitate the introduction of different uses of chemicals under different conditions. For illustration purposes, ab initio calculations are performed on heterocyclic nitrogen-containing compounds which currently serve as high energy density materials in the chemical industry. Since investigations of these compounds are still in their infancy, stability studies are imperative regarding their safe handling and storage, as well as registration under REACH

  3. Artificial Leaks in Container Closure Integrity Testing: Nonlinear Finite Element Simulation of Aperture Size Originated by a Copper Wire Sandwiched between the Stopper and the Glass Vial.

    Science.gov (United States)

    Nieto, Alejandra; Roehl, Holger; Brown, Helen; Adler, Michael; Chalus, Pascal; Mahler, Hanns-Christian

    2016-01-01

    Container closure integrity (CCI) testing is required by different regulatory authorities in order to provide assurance of tightness of the container closure system against possible contamination, for example, by microorganisms. Microbial ingress CCI testing is performed by incubation of the container closure system with microorganisms under specified testing conditions. Physical CCI uses surrogate endpoints, such as coloration by dye solution ingress or gas flow (helium leakage testing). In order to correlate microbial CCI and physical CCI test methods and to evaluate the methods' capability to detect a given leak, artificial leaks are being introduced into the container closure system in a variety of different ways. In our study, artificial leaks were generated using inserted copper wires between the glass vial opening and rubber stopper. However, the insertion of copper wires introduces leaks of unknown size and shape. With nonlinear finite element simulations, the aperture size between the rubber stopper and the glass vial was calculated, depending on wire diameter and capping force. The dependency of the aperture size on the copper wire diameter was quadratic. With the data obtained, we were able to calculate the leak size and model leak shape. Our results suggest that the size as well as the shape of the artificial leaks should be taken into account when evaluating critical leak sizes, as flow rate does not, independently, correlate to hole size. Capping force also affected leak size. An increase in the capping force from 30 to 70 N resulted in a reduction of the aperture (leak size) by approximately 50% for all wire diameters. From 30 to 50 N, the reduction was approximately 33%. Container closure integrity (CCI) testing is required by different regulatory authorities in order to provide assurance of tightness of the container closure system against contamination, for example, by microorganisms. Microbial ingress CCI testing is performed by incubation of the

  4. Authentic scientific data collection in support of an integrative model-based class: A framework for student engagement in the classroom

    Science.gov (United States)

    Sorensen, A. E.; Dauer, J. M.; Corral, L.; Fontaine, J. J.

    2017-12-01

    A core component of public scientific literacy, and thereby informed decision-making, is the ability of individuals to reason about complex systems. In response to students having difficulty learning about complex systems, educational research suggests that conceptual representations, or mental models, may help orient student thinking. Mental models provide a framework to support students in organizing and developing ideas. The PMC-2E model is a productive tool in teaching ideas of modeling complex systems in the classroom because the conceptual representation framework allows for self-directed learning where students can externalize systems thinking. Beyond mental models, recent work emphasizes the importance of facilitating integration of authentic science into the formal classroom. To align these ideas, a university class was developed around the theme of carnivore ecology, founded on PMC-2E framework and authentic scientific data collection. Students were asked to develop a protocol, collect, and analyze data around a scientific question in partnership with a scientist, and then use data to inform their own learning about the system through the mental model process. We identified two beneficial outcomes (1) scientific data is collected to address real scientific questions at a larger scale and (2) positive outcomes for student learning and views of science. After participating in the class, students report enjoying class structure, increased support for public understanding of science, and shifts in nature of science and interest in pursuing science metrics on post-assessments. Further work is ongoing investigating the linkages between engaging in authentic scientific practices that inform student mental models, and how it might promote students' systems-thinking skills, implications for student views of nature of science, and development of student epistemic practices.

  5. The economics of renewable electricity market integration. An empirical and model-based analysis of regulatory frameworks and their impacts on the power market

    Energy Technology Data Exchange (ETDEWEB)

    Nicolosi, Marco

    2012-07-01

    participate in the reserve power market. In general, the results show that if the flexibility of one system component is reduced, the flexibility values of other system components increase, which suggests a careful, integrated and long-term oriented policy setting.

  6. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

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

  7. Model-Based Security Testing

    Directory of Open Access Journals (Sweden)

    Ina Schieferdecker

    2012-02-01

    Full Text Available Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing, and the usage of security test patterns. This paper provides a survey on MBST techniques and the related models as well as samples of new methods and tools that are under development in the European ITEA2-project DIAMONDS.

  8. Integration of robotics and neuroscience beyond the hand: What kind of synergies?. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al.

    Science.gov (United States)

    d'Avella, Andrea

    2016-07-01

    Santello et al. [1] review an impressive amount of work on the control of biological and artificial hands that demonstrates how the concept of synergies can lead to a successful integration of robotics and neuroscience. Is it possible to generalize the same approach to the control of biological and artificial limbs and bodies beyond the hand? The human hand synergies that appear most relevant for robotic hands are those defined at the kinematic level, i.e. postural synergies [2]. Postural synergies capture the geometric relations among the many joints of the hand and allow for a low dimensional characterization and synthesis of the static hand postures involved in grasping and manipulating a large set of objects. However, many other complex motor skills such as walking, reaching, throwing, and catching require controlling multi-articular time-varying trajectories rather than static postures. Dynamic control of biological and artificial limbs and bodies, especially when geometric and inertial parameters are uncertain and the joints are compliant, poses great challenges. What kind of synergies might simplify the dynamic control of motor skills involving upper and lower limbs as well as the whole body?

  9. Integrated interpretation of AE clusters and fracture system in Hijiori HDR artificial reservoir; Hijiori koon gantai jinko choryuso no AE cluster to kiretsu system ni kansuru togoteki kaishaku

    Energy Technology Data Exchange (ETDEWEB)

    Tezuka, K [Japan Petroleum Exploration Corp., Tokyo (Japan); Niitsuma, H [Tohoku University, Sendai (Japan)

    1997-05-27

    With regard to a fracture system in the Hijiori hot dry rock artificial reservoir, an attempt was made on an interpretation which integrates different data. Major factors that characterize development and performance of an artificial reservoir are composed of a fracture system in rocks, which acts as circulating water paths, a heat exchange face and a reservoir space. The system relates not only with crack density distribution, but also with cracks activated by water pressure fracturing, cracks generating acoustic emission (AE), and cracks working as major flow paths, all of which are characterized by having respective behaviors and roles. Characteristics are shown on AE cluster distribution, crack distribution, production zone and estimated stress fields. Mutual relationship among these elements was discussed based on the Coulomb`s theory. The most important paths are characterized by distribution of slippery cracks. Directions and appearance frequencies of the slippery cracks affect strongly directionality of the paths, which are governed by distribution of the cracks (weak face) and stress field. Among the slippery cracks, cracks that generate AE are cracks that release large energy when a slip occurs. Evaluation on slippery crack distribution is important. 7 refs., 8 figs.

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

    Science.gov (United States)

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

    2018-08-01

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

  11. Artificial Consciousness or Artificial Intelligence

    OpenAIRE

    Spanache Florin

    2017-01-01

    Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

  12. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

  13. A novel system for simultaneous or sequential integration of multiple gene-loading vectors into a defined site of a human artificial chromosome.

    Science.gov (United States)

    Suzuki, Teruhiko; Kazuki, Yasuhiro; Oshimura, Mitsuo; Hara, Takahiko

    2014-01-01

    Human artificial chromosomes (HACs) are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV) into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system) via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming.

  14. A novel system for simultaneous or sequential integration of multiple gene-loading vectors into a defined site of a human artificial chromosome.

    Directory of Open Access Journals (Sweden)

    Teruhiko Suzuki

    Full Text Available Human artificial chromosomes (HACs are gene-delivery vectors suitable for introducing large DNA fragments into mammalian cells. Although a HAC theoretically incorporates multiple gene expression cassettes of unlimited DNA size, its application has been limited because the conventional gene-loading system accepts only one gene-loading vector (GLV into a HAC. We report a novel method for the simultaneous or sequential integration of multiple GLVs into a HAC vector (designated as the SIM system via combined usage of Cre, FLP, Bxb1, and φC31 recombinase/integrase. As a proof of principle, we first attempted simultaneous integration of three GLVs encoding EGFP, Venus, and TdTomato into a gene-loading site of a HAC in CHO cells. These cells successfully expressed all three fluorescent proteins. Furthermore, microcell-mediated transfer of HACs enabled the expression of those fluorescent proteins in recipient cells. We next demonstrated that GLVs could be introduced into a HAC one-by-one via reciprocal usage of recombinase/integrase. Lastly, we introduced a fourth GLV into a HAC after simultaneous integration of three GLVs by FLP-mediated DNA recombination. The SIM system expands the applicability of HAC vectors and is useful for various biomedical studies, including cell reprogramming.

  15. The Miracle of an Artificial Pancreas | NIH MedlinePlus the Magazine

    Science.gov (United States)

    ... Diabetes Follow us The Miracle of an Artificial Pancreas Four NIH-funded Artificial Pancreas Research Efforts Underway Thanks to investments in new ... diabetes are on the horizon, including the artificial pancreas. The artificial pancreas is an integrated system that ...

  16. [Artificial organs].

    Science.gov (United States)

    Raguin, Thibaut; Dupret-Bories, Agnès; Debry, Christian

    2017-01-01

    Research has been fighting against organ failure and shortage of donations by supplying artificial organs for many years. With the raise of new technologies, tissue engineering and regenerative medicine, many organs can benefit of an artificial equivalent: thanks to retinal implants some blind people can visualize stimuli, an artificial heart can be proposed in case of cardiac failure while awaiting for a heart transplant, artificial larynx enables laryngectomy patients to an almost normal life, while the diabetic can get a glycemic self-regulation controlled by smartphones with an artificial device. Dialysis devices become portable, as well as the oxygenation systems for terminal respiratory failure. Bright prospects are being explored or might emerge in a near future. However, the retrospective assessment of putative side effects is not yet sufficient. Finally, the cost of these new devices is significant even if the advent of three dimensional printers may reduce it. © 2017 médecine/sciences – Inserm.

  17. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

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

  18. Integrating artificial neural networks and empirical correlations for the prediction of water-subcooled critical heat flux

    International Nuclear Information System (INIS)

    Mazzola, A.

    1997-01-01

    The critical heat flux (CHF) is an important parameter for the design of nuclear reactors, heat exchangers and other boiling heat transfer units. Recently, the CHF in water-subcooled flow boiling at high mass flux and subcooling has been thoroughly studied in relation to the cooling of high-heat-flux components in thermonuclear fusion reactors. Due to the specific thermal-hydraulic situation, very few of the existing correlations, originally developed for operating conditions typical of pressurized water reactors, are able to provide consistent predictions of water-subcooled-flow-boiling CHF at high heat fluxes. Therefore, alternative predicting techniques are being investigated. Among these, artificial neural networks (ANN) have the advantage of not requiring a formal model structure to fit the experimental data; however, their main drawbacks are the loss of model transparency ('black-box' character) and the lack of any indicator for evaluating accuracy and reliability of the ANN answer when 'never-seen' patterns are presented. In the present work, the prediction of CHF is approached by a hybrid system which couples a heuristic correlation with a neural network. The ANN role is to predict a datum-dependent parameter required by the analytical correlation; ; this parameter was instead set to a constant value obtained by usual best-fitting techniques when a pure analytical approach was adopted. Upper and lower boundaries can be possibly assigned to the parameter value, thus avoiding the case of unexpected and unpredictable answer failure. The present approach maintains the advantage of the analytical model analysis, and it partially overcomes the 'black-box' character typical of the straight application of ANNs because the neural network role is limited to the correlation tuning. The proposed methodology allows us to achieve accurate results and it is likely to be suitable for thermal-hydraulic and heat transfer data processing. (author)

  19. Knowledge Discovery, Integration and Communication for Extreme Weather and Flood Resilience Using Artificial Intelligence: Flood AI Alpha

    Science.gov (United States)

    Demir, I.; Sermet, M. Y.

    2016-12-01

    Nobody is immune from extreme events or natural hazards that can lead to large-scale consequences for the nation and public. One of the solutions to reduce the impacts of extreme events is to invest in improving resilience with the ability to better prepare, plan, recover, and adapt to disasters. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This abstracts presents our project on developing a resilience framework for flooding to improve societal preparedness with objectives; (a) develop a generalized ontology for extreme events with primary focus on flooding; (b) develop a knowledge engine with voice recognition, artificial intelligence, natural language processing, and inference engine. The knowledge engine will utilize the flood ontology and concepts to connect user input to relevant knowledge discovery outputs on flooding; (c) develop a data acquisition and processing framework from existing environmental observations, forecast models, and social networks. The system will utilize the framework, capabilities and user base of the Iowa Flood Information System (IFIS) to populate and test the system; (d) develop a communication framework to support user interaction and delivery of information to users. The interaction and delivery channels will include voice and text input via web-based system (e.g. IFIS), agent-based bots (e.g. Microsoft Skype, Facebook Messenger), smartphone and augmented reality applications (e.g. smart assistant), and automated web workflows (e.g. IFTTT, CloudWork) to open the knowledge discovery for flooding to thousands of community extensible web workflows.

  20. Integrated Application of Random Forest and Artificial Neural Network Algorithms to Predict Viral Contamination in Coastal Waters

    Science.gov (United States)

    Shamkhali Chenar, S.; Deng, Z.

    2017-12-01

    Pathogenic viruses pose a significant public health threat and economic losses to shellfish industry in the coastal environment. Norovirus is a contagious virus and the leading cause of epidemic gastroenteritis following consumption of oysters harvested from sewage-contaminated waters. While it is challenging to detect noroviruses in coastal waters due to the lack of sensitive and routine diagnostic methods, machine learning techniques are allowing us to prevent or at least reduce the risks by developing effective predictive models. This study attempts to develop an algorithm between historical norovirus outbreak reports and environmental parameters including water temperature, solar radiation, water level, salinity, precipitation, and wind. For this purpose, the Random Forests statistical technique was utilized to select relevant environmental parameters and their various combinations with different time lags controlling the virus distribution in oyster harvesting areas along the Louisiana Coast. An Artificial Neural Networks (ANN) approach was then presented to predict the outbreaks using a final set of input variables. Finally, a sensitivity analysis was conducted to evaluate relative importance and contribution of the input variables to the model output. Findings demonstrated that the developed model was capable of reproducing historical oyster norovirus outbreaks along the Louisiana Coast with the overall accuracy of than 99.83%, demonstrating the efficacy of the model. Moreover, the increase in water temperature, solar radiation, water level, and salinity, and the decrease in wind and rainfall are associated with the reduction in the model-predicted risk of norovirus outbreak according to sensitivity analysis results. In conclusion, the presented machine learning approach provided reliable tools for predicting potential norovirus outbreaks and could be used for early detection of possible outbreaks and reduce the risk of norovirus to public health and the

  1. Development of a multiple-gene-loading method by combining multi-integration system-equipped mouse artificial chromosome vector and CRISPR-Cas9.

    Directory of Open Access Journals (Sweden)

    Kazuhisa Honma

    Full Text Available Mouse artificial chromosome (MAC vectors have several advantages as gene delivery vectors, such as stable and independent maintenance in host cells without integration, transferability from donor cells to recipient cells via microcell-mediated chromosome transfer (MMCT, and the potential for loading a megabase-sized DNA fragment. Previously, a MAC containing a multi-integrase platform (MI-MAC was developed to facilitate the transfer of multiple genes into desired cells. Although the MI system can theoretically hold five gene-loading vectors (GLVs, there are a limited number of drugs available for the selection of multiple-GLV integration. To overcome this issue, we attempted to knock out and reuse drug resistance genes (DRGs using the CRISPR-Cas9 system. In this study, we developed new methods for multiple-GLV integration. As a proof of concept, we introduced five GLVs in the MI-MAC by these methods, in which each GLV contained a gene encoding a fluorescent or luminescent protein (EGFP, mCherry, BFP, Eluc, and Cluc. Genes of interest (GOI on the MI-MAC were expressed stably and functionally without silencing in the host cells. Furthermore, the MI-MAC carrying five GLVs was transferred to other cells by MMCT, and the resultant recipient cells exhibited all five fluorescence/luminescence signals. Thus, the MI-MAC was successfully used as a multiple-GLV integration vector using the CRISPR-Cas9 system. The MI-MAC employing these methods may resolve bottlenecks in developing multiple-gene humanized models, multiple-gene monitoring models, disease models, reprogramming, and inducible gene expression systems.

  2. Artificial Reefs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An artificial reef is a human-made underwater structure, typically built to promote marine life in areas with a generally featureless bottom, control erosion, block...

  3. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  4. Natural - synthetic - artificial!

    DEFF Research Database (Denmark)

    Nielsen, Peter E

    2010-01-01

    The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

  5. WE-G-BRD-04: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An Integrated Model-Based Intrafractional Organ Motion Tracking Approach with Dynamic MRI in Head and Neck Radiotherapy

    Energy Technology Data Exchange (ETDEWEB)

    Chen, H; Dolly, S; Anastasio, M; Li, H; Wooten, H; Gay, H; Mutic, S; Thorstad, W; Li, H [Washington University School of Medicine, Saint Louis, MO (United States); Victoria, J; Dempsey, J [ViewRay incorporated, Oakwood Village, Ohio (United States); Ruan, S [University of Rouen, QuantIF - EA 4108 LITIS, Rouen (France); Low, D [Deparment of Radiation Oncology, University of California Los Angeles, Los Angeles, CA (United States)

    2015-06-15

    Purpose: In-treatment dynamic cine images, provided by the first commercially available MRI-guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model-based approach to automatically delineate and analyze moving structures from on-board cine images. Methods: The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target-to-be-tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face-jaw, and face-jaw-palate) was first built from a set of manually delineated shapes using principal component analysis. An integrated model-fitting algorithm was then employed to align the statistical shapes to the first to-be-detected cine frame, and multi-feature level-set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency. Conclusion: We proposed the integrated computational approach, which for the first

  6. WE-G-BRD-04: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An Integrated Model-Based Intrafractional Organ Motion Tracking Approach with Dynamic MRI in Head and Neck Radiotherapy

    International Nuclear Information System (INIS)

    Chen, H; Dolly, S; Anastasio, M; Li, H; Wooten, H; Gay, H; Mutic, S; Thorstad, W; Li, H; Victoria, J; Dempsey, J; Ruan, S; Low, D

    2015-01-01

    Purpose: In-treatment dynamic cine images, provided by the first commercially available MRI-guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model-based approach to automatically delineate and analyze moving structures from on-board cine images. Methods: The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target-to-be-tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face-jaw, and face-jaw-palate) was first built from a set of manually delineated shapes using principal component analysis. An integrated model-fitting algorithm was then employed to align the statistical shapes to the first to-be-detected cine frame, and multi-feature level-set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency. Conclusion: We proposed the integrated computational approach, which for the first

  7. Principles of models based engineering

    Energy Technology Data Exchange (ETDEWEB)

    Dolin, R.M.; Hefele, J.

    1996-11-01

    This report describes a Models Based Engineering (MBE) philosophy and implementation strategy that has been developed at Los Alamos National Laboratory`s Center for Advanced Engineering Technology. A major theme in this discussion is that models based engineering is an information management technology enabling the development of information driven engineering. Unlike other information management technologies, models based engineering encompasses the breadth of engineering information, from design intent through product definition to consumer application.

  8. Advanced Applications of Neural Networks and Artificial Intelligence: A Review

    OpenAIRE

    Koushal Kumar; Gour Sundar Mitra Thakur

    2012-01-01

    Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

  9. Artificial sweeteners

    DEFF Research Database (Denmark)

    Raben, Anne Birgitte; Richelsen, Bjørn

    2012-01-01

    Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie-containin......Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie......-containing sweeteners. The purpose of this review is to summarize the current evidence on the effect of artificial sweeteners on body weight, appetite, and risk markers for diabetes and CVD in humans....

  10. Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange

    Science.gov (United States)

    Jahangoshai Rezaee, Mustafa; Jozmaleki, Mehrdad; Valipour, Mahsa

    2018-01-01

    One of the main features to invest in stock exchange companies is their financial performance. On the other hand, conventional evaluation methods such as data envelopment analysis are not only a retrospective process, but are also a process, which are incomplete and ineffective approaches to evaluate the companies in the future. To remove this problem, it is required to plan an expert system for evaluating organizations when the online data are received from stock exchange market. This paper deals with an approach for predicting the online financial performance of companies when data are received in different time's intervals. The proposed approach is based on integrating fuzzy C-means (FCM), data envelopment analysis (DEA) and artificial neural network (ANN). The classical FCM method is unable to update the number of clusters and their members when the data are changed or the new data are received. Hence, this method is developed in order to make dynamic features for the number of clusters and clusters members in classical FCM. Then, DEA is used to evaluate DMUs by using financial ratios to provide targets in neural network. Finally, the designed network is trained and prepared for predicting companies' future performance. The data on Tehran Stock Market companies for six consecutive years (2007-2012) are used to show the abilities of the proposed approach.

  11. Determining the most suitable areas for artificial groundwater recharge via an integrated PROMETHEE II-AHP method in GIS environment (case study: Garabaygan Basin, Iran).

    Science.gov (United States)

    Nasiri, Hossein; Boloorani, Ali Darvishi; Sabokbar, Hassan Ali Faraji; Jafari, Hamid Reza; Hamzeh, Mohamad; Rafii, Yusef

    2013-01-01

    Flood spreading is a suitable strategy for controlling and benefiting from floods. Selecting suitable areas for flood spreading and directing the floodwater into permeable formations are amongst the most effective strategies in flood spreading projects. Having combined geographic information systems (GIS) and multi-criteria decision analysis approaches, the present study sought to locate the most suitable areas for flood spreading operation in the Garabaygan Basin of Iran. To this end, the data layers relating to the eight effective factors were prepared in GIS environment. This stage was followed by elimination of the exclusionary areas for flood spreading while determining the potentially suitable ones. Having closely examined the potentially suitable areas using the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) II and analytic hierarchy process (AHP) methods, the land suitability map for flood spreading was produced. The PROMETHEE II and AHP were used for ranking all the alternatives and weighting the criteria involved, respectively. The results of the study showed that most suitable areas for the artificial groundwater recharge are located in Quaternary Q(g) and Q(gsc) geologic units and in geomorphological units of pediment and Alluvial fans with slopes not exceeding 3%. Furthermore, significant correspondence between the produced map and the control areas, where the flood spreading projects were successfully performed, provided further evidence for the acceptable efficiency of the integrated PROMETHEE II-AHP method in locating suitable flood spreading areas.

  12. Identification and Mapping of Simple Sequence Repeat Markers from Common Bean (Phaseolus vulgaris L. Bacterial Artificial Chromosome End Sequences for Genome Characterization and Genetic–Physical Map Integration

    Directory of Open Access Journals (Sweden)

    Juana M. Córdoba

    2010-11-01

    Full Text Available Microsatellite markers or simple sequence repeat (SSR loci are useful for diversity characterization and genetic–physical mapping. Different in silico microsatellite search methods have been developed for mining bacterial artificial chromosome (BAC end sequences for SSRs. The overall goal of this study was genome characterization based on SSRs in 89,017 BAC end sequences (BESs from the G19833 common bean ( L. library. Another objective was to identify new SSR taking into account three tandem motif identification programs (Automated Microsatellite Marker Development [AMMD], Tandem Repeats Finder [TRF], and SSRLocator [SSRL]. Among the microsatellite search engines, SSRL identified the highest number of SSRs; however, when primer design was attempted, the number dropped due to poor primer design regions. Automated Microsatellite Marker Development software identified many SSRs with valuable AT/TA or AG/TC motifs, while TRF found fewer SSRs and produced no primers. A subgroup of 323 AT-rich, di-, and trinucleotide SSRs were selected from the AMMD results and used in a parental survey with DOR364 and G19833, of which 75 could be mapped in the corresponding population; these represented 4052 BAC clones. Together with 92 previously mapped BES- and 114 non-BES-derived markers, a total of 280 SSRs were included in the polymerase chain reaction (PCR-based map, integrating a total of 8232 BAC clones in 162 contigs from the physical map.

  13. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

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

  14. Artificial intelligence

    International Nuclear Information System (INIS)

    Perret-Galix, D.

    1992-01-01

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

  15. Integrating multiple vegetation indices via an artificial neural network model for estimating the leaf chlorophyll content of Spartina alterniflora under interspecies competition.

    Science.gov (United States)

    Liu, Pudong; Shi, Runhe; Zhang, Chao; Zeng, Yuyan; Wang, Jiapeng; Tao, Zhu; Gao, Wei

    2017-10-31

    The invasive species Spartina alterniflora and native species Phragmites australis display a significant co-occurrence zonation pattern and this co-exist region exerts most competitive situations between these two species, competing for the limited space, directly influencing the co-exist distribution in the future. However, these two species have different growth ratios in this area, which increase the difficulty to detect the distribution situation directly by remote sensing. As chlorophyll content is a key indicator of plant growth and physiological status, the objective of this study was to reduce the effect of interspecies competition when estimating Cab content; we evaluated 79 published representative indices to determine the optimal indices for estimating the chlorophyll a and b (Cab) content. After performing a sensitivity analysis for all 79 spectral indices, five spectral indices were selected and integrated using an artificial neural network (ANN) to estimate the Cab content of different competition ratios: the Gitelson ratio green index, the transformed chlorophyll absorption ratio index/optimized soil-adjusted vegetation index, the modified normalized difference vegetation index, the chlorophyll fluorescence index, and the Vogelmann chlorophyll index. The ANN method yielded better results (R 2  = 0.7110 and RMSE = 8.3829 μg cm -2 ) on average than the best single spectral index (R 2  = 0.6319 and RMSE = 9.3535 μg cm -2 ), representing an increase of 10.78% in R 2 and a decrease of 10.38% in RMSE. Our results indicated that integrating multiple vegetation indices with an ANN can alleviate the impact of interspecies competition and achieve higher estimation accuracy than the traditional approach using a single index.

  16. Catalytic, Conductive Bipolar Membrane Interfaces through Layer-by-Layer Deposition for the Design of Membrane-Integrated Artificial Photosynthesis Systems.

    Science.gov (United States)

    McDonald, Michael B; Freund, Michael S; Hammond, Paula T

    2017-11-23

    In the presence of an electric field, bipolar membranes (BPMs) are capable of initiating water disassociation (WD) within the interfacial region, which can make water splitting for renewable energy in the presence of a pH gradient possible. In addition to WD catalytic efficiency, there is also the need for electronic conductivity in this region for membrane-integrated artificial photosynthesis (AP) systems. Graphene oxide (GO) was shown to catalyze WD and to be controllably reduced, which resulted in electronic conductivity. Layer-by-layer (LbL) film deposition was employed to improve GO film uniformity in the interfacial region to enhance WD catalysis and, through the addition of a conducting polymer in the process, add electronic conductivity in a hybrid film. Three different deposition methods were tested to optimize conducting polymer synthesis with the oxidant in a metastable solution and to yield the best film properties. It was found that an approach that included substrate dipping in a solution containing the expected final monomer/oxidant ratio provided the most predictable film growth and smoothest films (by UV/Vis spectroscopy and atomic force microscopy/scanning electron microscopy, respectively), whereas dipping in excess oxidant or co-spraying the oxidant and monomer produced heterogeneous films. Optimized films were found to be electronically conductive and produced a membrane ohmic drop that was acceptable for AP applications. Films were integrated into the interfacial region of BPMs and revealed superior WD efficiency (≥1.4 V at 10 mA cm -2 ) for thinner films (<10 bilayers≈100 nm) than for either the pure GO catalyst or conducting polymer individually, which indicated that there was a synergistic effect between these materials in the structure configured by the LbL method. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

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

  18. Essentials of artificial intelligence

    CERN Document Server

    Ginsberg, Matt

    1993-01-01

    Since its publication, Essentials of Artificial Intelligence has beenadopted at numerous universities and colleges offering introductory AIcourses at the graduate and undergraduate levels. Based on the author'scourse at Stanford University, the book is an integrated, cohesiveintroduction to the field. The author has a fresh, entertaining writingstyle that combines clear presentations with humor and AI anecdotes. At thesame time, as an active AI researcher, he presents the materialauthoritatively and with insight that reflects a contemporary, first hand

  19. Artificial Consciousness or Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Spanache Florin

    2017-05-01

    Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

  20. Artificial Intelligence.

    Science.gov (United States)

    Lawrence, David R; Palacios-González, César; Harris, John

    2016-04-01

    It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries-namely, with regard to artificially (super)intelligent persons-but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

  1. Artificial intelligence

    OpenAIRE

    Duda, Antonín

    2009-01-01

    Abstract : Issue of this work is to acquaint the reader with the history of artificial inteligence, esspecialy branch of chess computing. Main attention is given to progress from fifties to the present. The work also deals with fighting chess programs against each other, and against human opponents. The greatest attention is focused on 1997 and duel Garry Kasparov against chess program Deep Blue. The work is divided into chapters according to chronological order.

  2. Artificial heart

    Energy Technology Data Exchange (ETDEWEB)

    1984-10-18

    Super-pure plutonium-238 could use heat produced during fission to power an implanted artificial heart. Three model hearts have worked for some time. Concern that excess heat would make the procedure unsafe for humans has broadened the search for another energy source, such as electrohydraulic drive or an external power battery. A back pack approach may provide an interim solution until materials are developed which can withstand heart activity and be small enough for implantation.

  3. Integration of Artificial Neural Network Modeling and Genetic Algorithm Approach for Enrichment of Laccase Production in Solid State Fermentation by Pleurotus ostreatus

    OpenAIRE

    Potu Venkata Chiranjeevi; Moses Rajasekara Pandian; Sathish Thadikamala

    2014-01-01

    Black gram husk was used as a solid substrate for laccase production by Pleurotus ostreatus, and various fermentation conditions were optimized based on an artificial intelligence method. A total of six parameters, i.e., temperature, inoculum concentration, moisture content, CuSO4, glucose, and peptone concentrations, were optimized. A total of 50 experiments were conducted, and the obtained data were modeled by a hybrid of artificial neural network (ANN) and genetic algorithm (GA) approaches...

  4. Artificial graphites

    International Nuclear Information System (INIS)

    Maire, J.

    1984-01-01

    Artificial graphites are obtained by agglomeration of carbon powders with an organic binder, then by carbonisation at 1000 0 C and graphitization at 2800 0 C. After description of the processes and products, we show how the properties of the various materials lead to the various uses. Using graphite enables us to solve some problems, but it is not sufficient to satisfy all the need of the application. New carbonaceous material open application range. Finally, if some products are becoming obsolete, other ones are being developed in new applications [fr

  5. Learning in robotic manipulation: The role of dimensionality reduction in policy search methods. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al.

    Science.gov (United States)

    Ficuciello, Fanny; Siciliano, Bruno

    2016-07-01

    learning into control naturally leads to relaxing the above requirements through the adoption of coordinated motion patterns and sensory-motor synergies as useful tools leading to a problem of reduced dimension. To this purpose, model-based control strategies relying on synergistic models of manipulation activities learned from human experience can be integrated with real-time learning from actions strategies [5]. In [6] a classification of learning strategies for robotics is provided, while the difference between imitation learning and reinforcement learning (RL) is highlighted in [7]. From recent research in the field [8,9], it seems that RL represents the future toward autonomous and intelligent robots since it provides learning capabilities as those of humans, i.e. based on exploration and trial-and-error policies. In this context, suitable policy search methods to be implemented in a synergy-based framework are to be sought in order to reduce the search space dimension while guaranteeing the convergence and efficiency of the learning algorithm.

  6. Cognitive components underpinning the development of model-based learning.

    Science.gov (United States)

    Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

    2017-06-01

    Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  7. Digital Genesis: Computers, Evolution and Artificial Life

    OpenAIRE

    Taylor, Tim; Dorin, Alan; Korb, Kevin

    2015-01-01

    The application of evolution in the digital realm, with the goal of creating artificial intelligence and artificial life, has a history as long as that of the digital computer itself. We illustrate the intertwined history of these ideas, starting with the early theoretical work of John von Neumann and the pioneering experimental work of Nils Aall Barricelli. We argue that evolutionary thinking and artificial life will continue to play an integral role in the future development of the digital ...

  8. Model-based Software Engineering

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2010-01-01

    The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...

  9. Graph Model Based Indoor Tracking

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Lu, Hua; Yang, Bin

    2009-01-01

    The tracking of the locations of moving objects in large indoor spaces is important, as it enables a range of applications related to, e.g., security and indoor navigation and guidance. This paper presents a graph model based approach to indoor tracking that offers a uniform data management...

  10. A GIS-based multi-criteria seismic vulnerability assessment using the integration of granular computing rule extraction and artificial neural networks

    NARCIS (Netherlands)

    Sheikhian, Hossein; Delavar, Mahmoud Reza; Stein, Alfred

    2017-01-01

    This study proposes multi‐criteria group decision‐making to address seismic physical vulnerability assessment. Granular computing rule extraction is combined with a feed forward artificial neural network to form a classifier capable of training a neural network on the basis of the rules provided by

  11. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  12. Working hard to make a simple definition of synergies. Comment on: "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al.

    Science.gov (United States)

    Alessandro, Cristiano; Oliveira Barroso, Filipe; Tresch, Matthew

    2016-07-01

    The paper ;Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands; [1] presents a comprehensive review of the work carried out as part of the EU funded project ;The Hand Embodied;. The work uses the concept of ;synergy; to study the neuromuscular control of the human hand and to design novel robotics systems. The project has been very productive and has made important contributions. We are therefore confident that it will lead to further advancements and experiments in the future.

  13. Neuro-prosthetic interplay. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by M. Santello et al.

    Science.gov (United States)

    Schieber, Marc H.

    2016-07-01

    Control of the human hand has been both difficult to understand scientifically and difficult to emulate technologically. The article by Santello and colleagues in the current issue of Physics of Life Reviews[1] highlights the accelerating pace of interaction between the neuroscience of controlling body movement and the engineering of robotic hands that can be used either autonomously or as part of a motor neuroprosthesis, an artificial body part that moves under control from a human subject's own nervous system. Motor neuroprostheses typically involve a brain-computer interface (BCI) that takes signals from the subject's nervous system or muscles, interprets those signals through a decoding algorithm, and then applies the resulting output to control the artificial device.

  14. A Developed Artificial Bee Colony Algorithm Based on Cloud Model

    Directory of Open Access Journals (Sweden)

    Ye Jin

    2018-04-01

    Full Text Available The Artificial Bee Colony (ABC algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants.

  15. A model-based risk management framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune

    2002-08-15

    The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

  16. GSFLOW - Coupled Ground-Water and Surface-Water Flow Model Based on the Integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005)

    Science.gov (United States)

    Markstrom, Steven L.; Niswonger, Richard G.; Regan, R. Steven; Prudic, David E.; Barlow, Paul M.

    2008-01-01

    The need to assess the effects of variability in climate, biota, geology, and human activities on water availability and flow requires the development of models that couple two or more components of the hydrologic cycle. An integrated hydrologic model called GSFLOW (Ground-water and Surface-water FLOW) was developed to simulate coupled ground-water and surface-water resources. The new model is based on the integration of the U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) and the U.S. Geological Survey Modular Ground-Water Flow Model (MODFLOW). Additional model components were developed, and existing components were modified, to facilitate integration of the models. Methods were developed to route flow among the PRMS Hydrologic Response Units (HRUs) and between the HRUs and the MODFLOW finite-difference cells. This report describes the organization, concepts, design, and mathematical formulation of all GSFLOW model components. An important aspect of the integrated model design is its ability to conserve water mass and to provide comprehensive water budgets for a location of interest. This report includes descriptions of how water budgets are calculated for the integrated model and for individual model components. GSFLOW provides a robust modeling system for simulating flow through the hydrologic cycle, while allowing for future enhancements to incorporate other simulation techniques.

  17. Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

    Science.gov (United States)

    Varatharajah, Yogatheesan; Berry, Brent; Cimbalnik, Jan; Kremen, Vaclav; Van Gompel, Jamie; Stead, Matt; Brinkmann, Benjamin; Iyer, Ravishankar; Worrell, Gregory

    2018-08-01

    An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between 90 min and 2 h are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

  18. Integrating an artificial intelligence approach with k-means clustering to model groundwater salinity: the case of Gaza coastal aquifer (Palestine)

    Science.gov (United States)

    Alagha, Jawad S.; Seyam, Mohammed; Md Said, Md Azlin; Mogheir, Yunes

    2017-12-01

    Artificial intelligence (AI) techniques have increasingly become efficient alternative modeling tools in the water resources field, particularly when the modeled process is influenced by complex and interrelated variables. In this study, two AI techniques—artificial neural networks (ANNs) and support vector machine (SVM)—were employed to achieve deeper understanding of the salinization process (represented by chloride concentration) in complex coastal aquifers influenced by various salinity sources. Both models were trained using 11 years of groundwater quality data from 22 municipal wells in Khan Younis Governorate, Gaza, Palestine. Both techniques showed satisfactory prediction performance, where the mean absolute percentage error (MAPE) and correlation coefficient ( R) for the test data set were, respectively, about 4.5 and 99.8% for the ANNs model, and 4.6 and 99.7% for SVM model. The performances of the developed models were further noticeably improved through preprocessing the wells data set using a k-means clustering method, then conducting AI techniques separately for each cluster. The developed models with clustered data were associated with higher performance, easiness and simplicity. They can be employed as an analytical tool to investigate the influence of input variables on coastal aquifer salinity, which is of great importance for understanding salinization processes, leading to more effective water-resources-related planning and decision making.

  19. Integration

    DEFF Research Database (Denmark)

    Emerek, Ruth

    2004-01-01

    Bidraget diskuterer de forskellige intergrationsopfattelse i Danmark - og hvad der kan forstås ved vellykket integration......Bidraget diskuterer de forskellige intergrationsopfattelse i Danmark - og hvad der kan forstås ved vellykket integration...

  20. COAXIAL DISK SHUNT FOR MEASURING IN THE HEAVY-CURRENT CHAIN OF HIGH-VOLTAGE GENERATOR OF STORM DISCHARGES OF IMPULSES OF CURRENT OF ARTIFICIAL LIGHTNING WITH THE INTEGRAL OF ACTION TO 15•106 J/OHM

    Directory of Open Access Journals (Sweden)

    M. I. Baranov

    2017-10-01

    Full Text Available Purpose. Description of construction and basic technical descriptions developed and created in Research & Design Institute «Molniya» National Technical University «Kharkiv Polytechnic Institute» high-voltage heavy-current coaxial disk shunt of type of SC-300M2, allowing reliably to measure the peak-temporal parameters (PTP of impulses of current of artificial lightning in wide peak and temporal ranges with the integral of their action to 15·106 J/Ohm. Methodology. Electrophysics bases of high-voltage impulsive technique, scientific and technical bases of development and creation of high-voltage heavy-current impulsive electrical equipment, including the powerful generators of current of lightning (GCL, and also measuring methods in bit chains powerful high-voltage GCL AVP large impulsive currents of micro- and millisecond temporal ranges. Results. Offered and described new construction of measuring high-voltage heavy-current shunt, containing a measuring round disk from stainless steel easily soiled a 12Х18Н10Т thickness 2 mm and external diameter 80 mm. Experimental a way impulsive active resistance of RS≈0,08 mOhm of the indicated measuring disk and on his basis a calculation coefficient transformation is found of SS of coaxial disk shunt of type of SC-300M2, numeral equal in the concerted mode of operations of his coaxial cable line (CCL SS≈2/RS≈25·103 A/V. It is rotined that it is expedient to use this value SS for measuring in the heavy-current bit chain of GCL ATP impulsive A- and repeated impulsive D- component of current of artificial lightning, and also ATP of aperiodic impulse of current of artificial lightning of temporal form 10 μc/350 μc. It is set that taking into account application in the end CCL of shunt of a co-ordinate divizor of voltage with two output coaxial sockets 1:1 (for SSA≈25·103 A/V and 1:2 (SSC≈12,5·103 A/V at measuring of ATP intermediate B-, protracted C- and shortened protracted C

  1. A programmable artificial retina

    International Nuclear Information System (INIS)

    Bernard, T.M.; Zavidovique, B.Y.; Devos, F.J.

    1993-01-01

    An artificial retina is a device that intimately associates an imager with processing facilities on a monolithic circuit. Yet, except for simple environments and applications, analog hardware will not suffice to process and compact the raw image flow from the photosensitive array. To solve this output problem, an on-chip array of bare Boolean processors with halftoning facilities might be used, providing versatility from programmability. By setting the pixel memory size to 3 b, the authors have demonstrated both the technological practicality and the computational efficiency of this programmable Boolean retina concept. Using semi-static shifting structures together with some interaction circuitry, a minimal retina Boolean processor can be built with less than 30 transistors and controlled by as few as 6 global clock signals. The successful design, integration, and test of such a 65x76 Boolean retina on a 50-mm 2 CMOS 2-μm circuit are presented

  2. Issues in practical model-based diagnosis

    NARCIS (Netherlands)

    Bakker, R.R.; Bakker, R.R.; van den Bempt, P.C.A.; van den Bempt, P.C.A.; Mars, Nicolaas; Out, D.-J.; Out, D.J.; van Soest, D.C.; van Soes, D.C.

    1993-01-01

    The model-based diagnosis project at the University of Twente has been directed at improving the practical usefulness of model-based diagnosis. In cooperation with industrial partners, the research addressed the modeling problem and the efficiency problem in model-based reasoning. Main results of

  3. Model-based sensor diagnosis

    International Nuclear Information System (INIS)

    Milgram, J.; Dormoy, J.L.

    1994-09-01

    Running a nuclear power plant involves monitoring data provided by the installation's sensors. Operators and computerized systems then use these data to establish a diagnostic of the plant. However, the instrumentation system is complex, and is not immune to faults and failures. This paper presents a system for detecting sensor failures using a topological description of the installation and a set of component models. This model of the plant implicitly contains relations between sensor data. These relations must always be checked if all the components are functioning correctly. The failure detection task thus consists of checking these constraints. The constraints are extracted in two stages. Firstly, a qualitative model of their existence is built using structural analysis. Secondly, the models are formally handled according to the results of the structural analysis, in order to establish the constraints on the sensor data. This work constitutes an initial step in extending model-based diagnosis, as the information on which it is based is suspect. This work will be followed by surveillance of the detection system. When the instrumentation is assumed to be sound, the unverified constraints indicate errors on the plant model. (authors). 8 refs., 4 figs

  4. [Integrity].

    Science.gov (United States)

    Gómez Rodríguez, Rafael Ángel

    2014-01-01

    To say that someone possesses integrity is to claim that that person is almost predictable about responses to specific situations, that he or she can prudentially judge and to act correctly. There is a closed interrelationship between integrity and autonomy, and the autonomy rests on the deeper moral claim of all humans to integrity of the person. Integrity has two senses of significance for medical ethic: one sense refers to the integrity of the person in the bodily, psychosocial and intellectual elements; and in the second sense, the integrity is the virtue. Another facet of integrity of the person is la integrity of values we cherish and espouse. The physician must be a person of integrity if the integrity of the patient is to be safeguarded. The autonomy has reduced the violations in the past, but the character and virtues of the physician are the ultimate safeguard of autonomy of patient. A field very important in medicine is the scientific research. It is the character of the investigator that determines the moral quality of research. The problem arises when legitimate self-interests are replaced by selfish, particularly when human subjects are involved. The final safeguard of moral quality of research is the character and conscience of the investigator. Teaching must be relevant in the scientific field, but the most effective way to teach virtue ethics is through the example of the a respected scientist.

  5. Model based risk assessment - the CORAS framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune; Thunem, Atoosa P-J.

    2004-04-15

    Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tested with successful outcome through a series of seven trial within the telemedicine and ecommerce areas. The CORAS project in general and the CORAS application of MBRA in particular have contributed positively to the visibility of model-based risk assessment and thus to the disclosure of several potentials for further exploitation of various aspects within this important research field. In that connection, the CORAS methodology's possibilities for further improvement towards utilization in more complex architectures and also in other application domains such as the nuclear field can be addressed. The latter calls for adapting the framework to address nuclear standards such as IEC 60880 and IEC 61513. For this development we recommend applying a trial driven approach within the nuclear field. The tool supported approach for combining risk analysis and system development also fits well with the HRP proposal for developing an Integrated Design Environment (IDE) providing efficient methods and tools to support control room systems design. (Author)

  6. Artificial Hydration and Nutrition

    Science.gov (United States)

    ... Crisis Situations Pets and Animals myhealthfinder Food and Nutrition Healthy Food Choices Weight Loss and Diet Plans ... Your Health Resources Healthcare Management Artificial Hydration and Nutrition Artificial Hydration and Nutrition Share Print Patients who ...

  7. Artificial Disc Replacement

    Science.gov (United States)

    ... Spondylolisthesis BLOG FIND A SPECIALIST Treatments Artificial Disc Replacement (ADR) Patient Education Committee Jamie Baisden The disc ... Disc An artificial disc (also called a disc replacement, disc prosthesis or spine arthroplasty device) is a ...

  8. 基于产业价值链整合探析移动互联网企业盈利模式%Integration of Mobile Internet Companies Profit Model Based on Industry Value Chain

    Institute of Scientific and Technical Information of China (English)

    颜华保

    2012-01-01

    Mobile Internet companies play the role of resource integration in the industry chain.Based on the industry value chain,mobile Internet companies and operators,content providers and equipment manufacturers show a high degree of association between the cone,and then the paper analyses factors that affect their profitability from the user,the value chain positioning,products and services,cross-border competition and cooperation,and explores the mobile Internet business profit model from pay for content,advertising media,product distribution and affiliate marketing interests share.The author believes that the mobile Internet companies must integrate internal and external resources to achieve profitability,to work closely with the various aspects of the industry chain,in order to ultimately achieve customer value.%移动互联网企业在产业链上扮演着资源整合的角色。基于产业价值链,移动互联网企业与运营商、内容供应商及设备制造商之间呈关联度高的锥型关系,进而从用户价值、价值链定位、产品与服务、跨界竞合四方面分析影响其盈利的因素,并从内容付费、广告媒介、产品分销以及联盟营销与利益分享四方面探析移动互联网企业的盈利模式。笔者认为,移动互联网企业要实现盈利,必须整合企业内外资源,与产业链各环节紧密合作,才能最终实现用户价值。

  9. Artificial life and Piaget.

    Science.gov (United States)

    Mueller, Ulrich; Grobman, K H.

    2003-04-01

    Artificial life provides important theoretical and methodological tools for the investigation of Piaget's developmental theory. This new method uses artificial neural networks to simulate living phenomena in a computer. A recent study by Parisi and Schlesinger suggests that artificial life might reinvigorate the Piagetian framework. We contrast artificial life with traditional cognitivist approaches, discuss the role of innateness in development, and examine the relation between physiological and psychological explanations of intelligent behaviour.

  10. Model based process-product design and analysis

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    This paper gives a perspective on modelling and the important role it has within product-process design and analysis. Different modelling issues related to development and application of systematic model-based solution approaches for product-process design is discussed and the need for a hybrid...... model-based framework is highlighted. This framework should be able to manage knowledge-data, models, and associated methods and tools integrated with design work-flows and data-flows for specific product-process design problems. In particular, the framework needs to manage models of different types......, forms and complexity, together with their associated parameters. An example of a model-based system for design of chemicals based formulated products is also given....

  11. Hydrogel–fibre composites with independent control over cell adhesion to gel and fibres as an integral approach towards a biomimetic artificial ECM

    International Nuclear Information System (INIS)

    Schulte, Vera A; Dhanasingh, Anandhan; Hahn, Kathrin; Heffels, Karl-Heinz; Groll, Jürgen

    2014-01-01

    In the body, cells are surrounded by an interconnected mesh of insoluble, bioactive protein fibres to which they adhere in a well-controlled manner, embedded in a hydrogel-like highly hydrated matrix. True morphological and biochemical mimicry of this so-called extracellular matrix (ECM) remains a challenge but appears decisive for a successful design of biomimetic three-dimensional in vitro cell culture systems. Herein, an approach is presented which describes the fabrication and in vitro assessment of an artificial ECM which contains two major components, i.e. specifically biofunctionalized fibres and a semi-synthetic hyaluronic acid-based hydrogel, which allows control over cell adhesion towards both components. As proof of principle for the control of cell adhesion, RGD as well-known cell adhesive cue and the control sequence RGE are immobilized in the system. In vitro studies with primary human dermal fibroblasts were conducted to evaluate the specificity of cell adhesion and the potential of the composite system to support cell growth. Finally, one possible application example for guided cell growth is shown by the use of oriented fibres in a hydrogel matrix. (paper)

  12. Application of artificial intelligence to the management of urological cancer.

    Science.gov (United States)

    Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

    2007-10-01

    Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

  13. Intellectual Model-Based Configuration Management Conception

    Directory of Open Access Journals (Sweden)

    Bartusevics Arturs

    2014-07-01

    Full Text Available Software configuration management is one of the most important disciplines within the software development project, which helps control the software evolution process and allows including into the end project only tested and validated changes. To achieve this, software management completes certain tasks. Concrete tools are used for technical implementation of tasks, such as version control systems, servers of continuous integration, compilers, etc. A correct configuration management process usually requires several tools, which mutually exchange information by generating various kinds of transfers. When it comes to introducing the configuration management process, often there are situations when tool installation is started, yet at that given moment there is no general picture of the total process. The article offers a model-based configuration management concept, which foresees the development of an abstract model for the configuration management process that later is transformed to lower abstraction level models and tools are indicated to support the technical process. A solution of this kind allows a more rational introduction and configuration of tools

  14. Integrating an automated activity monitor into an artificial insemination program and the associated risk factors affecting reproductive performance of dairy cows.

    Science.gov (United States)

    Burnett, Tracy A; Madureira, Augusto M L; Silper, Bruna F; Fernandes, A C C; Cerri, Ronaldo L A

    2017-06-01

    The aim of this study was to compare 2 reproductive programs for the management of first postpartum artificial insemination (AI) based on activity monitors and timed AI, as well as to determine the effect of health-related factors on detection and expression of estrus. Lactating Holstein cows (n = 918) from 2 commercial farms were enrolled. Estrous cycles of all cows were presynchronized with 2 injections of PGF 2α administered 2 wk apart. Treatments were (1) first insemination performed by timed AI (TAI) and (2) first insemination based upon the detection of estrus by activity monitors (ACT; Heatime, SCR Engineering, Netanya, Israel) after the presynchronization, whereas cows not inseminated by the detection of estrus were enrolled in the Ovsynch protocol. Body condition score (BCS; scale 1 to 5), hock score (scale: 1 to 4), gait score (scale: 1 to 4), and corpus luteum presence detected by ovarian ultrasonography were recorded twice during the presynchronization. On the ACT treatment, 50.5% of cows were inseminated based on detected estrus, whereas 83.2% of the cows on the TAI treatment were inseminated appropriately after the timed AI protocol. Pregnancy per AI did not differ by treatment (30.8 vs. 33.5% for ACT and TAI, respectively). Success of pregnancy was affected by parity, cyclicity, BCS, milk production, and a tendency for leg health. In addition, treatment × cyclicity and treatment × parity interactions were found to affect pregnancy success, where anovulatory cows and older cows had compromised pregnancy outcomes on the ACT treatment but not on the TAI treatment. Factors affecting pregnancy outcomes varied among farms. Hazard of pregnancy by 300 DIM was affected by farm, parity, BCS, a treatment × cyclicity interaction, and a tendency for an interaction between leg health and farm. Detection of estrus was affected by farm, parity, cyclicity, and leg health, but not BCS or milk production. Expression of estrus was compromised in anovular and older

  15. Model-based security engineering for the internet of things

    OpenAIRE

    NEISSE RICARDO; STERI GARY; NAI FOVINO Igor; BALDINI Gianmarco; VAN HOESEL Lodewijk

    2015-01-01

    We propose in this chapter a Model-based Security Toolkit (SecKit) and methodology to address the control and protection of user data in the deployment of the Internet of Things (IoT). This toolkit takes a more general approach for security engineering including risk analysis, establishment of aspect-specific trust relationships, and enforceable security policies. We describe the integrated metamodels used in the toolkit and the accompanying security engineering methodology for IoT systems...

  16. The Odda System: Integration of Conventional Programming and Artificial Intelligence Le système ODDA : intégration de programmation classique et d'intelligence artificielle

    Directory of Open Access Journals (Sweden)

    Cayeux E.

    2006-11-01

    Full Text Available The ODDA system (Offshore Directional Drilling Advisor is an example of how numerical packages, a relational database, graphical interfaces and knowledge bases can be integrated into an industrial application. Le système ODDA (Offshore Directional Drilling Advisor est un exemple illustrant la façon dont des progiciels numériques, une base de données relationnelle, des interfaces graphiques et des bases de connaissances peuvent être intégrés dans une application industrielle.

  17. Artificial cognition architectures

    CERN Document Server

    Crowder, James A; Friess, Shelli A

    2013-01-01

    The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution

  18. Artificial Intelligence Study (AIS).

    Science.gov (United States)

    1987-02-01

    ARTIFICIAL INTELLIGNECE HARDWARE ....... 2-50 AI Architecture ................................... 2-49 AI Hardware ....................................... 2...ftf1 829 ARTIFICIAL INTELLIGENCE STUDY (RIS)(U) MAY CONCEPTS 1/3 A~NLYSIS AGENCY BETHESA RD R B NOJESKI FED 6? CM-RP-97-1 NCASIFIED /01/6 M |K 1.0...p/ - - ., e -- CAA- RP- 87-1 SAOFŔ)11 I ARTIFICIAL INTELLIGENCE STUDY (AIS) tNo DTICFEBRUARY 1987 LECT 00 I PREPARED BY RESEARCH AND ANALYSIS

  19. Artificial Intelligence in Astronomy

    Science.gov (United States)

    Devinney, E. J.; Prša, A.; Guinan, E. F.; Degeorge, M.

    2010-12-01

    From the perspective (and bias) as Eclipsing Binary researchers, we give a brief overview of the development of Artificial Intelligence (AI) applications, describe major application areas of AI in astronomy, and illustrate the power of an AI approach in an application developed under the EBAI (Eclipsing Binaries via Artificial Intelligence) project, which employs Artificial Neural Network technology for estimating light curve solution parameters of eclipsing binary systems.

  20. Quo Vadis, Artificial Intelligence?

    OpenAIRE

    Berrar, Daniel; Sato, Naoyuki; Schuster, Alfons

    2010-01-01

    Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervou...

  1. Inteligencia artificial en vehiculo

    OpenAIRE

    Amador Díaz, Pedro

    2012-01-01

    Desarrollo de un robot seguidor de líneas, en el que se implementan diversas soluciones de las áreas de sistemas embebidos e inteligencia artificial. Desenvolupament d'un robot seguidor de línies, en el qual s'implementen diverses solucions de les àrees de sistemes encastats i intel·ligència artificial. Follower robot development of lines, in which various solutions are implemented in the areas of artificial intelligence embedded systems.

  2. STANFORD ARTIFICIAL INTELLIGENCE PROJECT.

    Science.gov (United States)

    ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.

  3. Mars 2020 Model Based Systems Engineering Pilot

    Science.gov (United States)

    Dukes, Alexandra Marie

    2017-01-01

    The pilot study is led by the Integration Engineering group in NASA's Launch Services Program (LSP). The Integration Engineering (IE) group is responsible for managing the interfaces between the spacecraft and launch vehicle. This pilot investigates the utility of Model-Based Systems Engineering (MBSE) with respect to managing and verifying interface requirements. The main objectives of the pilot are to model several key aspects of the Mars 2020 integrated operations and interface requirements based on the design and verification artifacts from Mars Science Laboratory (MSL) and to demonstrate how MBSE could be used by LSP to gain further insight on the interface between the spacecraft and launch vehicle as well as to enhance how LSP manages the launch service. The method used to accomplish this pilot started through familiarization of SysML, MagicDraw, and the Mars 2020 and MSL systems through books, tutorials, and NASA documentation. MSL was chosen as the focus of the model since its processes and verifications translate easily to the Mars 2020 mission. The study was further focused by modeling specialized systems and processes within MSL in order to demonstrate the utility of MBSE for the rest of the mission. The systems chosen were the In-Flight Disconnect (IFD) system and the Mass Properties process. The IFD was chosen as a system of focus since it is an interface between the spacecraft and launch vehicle which can demonstrate the usefulness of MBSE from a system perspective. The Mass Properties process was chosen as a process of focus since the verifications for mass properties occur throughout the lifecycle and can demonstrate the usefulness of MBSE from a multi-discipline perspective. Several iterations of both perspectives have been modeled and evaluated. While the pilot study will continue for another 2 weeks, pros and cons of using MBSE for LSP IE have been identified. A pro of using MBSE includes an integrated view of the disciplines, requirements, and

  4. Methods and algorithms for model-based integration and testing

    NARCIS (Netherlands)

    Boumen, R.; Braspenning, N.C.W.M.; Jong, de I.S.M.; Mortel - Fronczak, van de J.M.; Rooda, J.E.

    2007-01-01

    This paper describes three Ph.D. projects performed in the framework of the Tangram project [1], in which the Systems Engineering group (Dept. of Mechanical Engineering) from the Eindhoven University of Technology is involved. The Tangram project is a close cooperation between the Embedded Systems

  5. An Integrated Model-Based Distributed Diagnosis and Prognosis Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detec- tion, isolation...

  6. An Integrated Model-Based Diagnostic and Prognostic Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — Systems health monitoring is essential in guar- anteeing the safe, efficient, and correct opera- tion of complex engineered systems. Diagnosis, which consists of...

  7. Artificial life and life artificialization in Tron

    Directory of Open Access Journals (Sweden)

    Carolina Dantas Figueiredo

    2012-12-01

    Full Text Available Cinema constantly shows the struggle between the men and artificial intelligences. Fiction, and more specifically fiction films, lends itself to explore possibilities asking “what if?”. “What if”, in this case, is related to the eventual rebellion of artificial intelligences, theme explored in the movies Tron (1982 and Tron Legacy (2010 trat portray the conflict between programs and users. The present paper examines these films, observing particularly the possibility programs empowering. Finally, is briefly mentioned the concept of cyborg as a possibility of response to human concerns.

  8. Applying Model Based Systems Engineering to NASA's Space Communications Networks

    Science.gov (United States)

    Bhasin, Kul; Barnes, Patrick; Reinert, Jessica; Golden, Bert

    2013-01-01

    System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its

  9. Artificial neural networks for prediction of percentage of water ...

    Indian Academy of Sciences (India)

    have high compressive strengths in comparison with con- crete specimens ... presenting suitable model based on artificial neural networks. (ANNs) to ... by experimental ones to evaluate the software power for pre- dicting the ..... Figure 7. Correlation of measured and predicted percentage of water absorption values of.

  10. Development of a robust model-based reactivity control system

    International Nuclear Information System (INIS)

    Rovere, L.A.; Otaduy, P.J.; Brittain, C.R.

    1990-01-01

    This paper describes the development and implementation of a digital model-based reactivity control system that incorporates a knowledge of the plant physics into the control algorithm to improve system performance. This controller is composed of a model-based module and modified proportional-integral-derivative (PID) module. The model-based module has an estimation component to synthesize unmeasurable process variables that are necessary for the control action computation. These estimated variables, besides being used within the control algorithm, will be used for diagnostic purposes by a supervisory control system under development. The PID module compensates for inaccuracies in model coefficients by supplementing the model-based output with a correction term that eliminates any demand tracking or steady state errors. This control algorithm has been applied to develop controllers for a simulation of liquid metal reactors in a multimodular plant. It has shown its capability to track demands in neutron power much more accurately than conventional controllers, reducing overshoots to almost negligible value while providing a good degree of robustness to unmodeled dynamics. 10 refs., 4 figs

  11. Advanced Artificial Intelligence Technology Testbed

    Science.gov (United States)

    Anken, Craig S.

    1993-01-01

    The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

  12. Artificial Intelligence in Autonomous Telescopes

    Science.gov (United States)

    Mahoney, William; Thanjavur, Karun

    2011-03-01

    Artificial Intelligence (AI) is key to the natural evolution of today's automated telescopes to fully autonomous systems. Based on its rapid development over the past five decades, AI offers numerous, well-tested techniques for knowledge based decision making essential for real-time telescope monitoring and control, with minimal - and eventually no - human intervention. We present three applications of AI developed at CFHT for monitoring instantaneous sky conditions, assessing quality of imaging data, and a prototype for scheduling observations in real-time. Closely complementing the current remote operations at CFHT, we foresee further development of these methods and full integration in the near future.

  13. 'Integration'

    DEFF Research Database (Denmark)

    Olwig, Karen Fog

    2011-01-01

    , while the countries have adopted disparate policies and ideologies, differences in the actual treatment and attitudes towards immigrants and refugees in everyday life are less clear, due to parallel integration programmes based on strong similarities in the welfare systems and in cultural notions...... of equality in the three societies. Finally, it shows that family relations play a central role in immigrants’ and refugees’ establishment of a new life in the receiving societies, even though the welfare society takes on many of the social and economic functions of the family....

  14. Artificial Intelligence, Counseling, and Cognitive Psychology.

    Science.gov (United States)

    Brack, Greg; And Others

    With the exception of a few key writers, counselors largely ignore the benefits that Artificial Intelligence (AI) and Cognitive Psychology (CP) can bring to counseling. It is demonstrated that AI and CP can be integrated into the counseling literature. How AI and CP can offer new perspectives on information processing, cognition, and helping is…

  15. Model based methods and tools for process systems engineering

    DEFF Research Database (Denmark)

    Gani, Rafiqul

    need to be integrated with work-flows and data-flows for specific product-process synthesis-design problems within a computer-aided framework. The framework therefore should be able to manage knowledge-data, models and the associated methods and tools needed by specific synthesis-design work...... of model based methods and tools within a computer aided framework for product-process synthesis-design will be highlighted.......Process systems engineering (PSE) provides means to solve a wide range of problems in a systematic and efficient manner. This presentation will give a perspective on model based methods and tools needed to solve a wide range of problems in product-process synthesis-design. These methods and tools...

  16. An artificial ecosystem model used in the study of social, economic and technological dynamics: An artificial electrical energy market

    International Nuclear Information System (INIS)

    Arjona, D.

    1998-01-01

    This paper will present the artificial ecosystem as a tool, in the development of multi agent models for the simulation of economic and technological dynamics (as well as other possible applications). This tool is based on the mechanics of an artificial society and consists of autonomous artificial agents that interact with individuals that have different characteristics and behavior and other that have a similar conduct to their own. Initial conditions are assumed not to be controllable, however they can be influenced. The importance of the concept of the ecosystem is in understanding great units in the light of their own components which are relevant for the analysis and become interdependent among themselves and with other essential components that hold the total operation of the system. Ideas for the development of a simulation model based on autonomous intelligent agents are presented. These agents will have a brain that is based on artificial intelligence technologies. The Sand Kings Simulation Model, an artificial ecosystem model developed by the author, is described as well as the application of artificial intelligence to this artificial life model. An application to a real life problem is also offered as an artificial energy market that is currently being developed by the author is described

  17. [Total artificial heart].

    Science.gov (United States)

    Antretter, H; Dumfarth, J; Höfer, D

    2015-09-01

    To date the CardioWest™ total artificial heart is the only clinically available implantable biventricular mechanical replacement for irreversible cardiac failure. This article presents the indications, contraindications, implantation procedere and postoperative treatment. In addition to a overview of the applications of the total artificial heart this article gives a brief presentation of the two patients treated in our department with the CardioWest™. The clinical course, postoperative rehabilitation, device-related complications and control mechanisms are presented. The total artificial heart is a reliable implant for treating critically ill patients with irreversible cardiogenic shock. A bridge to transplantation is feasible with excellent results.

  18. Artificial Intelligent Platform as Decision Tool for Asset Management, Operations and Maintenance.

    Science.gov (United States)

    2018-01-04

    An Artificial Intelligence (AI) system has been developed and implemented for water, wastewater and reuse plants to improve management of sensors, short and long term maintenance plans, asset and investment management plans. It is based on an integrated approach to capture data from different computer systems and files. It adds a layer of intelligence to the data. It serves as a repository of key current and future operations and maintenance conditions that a plant needs have knowledge of. With this information, it is able to simulate the configuration of processes and assets for those conditions to improve or optimize operations, maintenance and asset management, using the IViewOps (Intelligent View of Operations) model. Based on the optimization through model runs, it is able to create output files that can feed data to other systems and inform the staff regarding optimal solutions to the conditions experienced or anticipated in the future.

  19. Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

    Directory of Open Access Journals (Sweden)

    Ye Tian

    2014-01-01

    Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

  20. Bibliography: Artificial Intelligence.

    Science.gov (United States)

    Smith, Richard L.

    1986-01-01

    Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

  1. Artificial intelligence in medicine.

    OpenAIRE

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

    2004-01-01

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

  2. Minimally Naturalistic Artificial Intelligence

    OpenAIRE

    Hansen, Steven Stenberg

    2017-01-01

    The rapid advancement of machine learning techniques has re-energized research into general artificial intelligence. While the idea of domain-agnostic meta-learning is appealing, this emerging field must come to terms with its relationship to human cognition and the statistics and structure of the tasks humans perform. The position of this article is that only by aligning our agents' abilities and environments with those of humans do we stand a chance at developing general artificial intellig...

  3. Artificial Intelligence Project

    Science.gov (United States)

    1990-01-01

    Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

  4. Artificial intelligence in cardiology

    OpenAIRE

    Bonderman, Diana

    2017-01-01

    Summary Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiol...

  5. Principles of artificial intelligence

    CERN Document Server

    Nilsson, Nils J

    1980-01-01

    A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of th

  6. Intelligence: Real or artificial?

    OpenAIRE

    Schlinger, Henry D.

    1992-01-01

    Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

  7. Traceability in Model-Based Testing

    Directory of Open Access Journals (Sweden)

    Mathew George

    2012-11-01

    Full Text Available The growing complexities of software and the demand for shorter time to market are two important challenges that face today’s IT industry. These challenges demand the increase of both productivity and quality of software. Model-based testing is a promising technique for meeting these challenges. Traceability modeling is a key issue and challenge in model-based testing. Relationships between the different models will help to navigate from one model to another, and trace back to the respective requirements and the design model when the test fails. In this paper, we present an approach for bridging the gaps between the different models in model-based testing. We propose relation definition markup language (RDML for defining the relationships between models.

  8. A model-based approach to stabilizing crutch supported paraplegic standing by artificial hip joint stiffness.

    Science.gov (United States)

    van der Spek, Jaap H; Veltink, Peter H; Hermens, Hermie J; Koopman, Bart F J M; Boom, Herman B K

    2003-12-01

    The prerequisites for stable crutch supported standing were analyzed in this paper. For this purpose, a biomechanical model of crutch supported paraplegic stance was developed assuming the patient was standing with extended knees. When using crutches during stance, the crutches will put a position constraint on the shoulder, thus reducing the number of degrees of freedom. Additional hip-joint stiffness was applied to stabilize the hip joint and, therefore, to stabilize stance. The required hip-joint stiffness for changing crutch placement and hip-joint offset angle was studied under static and dynamic conditions. Modeling results indicate that, by using additional hip-joint stiffness, stable crutch supported paraplegic standing can be achieved, both under static as well as dynamic situations. The static equilibrium postures and the stability under perturbations were calculated to be dependent on crutch placement and stiffness applied. However, postures in which the hip joint was in extension (C postures) appeared to the most stable postures. Applying at least 60 N x m/rad hip-joint stiffness gave stable equilibrium postures in all cases. Choosing appropriate hip-joint offset angles, the static equilibrium postures changed to more erect postures, without causing instability or excessive arm forces to occur.

  9. Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

    Directory of Open Access Journals (Sweden)

    J. C. Ochoa-Rivera

    2002-01-01

    Full Text Available A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain, while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2 model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series..

  10. Model-based analysis of photoinitiated coating degradation under artificial exposure conditions

    DEFF Research Database (Denmark)

    Kiil, Søren

    2012-01-01

    measurements of carbonyl groups formed in the surface zone. The thickness of the stable surface oxidation zone, which is established after an initial ablation lag time, is estimated by the model to 0.5–2 μm in good agreement with previous measurements. Simulated concentration profiles of active groups, oxygen...

  11. A novel soft sensor model based on artificial neural network in the ...

    African Journals Online (AJOL)

    ajl yemi

    2011-12-28

    Dec 28, 2011 ... School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, China. Accepted 9 .... by using 5- point numerical derivative method and n is the number of ..... Software sensors in bioprocess engineering. J.

  12. Model-based testing for embedded systems

    CERN Document Server

    Zander, Justyna; Mosterman, Pieter J

    2011-01-01

    What the experts have to say about Model-Based Testing for Embedded Systems: "This book is exactly what is needed at the exact right time in this fast-growing area. From its beginnings over 10 years ago of deriving tests from UML statecharts, model-based testing has matured into a topic with both breadth and depth. Testing embedded systems is a natural application of MBT, and this book hits the nail exactly on the head. Numerous topics are presented clearly, thoroughly, and concisely in this cutting-edge book. The authors are world-class leading experts in this area and teach us well-used

  13. Model-based internal wave processing

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J.V.; Chambers, D.H.

    1995-06-09

    A model-based approach is proposed to solve the oceanic internal wave signal processing problem that is based on state-space representations of the normal-mode vertical velocity and plane wave horizontal velocity propagation models. It is shown that these representations can be utilized to spatially propagate the modal (dept) vertical velocity functions given the basic parameters (wave numbers, Brunt-Vaisala frequency profile etc.) developed from the solution of the associated boundary value problem as well as the horizontal velocity components. Based on this framework, investigations are made of model-based solutions to the signal enhancement problem for internal waves.

  14. Model Based Control of Reefer Container Systems

    DEFF Research Database (Denmark)

    Sørensen, Kresten Kjær

    This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together with the Da......This thesis is concerned with the development of model based control for the Star Cool refrigerated container (reefer) with the objective of reducing energy consumption. This project has been carried out under the Danish Industrial PhD programme and has been financed by Lodam together...

  15. Integrated artificial intelligence algorithm for skin detection

    Directory of Open Access Journals (Sweden)

    Bush Idoko John

    2018-01-01

    Full Text Available The detection of skin colour has been a useful and renowned technique due to its wide range of application in both analyses based on diagnostic and human computer interactions. Various problems could be solved by simply providing an appropriate method for pixel-like skin parts. Presented in this study is a colour segmentation algorithm that works directly in RGB colour space without converting the colour space. Genfis function as used in this study formed the Sugeno fuzzy network and utilizing Fuzzy C-Mean (FCM clustering rule, clustered the data and for each cluster/class a rule is generated. Finally, corresponding output from data mapping of pseudo-polynomial is obtained from input dataset to the adaptive neuro fuzzy inference system (ANFIS.

  16. Information exchange in global logistics chains : An application for model-based auditing,

    NARCIS (Netherlands)

    Veenstra, A.W.; Hulstijn, J.; Christiaanse, R.M.J.; Tan, Y.

    2013-01-01

    An integrated data pipeline has been proposed to meet requirements for visibility, supervision and control in global supply chains. How can data integration be used for risk assessment, monitoring and control in global supply chains? We argue that concepts from model-based auditing can be used to

  17. Information Exchange in Global Logistics Chains : An application for Model-based Auditing (abstract)

    NARCIS (Netherlands)

    Veenstra, A.W.; Hulstijn, J.; Christiaanse, R.; Tan, Y.

    2013-01-01

    An integrated data pipeline has been proposed to meet requirements for supply chain visibility and control. How can data integration be used for risk assessment, monitoring and control in global supply chains? We argue that concepts from model-based auditing can be used to model the ‘ideal’ flow of

  18. Model-based Bayesian signal extraction algorithm for peripheral nerves

    Science.gov (United States)

    Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

    2017-10-01

    Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of

  19. Pneumatic artificial muscle actuators for compliant robotic manipulators

    Science.gov (United States)

    Robinson, Ryan Michael

    Robotic systems are increasingly being utilized in applications that require interaction with humans. In order to enable safe physical human-robot interaction, light weight and compliant manipulation are desirable. These requirements are problematic for many conventional actuation systems, which are often heavy, and typically use high stiffness to achieve high performance, leading to large impact forces upon collision. However, pneumatic artificial muscles (PAMs) are actuators that can satisfy these safety requirements while offering power-to-weight ratios comparable to those of conventional actuators. PAMs are extremely lightweight actuators that produce force in response to pressurization. These muscles demonstrate natural compliance, but have a nonlinear force-contraction profile that complicates modeling and control. This body of research presents solutions to the challenges associated with the implementation of PAMs as actuators in robotic manipulators, particularly with regard to modeling, design, and control. An existing PAM force balance model was modified to incorporate elliptic end geometry and a hyper-elastic constitutive relationship, dramatically improving predictions of PAM behavior at high contraction. Utilizing this improved model, two proof-of-concept PAM-driven manipulators were designed and constructed; design features included parallel placement of actuators and a tendon-link joint design. Genetic algorithm search heuristics were employed to determine an optimal joint geometry; allowing a manipulator to achieve a desired torque profile while minimizing the required PAM pressure. Performance of the manipulators was evaluated in both simulation and experiment employing various linear and nonlinear control strategies. These included output feedback techniques, such as proportional-integral-derivative (PID) and fuzzy logic, a model-based control for computed torque, and more advanced controllers, such as sliding mode, adaptive sliding mode, and

  20. USE OF ARTIFICIAL LIGHT IN MUSHROOM CULTIVATION

    Directory of Open Access Journals (Sweden)

    N. L. Poyedinok

    2013-12-01

    Full Text Available Artificial light is used in greenhouses to increase productivity and quality of agricultural and ornamental plants. Despite the awareness of the fact that light also plays important role in the life of nonhotosynthetic organisms, such as fungi, its using in their biotechnology cultivation is currently limited. Science has quite a large amount information about the influence of artificial light of different nature on morphogenesis, metabolic processes and productivity of more than 100 species of fungi, many of which are valuable producers of biologically active compounds. Themechanisms of photoreactions of various fungi, which is an integral part of a purposeful photoregulation their activity in biotechnological processes are described. The analysis of the researches and of the experience of their practical application allows predicting potential of using artificial light in mushroom growing industry, as well as in creating highly productive, environmentally clean technologies of targeted synthesis of the final product.

  1. Service creation: a model-based approach

    NARCIS (Netherlands)

    Quartel, Dick; van Sinderen, Marten J.; Ferreira Pires, Luis

    1999-01-01

    This paper presents a model-based approach to support service creation. In this approach, services are assumed to be created from (available) software components. The creation process may involve multiple design steps in which the requested service is repeatedly decomposed into more detailed

  2. Model based development of engine control algorithms

    NARCIS (Netherlands)

    Dekker, H.J.; Sturm, W.L.

    1996-01-01

    Model based development of engine control systems has several advantages. The development time and costs are strongly reduced because much of the development and optimization work is carried out by simulating both engine and control system. After optimizing the control algorithm it can be executed

  3. An acoustical model based monitoring network

    NARCIS (Netherlands)

    Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der

    2010-01-01

    In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

  4. Approximation Algorithms for Model-Based Diagnosis

    NARCIS (Netherlands)

    Feldman, A.B.

    2010-01-01

    Model-based diagnosis is an area of abductive inference that uses a system model, together with observations about system behavior, to isolate sets of faulty components (diagnoses) that explain the observed behavior, according to some minimality criterion. This thesis presents greedy approximation

  5. Probabilistic Model-based Background Subtraction

    DEFF Research Database (Denmark)

    Krüger, Volker; Anderson, Jakob; Prehn, Thomas

    2005-01-01

    is the correlation between pixels. In this paper we introduce a model-based background subtraction approach which facilitates prior knowledge of pixel correlations for clearer and better results. Model knowledge is being learned from good training video data, the data is stored for fast access in a hierarchical...

  6. Opinion dynamics model based on quantum formalism

    Energy Technology Data Exchange (ETDEWEB)

    Artawan, I. Nengah, E-mail: nengahartawan@gmail.com [Theoretical Physics Division, Department of Physics, Udayana University (Indonesia); Trisnawati, N. L. P., E-mail: nlptrisnawati@gmail.com [Biophysics, Department of Physics, Udayana University (Indonesia)

    2016-03-11

    Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

  7. Model-based auditing using REA

    NARCIS (Netherlands)

    Weigand, H.; Elsas, P.

    2012-01-01

    The recent financial crisis has renewed interest in the value of the owner-ordered auditing tradition that starts from society's long-term interest rather than management interest. This tradition uses a model-based auditing approach in which control requirements are derived in a principled way. A

  8. Model-based testing for software safety

    NARCIS (Netherlands)

    Gurbuz, Havva Gulay; Tekinerdogan, Bedir

    2017-01-01

    Testing safety-critical systems is crucial since a failure or malfunction may result in death or serious injuries to people, equipment, or environment. An important challenge in testing is the derivation of test cases that can identify the potential faults. Model-based testing adopts models of a

  9. Artificial intelligence in nanotechnology.

    Science.gov (United States)

    Sacha, G M; Varona, P

    2013-11-15

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  10. Artificial intelligence in nanotechnology

    Science.gov (United States)

    Sacha, G. M.; Varona, P.

    2013-11-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines.

  11. Artificial organs and transplantation.

    Science.gov (United States)

    Splendiani, G; Cipriani, S; Vega, A; Casciani, C U

    2003-05-01

    Nowadays artificial devices are not able to totally and undefinitely replace the loss of function of all vital organs and artificial organs can be used only to bridge the time to transplantation, which must be considered the first choice in the therapeutical approach for many chronic diseases. Since general population aging process is leading to an increase of organ demand, the gap between performed and requested transplantation is hard to fill. Xenotransplantation is nowadays only an experimental alternative solution and we have to do our best using available artificial organs to increase and improve the survival of patients waiting for transplantation. In this meeting we particularly dealt about organ function replacing therapy, especially regarding the kidney, heart, liver, pancreas and ear.

  12. Charlas sobre inteligencia artificial

    OpenAIRE

    Álvarez Sánchez, José Ramón; Ferrández Vicente, José Manuel; Paz López, Félix de la

    2014-01-01

    Serie: Informática en Radio 3 La Inteligencia Artificial es una de las ciencias que causa mayor impacto en la sociedad, mucho más si tenemos en cuenta que cambiará el futuro de la humanidad. En España existen actualmente un nutrido grupo de equipos de investigación relacionados con las tecnologías de computación natural-artificial que aúnan sus esfuerzos a través de la RTNAC la Red Temática en Tecnologías de Computación Natural-Artificial . La UNED participa en todas sus actividades desde ...

  13. Artificial Intelligence in Cardiology.

    Science.gov (United States)

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

    2018-06-12

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

  14. Artificial intelligence in nanotechnology

    International Nuclear Information System (INIS)

    Sacha, G M; Varona, P

    2013-01-01

    During the last decade there has been increasing use of artificial intelligence tools in nanotechnology research. In this paper we review some of these efforts in the context of interpreting scanning probe microscopy, the study of biological nanosystems, the classification of material properties at the nanoscale, theoretical approaches and simulations in nanoscience, and generally in the design of nanodevices. Current trends and future perspectives in the development of nanocomputing hardware that can boost artificial-intelligence-based applications are also discussed. Convergence between artificial intelligence and nanotechnology can shape the path for many technological developments in the field of information sciences that will rely on new computer architectures and data representations, hybrid technologies that use biological entities and nanotechnological devices, bioengineering, neuroscience and a large variety of related disciplines. (topical review)

  15. Artificial intelligence executive summary

    International Nuclear Information System (INIS)

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

    1984-01-01

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

  16. Artificial intelligence in cardiology.

    Science.gov (United States)

    Bonderman, Diana

    2017-12-01

    Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

  17. Spatially Resolved Artificial Chemistry

    DEFF Research Database (Denmark)

    Fellermann, Harold

    2009-01-01

    Although spatial structures can play a crucial role in chemical systems and can drastically alter the outcome of reactions, the traditional framework of artificial chemistry is a well-stirred tank reactor with no spatial representation in mind. Advanced method development in physical chemistry has...... made a class of models accessible to the realms of artificial chemistry that represent reacting molecules in a coarse-grained fashion in continuous space. This chapter introduces the mathematical models of Brownian dynamics (BD) and dissipative particle dynamics (DPD) for molecular motion and reaction...

  18. Spatially Resolved Artificial Chemistry

    DEFF Research Database (Denmark)

    Fellermann, Harold

    2009-01-01

    made a class of models accessible to the realms of artificial chemistry that represent reacting molecules in a coarse-grained fashion in continuous space. This chapter introduces the mathematical models of Brownian dynamics (BD) and dissipative particle dynamics (DPD) for molecular motion and reaction......Although spatial structures can play a crucial role in chemical systems and can drastically alter the outcome of reactions, the traditional framework of artificial chemistry is a well-stirred tank reactor with no spatial representation in mind. Advanced method development in physical chemistry has...

  19. Springer handbook of model-based science

    CERN Document Server

    Bertolotti, Tommaso

    2017-01-01

    The handbook offers the first comprehensive reference guide to the interdisciplinary field of model-based reasoning. It highlights the role of models as mediators between theory and experimentation, and as educational devices, as well as their relevance in testing hypotheses and explanatory functions. The Springer Handbook merges philosophical, cognitive and epistemological perspectives on models with the more practical needs related to the application of this tool across various disciplines and practices. The result is a unique, reliable source of information that guides readers toward an understanding of different aspects of model-based science, such as the theoretical and cognitive nature of models, as well as their practical and logical aspects. The inferential role of models in hypothetical reasoning, abduction and creativity once they are constructed, adopted, and manipulated for different scientific and technological purposes is also discussed. Written by a group of internationally renowned experts in ...

  20. Model-based version management system framework

    International Nuclear Information System (INIS)

    Mehmood, W.

    2016-01-01

    In this paper we present a model-based version management system. Version Management System (VMS) a branch of software configuration management (SCM) aims to provide a controlling mechanism for evolution of software artifacts created during software development process. Controlling the evolution requires many activities to perform, such as, construction and creation of versions, identification of differences between versions, conflict detection and merging. Traditional VMS systems are file-based and consider software systems as a set of text files. File based VMS systems are not adequate for performing software configuration management activities such as, version control on software artifacts produced in earlier phases of the software life cycle. New challenges of model differencing, merge, and evolution control arise while using models as central artifact. The goal of this work is to present a generic framework model-based VMS which can be used to overcome the problem of tradition file-based VMS systems and provide model versioning services. (author)

  1. Online constrained model-based reinforcement learning

    CSIR Research Space (South Africa)

    Van Niekerk, B

    2017-08-01

    Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...

  2. Statistical models based on conditional probability distributions

    International Nuclear Information System (INIS)

    Narayanan, R.S.

    1991-10-01

    We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)

  3. PV panel model based on datasheet values

    DEFF Research Database (Denmark)

    Sera, Dezso; Teodorescu, Remus; Rodriguez, Pedro

    2007-01-01

    This work presents the construction of a model for a PV panel using the single-diode five-parameters model, based exclusively on data-sheet parameters. The model takes into account the series and parallel (shunt) resistance of the panel. The equivalent circuit and the basic equations of the PV cell....... Based on these equations, a PV panel model, which is able to predict the panel behavior in different temperature and irradiance conditions, is built and tested....

  4. Research and applications: Artificial intelligence

    Science.gov (United States)

    Raphael, B.; Fikes, R. E.; Chaitin, L. J.; Hart, P. E.; Duda, R. O.; Nilsson, N. J.

    1971-01-01

    A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

  5. Artificial intelligence and process management

    International Nuclear Information System (INIS)

    Epton, J.B.A.

    1989-01-01

    Techniques derived from work in artificial intelligence over the past few decades are beginning to change the approach in applying computers to process management. To explore this new approach and gain real practical experience of its potential a programme of experimental applications was initiated by Sira in collaboration with the process industry. This programme encompassed a family of experimental applications ranging from process monitoring, through supervisory control and troubleshooting to planning and scheduling. The experience gained has led to a number of conclusions regarding the present level of maturity of the technology, the potential for further developments and the measures required to secure the levels of system integrity necessary in on-line applications to critical processes. (author)

  6. [Artificial Intelligence in Drug Discovery].

    Science.gov (United States)

    Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

    2018-04-01

    According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

  7. Innovative applications of artificial intelligence

    Science.gov (United States)

    Schorr, Herbert; Rappaport, Alain

    Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

  8. A Probabilistic Short-Term Water Demand Forecasting Model Based on the Markov Chain

    Directory of Open Access Journals (Sweden)

    Francesca Gagliardi

    2017-07-01

    Full Text Available This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals covering the expected total variability. More specifically, two models based on homogeneous and non-homogeneous Markov chains were developed and presented. These models, together with two benchmark models (based on artificial neural network and naïve methods, were applied to three real-life case studies for the purpose of forecasting the respective water demands from 1 to 24 h ahead. The results obtained show that the model based on a homogeneous Markov chain provides more accurate short-term forecasts than the one based on a non-homogeneous Markov chain, which is in line with the artificial neural network model. Both Markov chain models enable probabilistic information regarding the stochastic demand forecast to be easily obtained.

  9. e-Government Maturity Model Based on Systematic Review and Meta-Ethnography Approach

    Directory of Open Access Journals (Sweden)

    Darmawan Napitupulu

    2016-11-01

    Full Text Available Maturity model based on e-Government portal has been developed by a number of researchers both individually and institutionally, but still scattered in various journals and conference articles and can be said to have a different focus with each other, both in terms of stages and features. The aim of this research is conducting a study to integrate a number of maturity models existing today in order to build generic maturity model based on e-Government portal. The method used in this study is Systematic Review with meta-ethnography qualitative approach. Meta-ethnography, which is part of Systematic Review method, is a technique to perform data integration to obtain theories and concepts with a new level of understanding that is deeper and thorough. The result obtained is a maturity model based on e-Government portal that consists of 7 (seven stages, namely web presence, interaction, transaction, vertical integration, horizontal integration, full integration, and open participation. These seven stages are synthesized from the 111 key concepts related to 25 studies of maturity model based e-Government portal. The maturity model resulted is more comprehensive and generic because it is an integration of models (best practices that exists today.

  10. Control of a Heavy-Lift Robotic Manipulator with Pneumatic Artificial Muscles

    Directory of Open Access Journals (Sweden)

    Ryan M. Robinson

    2014-04-01

    Full Text Available Lightweight, compliant actuators are particularly desirable in robotic systems intended for interaction with humans. Pneumatic artificial muscles (PAMs exhibit these characteristics and are capable of higher specific work than comparably-sized hydraulic actuators and electric motors. The objective of this work is to develop a control algorithm that can smoothly and accurately track the desired motions of a manipulator actuated by pneumatic artificial muscles. The manipulator is intended for lifting humans in nursing assistance or casualty extraction scenarios; hence, the control strategy must be capable of responding to large variations in payload over a large range of motion. The present work first investigates the feasibility of two output feedback controllers (proportional-integral-derivative and fuzzy logic, but due to the limitations of pure output feedback control, a model-based feedforward controller is developed and combined with output feedback to achieve improved closed-loop performance. The model upon which the controller is based incorporates the internal airflow dynamics, the physical parameters of the pneumatic muscles and the manipulator dynamics. Simulations were performed in order to validate the control algorithms, guide controller design and predict optimal gains. Using real-time interface software and hardware, the controllers were implemented and experimentally tested on the manipulator, demonstrating the improved capability.

  11. A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.

    Science.gov (United States)

    Wang, Zhongqiang; Ambrogio, Stefano; Balatti, Simone; Ielmini, Daniele

    2014-01-01

    Resistive (or memristive) switching devices based on metal oxides find applications in memory, logic and neuromorphic computing systems. Their small area, low power operation, and high functionality meet the challenges of brain-inspired computing aiming at achieving a huge density of active connections (synapses) with low operation power. This work presents a new artificial synapse scheme, consisting of a memristive switch connected to 2 transistors responsible for gating the communication and learning operations. Spike timing dependent plasticity (STDP) is achieved through appropriate shaping of the pre-synaptic and the post synaptic spikes. Experiments with integrated artificial synapses demonstrate STDP with stochastic behavior due to (i) the natural variability of set/reset processes in the nanoscale switch, and (ii) the different response of the switch to a given stimulus depending on the initial state. Experimental results are confirmed by model-based simulations of the memristive switching. Finally, system-level simulations of a 2-layer neural network and a simplified STDP model show random learning and recognition of patterns.

  12. Generality in Artificial Intelligence

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 3. Generality in Artificial Intelligence. John McCarthy. Classics Volume 19 Issue 3 March 2014 pp 283-296. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/019/03/0283-0296. Author Affiliations.

  13. Artificial molecular motors

    NARCIS (Netherlands)

    Kassem, Salma; van Leeuwen, Thomas; Lubbe, Anouk S.; Wilson, Miriam R.; Feringa, Ben L.; Leigh, David A.

    2017-01-01

    Motor proteins are nature's solution for directing movement at the molecular level. The field of artificial molecular motors takes inspiration from these tiny but powerful machines. Although directional motion on the nanoscale performed by synthetic molecular machines is a relatively new

  14. Artificial intelligence within AFSC

    Science.gov (United States)

    Gersh, Mark A.

    1990-01-01

    Information on artificial intelligence research in the Air Force Systems Command is given in viewgraph form. Specific research that is being conducted at the Rome Air Development Center, the Space Technology Center, the Human Resources Laboratory, the Armstrong Aerospace Medical Research Laboratory, the Armamant Laboratory, and the Wright Research and Development Center is noted.

  15. Database in Artificial Intelligence.

    Science.gov (United States)

    Wilkinson, Julia

    1986-01-01

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

  16. Artificial skin and patient simulator comprising the artificial skin

    NARCIS (Netherlands)

    2011-01-01

    The invention relates to an artificial skin (10, 12, 14), and relates to a patient simulator (100) comprising the artificial skin. The artificial skin is a layered structure comprising a translucent cover layer (20) configured for imitating human or animal skin, and comprising a light emitting layer

  17. Providing Language Instructor with Artificial Intelligence Assistant

    OpenAIRE

    K. Pietroszek

    2007-01-01

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

  18. Introduction to Artificial Neural Networks

    DEFF Research Database (Denmark)

    Larsen, Jan

    1999-01-01

    The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

  19. Criminal Aspects of Artificial Abortion

    OpenAIRE

    Hartmanová, Leona

    2016-01-01

    Criminal Aspects of Artificial Abortion This diploma thesis deals with the issue of artificial abortion, especially its criminal aspects. Legal aspects are not the most important aspects of artificial abortion. Social, ethical or ideological aspects are of the same importance but this diploma thesis cannot analyse all of them. The main issue with artificial abortion is whether it is possible to force a pregnant woman to carry a child and give birth to a child when she cannot or does not want ...

  20. SLS Navigation Model-Based Design Approach

    Science.gov (United States)

    Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

    2018-01-01

    The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

  1. Least-squares model-based halftoning

    Science.gov (United States)

    Pappas, Thrasyvoulos N.; Neuhoff, David L.

    1992-08-01

    A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach

  2. Model-Based Motion Tracking of Infants

    DEFF Research Database (Denmark)

    Olsen, Mikkel Damgaard; Herskind, Anna; Nielsen, Jens Bo

    2014-01-01

    Even though motion tracking is a widely used technique to analyze and measure human movements, only a few studies focus on motion tracking of infants. In recent years, a number of studies have emerged focusing on analyzing the motion pattern of infants, using computer vision. Most of these studies...... are based on 2D images, but few are based on 3D information. In this paper, we present a model-based approach for tracking infants in 3D. The study extends a novel study on graph-based motion tracking of infants and we show that the extension improves the tracking results. A 3D model is constructed...

  3. Model-Based Power Plant Master Control

    Energy Technology Data Exchange (ETDEWEB)

    Boman, Katarina; Thomas, Jean; Funkquist, Jonas

    2010-08-15

    The main goal of the project has been to evaluate the potential of a coordinated master control for a solid fuel power plant in terms of tracking capability, stability and robustness. The control strategy has been model-based predictive control (MPC) and the plant used in the case study has been the Vattenfall power plant Idbaecken in Nykoeping. A dynamic plant model based on nonlinear physical models was used to imitate the true plant in MATLAB/SIMULINK simulations. The basis for this model was already developed in previous Vattenfall internal projects, along with a simulation model of the existing control implementation with traditional PID controllers. The existing PID control is used as a reference performance, and it has been thoroughly studied and tuned in these previous Vattenfall internal projects. A turbine model was developed with characteristics based on the results of steady-state simulations of the plant using the software EBSILON. Using the derived model as a representative for the actual process, an MPC control strategy was developed using linearization and gain-scheduling. The control signal constraints (rate of change) and constraints on outputs were implemented to comply with plant constraints. After tuning the MPC control parameters, a number of simulation scenarios were performed to compare the MPC strategy with the existing PID control structure. The simulation scenarios also included cases highlighting the robustness properties of the MPC strategy. From the study, the main conclusions are: - The proposed Master MPC controller shows excellent set-point tracking performance even though the plant has strong interactions and non-linearity, and the controls and their rate of change are bounded. - The proposed Master MPC controller is robust, stable in the presence of disturbances and parameter variations. Even though the current study only considered a very small number of the possible disturbances and modelling errors, the considered cases are

  4. Model-based surface soil moisture (SSM) retrieval algorithm using multi-temporal RISAT-1 C-band SAR data

    Science.gov (United States)

    Pandey, Dharmendra K.; Maity, Saroj; Bhattacharya, Bimal; Misra, Arundhati

    2016-05-01

    Accurate measurement of surface soil moisture of bare and vegetation covered soil over agricultural field and monitoring the changes in surface soil moisture is vital for estimation for managing and mitigating risk to agricultural crop, which requires information and knowledge to assess risk potential and implement risk reduction strategies and deliver essential responses. The empirical and semi-empirical model-based soil moisture inversion approach developed in the past are either sensor or region specific, vegetation type specific or have limited validity range, and have limited scope to explain physical scattering processes. Hence, there is need for more robust, physical polarimetric radar backscatter model-based retrieval methods, which are sensor and location independent and have wide range of validity over soil properties. In the present study, Integral Equation Model (IEM) and Vector Radiative Transfer (VRT) model were used to simulate averaged backscatter coefficients in various soil moisture (dry, moist and wet soil), soil roughness (smooth to very rough) and crop conditions (low to high vegetation water contents) over selected regions of Gujarat state of India and the results were compared with multi-temporal Radar Imaging Satellite-1 (RISAT-1) C-band Synthetic Aperture Radar (SAR) data in σ°HH and σ°HV polarizations, in sync with on field measured soil and crop conditions. High correlations were observed between RISAT-1 HH and HV with model simulated σ°HH & σ°HV based on field measured soil with the coefficient of determination R2 varying from 0.84 to 0.77 and RMSE varying from 0.94 dB to 2.1 dB for bare soil. Whereas in case of winter wheat crop, coefficient of determination R2 varying from 0.84 to 0.79 and RMSE varying from 0.87 dB to 1.34 dB, corresponding to with vegetation water content values up to 3.4 kg/m2. Artificial Neural Network (ANN) methods were adopted for model-based soil moisture inversion. The training datasets for the NNs were

  5. A review of European applications of artificial intelligence to space

    Science.gov (United States)

    Drummond, Mark (Editor); Stewart, Helen (Editor)

    1993-01-01

    The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.

  6. Artificial Intelligence: Threat or Boon to Radiologists?

    Science.gov (United States)

    Recht, Michael; Bryan, R Nick

    2017-11-01

    The development and integration of machine learning/artificial intelligence into routine clinical practice will significantly alter the current practice of radiology. Changes in reimbursement and practice patterns will also continue to affect radiology. But rather than being a significant threat to radiologists, we believe these changes, particularly machine learning/artificial intelligence, will be a boon to radiologists by increasing their value, efficiency, accuracy, and personal satisfaction. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  7. A Python Engine for Teaching Artificial Intelligence in Games

    OpenAIRE

    Riedl, Mark O.

    2015-01-01

    Computer games play an important role in our society and motivate people to learn computer science. Since artificial intelligence is integral to most games, they can also be used to teach artificial intelligence. We introduce the Game AI Game Engine (GAIGE), a Python game engine specifically designed to teach about how AI is used in computer games. A progression of seven assignments builds toward a complete, working Multi-User Battle Arena (MOBA) game. We describe the engine, the assignments,...

  8. Diagnosis and Model Based Identification of a Coupling Misalignment

    Directory of Open Access Journals (Sweden)

    P. Pennacchi

    2005-01-01

    Full Text Available This paper is focused on the application of two different diagnostic techniques aimed to identify the most important faults in rotating machinery as well as on the simulation and prediction of the frequency response of rotating machines. The application of the two diagnostics techniques, the orbit shape analysis and the model based identification in the frequency domain, is described by means of an experimental case study that concerns a gas turbine-generator unit of a small power plant whose rotor-train was affected by an angular misalignment in a flexible coupling, caused by a wrong machine assembling. The fault type is identified by means of the orbit shape analysis, then the equivalent bending moments, which enable the shaft experimental vibrations to be simulated, have been identified using a model based identification method. These excitations have been used to predict the machine vibrations in a large rotating speed range inside which no monitoring data were available. To the best of the authors' knowledge, this is the first case of identification of coupling misalignment and prediction of the consequent machine behaviour in an actual size rotating machinery. The successful results obtained emphasise the usefulness of integrating common condition monitoring techniques with diagnostic strategies.

  9. SLS Model Based Design: A Navigation Perspective

    Science.gov (United States)

    Oliver, T. Emerson; Anzalone, Evan; Park, Thomas; Geohagan, Kevin

    2018-01-01

    The SLS Program has implemented a Model-based Design (MBD) and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team is responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1B design, the additional GPS Receiver hardware model is managed as a DMM at the vehicle design level. This paper describes the models, and discusses the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the navigation components.

  10. Sandboxes for Model-Based Inquiry

    Science.gov (United States)

    Brady, Corey; Holbert, Nathan; Soylu, Firat; Novak, Michael; Wilensky, Uri

    2015-04-01

    In this article, we introduce a class of constructionist learning environments that we call Emergent Systems Sandboxes ( ESSs), which have served as a centerpiece of our recent work in developing curriculum to support scalable model-based learning in classroom settings. ESSs are a carefully specified form of virtual construction environment that support students in creating, exploring, and sharing computational models of dynamic systems that exhibit emergent phenomena. They provide learners with "entity"-level construction primitives that reflect an underlying scientific model. These primitives can be directly "painted" into a sandbox space, where they can then be combined, arranged, and manipulated to construct complex systems and explore the emergent properties of those systems. We argue that ESSs offer a means of addressing some of the key barriers to adopting rich, constructionist model-based inquiry approaches in science classrooms at scale. Situating the ESS in a large-scale science modeling curriculum we are implementing across the USA, we describe how the unique "entity-level" primitive design of an ESS facilitates knowledge system refinement at both an individual and social level, we describe how it supports flexible modeling practices by providing both continuous and discrete modes of executability, and we illustrate how it offers students a variety of opportunities for validating their qualitative understandings of emergent systems as they develop.

  11. Biomaterials for artificial organs

    CERN Document Server

    Lysaght, Michael J

    2010-01-01

    The worldwide demand for organ transplants far exceeds available donor organs. Consequently some patients die whilst waiting for a transplant. Synthetic alternatives are therefore imperative to improve the quality of, and in some cases, save people's lives. Advances in biomaterials have generated a range of materials and devices for use either outside the body or through implantation to replace or assist functions which may have been lost through disease or injury. Biomaterials for artificial organs reviews the latest developments in biomaterials and investigates how they can be used to improve the quality and efficiency of artificial organs. Part one discusses commodity biomaterials including membranes for oxygenators and plasmafilters, titanium and cobalt chromium alloys for hips and knees, polymeric joint-bearing surfaces for total joint replacements, biomaterials for pacemakers, defibrillators and neurostimulators and mechanical and bioprosthetic heart valves. Part two goes on to investigate advanced and ...

  12. Artificial structures on Mars

    Science.gov (United States)

    Van Flandern, T.

    2002-05-01

    Approximately 70,000 images of the surface of Mars at a resolution of up to 1.4 meters per pixel, taken by the Mars Global Surveyor spacecraft, are now in public archives. Approximately 1% of those images show features that can be broadly described as `special shapes', `tracks, trails, and possible vegetation', `spots, stripes, and tubes', `artistic imagery', and `patterns and symbols'. Rather than optical illusions and tricks of light and shadow, most of these have the character that, if photographed on Earth, no one would doubt that they were the products of large biology and intelligence. In a few cases, relationships, context, and fulfillment of a priori predictions provide objective evidence of artificiality that is exempt from the influence of experimenter biases. Only controlled test results can be trusted because biases are strong and operate both for and against artificiality.

  13. Artificial intelligence in medicine

    OpenAIRE

    Scerri, Mariella; Grech, Victor E.

    2016-01-01

    Various types of artificial intelligence programs are already available as consultants to physicians, and these help in medical diagnostics and treatment. At the time of writing, extant programs constitute “weak” AI—lacking in consciousness and intentionality. With AI currently making rapid progress in all domains, including those of healthcare, physicians face possible competitors—or worse, claims that doctors may become obsolete. We will explore the development of AI and robotics in medicin...

  14. 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...

  15. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

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

  16. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  17. [Model-based biofuels system analysis: a review].

    Science.gov (United States)

    Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

    2011-03-01

    Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.

  18. 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...

  19. Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

    Directory of Open Access Journals (Sweden)

    Zhiyong Yang

    2008-11-01

    Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

  20. Mechatronic Model Based Computed Torque Control of a Parallel Manipulator

    Directory of Open Access Journals (Sweden)

    Zhiyong Yang

    2008-03-01

    Full Text Available With high speed and accuracy the parallel manipulators have wide application in the industry, but there still exist many difficulties in the actual control process because of the time-varying and coupling. Unfortunately, the present-day commercial controlles cannot provide satisfying performance for its single axis linear control only. Therefore, aimed at a novel 2-DOF (Degree of Freedom parallel manipulator called Diamond 600, a motor-mechanism coupling dynamic model based control scheme employing the computed torque control algorithm are presented in this paper. First, the integrated dynamic coupling model is deduced, according to equivalent torques between the mechanical structure and the PM (Permanent Magnetism servomotor. Second, computed torque controller is described in detail for the above proposed model. At last, a series of numerical simulations and experiments are carried out to test the effectiveness of the system, and the results verify the favourable tracking ability and robustness.

  1. Artificial sweetener; Jinko kanmiryo

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-08-01

    The patents related to the artificial sweetener that it is introduced to the public in 3 years from 1996 until 1998 are 115 cases. The sugar quality which makes an oligosaccharide and sugar alcohol the subject is greatly over 28 cases of the non-sugar quality in the one by the kind as a general tendency of these patents at 73 cases in such cases as the Aspartame. The method of manufacture patent, which included new material around other peptides, the oligosaccharide and sugar alcohol isn`t inferior to 56 cases of the formation thing patent at 43 cases, and pays attention to the thing, which is many by the method of manufacture, formation. There is most improvement of the quality of sweetness with 31 cases in badness of the aftertaste which is characteristic of the artificial sweetener and so on, and much stability including the improvement in the flavor of food by the artificial sweetener, a long time and dissolution, fluid nature and productivity and improvement of the economy such as a cost are seen with effect on a purpose. (NEDO)

  2. Antithrombotic artificial organs

    Energy Technology Data Exchange (ETDEWEB)

    Takamatsu, T; Fukada, E; Saegusa, M; Hasegawa, T

    1971-07-12

    A new antithrombotic material useful for making artificial organs (artificial blood vessel, artificial heart, etc.) can be prepared by graft-polymerizing an acrylic ester (methyl methacrylate, methyl acrylate, ethyl acrylate, etc.) with a synthetic fiber (teflon, etc.). The graft-polymerization can be carried out by means of gamma radiation with cobalt 60 (dose rate 2.6x10/sup 3/ r/min., total dose 8x10/sup 4/ to 3.5x10/sup 5/ r). A graft ratio of 5 to 80% is attainable. In one example, a tubular sample made of teflon fiber having an inner diameter of 5 to 10 mm was immersed into methyl methacrylate in an ampoule in the absence of air and exposed to cobalt 60 gamma ray at the dose rate of 3.18x10/sup 3/ rad/min. After extraction with acetone, the sample was dried. The total dose was 3.5x10/sup 5/ rad and the graft ratio was ca. 25%. The sample was transplanted to vena cava of dog. No formation of thrombus was observed by autopsy (4 months after the transplantation). In control (teflon tube not graft-polymerized) thrombus was observed by autopsy 7 days after the transplantation.

  3. Model-based reasoning and the control of process plants

    International Nuclear Information System (INIS)

    Vaelisuo, Heikki

    1993-02-01

    In addition to feedback control, safe and economic operation of industrial process plants requires discrete-event type logic control like for example automatic control sequences, interlocks, etc. A lot of complex routine reasoning is involved in the design and verification and validation (VandV) of such automatics. Similar reasoning tasks are encountered during plant operation in action planning and fault diagnosis. The low-level part of the required problem solving is so straightforward that it could be accomplished by a computer if only there were plant models which allow versatile mechanised reasoning. Such plant models and corresponding inference algorithms are the main subject of this report. Deep knowledge and qualitative modelling play an essential role in this work. Deep knowledge refers to mechanised reasoning based on the first principles of the phenomena in the problem domain. Qualitative modelling refers to knowledge representation formalism and related reasoning methods which allow solving problems on an abstraction level higher than for example traditional simulation and optimisation. Prolog is a commonly used platform for artificial intelligence (Al) applications. Constraint logic languages like CLP(R) and Prolog-III extend the scope of logic programming to numeric problem solving. In addition they allow a programming style which often reduces the computational complexity significantly. An approach to model-based reasoning implemented in constraint logic programming language CLP(R) is presented. The approach is based on some of the principles of QSIM, an algorithm for qualitative simulation. It is discussed how model-based reasoning can be applied in the design and VandV of plant automatics and in action planning during plant operation. A prototype tool called ISIR is discussed and some initial results obtained during the development of the tool are presented. The results presented originate from preliminary test results of the prototype obtained

  4. Unifying Model-Based and Reactive Programming within a Model-Based Executive

    Science.gov (United States)

    Williams, Brian C.; Gupta, Vineet; Norvig, Peter (Technical Monitor)

    1999-01-01

    Real-time, model-based, deduction has recently emerged as a vital component in AI's tool box for developing highly autonomous reactive systems. Yet one of the current hurdles towards developing model-based reactive systems is the number of methods simultaneously employed, and their corresponding melange of programming and modeling languages. This paper offers an important step towards unification. We introduce RMPL, a rich modeling language that combines probabilistic, constraint-based modeling with reactive programming constructs, while offering a simple semantics in terms of hidden state Markov processes. We introduce probabilistic, hierarchical constraint automata (PHCA), which allow Markov processes to be expressed in a compact representation that preserves the modularity of RMPL programs. Finally, a model-based executive, called Reactive Burton is described that exploits this compact encoding to perform efficIent simulation, belief state update and control sequence generation.

  5. Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

    Science.gov (United States)

    Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

    1993-01-01

    The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

  6. Modeling Based Decision Support Environment, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Phoenix Integration's vision is the creation of an intuitive human-in-the-loop engineering environment called Decision Navigator that leverages recent advances in...

  7. Model Based Control of Refrigeration Systems

    DEFF Research Database (Denmark)

    Larsen, Lars Finn Sloth

    for automation of these procedures, that is to incorporate some "intelligence" in the control system, this project was started up. The main emphasis of this work has been on model based methods for system optimizing control in supermarket refrigeration systems. The idea of implementing a system optimizing...... control is to let an optimization procedure take over the task of operating the refrigeration system and thereby replace the role of the operator in the traditional control structure. In the context of refrigeration systems, the idea is to divide the optimizing control structure into two parts: A part...... optimizing the steady state operation "set-point optimizing control" and a part optimizing dynamic behaviour of the system "dynamical optimizing control". A novel approach for set-point optimization will be presented. The general idea is to use a prediction of the steady state, for computation of the cost...

  8. Artificial intelligence model for sustain ability measurement

    International Nuclear Information System (INIS)

    Navickiene, R.; Navickas, K.

    2012-01-01

    The article analyses the main dimensions of organizational sustain ability, their possible integrations into artificial neural network. In this article authors performing analyses of organizational internal and external environments, their possible correlations with 4 components of sustain ability, and the principal determination models for sustain ability of organizations. Based on the general principles of sustainable development organizations, a artificial intelligence model for the determination of organizational sustain ability has been developed. The use of self-organizing neural networks allows the identification of the organizational sustain ability and the endeavour to explore vital, social, antropogenical and economical efficiency. The determination of the forest enterprise sustain ability is expected to help better manage the sustain ability. (Authors)

  9. Nuclear-powered artificial heart system

    International Nuclear Information System (INIS)

    Pouchot, W.D.; Lehrfeld, D.

    1976-01-01

    As reported to the 9th IECEC, a bench model version of a nuclear-powered artificial heart system to be used as a replacement for the natural heart was constructed and tested as part of a broader U.S. ERDA program. A report is given of the system design and integration, bench testing, and field support equipment of an implantable and advanced version of the bench model incorporating some of the component developments reported to the 10th IECEC. The basic elements of the system are a 32-watt Pu-238 heat source, a Stirling engine thermal converter, a coupling mechanism, and a mechanical blood pump drive actuating, alternatively, two artificial ventricles of polymeric material. As tested on the bench using a mock circulation, the system provides approximately 9 liters/minute at 120/80 mm Hg aortic pressure. At 190/145 mm Hg aortic pressure, the maximum flow decreases to about 7 liters/minute

  10. Artificial intelligence - NASA. [robotics for Space Station

    Science.gov (United States)

    Erickson, J. D.

    1985-01-01

    Artificial Intelligence (AI) represents a vital common space support element needed to enable the civil space program and commercial space program to perform their missions successfully. It is pointed out that advances in AI stimulated by the Space Station Program could benefit the U.S. in many ways. A fundamental challenge for the civil space program is to meet the needs of the customers and users of space with facilities enabling maximum productivity and having low start-up costs, and low annual operating costs. An effective way to meet this challenge may involve a man-machine system in which artificial intelligence, robotics, and advanced automation are integrated into high reliability organizations. Attention is given to the benefits, NASA strategy for AI, candidate space station systems, the Space Station as a stepping stone, and the commercialization of space.

  11. Artificial intelligence in hematology.

    Science.gov (United States)

    Zini, Gina

    2005-10-01

    Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

  12. Artificial intelligence in cardiology

    Directory of Open Access Journals (Sweden)

    Srishti Sharma

    2017-01-01

    Full Text Available Artificial intelligence (AI provides machines with the ability to learn and respond the way humans do and is also referred to as machine learning. The step to building an AI system is to provide the data to learn from so that it can map relations between inputs and outputs and set up parameters such as “weights”/decision boundaries to predict responses for inputs in the future. Then, the model is tested on a second data set. This article outlines the promise this analytic approach has in medicine and cardiology.

  13. Is Intelligence Artificial?

    OpenAIRE

    Greer, Kieran

    2014-01-01

    Our understanding of intelligence is directed primarily at the level of human beings. This paper attempts to give a more unifying definition that can be applied to the natural world in general. The definition would be used more to verify a degree of intelligence, not to quantify it and might help when making judgements on the matter. A version of an accepted test for AI is then put forward as the 'acid test' for Artificial Intelligence itself. It might be what a free-thinking program or robot...

  14. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2010-01-01

    Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.New to the Second EditionNew chapter on Bayesian network classifiersNew section on object-oriente

  15. Uncertainty in artificial intelligence

    CERN Document Server

    Kanal, LN

    1986-01-01

    How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

  16. Mechanism of artificial heart

    CERN Document Server

    Yamane, Takashi

    2016-01-01

    This book first describes medical devices in relation to regenerative medicine before turning to a more specific topic: artificial heart technologies. Not only the pump mechanisms but also the bearing, motor mechanisms, and materials are described, including expert information. Design methods are described to enhance hemocompatibility: main concerns are reduction of blood cell damage and protein break, as well as prevention of blood clotting. Regulatory science from R&D to clinical trials is also discussed to verify the safety and efficacy of the devices.

  17. Short-Term Load Forecasting Model Based on Quantum Elman Neural Networks

    Directory of Open Access Journals (Sweden)

    Zhisheng Zhang

    2016-01-01

    Full Text Available Short-term load forecasting model based on quantum Elman neural networks was constructed in this paper. The quantum computation and Elman feedback mechanism were integrated into quantum Elman neural networks. Quantum computation can effectively improve the approximation capability and the information processing ability of the neural networks. Quantum Elman neural networks have not only the feedforward connection but also the feedback connection. The feedback connection between the hidden nodes and the context nodes belongs to the state feedback in the internal system, which has formed specific dynamic memory performance. Phase space reconstruction theory is the theoretical basis of constructing the forecasting model. The training samples are formed by means of K-nearest neighbor approach. Through the example simulation, the testing results show that the model based on quantum Elman neural networks is better than the model based on the quantum feedforward neural network, the model based on the conventional Elman neural network, and the model based on the conventional feedforward neural network. So the proposed model can effectively improve the prediction accuracy. The research in the paper makes a theoretical foundation for the practical engineering application of the short-term load forecasting model based on quantum Elman neural networks.

  18. Synthetic and Bio-Artificial Tactile Sensing: A Review

    Directory of Open Access Journals (Sweden)

    Maria Chiara Carrozza

    2013-01-01

    Full Text Available This paper reviews the state of the art of artificial tactile sensing, with a particular focus on bio-hybrid and fully-biological approaches. To this aim, the study of physiology of the human sense of touch and of the coding mechanisms of tactile information is a significant starting point, which is briefly explored in this review. Then, the progress towards the development of an artificial sense of touch are investigated. Artificial tactile sensing is analysed with respect to the possible approaches to fabricate the outer interface layer: synthetic skin versus bio-artificial skin. With particular respect to the synthetic skin approach, a brief overview is provided on various technologies and transduction principles that can be integrated beneath the skin layer. Then, the main focus moves to approaches characterized by the use of bio-artificial skin as an outer layer of the artificial sensory system. Within this design solution for the skin, bio-hybrid and fully-biological tactile sensing systems are thoroughly presented: while significant results have been reported for the development of tissue engineered skins, the development of mechanotransduction units and their integration is a recent trend that is still lagging behind, therefore requiring research efforts and investments. In the last part of the paper, application domains and perspectives of the reviewed tactile sensing technologies are discussed.

  19. How to teach artificial organs.

    Science.gov (United States)

    Zapanta, Conrad M; Borovetz, Harvey S; Lysaght, Michael J; Manning, Keefe B

    2011-01-01

    Artificial organs education is often an overlooked field for many bioengineering and biomedical engineering students. The purpose of this article is to describe three different approaches to teaching artificial organs. This article can serve as a reference for those who wish to offer a similar course at their own institutions or incorporate these ideas into existing courses. Artificial organ classes typically fulfill several ABET (Accreditation Board for Engineering and Technology) criteria, including those specific to bioengineering and biomedical engineering programs.

  20. Artificial Photosynthesis: Beyond Mimicking Nature

    International Nuclear Information System (INIS)

    Dau, Holger; Fujita, Etsuko; Sun, Licheng

    2017-01-01

    In this Editorial, Guest Editors Holger Dau, Etsuko Fujita, and Licheng Sun introduce the Special Issue of ChemSusChem on “Artificial Photosynthesis for Sustainable Fuels”. Here, they discuss the need for non-fossil based fuels, introduce both biological and artificial photosynthesis, and outline various important concepts in artificial photosynthesis, including molecular and solid-state catalysts for water oxidation and hydrogen evolution, catalytic CO 2 reduction, and photoelectrochemical systems.

  1. Artificial Intelligence in Space Platforms.

    Science.gov (United States)

    1984-12-01

    computer algorithms, there still appears to be a need for Artificial Inteligence techniques in the navigation area. The reason is that navigaion, in...RD-RI32 679 ARTIFICIAL INTELLIGENCE IN SPACE PLRTFORNSMU AIR FORCE 1/𔃼 INST OF TECH WRIGHT-PRTTERSON AFB OH SCHOOL OF ENGINEERING M A WRIGHT DEC 94...i4 Preface The purpose of this study was to analyze the feasibility of implementing Artificial Intelligence techniques to increase autonomy for

  2. Artificial Intelligence and Moral intelligence

    OpenAIRE

    Laura Pana

    2008-01-01

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

  3. Trimaran Resistance Artificial Neural Network

    Science.gov (United States)

    2011-01-01

    11th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 Trimaran Resistance Artificial Neural Network Richard...Trimaran Resistance Artificial Neural Network 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e... Artificial Neural Network and is restricted to the center and side-hull configurations tested. The value in the parametric model is that it is able to

  4. Artificial Intelligence and Economic Theories

    OpenAIRE

    Marwala, Tshilidzi; Hurwitz, Evan

    2017-01-01

    The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence such as the swarming of birds, the working of the brain and the pathfinding of the ants. These techniques have impact on economic theories. This book studies the impact of artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that...

  5. Model-based control of hopper dredgers

    NARCIS (Netherlands)

    Braaksma, J.

    2008-01-01

    The modern trailing suction hopper dredgers are advanced ships that are equipped with many automation systems that can be controlled with integrated computer systems from the bridge. From the operators it is expected that they generate the right set-points for all these systems. The latest ships are

  6. Artificial Enzymes, "Chemzymes"

    DEFF Research Database (Denmark)

    Bjerre, Jeannette; Rousseau, Cyril Andre Raphaël; Pedersen, Lavinia Georgeta M

    2008-01-01

    Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models that successf......Enzymes have fascinated scientists since their discovery and, over some decades, one aim in organic chemistry has been the creation of molecules that mimic the active sites of enzymes and promote catalysis. Nevertheless, even today, there are relatively few examples of enzyme models...... that successfully perform Michaelis-Menten catalysis under enzymatic conditions (i.e., aqueous medium, neutral pH, ambient temperature) and for those that do, very high rate accelerations are seldomly seen. This review will provide a brief summary of the recent developments in artificial enzymes, so called...... "Chemzymes", based on cyclodextrins and other molecules. Only the chemzymes that have shown enzyme-like activity that has been quantified by different methods will be mentioned. This review will summarize the work done in the field of artificial glycosidases, oxidases, epoxidases, and esterases, as well...

  7. The total artificial heart.

    Science.gov (United States)

    Cook, Jason A; Shah, Keyur B; Quader, Mohammed A; Cooke, Richard H; Kasirajan, Vigneshwar; Rao, Kris K; Smallfield, Melissa C; Tchoukina, Inna; Tang, Daniel G

    2015-12-01

    The total artificial heart (TAH) is a form of mechanical circulatory support in which the patient's native ventricles and valves are explanted and replaced by a pneumatically powered artificial heart. Currently, the TAH is approved for use in end-stage biventricular heart failure as a bridge to heart transplantation. However, with an increasing global burden of cardiovascular disease and congestive heart failure, the number of patients with end-stage heart failure awaiting heart transplantation now far exceeds the number of available hearts. As a result, the use of mechanical circulatory support, including the TAH and left ventricular assist device (LVAD), is growing exponentially. The LVAD is already widely used as destination therapy, and destination therapy for the TAH is under investigation. While most patients requiring mechanical circulatory support are effectively treated with LVADs, there is a subset of patients with concurrent right ventricular failure or major structural barriers to LVAD placement in whom TAH may be more appropriate. The history, indications, surgical implantation, post device management, outcomes, complications, and future direction of the TAH are discussed in this review.

  8. THRESHOLD LOGIC IN ARTIFICIAL INTELLIGENCE

    Science.gov (United States)

    COMPUTER LOGIC, ARTIFICIAL INTELLIGENCE , BIONICS, GEOMETRY, INPUT OUTPUT DEVICES, LINEAR PROGRAMMING, MATHEMATICAL LOGIC, MATHEMATICAL PREDICTION, NETWORKS, PATTERN RECOGNITION, PROBABILITY, SWITCHING CIRCUITS, SYNTHESIS

  9. Diminishing musyarakah investment model based on equity

    Science.gov (United States)

    Jaffar, Maheran Mohd; Zain, Shaharir Mohamad; Jemain, Abdul Aziz

    2017-11-01

    Most of the mudharabah and musyarakah contract funds are involved in debt financing. This does not support the theory that profit sharing contract is better than that of debt financing due to the sharing of risks and ownership of equity. Indeed, it is believed that Islamic banking is a financial model based on equity or musyarakah which emphasis on the sharing of risks, profit and loss in the investment between the investor and entrepreneur. The focus of this paper is to introduce the mathematical model that internalizes diminishing musyarakah, the sharing of profit and equity between entrepreneur and investor. The entrepreneur pays monthly-differed payment to buy out the equity that belongs to the investor (bank) where at the end of the specified period, the entrepreneur owns the business and the investor (bank) exits the joint venture. The model is able to calculate the amount of equity at any time for both parties and hence would be a guide in helping to estimate the value of investment should the entrepreneur or investor exit before the end of the specified period. The model is closer to the Islamic principles for justice and fairness.

  10. Model-Based Method for Sensor Validation

    Science.gov (United States)

    Vatan, Farrokh

    2012-01-01

    Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

  11. Model based energy benchmarking for glass furnace

    International Nuclear Information System (INIS)

    Sardeshpande, Vishal; Gaitonde, U.N.; Banerjee, Rangan

    2007-01-01

    Energy benchmarking of processes is important for setting energy efficiency targets and planning energy management strategies. Most approaches used for energy benchmarking are based on statistical methods by comparing with a sample of existing plants. This paper presents a model based approach for benchmarking of energy intensive industrial processes and illustrates this approach for industrial glass furnaces. A simulation model for a glass furnace is developed using mass and energy balances, and heat loss equations for the different zones and empirical equations based on operating practices. The model is checked with field data from end fired industrial glass furnaces in India. The simulation model enables calculation of the energy performance of a given furnace design. The model results show the potential for improvement and the impact of different operating and design preferences on specific energy consumption. A case study for a 100 TPD end fired furnace is presented. An achievable minimum energy consumption of about 3830 kJ/kg is estimated for this furnace. The useful heat carried by glass is about 53% of the heat supplied by the fuel. Actual furnaces operating at these production scales have a potential for reduction in energy consumption of about 20-25%

  12. 3-D model-based vehicle tracking.

    Science.gov (United States)

    Lou, Jianguang; Tan, Tieniu; Hu, Weiming; Yang, Hao; Maybank, Steven J

    2005-10-01

    This paper aims at tracking vehicles from monocular intensity image sequences and presents an efficient and robust approach to three-dimensional (3-D) model-based vehicle tracking. Under the weak perspective assumption and the ground-plane constraint, the movements of model projection in the two-dimensional image plane can be decomposed into two motions: translation and rotation. They are the results of the corresponding movements of 3-D translation on the ground plane (GP) and rotation around the normal of the GP, which can be determined separately. A new metric based on point-to-line segment distance is proposed to evaluate the similarity between an image region and an instantiation of a 3-D vehicle model under a given pose. Based on this, we provide an efficient pose refinement method to refine the vehicle's pose parameters. An improved EKF is also proposed to track and to predict vehicle motion with a precise kinematics model. Experimental results with both indoor and outdoor data show that the algorithm obtains desirable performance even under severe occlusion and clutter.

  13. Artificial exomuscle investigations for applications-metal hydride

    International Nuclear Information System (INIS)

    Crevier, Marie-Charlotte; Richard, Martin; Rittenhouse, D Matheson; Roy, Pierre-Olivier; Bedard, Stephane

    2007-01-01

    In pursuing the development of bionic devices, Victhom identified a need for technologies that could replace current motorized systems and be better integrated into the human body motion. The actuators used to obtain large displacements are noisy, heavy, and do not adequately reproduce human muscle behavior. Subsequently, a project at Victhom was devoted to the development of active materials to obtain an artificial exomuscle actuator. An exhaustive literature review was done at Victhom to identify promising active materials for the development of artificial muscles. According to this review, metal hydrides were identified as a promising technology for artificial muscle development. Victhom's investigations focused on determining metal hydride actuator potential in the context of bionics technology. Based on metal hydride properties and artificial muscle requirements such as force, displacement and rise time, an exomuscle was built. In addition, a finite element model, including heat and mass transfer in the metal hydride, was developed and implemented in FEMLAB software. (review article)

  14. Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

    NARCIS (Netherlands)

    van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

    2013-01-01

    The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

  15. Artificial organs: recent progress in artificial hearing and vision.

    Science.gov (United States)

    Ifukube, Tohru

    2009-01-01

    Artificial sensory organs are a prosthetic means of sending visual or auditory information to the brain by electrical stimulation of the optic or auditory nerves to assist visually impaired or hearing-impaired people. However, clinical application of artificial sensory organs, except for cochlear implants, is still a trial-and-error process. This is because how and where the information transmitted to the brain is processed is still unknown, and also because changes in brain function (plasticity) remain unknown, even though brain plasticity plays an important role in meaningful interpretation of new sensory stimuli. This article discusses some basic unresolved issues and potential solutions in the development of artificial sensory organs such as cochlear implants, brainstem implants, artificial vision, and artificial retinas.

  16. Spatial analysis and modelling based on activities

    CSIR Research Space (South Africa)

    Conradie, Dirk CU

    2010-01-01

    Full Text Available (deliberative attitudes) (Pokahr, 2005). The BDI model does not cover emotional and other ‘higher’ human attitudes. KRONOS is a generic Computational Building Simulation (CBS) tool that was developed over the past three years to work on advanced... featured, stable, mature and platform independent with an easy to use C/C++ Application Program Interface (API). It has advanced joint types and integrated collision detection with friction. ODE is particularly useful for simulating vehicles, objects...

  17. Model based control of refrigeration systems

    Energy Technology Data Exchange (ETDEWEB)

    Sloth Larsen, L.F.

    2005-11-15

    The subject for this Ph.D. thesis is model based control of refrigeration systems. Model based control covers a variety of different types of controls, that incorporates mathematical models. In this thesis the main subject therefore has been restricted to deal with system optimizing control. The optimizing control is divided into two layers, where the system oriented top layers deals with set-point optimizing control and the lower layer deals with dynamical optimizing control in the subsystems. The thesis has two main contributions, i.e. a novel approach for set-point optimization and a novel approach for desynchronization based on dynamical optimization. The focus in the development of the proposed set-point optimizing control has been on deriving a simple and general method, that with ease can be applied on various compositions of the same class of systems, such as refrigeration systems. The method is based on a set of parameter depended static equations describing the considered process. By adapting the parameters to the given process, predict the steady state and computing a steady state gradient of the cost function, the process can be driven continuously towards zero gradient, i.e. the optimum (if the cost function is convex). The method furthermore deals with system constrains by introducing barrier functions, hereby the best possible performance taking the given constrains in to account can be obtained, e.g. under extreme operational conditions. The proposed method has been applied on a test refrigeration system, placed at Aalborg University, for minimization of the energy consumption. Here it was proved that by using general static parameter depended system equations it was possible drive the set-points close to the optimum and thus reduce the power consumption with up to 20%. In the dynamical optimizing layer the idea is to optimize the operation of the subsystem or the groupings of subsystems, that limits the obtainable system performance. In systems

  18. Model Based Autonomy for Robust Mars Operations

    Science.gov (United States)

    Kurien, James A.; Nayak, P. Pandurang; Williams, Brian C.; Lau, Sonie (Technical Monitor)

    1998-01-01

    Space missions have historically relied upon a large ground staff, numbering in the hundreds for complex missions, to maintain routine operations. When an anomaly occurs, this small army of engineers attempts to identify and work around the problem. A piloted Mars mission, with its multiyear duration, cost pressures, half-hour communication delays and two-week blackouts cannot be closely controlled by a battalion of engineers on Earth. Flight crew involvement in routine system operations must also be minimized to maximize science return. It also may be unrealistic to require the crew have the expertise in each mission subsystem needed to diagnose a system failure and effect a timely repair, as engineers did for Apollo 13. Enter model-based autonomy, which allows complex systems to autonomously maintain operation despite failures or anomalous conditions, contributing to safe, robust, and minimally supervised operation of spacecraft, life support, In Situ Resource Utilization (ISRU) and power systems. Autonomous reasoning is central to the approach. A reasoning algorithm uses a logical or mathematical model of a system to infer how to operate the system, diagnose failures and generate appropriate behavior to repair or reconfigure the system in response. The 'plug and play' nature of the models enables low cost development of autonomy for multiple platforms. Declarative, reusable models capture relevant aspects of the behavior of simple devices (e.g. valves or thrusters). Reasoning algorithms combine device models to create a model of the system-wide interactions and behavior of a complex, unique artifact such as a spacecraft. Rather than requiring engineers to all possible interactions and failures at design time or perform analysis during the mission, the reasoning engine generates the appropriate response to the current situation, taking into account its system-wide knowledge, the current state, and even sensor failures or unexpected behavior.

  19. Artificial Diets for Mosquitoes

    Directory of Open Access Journals (Sweden)

    Kristina K. Gonzales

    2016-12-01

    Full Text Available Mosquito-borne diseases are responsible for more than a million human deaths every year. Modern mosquito control strategies such as sterile insect technique (SIT, release of insects carrying a dominant lethal (RIDL, population replacement strategies (PR, and Wolbachia-based strategies require the rearing of large numbers of mosquitoes in culture for continuous release over an extended period of time. Anautogenous mosquitoes require essential nutrients for egg production, which they obtain through the acquisition and digestion of a protein-rich blood meal. Therefore, mosquito mass production in laboratories and other facilities relies on vertebrate blood from live animal hosts. However, vertebrate blood is expensive to acquire and hard to store for longer times especially under field conditions. This review discusses older and recent studies that were aimed at the development of artificial diets for mosquitoes in order to replace vertebrate blood.

  20. Artificial intelligence in radiology.

    Science.gov (United States)

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

    2018-05-17

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

  1. Hydraulically actuated artificial muscles

    Science.gov (United States)

    Meller, M. A.; Tiwari, R.; Wajcs, K. B.; Moses, C.; Reveles, I.; Garcia, E.

    2012-04-01

    Hydraulic Artificial Muscles (HAMs) consisting of a polymer tube constrained by a nylon mesh are presented in this paper. Despite the actuation mechanism being similar to its popular counterpart, which are pneumatically actuated (PAM), HAMs have not been studied in depth. HAMs offer the advantage of compliance, large force to weight ratio, low maintenance, and low cost over traditional hydraulic cylinders. Muscle characterization for isometric and isobaric tests are discussed and compared to PAMs. A model incorporating the effect of mesh angle and friction have also been developed. In addition, differential swelling of the muscle on actuation has also been included in the model. An application of lab fabricated HAMs for a meso-scale robotic system is also presented.

  2. Artificially Engineered Protein Polymers.

    Science.gov (United States)

    Yang, Yun Jung; Holmberg, Angela L; Olsen, Bradley D

    2017-06-07

    Modern polymer science increasingly requires precise control over macromolecular structure and properties for engineering advanced materials and biomedical systems. The application of biological processes to design and synthesize artificial protein polymers offers a means for furthering macromolecular tunability, enabling polymers with dispersities of ∼1.0 and monomer-level sequence control. Taking inspiration from materials evolved in nature, scientists have created modular building blocks with simplified monomer sequences that replicate the function of natural systems. The corresponding protein engineering toolbox has enabled the systematic development of complex functional polymeric materials across areas as diverse as adhesives, responsive polymers, and medical materials. This review discusses the natural proteins that have inspired the development of key building blocks for protein polymer engineering and the function of these elements in material design. The prospects and progress for scalable commercialization of protein polymers are reviewed, discussing both technology needs and opportunities.

  3. Artificial resuspension studies

    International Nuclear Information System (INIS)

    Cooper, B.M.; Marchall, K.B.; Thomas, K.A.; Tracy, B.L.

    1990-01-01

    Artificial resuspension studies on a range of Taranaki and other major trial site soils were performed by use of a mechanical dust-raising apparatus. A cascade impactor was used to analyse airborne dust in terms of mass and 241 Am activities for particle sizes less than 7 μm. Plutonium and americium activities were found to be enhanced in the respirable fraction. Reported enhancement factors (defined as the ratio of activity concentration of the respirable fraction to that of the total soil) ranged from 3.7 to 32.5 for Taranaki soils with an average value of 6 appearing reasonable for general application in outer (plume) areas. Values close to unity were measured at major trial sites , One Tree and Tadje. Results of some experiments where uncontamined dust was raised by activities such as walking and driving over dusty ground are also presented. 7 refs., 9 tabs., 4 figs

  4. Artificial Intelligence and brain.

    Science.gov (United States)

    Shapshak, Paul

    2018-01-01

    From the start, Kurt Godel observed that computer and brain paradigms were considered on a par by researchers and that researchers had misunderstood his theorems. He hailed with displeasure that the brain transcends computers. In this brief article, we point out that Artificial Intelligence (AI) comprises multitudes of human-made methodologies, systems, and languages, and implemented with computer technology. These advances enhance development in the electron and quantum realms. In the biological realm, animal neurons function, also utilizing electron flow, and are products of evolution. Mirror neurons are an important paradigm in neuroscience research. Moreover, the paradigm shift proposed here - 'hall of mirror neurons' - is a potentially further productive research tactic. These concepts further expand AI and brain research.

  5. Sucrose compared with artificial sweeteners

    DEFF Research Database (Denmark)

    Sørensen, Lone Brinkmann; Vasilaras, Tatjana H; Astrup, Arne

    2014-01-01

    There is a lack of appetite studies in free-living subjects supplying the habitual diet with either sucrose or artificially sweetened beverages and foods. Furthermore, the focus of artificial sweeteners has only been on the energy intake (EI) side of the energy-balance equation. The data are from...

  6. Artificial insemination in marsupials.

    Science.gov (United States)

    Rodger, John C; Paris, Damien B B P; Czarny, Natasha A; Harris, Merrilee S; Molinia, Frank C; Taggart, David A; Allen, Camryn D; Johnston, Stephen D

    2009-01-01

    Assisted breeding technology (ART), including artificial insemination (AI), has the potential to advance the conservation and welfare of marsupials. Many of the challenges facing AI and ART for marsupials are shared with other wild species. However, the marsupial mode of reproduction and development also poses unique challenges and opportunities. For the vast majority of marsupials, there is a dearth of knowledge regarding basic reproductive biology to guide an AI strategy. For threatened or endangered species, only the most basic reproductive information is available in most cases, if at all. Artificial insemination has been used to produce viable young in two marsupial species, the koala and tammar wallaby. However, in these species the timing of ovulation can be predicted with considerably more confidence than in any other marsupial. In a limited number of other marsupials, such precise timing of ovulation has only been achieved using hormonal treatment leading to conception but not live young. A unique marsupial ART strategy which has been shown to have promise is cross-fostering; the transfer of pouch young of a threatened species to the pouches of foster mothers of a common related species as a means to increase productivity. For the foreseeable future, except for a few highly iconic or well studied species, there is unlikely to be sufficient reproductive information on which to base AI. However, if more generic approaches can be developed; such as ICSI (to generate embryos) and female synchronization (to provide oocyte donors or embryo recipients), then the prospects for broader application of AI/ART to marsupials are promising.

  7. Providing Language Instructor with Artificial Intelligence Assistant

    Directory of Open Access Journals (Sweden)

    K. Pietroszek

    2007-12-01

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

  8. Vibration behavior of the artificial barrier system

    International Nuclear Information System (INIS)

    Mikoshiba, Tadashi; Ogawa, Nobuyuki; Nakamura, Izuru

    2000-01-01

    This study aims at production of a mimic specimen of artificial barrier, experimental elucidation of influence of seismic motion due to a vibration experiment on the artificial barrier system, and establishment of an evaluating method on its long-term behavior. The study has been carried out under a cooperative study of the National Research Institute for Earth Science and Disaster Prevention and the Japan Nuclear Cycle Development Institute. In 1998 fiscal year, an artificial barrier specimen initiated by crosscut road was produced, and their random wave and actual seismic wave vibrations were carried out to acquire their fundamental data. As a result of the both vibrations, it was found that in a Case 2 specimen of which buffer material was swelled by poured water, the material was integrated with a mimic over-pack to vibrate under judgement of eigen-frequency, maximum acceleration ratio, and so forth on the test results. And, in a Case 1 specimen, it was thought that the mimic over-pack showed an extreme non-linear performance (soft spring) because of reducing eigen-frequency with increase of its vibration level. (G.K.)

  9. Vibration behavior of the artificial barrier system

    Energy Technology Data Exchange (ETDEWEB)

    Mikoshiba, Tadashi; Ogawa, Nobuyuki; Nakamura, Izuru [National Research Inst. for Earth sceince and Disaster Prevention (Japan)

    2000-02-01

    This study aims at production of a mimic specimen of artificial barrier, experimental elucidation of influence of seismic motion due to a vibration experiment on the artificial barrier system, and establishment of an evaluating method on its long-term behavior. The study has been carried out under a cooperative study of the National Research Institute for Earth Science and Disaster Prevention and the Japan Nuclear Cycle Development Institute. In 1998 fiscal year, an artificial barrier specimen initiated by crosscut road was produced, and their random wave and actual seismic wave vibrations were carried out to acquire their fundamental data. As a result of the both vibrations, it was found that in a Case 2 specimen of which buffer material was swelled by poured water, the material was integrated with a mimic over-pack to vibrate under judgement of eigen-frequency, maximum acceleration ratio, and so forth on the test results. And, in a Case 1 specimen, it was thought that the mimic over-pack showed an extreme non-linear performance (soft spring) because of reducing eigen-frequency with increase of its vibration level. (G.K.)

  10. Beyond AI: Artificial Dreams Conference

    CERN Document Server

    Zackova, Eva; Kelemen, Jozef; Beyond Artificial Intelligence : The Disappearing Human-Machine Divide

    2015-01-01

    This book is an edited collection of chapters based on the papers presented at the conference “Beyond AI: Artificial Dreams” held in Pilsen in November 2012. The aim of the conference was to question deep-rooted ideas of artificial intelligence and cast critical reflection on methods standing at its foundations.  Artificial Dreams epitomize our controversial quest for non-biological intelligence, and therefore the contributors of this book tried to fully exploit such a controversy in their respective chapters, which resulted in an interdisciplinary dialogue between experts from engineering, natural sciences and humanities.   While pursuing the Artificial Dreams, it has become clear that it is still more and more difficult to draw a clear divide between human and machine. And therefore this book tries to portrait such an image of what lies beyond artificial intelligence: we can see the disappearing human-machine divide, a very important phenomenon of nowadays technological society, the phenomenon which i...

  11. 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...

  12. A Requirements Analysis Model Based on QFD

    Institute of Scientific and Technical Information of China (English)

    TANG Zhi-wei; Nelson K.H.Tang

    2004-01-01

    The enterprise resource planning (ERP) system has emerged to offer an integrated IT solution and more and more enterprises are increasing by adopting this system and regarding it as an important innovation. However, there is already evidence of high failure risks in ERP project implementation, one major reason is poor analysis of the requirements for system implementation. In this paper, the importance of requirements analysis for ERP project implementation is highlighted, and a requirements analysis model by applying quality function deployment (QFD) is presented, which will support to conduct requirements analysis for ERP project.

  13. An introduction to artificial intelligence and its potential use in space systems.

    OpenAIRE

    McDonald, Gary Wayne

    1986-01-01

    Approved for public release; distribution is unlimited This thesis provides an introduction to Artificial Intelligence and Space Systems, with comments regarding their integration. The survey of Artificial Intelligence (AI) is based upon a review of its history, its philosophical development, and subcategories of its current technologies. These subcategories are Expert Systems (ES), Natural Language Processing (NLP), Computer Vision and Pattern Recognition, and Robotic...

  14. The development of artificial organs and prostheses worldwide and in the Ottoman Empire.

    Science.gov (United States)

    Birdane, Leman; Cingi, Cemal; Elçioğlu, Ömür; Muluk, Nuray Bayar

    2016-08-01

    An artificial organ or prosthesis is a man-made device that is implanted or integrated into a human to replace a natural organ. There were many historical steps in the development of artificial organs and prostheses. New surgical techniques, the development of prosthetic materials and the creative ideas of engineers led to progress in this field. © The European Society of Cardiology 2014.

  15. Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production

    Science.gov (United States)

    2017-06-30

    collect light energy and separate charge for developing new types of nanobiodevices to construct ”artificial leaf” from solar to fuel. or Concept of...AFRL-AFOSR-JP-TR-2017-0054 Artificial Leaf Based on Artificial Photosynthesis for Solar Fuel Production Mamoru Nango NAGOYA INSTITUTE OF TECHNOLOGY...display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      30-06-2017 2

  16. On the feasibility of detecting flaws in artificial heart valves

    NARCIS (Netherlands)

    Lepelaars, E.S.A.M.; Ooijen, van W.D.R.; Tijhuis, A.G.

    2000-01-01

    Investigates the feasibility of detecting defects in certain artificial heart valves by determining the electromagnetic behavior of some simple models with the aid of thin-wire integral equations. The idea is to use the stationary current that occurs at late times after the excitation of a closed

  17. Impacts of Artificial Reefs on Surrounding Ecosystems

    Science.gov (United States)

    Manoukian, Sarine

    Artificial reefs are becoming a popular biological and management component in shallow water environments characterized by soft seabed, representing both important marine habitats and tools to manage coastal fisheries and resources. An artificial reef in the marine environment acts as an open system with exchange of material and energy, altering the physical and biological characteristics of the surrounding area. Reef stability will depend on the balance of scour, settlement, and burial resulting from ocean conditions over time. Because of the unstable nature of sediments, they require a detailed and systematic investigation. Acoustic systems like high-frequency multibeam sonar are efficient tools in monitoring the environmental evolution around artificial reefs, whereas water turbidity can limit visual dive and ROV inspections. A high-frequency multibeam echo sounder offers the potential of detecting fine-scale distribution of reef units, providing an unprecedented level of resolution, coverage, and spatial definition. How do artificial reefs change over time in relation to the coastal processes? How accurately does multibeam technology map different typologies of artificial modules of known size and shape? How do artificial reefs affect fish school behavior? What are the limitations of multibeam technology for investigating fish school distribution as well as spatial and temporal changes? This study addresses the above questions and presents results of a new approach for artificial reef seafloor mapping over time, based upon an integrated analysis of multibeam swath bathymetry data and geoscientific information (backscatter data analysis, SCUBA observations, physical oceanographic data, and previous findings on the geology and sedimentation processes, integrated with unpublished data) from Senigallia artificial reef, northwestern Adriatic Sea (Italy) and St. Petersburg Beach Reef, west-central Florida continental shelf. A new approach for observation of fish

  18. natural or artificial diets

    Directory of Open Access Journals (Sweden)

    A. O. Meyer-Willerer

    2005-01-01

    Full Text Available Se probaron alimentos artificiales y naturales con larva de camarón (Litopenaeus vannamei cultivados en diferentes recipientes. Estos fueron ocho frascos cónicos con 15L, ocho acuarios con 50L y como grupo control, seis tanques de fibra de vidrio con 1500L; todos con agua marina fresca y filtrada. La densidad inicial en todos los recipientes fue de 70 nauplios/L. Aquellos en frascos y acuarios recibieron ya sea dieta natural o artificial. El grupo control fue cultivado con dieta natural en los tanques grandes que utilizan los laboratorios para la producción masiva de postlarvas. El principal producto de excreción de larva de camarón es el ión amonio, que es tóxico cuando está presente en concentraciones elevadas. Se determinó diariamente con el método colorimétrico del indofenol. Los resultados muestran diferencias en la concentración del ión amonio y en la sobrevivencia de larvas entre las diferentes dietas y también entre los diferentes recipientes. En aquellos con volúmenes pequeños comparados con los grandes, se presentó mayor concentración de amonio (500 a 750µg/L, en aquellos con dietas naturales, debido a que este ión sirve de fertilizante a las algas adicionadas, necesitando efectuar recambios diarios de agua posteriores al noveno día de cultivo para mantener este ión a una concentración subletal. Se obtuvo una baja cosecha de postlarvas (menor a 15% con el alimento artificial larvario, debido a la presencia de protozoarios, alimentándose con el producto comercial precipitado en el fondo de los frascos o acuarios. Los acuarios con larvas alimentadas con dieta natural también mostraron concentraciones subletales de amonio al noveno día; sin embargo, la sobrevivencia fue cuatro veces mayor que con dietas artificiales. Los tanques control con dietas naturales presentaron tasas de sobrevivencia (70 ± 5% similares a la reportada por otros laboratorios.

  19. Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

    Science.gov (United States)

    Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

    2017-12-01

    To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

  20. Future applications of artificial intelligence to Mission Control Centers

    Science.gov (United States)

    Friedland, Peter

    1991-01-01

    Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

  1. Model-Based Systems Engineering in Concurrent Engineering Centers

    Science.gov (United States)

    Iwata, Curtis; Infeld, Samantha; Bracken, Jennifer Medlin; McGuire, Melissa; McQuirk, Christina; Kisdi, Aron; Murphy, Jonathan; Cole, Bjorn; Zarifian, Pezhman

    2015-01-01

    Concurrent Engineering Centers (CECs) are specialized facilities with a goal of generating and maturing engineering designs by enabling rapid design iterations. This is accomplished by co-locating a team of experts (either physically or virtually) in a room with a narrow design goal and a limited timeline of a week or less. The systems engineer uses a model of the system to capture the relevant interfaces and manage the overall architecture. A single model that integrates other design information and modeling allows the entire team to visualize the concurrent activity and identify conflicts more efficiently, potentially resulting in a systems model that will continue to be used throughout the project lifecycle. Performing systems engineering using such a system model is the definition of model-based systems engineering (MBSE); therefore, CECs evolving their approach to incorporate advances in MBSE are more successful in reducing time and cost needed to meet study goals. This paper surveys space mission CECs that are in the middle of this evolution, and the authors share their experiences in order to promote discussion within the community.

  2. Model-based accelerator controls: What, why and how

    International Nuclear Information System (INIS)

    Sidhu, S.S.

    1987-01-01

    Model-based control is defined as a gamut of techniques whose aim is to improve the reliability of an accelerator and enhance the capabilities of the operator, and therefore of the whole control system. The aim of model-based control is seen as gradually moving the function of model-reference from the operator to the computer. The role of the operator in accelerator control and the need for and application of model-based control are briefly summarized

  3. Model-based setup assistant for progressive tools

    Science.gov (United States)

    Springer, Robert; Gräler, Manuel; Homberg, Werner; Henke, Christian; Trächtler, Ansgar

    2018-05-01

    In the field of production systems, globalization and technological progress lead to increasing requirements regarding part quality, delivery time and costs. Hence, today's production is challenged much more than a few years ago: it has to be very flexible and produce economically small batch sizes to satisfy consumer's demands and avoid unnecessary stock. Furthermore, a trend towards increasing functional integration continues to lead to an ongoing miniaturization of sheet metal components. In the industry of electric connectivity for example, the miniaturized connectors are manufactured by progressive tools, which are usually used for very large batches. These tools are installed in mechanical presses and then set up by a technician, who has to manually adjust a wide range of punch-bending operations. Disturbances like material thickness, temperatures, lubrication or tool wear complicate the setup procedure. In prospect of the increasing demand of production flexibility, this time-consuming process has to be handled more and more often. In this paper, a new approach for a model-based setup assistant is proposed as a solution, which is exemplarily applied in combination with a progressive tool. First, progressive tools, more specifically, their setup process is described and based on that, the challenges are pointed out. As a result, a systematic process to set up the machines is introduced. Following, the process is investigated with an FE-Analysis regarding the effects of the disturbances. In the next step, design of experiments is used to systematically develop a regression model of the system's behaviour. This model is integrated within an optimization in order to calculate optimal machine parameters and the following necessary adjustment of the progressive tool due to the disturbances. Finally, the assistant is tested in a production environment and the results are discussed.

  4. Wet-Spun Biofiber for Torsional Artificial Muscles.

    Science.gov (United States)

    Mirabedini, Azadeh; Aziz, Shazed; Spinks, Geoffrey M; Foroughi, Javad

    2017-12-01

    The demands for new types of artificial muscles continue to grow and novel approaches are being enabled by the advent of new materials and novel fabrication strategies. Self-powered actuators have attracted significant attention due to their ability to be driven by elements in the ambient environment such as moisture. In this study, we demonstrate the use of twisted and coiled wet-spun hygroscopic chitosan fibers to achieve a novel torsional artificial muscle. The coiled fibers exhibited significant torsional actuation where the free end of the coiled fiber rotated up to 1155 degrees per mm of coil length when hydrated. This value is 96%, 362%, and 2210% higher than twisted graphene fiber, carbon nanotube torsional actuators, and coiled nylon muscles, respectively. A model based on a single helix was used to evaluate the torsional actuation behavior of these coiled chitosan fibers.

  5. A new global geomagnetic model based on archeomagnetic, volcanic and historical records

    Science.gov (United States)

    Arneitz, Patrick; Leonhardt, Roman; Fabian, Karl

    2016-04-01

    The major challenge of geomagnetic field reconstruction lies in the inhomogeneous spatio-temporal distribution of the available data and their highly variable quality. Paleo- and archeomagnetic records provide information about the ancient geomagnetic field beyond the historical period. Typically these data types have larger errors than their historical counterparts, and investigated materials and applied experimental methods potentially bias field readings. Input data for the modelling approach were extracted from available collections of archeomagnetic, volcanic and historical records, which were integrated into a single database along with associated meta-data. The used iterative Bayesian inversion scheme targets the implementation of reliable error treatments, which allows to combine the different data types. The proposed model is scrutinized by carrying out tests with artificial records. Records are synthesized using a known field evolution generated by a geodynamo model showing realistic energy characteristics. Using the artificial field, a synthetic data set is generated that exactly mirrors the existing measured records in all meta-data, but provides data that would have been observed if the artificial field would have been real. After inversion of the synthetic data, the comparison of known artificial Gauss coefficients and modelled ones allows for the verification of the applied modelling strategy as well as for the examination of the potential and limits of the current data compilation.

  6. A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

    Science.gov (United States)

    Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

    2016-06-01

    To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

  7. Bioengineering of Artificial Lymphoid Organs.

    Science.gov (United States)

    Nosenko, M A; Drutskaya, M S; Moisenovich, M M; Nedospasov, S A

    2016-01-01

    This review addresses the issue of bioengineering of artificial lymphoid organs.Progress in this field may help to better understand the nature of the structure-function relations that exist in immune organs. Artifical lymphoid organs may also be advantageous in the therapy or correction of immunodefficiencies, autoimmune diseases, and cancer. The structural organization, development, and function of lymphoid tissue are analyzed with a focus on the role of intercellular contacts and on the cytokine signaling pathways regulating these processes. We describe various polymeric materials, as scaffolds, for artificial tissue engineering. Finally, published studies in which artificial lymphoid organs were generated are reviewed and possible future directions in the field are discussed.

  8. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  9. Artificial radioelements; Radioelements artificiels

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1952-07-01

    This catalogs retails the list of the artificial radioelements obtained at the Zoe reactor. A certain number of methods of concentration and separation has been finalized. The targets are submitted to irradiation in a thermal neutron flux in order to get by neutron reaction the wanted radioelements. In the case of the reaction (n,p), the radioactive element separated chemically in order to produce some radioelements 'without trainer'. For the radioelements obtained from the reaction (n, {gamma}) one uses the effect of Szilard and Chalmers to separate the active and inactive atoms in order to increase the specific activity of the radioelement of interest. (M.B.) [French] Ce catalogue detaille la liste des radioelements artificiels obtenus a la Pile ZOE. un certain nombre de methodes de concentration et de separation ont ete mises au point. Les cibles sont soumis a irradiation dans un flux de neutron thermique en vue d'obtenir par reaction neutronique les radioelements desires. Dans le cas de la reaction (n,p), l'element radioactif est separe chimiquement afin de produire des radioelements ''sans entraineur''. Pour les radioelements issus de la reaction (n, {gamma}) on utilise l'Effet de Szilard et Chalmers pour separer les atomes actifs et inactifs afin d'augmenter l'activite specifique du radioelement d'interet. (M.B.)

  10. BioArtificial polymers

    Science.gov (United States)

    Szałata, Kamila; Gumi, Tania

    2017-07-01

    Nowadays, the polymer science has impact in practically all life areas. Countless benefits coming from the usage of materials with high mechanical and chemical resistance, variety of functionalities and potentiality of modification drive to the development of new application fields. Novel approaches of combining these synthetic substances with biomolecules lead to obtain multifunctional hybrid conjugates which merge the bioactivity of natural component with outstanding properties of artificial polymer. Over the decades, an immense progress in bioartificial composites domain allowed to reach a high level of knowledge in terms of natural-like systems engineering, leading to diverse strategies of biomolecule immobilization. Together with different available options, including covalent and noncovalent attachment, come various challenges, related mainly with maintaining the biological activity of fixed molecules. Even though the amount of applications that achieve commercial status is still not substantial, and is expanding continuously in the disciplines like "smart materials," biosensors, delivery systems, nanoreactors and many others. A huge number of remarkable developments reported in the literature present a potential of bioartificial conjugates as a fabrics with highly controllable structure and multiple functionalities, serving as a powerful nanotechnological tool. This novel approach brings closer biologists, chemists and engineers, who sharing their effort and complementing the knowledge can revolutionize the field of bioartificial polymer science.

  11. Artificial intelligence in medicine.

    Science.gov (United States)

    Hamet, Pavel; Tremblay, Johanne

    2017-04-01

    Artificial Intelligence (AI) is a general term that implies the use of a computer to model intelligent behavior with minimal human intervention. AI is generally accepted as having started with the invention of robots. The term derives from the Czech word robota, meaning biosynthetic machines used as forced labor. In this field, Leonardo Da Vinci's lasting heritage is today's burgeoning use of robotic-assisted surgery, named after him, for complex urologic and gynecologic procedures. Da Vinci's sketchbooks of robots helped set the stage for this innovation. AI, described as the science and engineering of making intelligent machines, was officially born in 1956. The term is applicable to a broad range of items in medicine such as robotics, medical diagnosis, medical statistics, and human biology-up to and including today's "omics". AI in medicine, which is the focus of this review, has two main branches: virtual and physical. The virtual branch includes informatics approaches from deep learning information management to control of health management systems, including electronic health records, and active guidance of physicians in their treatment decisions. The physical branch is best represented by robots used to assist the elderly patient or the attending surgeon. Also embodied in this branch are targeted nanorobots, a unique new drug delivery system. The societal and ethical complexities of these applications require further reflection, proof of their medical utility, economic value, and development of interdisciplinary strategies for their wider application. Copyright © 2017. Published by Elsevier Inc.

  12. Advances in Artificial Neural Networks – Methodological Development and Application

    Directory of Open Access Journals (Sweden)

    Yanbo Huang

    2009-08-01

    Full Text Available Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a backpropagation training algorithm, have gained recognition in research and applications in various scientific and engineering areas. In order to accelerate the training process and overcome data over-fitting, research has been conducted to improve the backpropagation algorithm. Further, artificial neural networks have been integrated with other advanced methods such as fuzzy logic and wavelet analysis, to enhance the ability of data interpretation and modeling and to avoid subjectivity in the operation of the training algorithm. In recent years, support vector machines have emerged as a set of high-performance supervised generalized linear classifiers in parallel with artificial neural networks. A review on development history of artificial neural networks is presented and the standard architectures and algorithms of artificial neural networks are described. Furthermore, advanced artificial neural networks will be introduced with support vector machines, and limitations of ANNs will be identified. The future of artificial neural network development in tandem with support vector machines will be discussed in conjunction with further applications to food science and engineering, soil and water relationship for crop management, and decision support for precision agriculture. Along with the network structures and training algorithms, the applications of artificial neural networks will be reviewed as well, especially in the fields of agricultural and biological

  13. Artificial Intelligence for the Artificial Kidney: Pointers to the Future of a Personalized Hemodialysis Therapy.

    Science.gov (United States)

    Hueso, Miguel; Vellido, Alfredo; Montero, Nuria; Barbieri, Carlo; Ramos, Rosa; Angoso, Manuel; Cruzado, Josep Maria; Jonsson, Anders

    2018-02-01

    Current dialysis devices are not able to react when unexpected changes occur during dialysis treatment or to learn about experience for therapy personalization. Furthermore, great efforts are dedicated to develop miniaturized artificial kidneys to achieve a continuous and personalized dialysis therapy, in order to improve the patient's quality of life. These innovative dialysis devices will require a real-time monitoring of equipment alarms, dialysis parameters, and patient-related data to ensure patient safety and to allow instantaneous changes of the dialysis prescription for the assessment of their adequacy. The analysis and evaluation of the resulting large-scale data sets enters the realm of "big data" and will require real-time predictive models. These may come from the fields of machine learning and computational intelligence, both included in artificial intelligence, a branch of engineering involved with the creation of devices that simulate intelligent behavior. The incorporation of artificial intelligence should provide a fully new approach to data analysis, enabling future advances in personalized dialysis therapies. With the purpose to learn about the present and potential future impact on medicine from experts in artificial intelligence and machine learning, a scientific meeting was organized in the Hospital Universitari Bellvitge (L'Hospitalet, Barcelona). As an outcome of that meeting, the aim of this review is to investigate artificial intel ligence experiences on dialysis, with a focus on potential barriers, challenges, and prospects for future applications of these technologies. Artificial intelligence research on dialysis is still in an early stage, and the main challenge relies on interpretability and/or comprehensibility of data models when applied to decision making. Artificial neural networks and medical decision support systems have been used to make predictions about anemia, total body water, or intradialysis hypotension and are promising

  14. Model-based cartilage thickness measurement in the submillimeter range

    International Nuclear Information System (INIS)

    Streekstra, G. J.; Strackee, S. D.; Maas, M.; Wee, R. ter; Venema, H. W.

    2007-01-01

    Current methods of image-based thickness measurement in thin sheet structures utilize second derivative zero crossings to locate the layer boundaries. It is generally acknowledged that the nonzero width of the point spread function (PSF) limits the accuracy of this measurement procedure. We propose a model-based method that strongly reduces PSF-induced bias by incorporating the PSF into the thickness estimation method. We estimated the bias in thickness measurements in simulated thin sheet images as obtained from second derivative zero crossings. To gain insight into the range of sheet thickness where our method is expected to yield improved results, sheet thickness was varied between 0.15 and 1.2 mm with an assumed PSF as present in the high-resolution modes of current computed tomography (CT) scanners [full width at half maximum (FWHM) 0.5-0.8 mm]. Our model-based method was evaluated in practice by measuring layer thickness from CT images of a phantom mimicking two parallel cartilage layers in an arthrography procedure. CT arthrography images of cadaver wrists were also evaluated, and thickness estimates were compared to those obtained from high-resolution anatomical sections that served as a reference. The thickness estimates from the simulated images reveal that the method based on second derivative zero crossings shows considerable bias for layers in the submillimeter range. This bias is negligible for sheet thickness larger than 1 mm, where the size of the sheet is more than twice the FWHM of the PSF but can be as large as 0.2 mm for a 0.5 mm sheet. The results of the phantom experiments show that the bias is effectively reduced by our method. The deviations from the true thickness, due to random fluctuations induced by quantum noise in the CT images, are of the order of 3% for a standard wrist imaging protocol. In the wrist the submillimeter thickness estimates from the CT arthrography images correspond within 10% to those estimated from the anatomical

  15. Artificial UV sources in perspective

    International Nuclear Information System (INIS)

    Coppell, R.

    1993-01-01

    With rare exceptions, the sun is by far the most important source of exposure to ultraviolet radiation. This is the conclusion of a brief examination into use of artificial sources in New Zealand. (author). 1 tab

  16. Parallel artificial liquid membrane extraction

    DEFF Research Database (Denmark)

    Gjelstad, Astrid; Rasmussen, Knut Einar; Parmer, Marthe Petrine

    2013-01-01

    This paper reports development of a new approach towards analytical liquid-liquid-liquid membrane extraction termed parallel artificial liquid membrane extraction. A donor plate and acceptor plate create a sandwich, in which each sample (human plasma) and acceptor solution is separated by an arti......This paper reports development of a new approach towards analytical liquid-liquid-liquid membrane extraction termed parallel artificial liquid membrane extraction. A donor plate and acceptor plate create a sandwich, in which each sample (human plasma) and acceptor solution is separated...... by an artificial liquid membrane. Parallel artificial liquid membrane extraction is a modification of hollow-fiber liquid-phase microextraction, where the hollow fibers are replaced by flat membranes in a 96-well plate format....

  17. Building Explainable Artificial Intelligence Systems

    National Research Council Canada - National Science Library

    Core, Mark G; Lane, H. Chad; van Lent, Michael; Gomboc, Dave; Solomon, Steve; Rosenberg, Milton

    2006-01-01

    As artificial intelligence (AI) systems and behavior models in military simulations become increasingly complex, it has been difficult for users to understand the activities of computer-controlled entities...

  18. 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.

  19. Artificial intelligence: Deep neural reasoning

    Science.gov (United States)

    Jaeger, Herbert

    2016-10-01

    The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471

  20. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

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

  1. Artificial Seeds and their Applications

    Indian Academy of Sciences (India)

    currently working on ... heterozygosity of seed, minute seed size, presence of reduced ... Advantages of Artificial or Synthetic Seeds over Somatic Embryos for Propagation .... hour gives optimum bead hardness and rigidity for the produc-.

  2. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    OpenAIRE

    Jun-He Yang; Ching-Hsue Cheng; Chia-Pan Chan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting m...

  3. Stochastic Interest Model Based on Compound Poisson Process and Applications in Actuarial Science

    OpenAIRE

    Li, Shilong; Yin, Chuancun; Zhao, Xia; Dai, Hongshuai

    2017-01-01

    Considering stochastic behavior of interest rates in financial market, we construct a new class of interest models based on compound Poisson process. Different from the references, this paper describes the randomness of interest rates by modeling the force of interest with Poisson random jumps directly. To solve the problem in calculation of accumulated interest force function, one important integral technique is employed. And a conception called the critical value is introduced to investigat...

  4. Model based design of electronic throttle control

    Science.gov (United States)

    Cherian, Fenin; Ranjan, Ashish; Bhowmick, Pathikrit; Rammohan, A.

    2017-11-01

    With the advent of torque based Engine Management Systems, the precise control and robust performance of the throttle body becomes a key factor in the overall performance of the vehicle. Electronic Throttle Control provides benefits such as improved air-fuel ratio for improving the vehicle performance and lower exhausts emissions to meet the stringent emission norms. Modern vehicles facilitate various features such as Cruise Control, Traction Control, Electronic Stability Program and Pre-crash systems. These systems require control over engine power without driver intervention, which is not possible with conventional mechanical throttle system. Thus these systems are integrated to function with the electronic throttle control. However, due to inherent non-linearities in the throttle body, the control becomes a difficult task. In order to eliminate the influence of this hysteresis at the initial operation of the butterfly valve, a control to compensate the shortage must be added to the duty required for starting throttle operation when the initial operation is detected. Therefore, a lot of work is being done in this field to incorporate the various nonlinearities to achieve robust control. In our present work, the ETB was tested to verify the working of the system. Calibration of the TPS sensors was carried out in order to acquire accurate throttle opening angle. The response of the calibrated system was then plotted against a step input signal. A linear model of the ETB was prepared using Simulink and its response was compared with the experimental data to find out the initial deviation of the model from the actual system. To reduce this deviation, non-linearities from existing literature were introduced to the system and a response analysis was performed to check the deviation from the actual system. Based on this investigation, an introduction of a new nonlinearity parameter can be used in future to reduce the deviation further making the control of the ETB more

  5. ASAP- ARTIFICIAL SATELLITE ANALYSIS PROGRAM

    Science.gov (United States)

    Kwok, J.

    1994-01-01

    The Artificial Satellite Analysis Program (ASAP) is a general orbit prediction program which incorporates sufficient orbit modeling accuracy for mission design, maneuver analysis, and mission planning. ASAP is suitable for studying planetary orbit missions with spacecraft trajectories of reconnaissance (flyby) and exploratory (mapping) nature. Sample data is included for a geosynchronous station drift cycle study, a Venus radar mapping strategy, a frozen orbit about Mars, and a repeat ground trace orbit. ASAP uses Cowell's method in the numerical integration of the equations of motion. The orbital mechanics calculation contains perturbations due to non-sphericity (up to a 40 X 40 field) of the planet, lunar and solar effects, and drag and solar radiation pressure. An 8th order Runge-Kutta integration scheme with variable step size control is used for efficient propagation. The input includes the classical osculating elements, orbital elements of the sun relative to the planet, reference time and dates, drag coefficient, gravitational constants, and planet radius, rotation rate, etc. The printed output contains Cartesian coordinates, velocity, equinoctial elements, and classical elements for each time step or event step. At each step, selected output is added to a plot file. The ASAP package includes a program for sorting this plot file. LOTUS 1-2-3 is used in the supplied examples to graph the results, but any graphics software package could be used to process the plot file. ASAP is not written to be mission-specific. Instead, it is intended to be used for most planetary orbiting missions. As a consequence, the user has to have some basic understanding of orbital mechanics to provide the correct input and interpret the subsequent output. ASAP is written in FORTRAN 77 for batch execution and has been implemented on an IBM PC compatible computer operating under MS-DOS. The ASAP package requires a math coprocessor and a minimum of 256K RAM. This program was last

  6. 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...

  7. The handbook of artificial intelligence

    CERN Document Server

    Barr, Avron

    1982-01-01

    The Handbook of Artificial Intelligence, Volume II focuses on the improvements in artificial intelligence (AI) and its increasing applications, including programming languages, intelligent CAI systems, and the employment of AI in medicine, science, and education. The book first elaborates on programming languages for AI research and applications-oriented AI research. Discussions cover scientific applications, teiresias, applications in chemistry, dependencies and assumptions, AI programming-language features, and LISP. The manuscript then examines applications-oriented AI research in medicine

  8. Artificial limb representation in amputees

    OpenAIRE

    van den Heiligenberg, FMZ; Orlov, T; Macdonald, SN; Duff, EP; Henderson Slater, JDE; Beckmann, CF; Johansen-Berg, H; Culham, JC; Makin, TR

    2018-01-01

    The human brain contains multiple hand-selective areas, in both the sensorimotor and visual systems. Could our brain repurpose neural resources, originally developed for supporting hand function, to represent and control artificial limbs? We studied individuals with congenital or acquired hand-loss (hereafter one-handers) using functional MRI. We show that the more one-handers use an artificial limb (prosthesis) in their everyday life, the stronger visual hand-selective areas in the lateral o...

  9. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  10. What are artificial neural networks?

    DEFF Research Database (Denmark)

    Krogh, Anders

    2008-01-01

    Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...

  11. Artificial weathering of granite

    Directory of Open Access Journals (Sweden)

    Silva Hermo, B.

    2008-06-01

    Full Text Available This article summarizes a series of artificial weathering tests run on granite designed to: simulate the action of weathering agents on buildings and identify the underlying mechanisms, determine the salt resistance of different types of rock; evaluate consolidation and water-repellent treatment durability; and confirm hypotheses about the origin of salts such as gypsum that are often found in granite buildings. Salt crystallization tests were also conducted, using sodium chloride, sodium sulphate, calcium sulphate and seawater solutions. One of these tests was conducted in a chamber specifically designed to simulate salt spray weathering and another in an SO2 chamber to ascertain whether granite is subject to sulphation. The test results are analyzed and discussed, along with the shortcomings of each type of trial as a method for simulating the decay observed in monuments. The effect of factors such as wet-dry conditions, type of saline solution and the position of the planes of weakness on the type of decay is also addressed.En este trabajo se hace una síntesis de varios ensayos de alteración artificial realizados con rocas graníticas. Estos ensayos tenían distintos objetivos: reproducir las formas de alteración encontradas en los edificios para llegar a conocer los mecanismos que las generan, determinar la resistencia de las diferentes rocas a la acción de las sales, evaluar la durabilidad de tratamientos de consolidación e hidrofugación y constatar hipótesis acerca del origen de algunas sales, como el yeso, que aparecen frecuentemente en edificios graníticos. En los ensayos de cristalización de sales se utilizaron disoluciones de cloruro de sodio, sulfato de sodio, sulfato de calcio y agua de mar. Uno de estos ensayos se llevó a cabo en una cámara especialmente diseñada para reproducir la alteración por aerosol marino y otro se realizó en una cámara de SO2, con el objeto de comprobar si en rocas graníticas se puede producir

  12. A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents

    DEFF Research Database (Denmark)

    Goldschmidt, Dennis; Manoonpong, Poramate; Dasgupta, Sakyasingha

    2017-01-01

    in artificial agents. The model consists of a path integration mechanism, reward-modulated global learning, random search, and action selection. The path integration mechanism integrates compass and odometric cues to compute a vectorial representation of the agent's current location as neural activity patterns...

  13. Enabling Accessibility Through Model-Based User Interface Development.

    Science.gov (United States)

    Ziegler, Daniel; Peissner, Matthias

    2017-01-01

    Adaptive user interfaces (AUIs) can increase the accessibility of interactive systems. They provide personalized display and interaction modes to fit individual user needs. Most AUI approaches rely on model-based development, which is considered relatively demanding. This paper explores strategies to make model-based development more attractive for mainstream developers.

  14. Model-Based Software Testing for Object-Oriented Software

    Science.gov (United States)

    Biju, Soly Mathew

    2008-01-01

    Model-based testing is one of the best solutions for testing object-oriented software. It has a better test coverage than other testing styles. Model-based testing takes into consideration behavioural aspects of a class, which are usually unchecked in other testing methods. An increase in the complexity of software has forced the software industry…

  15. Towards automatic model based controller design for reconfigurable plants

    DEFF Research Database (Denmark)

    Michelsen, Axel Gottlieb; Stoustrup, Jakob; Izadi-Zamanabadi, Roozbeh

    2008-01-01

    This paper introduces model-based Plug and Play Process Control, a novel concept for process control, which allows a model-based control system to be reconfigured when a sensor or an actuator is plugged into a controlled process. The work reported in this paper focuses on composing a monolithic m...

  16. Model based design introduction: modeling game controllers to microprocessor architectures

    Science.gov (United States)

    Jungwirth, Patrick; Badawy, Abdel-Hameed

    2017-04-01

    We present an introduction to model based design. Model based design is a visual representation, generally a block diagram, to model and incrementally develop a complex system. Model based design is a commonly used design methodology for digital signal processing, control systems, and embedded systems. Model based design's philosophy is: to solve a problem - a step at a time. The approach can be compared to a series of steps to converge to a solution. A block diagram simulation tool allows a design to be simulated with real world measurement data. For example, if an analog control system is being upgraded to a digital control system, the analog sensor input signals can be recorded. The digital control algorithm can be simulated with the real world sensor data. The output from the simulated digital control system can then be compared to the old analog based control system. Model based design can compared to Agile software develop. The Agile software development goal is to develop working software in incremental steps. Progress is measured in completed and tested code units. Progress is measured in model based design by completed and tested blocks. We present a concept for a video game controller and then use model based design to iterate the design towards a working system. We will also describe a model based design effort to develop an OS Friendly Microprocessor Architecture based on the RISC-V.

  17. Learning of Chemical Equilibrium through Modelling-Based Teaching

    Science.gov (United States)

    Maia, Poliana Flavia; Justi, Rosaria

    2009-01-01

    This paper presents and discusses students' learning process of chemical equilibrium from a modelling-based approach developed from the use of the "Model of Modelling" diagram. The investigation was conducted in a regular classroom (students 14-15 years old) and aimed at discussing how modelling-based teaching can contribute to students…

  18. Mechanics and model-based control of advanced engineering systems

    CERN Document Server

    Irschik, Hans; Krommer, Michael

    2014-01-01

    Mechanics and Model-Based Control of Advanced Engineering Systems collects 32 contributions presented at the International Workshop on Advanced Dynamics and Model Based Control of Structures and Machines, which took place in St. Petersburg, Russia in July 2012. The workshop continued a series of international workshops, which started with a Japan-Austria Joint Workshop on Mechanics and Model Based Control of Smart Materials and Structures and a Russia-Austria Joint Workshop on Advanced Dynamics and Model Based Control of Structures and Machines. In the present volume, 10 full-length papers based on presentations from Russia, 9 from Austria, 8 from Japan, 3 from Italy, one from Germany and one from Taiwan are included, which represent the state of the art in the field of mechanics and model based control, with particular emphasis on the application of advanced structures and machines.

  19. Maximizing performance of fuel cell using artificial neural network approach for smart grid applications

    International Nuclear Information System (INIS)

    Bicer, Y.; Dincer, I.; Aydin, M.

    2016-01-01

    This paper presents an artificial neural network (ANN) approach of a smart grid integrated proton exchange membrane (PEM) fuel cell and proposes a neural network model of a 6 kW PEM fuel cell. The data required to train the neural network model are generated by a model of 6 kW PEM fuel cell. After the model is trained and validated, it is used to analyze the dynamic behavior of the PEM fuel cell. The study results demonstrate that the model based on neural network approach is appropriate for predicting the outlet parameters. Various types of training methods, sample numbers and sample distribution methods are utilized to compare the results. The fuel cell stack efficiency considerably varies between 20% and 60%, according to input variables and models. The rapid changes in the input variables can be recovered within a short time period, such as 10 s. The obtained response graphs point out the load tracking features of ANN model and the projected changes in the input variables are controlled quickly in the study. - Highlights: • An ANN approach of a proton exchange membrane (PEM) fuel cell is proposed. • Dynamic behavior of the PEM fuel cell is analyzed. • The effects of various variables on model accuracy are investigated. • Response curves indicate the load following characteristics of the model.

  20. Grasping versus knitting: A geometric perspective. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by M. Santello et al.

    Science.gov (United States)

    Laumond, Jean-Paul

    2016-07-01

    Grasping an object is a matter of first moving a prehensile organ at some position in the world, and then managing the contact relationship between the prehensile organ and the object. Once the contact relationship has been established and made stable, the object is part of the body and it can move in the world. As any action, the action of grasping is ontologically anchored in the physical space while the correlative movement originates in the space of the body. Robots-as any living system-access the physical space only indirectly through sensors and motors. Sensors and motors constitute the space of the body where homeostasis takes place. Physical space and both sensor space and motor space constitute a triangulation, which is the locus of the action embodiment, i.e. the locus of operations allowing the fundamental inversion between world-centered and body-centered frames. Referring to these three fundamental spaces, geometry appears as the best abstraction to capture the nature of action-driven movements. Indeed, a particular geometry is captured by a particular group of transformations of the points of a space such that every point or every direction in space can be transformed by an element of the group to every other point or direction within the group. Quoting mathematician Poincaré, the issue is not find the truest geometry but the most practical one to account for the complexity of the world [1]. Geometry is then the language fostering the dialog between neurophysiology and engineering about natural and artificial movement science and technology. Evolution has found amazing solutions that allow organisms to rapidly and efficiently manage the relationship between their body and the world [2]. It is then natural that roboticists consider taking inspiration of these natural solutions, while contributing to better understand their origin.

  1. The coming of age of artificial intelligence in medicine.

    Science.gov (United States)

    Patel, Vimla L; Shortliffe, Edward H; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-05-01

    This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems.

  2. Tuberculosis control, and the where and why of artificial intelligence

    Directory of Open Access Journals (Sweden)

    Riddhi Doshi

    2017-06-01

    Full Text Available Countries aiming to reduce their tuberculosis (TB burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  3. The Coming of Age of Artificial Intelligence in Medicine*

    Science.gov (United States)

    Patel, Vimla L.; Shortliffe, Edward H.; Stefanelli, Mario; Szolovits, Peter; Berthold, Michael R.; Bellazzi, Riccardo; Abu-Hanna, Ameen

    2009-01-01

    Summary This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its “adolescence” (Shortliffe EH. The adolescence of AI in medicine: Will the field come of age in the ‘90s? Artificial Intelligence in Medicine 1993; 5:93–106). In this article, the discussants reflect on medical AI research during the subsequent years and attempt to characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems. PMID:18790621

  4. Tuberculosis control, and the where and why of artificial intelligence.

    Science.gov (United States)

    Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

    2017-04-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  5. Tuberculosis control, and the where and why of artificial intelligence

    Science.gov (United States)

    Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

    2017-01-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

  6. Dynamic cardiomyoplasty using artificial muscle.

    Science.gov (United States)

    Suzuki, Yasuyuki; Daitoku, Kazuyuki; Minakawa, Masahito; Fukui, Kozo; Fukuda, Ikuo

    2008-01-01

    Dynamic cardiomyoplasty using latissimus dorsi muscle was previously used to compensate for congestive heart failure. Now, however, this method is not acceptable because the long-term result was not as expected owing to fatigue of the skeletal muscle. BioMetal fiber developed by Toki Corporation is one of the artificial muscles activated by electric current. The behavior of this fiber is similar to that of organic muscle. We made an artificial muscle like the latissimus dorsi using BioMetal fiber and tested whether we could use this new muscle as a cardiac supporting device. Testing one Biometal fiber showed the following performance: practical use maximal generative force was 30 g, exercise variation was 50%, and the standard driving current was 220 mA. We created a 4 x 12-cm tabular artificial muscle using 8 BioMetal fibers as a cardiac support device. We also made a simulation circuit composed of a 6 x 8-cm soft bag with unidirectional valves, reservoir, and connecting tube. The simulation circuit was filled with water and the soft bag was wrapped with the artificial muscle device. After powering the device electrically at 9 V with a current of 220 mA for each fiber, we measured the inside pressure and observed the movement of the artificial device. The artificial muscle contracted in 0.5 s for peak time and squeezed the soft bag. The peak pressure inside the soft bag was measured as 10 mmHg. Although further work will be needed to enhance the speed of deformability and movement simulating contraction, we conclude that artificial muscle may be potentially useful as a cardiac assistance device that can be developed for dynamic cardiomyoplasty.

  7. Adaptive surrogate model based multiobjective optimization for coastal aquifer management

    Science.gov (United States)

    Song, Jian; Yang, Yun; Wu, Jianfeng; Wu, Jichun; Sun, Xiaomin; Lin, Jin

    2018-06-01

    In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is developed for optimal pumping strategies of large-scale coastal groundwater problems. The proposed SMOMA integrates an efficient data-driven surrogate model with an improved non-dominated sorted genetic algorithm-II (NSGAII) that employs a local search operator to accelerate its convergence in optimization. The surrogate model based on Kernel Extreme Learning Machine (KELM) is developed and evaluated as an approximate simulator to generate the patterns of regional groundwater flow and salinity levels in coastal aquifers for reducing huge computational burden. The KELM model is adaptively trained during evolutionary search to satisfy desired fidelity level of surrogate so that it inhibits error accumulation of forecasting and results in correctly converging to true Pareto-optimal front. The proposed methodology is then applied to a large-scale coastal aquifer management in Baldwin County, Alabama. Objectives of minimizing the saltwater mass increase and maximizing the total pumping rate in the coastal aquifers are considered. The optimal solutions achieved by the proposed adaptive surrogate model are compared against those solutions obtained from one-shot surrogate model and original simulation model. The adaptive surrogate model does not only improve the prediction accuracy of Pareto-optimal solutions compared with those by the one-shot surrogate model, but also maintains the equivalent quality of Pareto-optimal solutions compared with those by NSGAII coupled with original simulation model, while retaining the advantage of surrogate models in reducing computational burden up to 94% of time-saving. This study shows that the proposed methodology is a computationally efficient and promising tool for multiobjective optimizations of coastal aquifer managements.

  8. Comparison between two photovoltaic module models based on transistors

    Science.gov (United States)

    Saint-Eve, Frédéric; Sawicki, Jean-Paul; Petit, Pierre; Maufay, Fabrice; Aillerie, Michel

    2018-05-01

    The main objective of this paper is to verify the possibility to reduce to a simple electronic circuit with very few components the behavior simulation of an un-shaded photovoltaic (PV) module. Particularly, two models based on well-tried elementary structures, i.e., the Darlington structure in first model and the voltage regulation with programmable Zener diode in the second are analyzed. Specifications extracted from the behavior of a real I-V characteristic of a panel are considered and the principal electrical variables are deduced. The two models are expected to match with open circuit voltage, maximum power point (MPP) and short circuit current, without forgetting realistic current slopes on the both sides of MPP. The robustness is mentioned when irradiance varies and is considered as an additional fundamental property. For both models, two simulations are done to identify influence of some parameters. In the first model, a parameter allowing to adjust current slope on left side of MPP proves to be also important for the calculation of open circuit voltage. Besides this model does not authorize an entirely adjustment of I-V characteristic and MPP moves significantly away from real value when irradiance increases. On the contrary, the second model seems to have only qualities: open circuit voltage is easy to calculate, current slopes are realistic and there is perhaps a good robustness when irradiance variations are simulated by adjusting short circuit current of PV module. We have shown that these two simplified models are expected to make reliable and easier simulations of complex PV architecture integrating many different devices like PV modules or other renewable energy sources and storage capacities coupled in parallel association.

  9. Model-Based Reasoning in Humans Becomes Automatic with Training.

    Directory of Open Access Journals (Sweden)

    Marcos Economides

    2015-09-01

    Full Text Available Model-based and model-free reinforcement learning (RL have been suggested as algorithmic realizations of goal-directed and habitual action strategies. Model-based RL is more flexible than model-free but requires sophisticated calculations using a learnt model of the world. This has led model-based RL to be identified with slow, deliberative processing, and model-free RL with fast, automatic processing. In support of this distinction, it has recently been shown that model-based reasoning is impaired by placing subjects under cognitive load--a hallmark of non-automaticity. Here, using the same task, we show that cognitive load does not impair model-based reasoning if subjects receive prior training on the task. This finding is replicated across two studies and a variety of analysis methods. Thus, task familiarity permits use of model-based reasoning in parallel with other cognitive demands. The ability to deploy model-based reasoning in an automatic, parallelizable fashion has widespread theoretical implications, particularly for the learning and execution of complex behaviors. It also suggests a range of important failure modes in psychiatric disorders.

  10. Model-Based GN and C Simulation and Flight Software Development for Orion Missions beyond LEO

    Science.gov (United States)

    Odegard, Ryan; Milenkovic, Zoran; Henry, Joel; Buttacoli, Michael

    2014-01-01

    For Orion missions beyond low Earth orbit (LEO), the Guidance, Navigation, and Control (GN&C) system is being developed using a model-based approach for simulation and flight software. Lessons learned from the development of GN&C algorithms and flight software for the Orion Exploration Flight Test One (EFT-1) vehicle have been applied to the development of further capabilities for Orion GN&C beyond EFT-1. Continuing the use of a Model-Based Development (MBD) approach with the Matlab®/Simulink® tool suite, the process for GN&C development and analysis has been largely improved. Furthermore, a model-based simulation environment in Simulink, rather than an external C-based simulation, greatly eases the process for development of flight algorithms. The benefits seen by employing lessons learned from EFT-1 are described, as well as the approach for implementing additional MBD techniques. Also detailed are the key enablers for improvements to the MBD process, including enhanced configuration management techniques for model-based software systems, automated code and artifact generation, and automated testing and integration.

  11. A Fault Diagnosis Model Based on LCD-SVD-ANN-MIV and VPMCD for Rotating Machinery

    Directory of Open Access Journals (Sweden)

    Songrong Luo

    2016-01-01

    Full Text Available The fault diagnosis process is essentially a class discrimination problem. However, traditional class discrimination methods such as SVM and ANN fail to capitalize the interactions among the feature variables. Variable predictive model-based class discrimination (VPMCD can adequately use the interactions. But the feature extraction and selection will greatly affect the accuracy and stability of VPMCD classifier. Aiming at the nonstationary characteristics of vibration signal from rotating machinery with local fault, singular value decomposition (SVD technique based local characteristic-scale decomposition (LCD was developed to extract the feature variables. Subsequently, combining artificial neural net (ANN and mean impact value (MIV, ANN-MIV as a kind of feature selection approach was proposed to select more suitable feature variables as input vector of VPMCD classifier. In the end of this paper, a novel fault diagnosis model based on LCD-SVD-ANN-MIV and VPMCD is proposed and proved by an experimental application for roller bearing fault diagnosis. The results show that the proposed method is effective and noise tolerant. And the comparative results demonstrate that the proposed method is superior to the other methods in diagnosis speed, diagnosis success rate, and diagnosis stability.

  12. Biological Effects Of Artificial Illumination

    Science.gov (United States)

    Corth, Richard

    1980-10-01

    We are increasingly being warned of the possible effects of so called "polluted" light, that is light that differs in spectral content from that of sunlight. We should be concerned, we are told, because all animals and plants have evolved under this natural daylight and therefore any difference between that illuminant and the artificial illuminants that are on the market today, is suspect. The usual presentation of the differences between the sunlight and the artificial illuminants are as shown in Figure 1. Here we are shown the spectral power distribution of sunlight and Cool White fluorescent light. The spectral power distributions of each have been normalized to some convenient wavelength so that each can be seen and easily compared on the same figure. But this presentation is misleading for one does not experience artificial illuminants at the same intensity as one experiences sunlight. Sunlight intensities are ordinarily found to be in the 8000 to 10,000 footcandle range whereas artificial illuminants are rarely experienced at intensity levels greater than 100 footcandles. Therefore a representative difference between the two types of illumination conditions is more accurately represented as in Figure 2. Thus if evolutionary adaptations require that humans and other animals be exposed to sunlight to ensure wellbeing, it is clear that one must be exposed to sunlight intensities. It is not feasible to expect that artificially illuminated environments will be lit to the same intensity as sunlight

  13. Artificial immune system algorithm in VLSI circuit configuration

    Science.gov (United States)

    Mansor, Mohd. Asyraf; Sathasivam, Saratha; Kasihmuddin, Mohd Shareduwan Mohd

    2017-08-01

    In artificial intelligence, the artificial immune system is a robust bio-inspired heuristic method, extensively used in solving many constraint optimization problems, anomaly detection, and pattern recognition. This paper discusses the implementation and performance of artificial immune system (AIS) algorithm integrated with Hopfield neural networks for VLSI circuit configuration based on 3-Satisfiability problems. Specifically, we emphasized on the clonal selection technique in our binary artificial immune system algorithm. We restrict our logic construction to 3-Satisfiability (3-SAT) clauses in order to outfit with the transistor configuration in VLSI circuit. The core impetus of this research is to find an ideal hybrid model to assist in the VLSI circuit configuration. In this paper, we compared the artificial immune system (AIS) algorithm (HNN-3SATAIS) with the brute force algorithm incorporated with Hopfield neural network (HNN-3SATBF). Microsoft Visual C++ 2013 was used as a platform for training, simulating and validating the performances of the proposed network. The results depict that the HNN-3SATAIS outperformed HNN-3SATBF in terms of circuit accuracy and CPU time. Thus, HNN-3SATAIS can be used to detect an early error in the VLSI circuit design.

  14. Artificial locomotion control

    DEFF Research Database (Denmark)

    Azevedo, Christine; Poignet, Philippe; Espiau, Bernard

    2004-01-01

    of postural and walking control; use of evolutive optimization objectives; on-line event handling and environment adaptation and anticipation. This leads to the synthesis of an original control scheme based on non-linear model predictive control: Trajectory Free NMPC. The movement is specified implicitly......This paper concerns the simultaneous synthesis and control of walking gaits for biped robots. The goal is to propose an adaptable and reactive control law for two-legged machines. The problem is addressed with human locomotion as a reference. The starting point of our work is an analysis of human...... walking from descriptive (biomechanics) as well as explicative (neuroscience and physiology) points of view, the objective being to stress the relevant elements for the approach of robot control. The adopted principles are then: no joint trajectory tracking; explicit distinction and integration...

  15. Artificial Intelligence in Surgery: Promises and Perils.

    Science.gov (United States)

    Hashimoto, Daniel A; Rosman, Guy; Rus, Daniela; Meireles, Ozanan R

    2018-07-01

    The aim of this review was to summarize major topics in artificial intelligence (AI), including their applications and limitations in surgery. This paper reviews the key capabilities of AI to help surgeons understand and critically evaluate new AI applications and to contribute to new developments. AI is composed of various subfields that each provide potential solutions to clinical problems. Each of the core subfields of AI reviewed in this piece has also been used in other industries such as the autonomous car, social networks, and deep learning computers. A review of AI papers across computer science, statistics, and medical sources was conducted to identify key concepts and techniques within AI that are driving innovation across industries, including surgery. Limitations and challenges of working with AI were also reviewed. Four main subfields of AI were defined: (1) machine learning, (2) artificial neural networks, (3) natural language processing, and (4) computer vision. Their current and future applications to surgical practice were introduced, including big data analytics and clinical decision support systems. The implications of AI for surgeons and the role of surgeons in advancing the technology to optimize clinical effectiveness were discussed. Surgeons are well positioned to help integrate AI into modern practice. Surgeons should partner with data scientists to capture data across phases of care and to provide clinical context, for AI has the potential to revolutionize the way surgery is taught and practiced with the promise of a future optimized for the highest quality patient care.

  16. Knitting and weaving artificial muscles.

    Science.gov (United States)

    Maziz, Ali; Concas, Alessandro; Khaldi, Alexandre; Stålhand, Jonas; Persson, Nils-Krister; Jager, Edwin W H

    2017-01-01

    A need exists for artificial muscles that are silent, soft, and compliant, with performance characteristics similar to those of skeletal muscle, enabling natural interaction of assistive devices with humans. By combining one of humankind's oldest technologies, textile processing, with electroactive polymers, we demonstrate here the feasibility of wearable, soft artificial muscles made by weaving and knitting, with tunable force and strain. These textile actuators were produced from cellulose yarns assembled into fabrics and coated with conducting polymers using a metal-free deposition. To increase the output force, we assembled yarns in parallel by weaving. The force scaled linearly with the number of yarns in the woven fabric. To amplify the strain, we knitted a stretchable fabric, exhibiting a 53-fold increase in strain. In addition, the textile construction added mechanical stability to the actuators. Textile processing permits scalable and rational production of wearable artificial muscles, and enables novel ways to design assistive devices.

  17. Artificial sensory organs: latest progress.

    Science.gov (United States)

    Nakamura, Tatsuo; Inada, Yuji; Shigeno, Keiji

    2018-03-01

    This study introduces the latest progress on the study of artificial sensory organs, with a special emphasis on the clinical results of artificial nerves and the concept of in situ tissue engineering. Peripheral nerves have a strong potential for regeneration. An artificial nerve uses this potential to recover a damaged peripheral nerve. The polyglycolic acid collagen tube (PGA-C tube) is a bio-absorbable tube stuffed with collagen of multi-chamber structure that consists of thin collagen films. The clinical application of the PGA-C tube began in 2002 in Japan. The number of PGA-C tubes used is now beyond 300, and satisfactory results have been reported on peripheral nerve repairs. This PGA-C tube is also effective for patients suffering from neuropathic pain.

  18. Artificial heart for humanoid robot

    Science.gov (United States)

    Potnuru, Akshay; Wu, Lianjun; Tadesse, Yonas

    2014-03-01

    A soft robotic device inspired by the pumping action of a biological heart is presented in this study. Developing artificial heart to a humanoid robot enables us to make a better biomedical device for ultimate use in humans. As technology continues to become more advanced, the methods in which we implement high performance and biomimetic artificial organs is getting nearer each day. In this paper, we present the design and development of a soft artificial heart that can be used in a humanoid robot and simulate the functions of a human heart using shape memory alloy technology. The robotic heart is designed to pump a blood-like fluid to parts of the robot such as the face to simulate someone blushing or when someone is angry by the use of elastomeric substrates and certain features for the transport of fluids.

  19. Towards a synergy framework across neuroscience and robotics: Lessons learned and open questions. Reply to comments on: "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands"

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jorntell, Henrik; Kappers, Astrid M. L.; Kyriakopoulos, Kostas; Schaeffer, Alin Abu; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    We would like to thank all commentators for their insightful commentaries. Thanks to their diverse and complementary expertise in neuroscience and robotics, the commentators have provided us with the opportunity to further discuss state-of-the-art and gaps in the integration of neuroscience and robotics reviewed in our article. We organized our reply in two sections that capture the main points of all commentaries [1-9]: (1) Advantages and limitations of the synergy approach in neuroscience and robotics, and (2) Learning and role of sensory feedback in biological and robotics synergies.

  20. A Model-based Avionic Prognostic Reasoner (MAPR)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and...

  1. A Model-Based Prognostics Approach Applied to Pneumatic Valves

    Data.gov (United States)

    National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

  2. A Model-based Prognostics Approach Applied to Pneumatic Valves

    Data.gov (United States)

    National Aeronautics and Space Administration — Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain...

  3. Model-based Prognostics with Concurrent Damage Progression Processes

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics approaches rely on physics-based models that describe the behavior of systems and their components. These models must account for the several...

  4. Model-based reasoning technology for the power industry

    International Nuclear Information System (INIS)

    Touchton, R.A.; Subramanyan, N.S.; Naser, J.A.

    1991-01-01

    This paper reports on model-based reasoning which refers to an expert system implementation methodology that uses a model of the system which is being reasoned about. Model-based representation and reasoning techniques offer many advantages and are highly suitable for domains where the individual components, their interconnection, and their behavior is well-known. Technology Applications, Inc. (TAI), under contract to the Electric Power Research Institute (EPRI), investigated the use of model-based reasoning in the power industry including the nuclear power industry. During this project, a model-based monitoring and diagnostic tool, called ProSys, was developed. Also, an alarm prioritization system was developed as a demonstration prototype

  5. Model-based Prognostics with Fixed-lag Particle Filters

    Data.gov (United States)

    National Aeronautics and Space Administration — Model-based prognostics exploits domain knowl- edge of the system, its components, and how they fail by casting the underlying physical phenom- ena in a...

  6. Educational Technology: Integration?

    Science.gov (United States)

    Christensen, Dean L.; Tennyson, Robert D.

    This paper presents a perspective of the current state of technology-assisted instruction integrating computer language, artificial intelligence (AI), and a review of cognitive science applied to instruction. The following topics are briefly discussed: (1) the language of instructional technology, i.e., programming languages, including authoring…

  7. Short-Term Price Forecasting Models Based on Artificial Neural Networks for Intraday Sessions in the Iberian Electricity Market

    Directory of Open Access Journals (Sweden)

    Claudio Monteiro

    2016-09-01

    Full Text Available This paper presents novel intraday session models for price forecasts (ISMPF models for hourly price forecasting in the six intraday sessions of the Iberian electricity market (MIBEL and the analysis of mean absolute percentage errors (MAPEs obtained with suitable combinations of their input variables in order to find the best ISMPF models. Comparisons of errors from different ISMPF models identified the most important variables for forecasting purposes. Similar analyses were applied to determine the best daily session models for price forecasts (DSMPF models for the day-ahead price forecasting in the daily session of the MIBEL, considering as input variables extensive hourly time series records of recent prices, power demands and power generations in the previous day, forecasts of demand, wind power generation and weather for the day-ahead, and chronological variables. ISMPF models include the input variables of DSMPF models as well as the daily session prices and prices of preceding intraday sessions. The best ISMPF models achieved lower MAPEs for most of the intraday sessions compared to the error of the best DSMPF model; furthermore, such DSMPF error was very close to the lowest limit error for the daily session. The best ISMPF models can be useful for MIBEL agents of the electricity intraday market and the electric energy industry.

  8. Fuzzy model-based control of a nuclear reactor

    International Nuclear Information System (INIS)

    Van Den Durpel, L.; Ruan, D.

    1994-01-01

    The fuzzy model-based control of a nuclear power reactor is an emerging research topic world-wide. SCK-CEN is dealing with this research in a preliminary stage, including two aspects, namely fuzzy control and fuzzy modelling. The aim is to combine both methodologies in contrast to conventional model-based PID control techniques, and to state advantages of including fuzzy parameters as safety and operator feedback. This paper summarizes the general scheme of this new research project

  9. System Dynamics as Model-Based Theory Building

    OpenAIRE

    Schwaninger, Markus; Grösser, Stefan N.

    2008-01-01

    This paper introduces model-based theory building as a feature of system dynamics (SD) with large potential. It presents a systemic approach to actualizing that potential, thereby opening up a new perspective on theory building in the social sciences. The question addressed is if and how SD enables the construction of high-quality theories. This contribution is based on field experiment type projects which have been focused on model-based theory building, specifically the construction of a mi...

  10. A model-based approach to estimating forest area

    Science.gov (United States)

    Ronald E. McRoberts

    2006-01-01

    A logistic regression model based on forest inventory plot data and transformations of Landsat Thematic Mapper satellite imagery was used to predict the probability of forest for 15 study areas in Indiana, USA, and 15 in Minnesota, USA. Within each study area, model-based estimates of forest area were obtained for circular areas with radii of 5 km, 10 km, and 15 km and...

  11. Model-based Sensor Data Acquisition and Management

    OpenAIRE

    Aggarwal, Charu C.; Sathe, Saket; Papaioannou, Thanasis G.; Jeung, Ho Young; Aberer, Karl

    2012-01-01

    In recent years, due to the proliferation of sensor networks, there has been a genuine need of researching techniques for sensor data acquisition and management. To this end, a large number of techniques have emerged that advocate model-based sensor data acquisition and management. These techniques use mathematical models for performing various, day-to-day tasks involved in managing sensor data. In this chapter, we survey the state-of-the-art techniques for model-based sensor data acquisition...

  12. Artificial radioactivity in Lough Foyle

    International Nuclear Information System (INIS)

    Cunningham, J.D.; Ryan, T.P.; Lyons, S.; Smith, V.; McGarry, A.; Mitchell, P.I.; Leon Vintro, L.; Larmour, R.A.; Ledgerwood, F.K.

    1996-04-01

    The purpose of this study was to assess the extent to which the marine environment of Lough Foyle, situated on the north coast of Ireland, has been affected by artificial radioactivity released from Sellafield. Although traces of plutonium, americium and radiocaesium from Sellafield are detectable in Lough Foyle, the concentrations in various marine media are significantly lower than those found along the NE coast of Ireland and in the western Irish Sea. The minute quantities of artificial radioactivity found in Lough Foyle are of negligible radiological significance

  13. In Defense of Artificial Replacement.

    Science.gov (United States)

    Shiller, Derek

    2017-06-01

    If it is within our power to provide a significantly better world for future generations at a comparatively small cost to ourselves, we have a strong moral reason to do so. One way of providing a significantly better world may involve replacing our species with something better. It is plausible that in the not-too-distant future, we will be able to create artificially intelligent creatures with whatever physical and psychological traits we choose. Granted this assumption, it is argued that we should engineer our extinction so that our planet's resources can be devoted to making artificial creatures with better lives. © 2017 John Wiley & Sons Ltd.

  14. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  15. 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.

  16. Artificial intelligence in the materials processing laboratory

    Science.gov (United States)

    Workman, Gary L.; Kaukler, William F.

    1990-01-01

    Materials science and engineering provides a vast arena for applications of artificial intelligence. Advanced materials research is an area in which challenging requirements confront the researcher, from the drawing board through production and into service. Advanced techniques results in the development of new materials for specialized applications. Hand-in-hand with these new materials are also requirements for state-of-the-art inspection methods to determine the integrity or fitness for service of structures fabricated from these materials. Two problems of current interest to the Materials Processing Laboratory at UAH are an expert system to assist in eddy current inspection of graphite epoxy components for aerospace and an expert system to assist in the design of superalloys for high temperature applications. Each project requires a different approach to reach the defined goals. Results to date are described for the eddy current analysis, but only the original concepts and approaches considered are given for the expert system to design superalloys.

  17. A development framework for distributed artificial intelligence

    Science.gov (United States)

    Adler, Richard M.; Cottman, Bruce H.

    1989-01-01

    The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

  18. Student use of model-based reasoning when troubleshooting an electronic circuit

    Science.gov (United States)

    Lewandowski, Heather; Stetzer, Mackenzie; van de Bogart, Kevin; Dounas-Frazer, Dimitri

    2016-03-01

    Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

  19. Student use of model-based reasoning when troubleshooting an electric circuit

    Science.gov (United States)

    Dounas-Frazer, Dimitri

    2016-05-01

    Troubleshooting systems is an integral part of experimental physics in both research and educational settings. Accordingly, ability to troubleshoot is an important learning goal for undergraduate physics lab courses. We investigate students' model-based reasoning on a troubleshooting task using data collected in think-aloud interviews during which pairs of students from two institutions attempted to diagnose and repair a malfunctioning circuit. Our analysis scheme was informed by the Experimental Modeling Framework, which describes physicists' use of mathematical and conceptual models when reasoning about experimental systems. We show that system and subsystem models were crucial for the evaluation of repairs to the circuit and played an important role in some troubleshooting strategies. Finally, drawing on data from interviews with electronics instructors from a broad range of institution types, we outline recommendations for model-based approaches to teaching and learning troubleshooting skills.

  20. Top-Down and Bottom-Up Approach for Model-Based Testing of Product Lines

    Directory of Open Access Journals (Sweden)

    Stephan Weißleder

    2013-03-01

    Full Text Available Systems tend to become more and more complex. This has a direct impact on system engineering processes. Two of the most important phases in these processes are requirements engineering and quality assurance. Two significant complexity drivers located in these phases are the growing number of product variants that have to be integrated into the requirements engineering and the ever growing effort for manual test design. There are modeling techniques to deal with both complexity drivers like, e.g., feature modeling and model-based test design. Their combination, however, has been seldom the focus of investigation. In this paper, we present two approaches to combine feature modeling and model-based testing as an efficient quality assurance technique for product lines. We present the corresponding difficulties and approaches to overcome them. All explanations are supported by an example of an online shop product line.

  1. Natural and artificial photoprotection

    International Nuclear Information System (INIS)

    Cripps, D.J.

    1981-01-01

    A solar simulator is described with collimated filtered radiation incorporating an optical integrator to more evenly diffuse the xenon 2.5 KW light source. Populations can be catogorized into skin types I-VI and the minimal erythema dose (MED) in each skin type measured in Joules/cm2 was compared to give a relative suntan photoprotection factor or SPF compared with type I (1.0) so that type II had an SPF of 1.67, type III SPF of 2.5, type IV V had an SPF of nearly 4, whereas the darker Negroid skin (type VI) had an SPF of 9.68, or nearly 10 times that of type I. In addition, various studies were performed to determine the natural protection factor after natural sunlight (3 1/2 mo of summer sun). In 21 subjects the mean SPF was 2.33 when compared to the MED on unexposed skin on the buttocks. Five subjects who had received a mean total dose of 3.49 J/cm2 of UVB within a 4-week period had a mean SPF of 8.01 and 5 subjects who had received a mean total dose of 20 J/cm2 of UVA with PUVA therapy within 2 weeks had a mean SPF of 2.7. These studies were compared with the photoprotection ability of topical chemical protective agents with a range of 4-15

  2. Artificial proprioceptive feedback for myoelectric control.

    Science.gov (United States)

    Pistohl, Tobias; Joshi, Deepak; Ganesh, Gowrishankar; Jackson, Andrew; Nazarpour, Kianoush

    2015-05-01

    The typical control of myoelectric interfaces, whether in laboratory settings or real-life prosthetic applications, largely relies on visual feedback because proprioceptive signals from the controlling muscles are either not available or very noisy. We conducted a set of experiments to test whether artificial proprioceptive feedback, delivered noninvasively to another limb, can improve control of a two-dimensional myoelectrically-controlled computer interface. In these experiments, participants were required to reach a target with a visual cursor that was controlled by electromyogram signals recorded from muscles of the left hand, while they were provided with an additional proprioceptive feedback on their right arm by moving it with a robotic manipulandum. Provision of additional artificial proprioceptive feedback improved the angular accuracy of their movements when compared to using visual feedback alone but did not increase the overall accuracy quantified with the average distance between the cursor and the target. The advantages conferred by proprioception were present only when the proprioceptive feedback had similar orientation to the visual feedback in the task space and not when it was mirrored, demonstrating the importance of congruency in feedback modalities for multi-sensory integration. Our results reveal the ability of the human motor system to learn new inter-limb sensory-motor associations; the motor system can utilize task-related sensory feedback, even when it is available on a limb distinct from the one being actuated. In addition, the proposed task structure provides a flexible test paradigm by which the effectiveness of various sensory feedback and multi-sensory integration for myoelectric prosthesis control can be evaluated.

  3. Multidirectional Artificial Muscles from Nylon.

    Science.gov (United States)

    Mirvakili, Seyed M; Hunter, Ian W

    2017-01-01

    Multidirectional artificial muscles are made from highly oriented nylon filaments. Thanks to the low thermal conductivity of nylon and its anisotropic thermal expansion, bending occurs when a nylon beam is differentially heated. This heat can be generated via a Joule heating mechanism or high power laser pulses. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Artificial Intelligence: A Selected Bibliography.

    Science.gov (United States)

    Smith, Linda C., Comp.

    1984-01-01

    This 19-item annotated bibliography introducing the literature of artificial intelligence (AI) is arranged by type of material--handbook, books (general interest, textbooks, collected readings), journals and newsletters, and conferences and workshops. The availability of technical reports from AI laboratories at universities and private companies…

  5. Artificial epitaxy of indium antimonide

    International Nuclear Information System (INIS)

    Ershov, V.I.; Givargizov, E.I.

    1987-01-01

    The results of the experiments on recrystallization of thin InSb films deposited on oxidized silicon by flash evaporation with ionized beams are given. Artificial microreliefs (topographic and thermal ones) were used for controlling the growth process. An orientation mechanism of the growing film by the microrelief is discussed. The experiments on preparation of regular single-crystal islands are described

  6. Hybrid Applications Of Artificial Intelligence

    Science.gov (United States)

    Borchardt, Gary C.

    1988-01-01

    STAR, Simple Tool for Automated Reasoning, is interactive, interpreted programming language for development and operation of artificial-intelligence application systems. Couples symbolic processing with compiled-language functions and data structures. Written in C language and currently available in UNIX version (NPO-16832), and VMS version (NPO-16965).

  7. Artificial Intelligence: Applications in Education.

    Science.gov (United States)

    Thorkildsen, Ron J.; And Others

    1986-01-01

    Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

  8. Artificial Intelligence and Science Education.

    Science.gov (United States)

    Good, Ron

    1987-01-01

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

  9. Research and applications: Artificial intelligence

    Science.gov (United States)

    Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

    1970-01-01

    The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

  10. Artificial Promoters for Metabolic Optimization

    DEFF Research Database (Denmark)

    Jensen, Peter Ruhdal; Hammer, Karin

    1998-01-01

    In this article, we review some of the expression systems that are available for Metabolic Control Analysis and Metabolic Engineering, and examine their advantages and disadvantages in different contexts. In a recent approach, artificial promoters for modulating gene expression in micro-organisms...

  11. What Is Artificial Intelligence Anyway?

    Science.gov (United States)

    Kurzweil, Raymond

    1985-01-01

    Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

  12. Artificial Intelligence: The Expert Way.

    Science.gov (United States)

    Bitter, Gary G.

    1989-01-01

    Discussion of artificial intelligence (AI) and expert systems focuses on their use in education. Characteristics of good expert systems are explained; computer software programs that contain applications of AI are described, highlighting one used to help educators identify learning-disabled students; and the future of AI is discussed. (LRW)

  13. Electrophotometric observations of artificial satellites

    International Nuclear Information System (INIS)

    Vovchyk, Yeva; Blagodyr, Yaroslav; Kraynyuk, Gennadiy; Bilinsky, Andriy; Lohvynenko, Alexander; Klym, Bogdan; Pochapsky, Yevhen

    2004-01-01

    Problems associated with polarimetric observations of low Earth orbit artificial satellites as important solar system objects are discussed. The instrumentation (the optical and mechanical parts, the control and drive electronics, and the application software) for performing such observations is also described

  14. Artificial life, the new paradigm

    International Nuclear Information System (INIS)

    Martinez Paez, Jose Jesus

    1998-01-01

    A chronological synthesis of the most important facts is presented in the theoretical development and computational simulation that they have taken to the formation of a new paradigm that is known as artificial life; their characteristics and their main investigation lines are analyzed. Finally, a description of its work is made in the National University of Colombia

  15. Artificial intelligence approaches in statistics

    International Nuclear Information System (INIS)

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

    1986-01-01

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

  16. Artificial Intelligence Assists Ultrasonic Inspection

    Science.gov (United States)

    Schaefer, Lloyd A.; Willenberg, James D.

    1992-01-01

    Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

  17. 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)

  18. Clinical Utility and Safety of a Model-Based Patient-Tailored Dose of Vancomycin in Neonates.

    Science.gov (United States)

    Leroux, Stéphanie; Jacqz-Aigrain, Evelyne; Biran, Valérie; Lopez, Emmanuel; Madeleneau, Doriane; Wallon, Camille; Zana-Taïeb, Elodie; Virlouvet, Anne-Laure; Rioualen, Stéphane; Zhao, Wei

    2016-04-01

    Pharmacokinetic modeling has often been applied to evaluate vancomycin pharmacokinetics in neonates. However, clinical application of the model-based personalized vancomycin therapy is still limited. The objective of the present study was to evaluate the clinical utility and safety of a model-based patient-tailored dose of vancomycin in neonates. A model-based vancomycin dosing calculator, developed from a population pharmacokinetic study, has been integrated into the routine clinical care in 3 neonatal intensive care units (Robert Debré, Cochin Port Royal, and Clocheville hospitals) between 2012 and 2014. The target attainment rate, defined as the percentage of patients with a first therapeutic drug monitoring serum vancomycin concentration achieving the target window of 15 to 25 mg/liter, was selected as an endpoint for evaluating the clinical utility. The safety evaluation was focused on nephrotoxicity. The clinical application of the model-based patient-tailored dose of vancomycin has been demonstrated in 190 neonates. The mean (standard deviation) gestational and postnatal ages of the study population were 31.1 (4.9) weeks and 16.7 (21.7) days, respectively. The target attainment rate increased from 41% to 72% without any case of vancomycin-related nephrotoxicity. This proof-of-concept study provides evidence for integrating model-based antimicrobial therapy in neonatal routine care. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  19. Fifth Conference on Artificial Intelligence for Space Applications

    Science.gov (United States)

    Odell, Steve L. (Compiler)

    1990-01-01

    The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

  20. Meaning of cognitive processes for creating artificial intelligence

    OpenAIRE

    Pangrác, Vojtěch

    2011-01-01

    This diploma thesis brings an integral view at cognitive processes connected with artificial intelligence systems, and makes a comparison with the processes observed in nature, including human being. A historical background helps us to look at the whole issue from a certain point of view. The main axis of interest comes after the historical overview and includes the following: environment -- stimulations -- processing -- reflection in the cognitive system -- reaction to stimulation; I balance...

  1. Model-based PEEP optimisation in mechanical ventilation

    Directory of Open Access Journals (Sweden)

    Chiew Yeong Shiong

    2011-12-01

    Full Text Available Abstract Background Acute Respiratory Distress Syndrome (ARDS patients require mechanical ventilation (MV for breathing support. Patient-specific PEEP is encouraged for treating different patients but there is no well established method in optimal PEEP selection. Methods A study of 10 patients diagnosed with ALI/ARDS whom underwent recruitment manoeuvre is carried out. Airway pressure and flow data are used to identify patient-specific constant lung elastance (Elung and time-variant dynamic lung elastance (Edrs at each PEEP level (increments of 5cmH2O, for a single compartment linear lung model using integral-based methods. Optimal PEEP is estimated using Elung versus PEEP, Edrs-Pressure curve and Edrs Area at minimum elastance (maximum compliance and the inflection of the curves (diminishing return. Results are compared to clinically selected PEEP values. The trials and use of the data were approved by the New Zealand South Island Regional Ethics Committee. Results Median absolute percentage fitting error to the data when estimating time-variant Edrs is 0.9% (IQR = 0.5-2.4 and 5.6% [IQR: 1.8-11.3] when estimating constant Elung. Both Elung and Edrs decrease with PEEP to a minimum, before rising, and indicating potential over-inflation. Median Edrs over all patients across all PEEP values was 32.2 cmH2O/l [IQR: 26.1-46.6], reflecting the heterogeneity of ALI/ARDS patients, and their response to PEEP, that complicates standard approaches to PEEP selection. All Edrs-Pressure curves have a clear inflection point before minimum Edrs, making PEEP selection straightforward. Model-based selected PEEP using the proposed metrics were higher than clinically selected values in 7/10 cases. Conclusion Continuous monitoring of the patient-specific Elung and Edrs and minimally invasive PEEP titration provide a unique, patient-specific and physiologically relevant metric to optimize PEEP selection with minimal disruption of MV therapy.

  2. ARTIFICIAL INTELLIGENCE APPLICATIONS IN THE FINANCIAL SECTOR

    OpenAIRE

    Adrian Cozgarea; Gabriel Cozgarea; Andrei Stanciu

    2008-01-01

    The present paper exposes some of artificial intelligence specific technologies regarding financial sector. Through non-deterministic solutions and simple algorithms, artificial intelligence could become a base alternative for solving financial problems which require complex mathematic calculations or complex optimization.

  3. Long term integrity of reactor pressure vessel and primary containment vessel after the severe accidents in Fukushima Daiichi Nuclear Power Station. Leaching property of spent oxide fuel segment and corrosion property of a carbon steel under artificial seawater immersion

    International Nuclear Information System (INIS)

    2014-06-01

    Primary containment vessel (PCV), reactor pressure vessel and pedestal in Fukushima Daiichi Nuclear power station units 1 through 3 have been exposed to severe thermal, chemical and mechanical conditions due to core meltdown events and seawater injections for emergent core cooling. These components will be immersed in diluted seawater with dissolved fission products under irradiation until the end of debris removal. Fresh water injected into the cores contacts with debris to cool, dissolves or erodes their constituents, mixed with retained water, and becomes 'accumulated water' with radioactive nuclides. We have focused the leaching of fission products into the accumulated water under lower temperature (323 K). FUGEN spent oxide fuel segments were immersed to determine the leaching factor of fission product and actinide elements. Since PCV made from carbon steel is one of the most important boundaries to prevent from fission products release, corrosion behavior has been paid attention to evaluate their integrity. Carbon steel specimens were immersion- and electrochemical-tested in diluted seawater with simulants of the accumulated water at 323 K in order to evaluate the effect of fission products in particular cesium and radiation. (author)

  4. Embracing model-based designs for dose-finding trials.

    Science.gov (United States)

    Love, Sharon B; Brown, Sarah; Weir, Christopher J; Harbron, Chris; Yap, Christina; Gaschler-Markefski, Birgit; Matcham, James; Caffrey, Louise; McKevitt, Christopher; Clive, Sally; Craddock, Charlie; Spicer, James; Cornelius, Victoria

    2017-07-25

    Dose-finding trials are essential to drug development as they establish recommended doses for later-phase testing. We aim to motivate wider use of model-based designs for dose finding, such as the continual reassessment method (CRM). We carried out a literature review of dose-finding designs and conducted a survey to identify perceived barriers to their implementation. We describe the benefits of model-based designs (flexibility, superior operating characteristics, extended scope), their current uptake, and existing resources. The most prominent barriers to implementation of a model-based design were lack of suitable training, chief investigators' preference for algorithm-based designs (e.g., 3+3), and limited resources for study design before funding. We use a real-world example to illustrate how these barriers can be overcome. There is overwhelming evidence for the benefits of CRM. Many leading pharmaceutical companies routinely implement model-based designs. Our analysis identified barriers for academic statisticians and clinical academics in mirroring the progress industry has made in trial design. Unified support from funders, regulators, and journal editors could result in more accurate doses for later-phase testing, and increase the efficiency and success of clinical drug development. We give recommendations for increasing the uptake of model-based designs for dose-finding trials in academia.

  5. Introduction to Concepts in Artificial Neural Networks

    Science.gov (United States)

    Niebur, Dagmar

    1995-01-01

    This introduction to artificial neural networks summarizes some basic concepts of computational neuroscience and the resulting models of artificial neurons. The terminology of biological and artificial neurons, biological and machine learning and neural processing is introduced. The concepts of supervised and unsupervised learning are explained with examples from the power system area. Finally, a taxonomy of different types of neurons and different classes of artificial neural networks is presented.

  6. Artificial humidification for the mechanically ventilated patient.

    Science.gov (United States)

    Selvaraj, N

    Caring for patients who are mechanically ventilated poses many challenges for critical care nurses. It is important to humidify the patient's airways artificially to prevent complications such as ventilator-associated pneumonia. There is no gold standard to determine which type of humidification is best for patients who are artificially ventilated. This article provides an overview of commonly used artificial humidification for mechanically ventilated patients and discusses nurses' responsibilities in caring for patients receiving artificial humidification.

  7. [Preparation of nano-nacre artificial bone].

    Science.gov (United States)

    Chen, Jian-ting; Tang, Yong-zhi; Zhang, Jian-gang; Wang, Jian-jun; Xiao, Ying

    2008-12-01

    To assess the improvements in the properties of nano-nacre artificial bone prepared on the basis of nacre/polylactide acid composite artificial bone and its potential for clinical use. The compound of nano-scale nacre powder and poly-D, L-lactide acid (PDLLA) was used to prepare the cylindrical hollow artificial bone, whose properties including raw material powder scale, pore size, porosity and biomechanical characteristics were compared with another artificial bone made of micron-scale nacre powder and PDLLA. Scanning electron microscope showed that the average particle size of the nano-nacre powder was 50.4-/+12.4 nm, and the average pore size of the artificial bone prepared using nano-nacre powder was 215.7-/+77.5 microm, as compared with the particle size of the micron-scale nacre powder of 5.0-/+3.0 microm and the pore size of the resultant artificial bone of 205.1-/+72.0 microm. The porosities of nano-nacre artificial bone and the micron-nacre artificial bone were (65.4-/+2.9)% and (53.4-/+2.2)%, respectively, and the two artificial bones had comparable compressive strength and Young's modulus, but the flexural strength of the nano-nacre artificial bone was lower than that of the micro-nacre artificial bone. The nano-nacre artificial bone allows better biodegradability and possesses appropriate pore size, porosity and biomechanical properties for use as a promising material in bone tissue engineering.

  8. Artificial Intelligence and Its Importance in Education.

    Science.gov (United States)

    Tilmann, Martha J.

    Artificial intelligence, or the study of ideas that enable computers to be intelligent, is discussed in terms of what it is, what it has done, what it can do, and how it may affect the teaching of tomorrow. An extensive overview of artificial intelligence examines its goals and applications and types of artificial intelligence including (1) expert…

  9. Impact of Artificial Intelligence on Economic Theory

    OpenAIRE

    Tshilidzi Marwala

    2015-01-01

    Artificial intelligence has impacted many aspects of human life. This paper studies the impact of artificial intelligence on economic theory. In particular we study the impact of artificial intelligence on the theory of bounded rationality, efficient market hypothesis and prospect theory.

  10. Integrated control algorithms for plant environment in greenhouse

    Science.gov (United States)

    Zhang, Kanyu; Deng, Lujuan; Gong, Youmin; Wang, Shengxue

    2003-09-01

    In this paper a survey of plant environment control in artificial greenhouse was put forward for discussing the future development. Firstly, plant environment control started with the closed loop control of air temperature in greenhouse. With the emergence of higher property computer, the adaptive control algorithm and system identification were integrated into the control system. As adaptation control is more depending on observation of variables by sensors and yet many variables are unobservable or difficult to observe, especially for observation of crop growth status, so model-based control algorithm were developed. In order to evade modeling difficulty, one method is predigesting the models and the other method is utilizing fuzzy logic and neural network technology that realize the models by the black box and gray box theory. Studies on control method of plant environment in greenhouse by means of expert system (ES) and artificial intelligence (AI) have been initiated and developed. Nowadays, the research of greenhouse environment control focus on energy saving, optimal economic profit, enviornment protection and continualy develop.

  11. Model-Based Reconstructive Elasticity Imaging Using Ultrasound

    Directory of Open Access Journals (Sweden)

    Salavat R. Aglyamov

    2007-01-01

    Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

  12. Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

    Science.gov (United States)

    Evans, John W.; DiVenti, Tony

    2016-01-01

    The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

  13. Artificial Intelligence and Moral intelligence

    Directory of Open Access Journals (Sweden)

    Laura Pana

    2008-07-01

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

  14. Separation prediction in two dimensional boundary layer flows using artificial neural networks

    International Nuclear Information System (INIS)

    Sabetghadam, F.; Ghomi, H.A.

    2003-01-01

    In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

  15. FORECASTING KUALA LUMPUR COMPOSITE INDEX: EVIDENCE OF THE ARTIFICIAL NEURAL NETWORK AND ARIMA

    OpenAIRE

    Sukmana, Raditya; Solihin, Mahmud Iwan

    2007-01-01

    The aim of this paper is to use, compare, and analyze two forecasting technique: namelyAuto Regressive Integrated Moving Average(ARIMA) and Artificial NeuralNetwork(ANN) using Kuala Lumpur Composite Index(KLCI) in Malaysia. ArtificialNeural Network is used because of its popularity of capturing the volatility patterns innonlinear time series while ARIMA used since it is a standard method in the forecastingtool. Daily data of Kuala Lumpur Composite Index from 4 January 1999 to 26 September2005...

  16. Forecasting Kuala Lumpur Composite Index: Evidence of the Artificial Neural Network and Arima

    OpenAIRE

    Mahmud Iwan, Raditya Sukmana,

    2007-01-01

    The aim of this paper is to use, compare, and analyze two forecasting technique: namely Auto Regressive Integrated Moving Average(ARIMA) and Artificial Neural Network(ANN) using Kuala Lumpur Composite Index(KLCI) in Malaysia. Artificial Neural Network is used because of its popularity of capturing the volatility patterns in nonlinear time series while ARIMA used since it is a standard method in the forecasting tool. Daily data of Kuala Lumpur Composite Index from 4 January 1999 to 26 Septembe...

  17. Toward a Model-Based Approach for Flight System Fault Protection

    Science.gov (United States)

    Day, John; Meakin, Peter; Murray, Alex

    2012-01-01

    Use SysML/UML to describe the physical structure of the system This part of the model would be shared with other teams - FS Systems Engineering, Planning & Execution, V&V, Operations, etc., in an integrated model-based engineering environment Use the UML Profile mechanism, defining Stereotypes to precisely express the concepts of the FP domain This extends the UML/SysML languages to contain our FP concepts Use UML/SysML, along with our profile, to capture FP concepts and relationships in the model Generate typical FP engineering products (the FMECA, Fault Tree, MRD, V&V Matrices)

  18. A model based message passing approach for flexible and scalable home automation controllers

    Energy Technology Data Exchange (ETDEWEB)

    Bienhaus, D. [INNIAS GmbH und Co. KG, Frankenberg (Germany); David, K.; Klein, N.; Kroll, D. [ComTec Kassel Univ., SE Kassel Univ. (Germany); Heerdegen, F.; Jubeh, R.; Zuendorf, A. [Kassel Univ. (Germany). FG Software Engineering; Hofmann, J. [BSC Computer GmbH, Allendorf (Germany)

    2012-07-01

    There is a large variety of home automation systems that are largely proprietary systems from different vendors. In addition, the configuration and administration of home automation systems is frequently a very complex task especially, if more complex functionality shall be achieved. Therefore, an open model for home automation was developed that is especially designed for easy integration of various home automation systems. This solution also provides a simple modeling approach that is inspired by typical home automation components like switches, timers, etc. In addition, a model based technology to achieve rich functionality and usability was implemented. (orig.)

  19. Model-based monitoring techniques for leakage localization in distribution water networks

    OpenAIRE

    Meseguer Amela, Jordi; Mirats Tur, Josep Maria; Cembrano Gennari, Gabriela; Puig Cayuela, Vicenç

    2015-01-01

    This is an open access article under the CC BY-NC-ND license This paper describes an integrated model-based monitoring framework for leakage localization in district-metered areas (DMA) of water distribution networks, which takes advantage of the availability of a hydraulic model of the network. The leakage localization methodology is based on the use of flow and pressure sensors at the DMA inlets and a limited number of pressure sensors deployed inside the DMA. The placement of these sens...

  20. Model Based Analysis and Test Generation for Flight Software

    Science.gov (United States)

    Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

    2009-01-01

    We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.