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Sample records for network ann technology

  1. Super capacitor modeling with artificial neural network (ANN)

    Energy Technology Data Exchange (ETDEWEB)

    Marie-Francoise, J.N.; Gualous, H.; Berthon, A. [Universite de Franche-Comte, Lab. en Electronique, Electrotechnique et Systemes (L2ES), UTBM, INRETS (LRE T31) 90 - Belfort (France)

    2004-07-01

    This paper presents super-capacitors modeling using Artificial Neural Network (ANN). The principle consists on a black box nonlinear multiple inputs single output (MISO) model. The system inputs are temperature and current, the output is the super-capacitor voltage. The learning and the validation of the ANN model from experimental charge and discharge of super-capacitor establish the relationship between inputs and output. The learning and the validation of the ANN model use experimental results of 2700 F, 3700 F and a super-capacitor pack. Once the network is trained, the ANN model can predict the super-capacitor behaviour with temperature variations. The update parameters of the ANN model are performed thanks to Levenberg-Marquardt method in order to minimize the error between the output of the system and the predicted output. The obtained results with the ANN model of super-capacitor and experimental ones are in good agreement. (authors)

  2. Development of a new software tool, based on ANN technology, in neutron spectrometry and dosimetry research

    International Nuclear Information System (INIS)

    Ortiz R, J.M.; Martinez B, M.R.; Vega C, H.R.

    2007-01-01

    Artificial Intelligence is a branch of study which enhances the capability of computers by giving them human-like intelligence. The brain architecture has been extensively studied and attempts have been made to emulate it as in the Artificial Neural Network technology. A large variety of neural network architectures have been developed and they have gained wide-spread popularity over the last few decades. Their application is considered as a substitute for many classical techniques that have been used for many years, as in the case of neutron spectrometry and dosimetry research areas. In previous works, a new approach called Robust Design of Artificial Neural network was applied to build an ANN topology capable to solve the neutron spectrometry and dosimetry problems within the Mat lab programming environment. In this work, the knowledge stored at Mat lab ANN's synaptic weights was extracted in order to develop for first time a customized software application based on ANN technology, which is proposed to be used in the neutron spectrometry and simultaneous dosimetry fields. (Author)

  3. Development of a new software tool, based on ANN technology, in neutron spectrometry and dosimetry research

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz R, J.M.; Martinez B, M.R.; Vega C, H.R. [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, A.P. 336, 98000 Zacatecas (Mexico)

    2007-07-01

    Artificial Intelligence is a branch of study which enhances the capability of computers by giving them human-like intelligence. The brain architecture has been extensively studied and attempts have been made to emulate it as in the Artificial Neural Network technology. A large variety of neural network architectures have been developed and they have gained wide-spread popularity over the last few decades. Their application is considered as a substitute for many classical techniques that have been used for many years, as in the case of neutron spectrometry and dosimetry research areas. In previous works, a new approach called Robust Design of Artificial Neural network was applied to build an ANN topology capable to solve the neutron spectrometry and dosimetry problems within the Mat lab programming environment. In this work, the knowledge stored at Mat lab ANN's synaptic weights was extracted in order to develop for first time a customized software application based on ANN technology, which is proposed to be used in the neutron spectrometry and simultaneous dosimetry fields. (Author)

  4. RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks.

    Directory of Open Access Journals (Sweden)

    Marco Grimaldi

    Full Text Available RegnANN is a novel method for reverse engineering gene networks based on an ensemble of multilayer perceptrons. The algorithm builds a regressor for each gene in the network, estimating its neighborhood independently. The overall network is obtained by joining all the neighborhoods. RegnANN makes no assumptions about the nature of the relationships between the variables, potentially capturing high-order and non linear dependencies between expression patterns. The evaluation focuses on synthetic data mimicking plausible submodules of larger networks and on biological data consisting of submodules of Escherichia coli. We consider Barabasi and Erdös-Rényi topologies together with two methods for data generation. We verify the effect of factors such as network size and amount of data to the accuracy of the inference algorithm. The accuracy scores obtained with RegnANN is methodically compared with the performance of three reference algorithms: ARACNE, CLR and KELLER. Our evaluation indicates that RegnANN compares favorably with the inference methods tested. The robustness of RegnANN, its ability to discover second order correlations and the agreement between results obtained with this new methods on both synthetic and biological data are promising and they stimulate its application to a wider range of problems.

  5. Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

    Science.gov (United States)

    Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

    2011-01-01

    Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

  6. Review of Artificial Neural Networks (ANN) applied to corrosion monitoring

    International Nuclear Information System (INIS)

    Mabbutt, S; Picton, P; Shaw, P; Black, S

    2012-01-01

    The assessment of corrosion within an engineering system often forms an important aspect of condition monitoring but it is a parameter that is inherently difficult to measure and predict. The electrochemical nature of the corrosion process allows precise measurements to be made. Advances in instruments, techniques and software have resulted in devices that can gather data and perform various analysis routines that provide parameters to identify corrosion type and corrosion rate. Although corrosion rates are important they are only useful where general or uniform corrosion dominates. However, pitting, inter-granular corrosion and environmentally assisted cracking (stress corrosion) are examples of corrosion mechanisms that can be dangerous and virtually invisible to the naked eye. Electrochemical noise (EN) monitoring is a very useful technique for detecting these types of corrosion and it is the only non-invasive electrochemical corrosion monitoring technique commonly available. Modern instrumentation is extremely sensitive to changes in the system and new experimental configurations for gathering EN data have been proven. In this paper the identification of localised corrosion by different data analysis routines has been reviewed. In particular the application of Artificial Neural Network (ANN) analysis to corrosion data is of key interest. In most instances data needs to be used with conventional theory to obtain meaningful information and relies on expert interpretation. Recently work has been carried out using artificial neural networks to investigate various types of corrosion data in attempts to predict corrosion behaviour with some success. This work aims to extend this earlier work to identify reliable electrochemical indicators of localised corrosion onset and propagation stages.

  7. Artificial Neural Networks (ANNs for flood forecasting at Dongola Station in the River Nile, Sudan

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    Sulafa Hag Elsafi

    2014-09-01

    Full Text Available Heavy seasonal rains cause the River Nile in Sudan to overflow and flood the surroundings areas. The floods destroy houses, crops, roads, and basic infrastructure, resulting in the displacement of people. This study aimed to forecast the River Nile flow at Dongola Station in Sudan using an Artificial Neural Network (ANN as a modeling tool and validated the accuracy of the model against actual flow. The ANN model was formulated to simulate flows at a certain location in the river reach, based on flow at upstream locations. Different procedures were applied to predict flooding by the ANN. Readings from stations along the Blue Nile, White Nile, Main Nile, and River Atbara between 1965 and 2003 were used to predict the likelihood of flooding at Dongola Station. The analysis indicated that the ANN provides a reliable means of detecting the flood hazard in the River Nile.

  8. Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

    Energy Technology Data Exchange (ETDEWEB)

    Yildiz, Sayiter [Engineering Faculty, Cumhuriyet University, Sivas (Turkmenistan)

    2017-09-15

    Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R{sup 2} value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R{sup 2} values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

  9. Artificial neural network (ANN) approach for modeling Zn(II) adsorption in batch process

    International Nuclear Information System (INIS)

    Yildiz, Sayiter

    2017-01-01

    Artificial neural networks (ANN) were applied to predict adsorption efficiency of peanut shells for the removal of Zn(II) ions from aqueous solutions. Effects of initial pH, Zn(II) concentrations, temperature, contact duration and adsorbent dosage were determined in batch experiments. The sorption capacities of the sorbents were predicted with the aid of equilibrium and kinetic models. The Zn(II) ions adsorption onto peanut shell was better defined by the pseudo-second-order kinetic model, for both initial pH, and temperature. The highest R"2 value in isotherm studies was obtained from Freundlich isotherm for the inlet concentration and from Temkin isotherm for the sorbent amount. The high R"2 values prove that modeling the adsorption process with ANN is a satisfactory approach. The experimental results and the predicted results by the model with the ANN were found to be highly compatible with each other.

  10. Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

    Science.gov (United States)

    Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

    2016-11-01

    This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R 2 ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016. © 2016 American Institute of Chemical Engineers.

  11. Predicting the Deflections of Micromachined Electrostatic Actuators Using Artificial Neural Network (ANN

    Directory of Open Access Journals (Sweden)

    Hing Wah LEE

    2009-03-01

    Full Text Available In this study, a general purpose Artificial Neural Network (ANN model based on the feed-forward back-propagation (FFBP algorithm has been used to predict the deflections of a micromachined structures actuated electrostatically under different loadings and geometrical parameters. A limited range of simulation results obtained via CoventorWare™ numerical software will be used initially to train the neural network via back-propagation algorithm. The micromachined structures considered in the analyses are diaphragm, fixed-fixed beams and cantilevers. ANN simulation results are compared with results obtained via CoventorWare™ simulations and existing analytical work for validation purpose. The proposed ANN model accurately predicts the deflections of the micromachined structures with great reduction of simulation efforts, establishing the method superiority. This method can be extended for applications in other sensors particularly for modeling sensors applying electrostatic actuation which are difficult in nature due to the inherent non-linearity of the electro-mechanical coupling response.

  12. Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

    Science.gov (United States)

    Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

    2018-02-01

    This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

  13. IDI diesel engine performance and exhaust emission analysis using biodiesel with an artificial neural network (ANN

    Directory of Open Access Journals (Sweden)

    K. Prasada Rao

    2017-09-01

    Full Text Available Biodiesel is receiving increasing attention each passing day because of its fuel properties and compatibility. This study investigates the performance and emission characteristics of single cylinder four stroke indirect diesel injection (IDI engine fueled with Rice Bran Methyl Ester (RBME with Isopropanol additive. The investigation is done through a combination of experimental data analysis and artificial neural network (ANN modeling. The study used IDI engine experimental data to evaluate nine engine performance and emission parameters including Exhaust Gas Temperature (E.G.T, Brake Specific Fuel Consumption (BSFC, Brake Thermal Efficiency (B.The and various emissions like Hydrocarbons (HC, Carbon monoxide (CO, Carbon dioxide (CO2, Oxygen (O2, Nitrogen oxides (NOX and smoke. For the ANN modeling standard back propagation algorithm was found to be the optimum choice for training the model. A multi-layer perception (MLP network was used for non-linear mapping between the input and output parameters. It was found that ANN was able to predict the engine performance and exhaust emissions with a correlation coefficient of 0.995, 0.980, 0.999, 0.985, 0.999, 0.999, 0.980, 0.999, and 0.999 for E.G.T, BSFC, B.The, HC, O2, CO2, CO, NOX, smoke respectively.

  14. Comparison of the accuracy of SST estimates by artificial neural networks (ANN) and other quantitative methods using radiolarian data from the Antarctic and Pacific Oceans

    Digital Repository Service at National Institute of Oceanography (India)

    Gupta, S.M.; Malmgren, B.A.

    ) regression, the maximum likelihood (ML) method, and artificial neural networks (ANNs), based on radiolarian faunal abundance data from surface sediments from the Antarctic and Pacific Oceans. Recent studies have suggested that ANNs may represent one...

  15. Exploration of artificial neural network [ANN] to predict the electrochemical characteristics of lithium-ion cells

    Energy Technology Data Exchange (ETDEWEB)

    Parthiban, Thirumalai; Ravi, R.; Kalaiselvi, N. [Central Electrochemical Research Institute (CECRI), Karaikudi 630006 (India)

    2007-12-31

    CoO anode, as an alternate to the carbonaceous anodes of lithium-ion cells has been prepared and investigated for electrochemical charge-discharge characteristics for about 50 cycles. Artificial neural networks (ANNs), which are useful in estimating battery performance, has been deployed for the first time to forecast and to verify the charge-discharge behavior of lithium-ion cells containing CoO anode for a total of 50 cycles. In this novel approach, ANN that has one input layer with one neuron corresponding to one input variable, viz., cycles [charge-discharge cycles] and a hidden layer consisting of three neurons to produce their outputs to the output layer through a sigmoid function has been selected for the present investigation. The output layer consists of two neurons, representing the charge and discharge capacity, whose activation function is also the sigmoid transfer function. In this ever first attempt to exploit ANN as an effective theoretical tool to understand the charge-discharge characteristics of lithium-ion cells, an excellent agreement between the calculated and observed capacity values was found with CoO anodes with the best fit values corresponding to an error factor of <1%, which is the highlight of the present study. (author)

  16. Predicting PM10 concentration in Seoul metropolitan subway stations using artificial neural network (ANN).

    Science.gov (United States)

    Park, Sechan; Kim, Minjeong; Kim, Minhae; Namgung, Hyeong-Gyu; Kim, Ki-Tae; Cho, Kyung Hwa; Kwon, Soon-Bark

    2018-01-05

    The indoor air quality of subway systems can significantly affect the health of passengers since these systems are widely used for short-distance transit in metropolitan urban areas in many countries. The particles generated by abrasion during subway operations and the vehicle-emitted pollutants flowing in from the street in particular affect the air quality in underground subway stations. Thus the continuous monitoring of particulate matter (PM) in underground station is important to evaluate the exposure level of PM to passengers. However, it is difficult to obtain indoor PM data because the measurement systems are expensive and difficult to install and operate for significant periods of time in spaces crowded with people. In this study, we predicted the indoor PM concentration using the information of outdoor PM, the number of subway trains running, and information on ventilation operation by the artificial neural network (ANN) model. As well, we investigated the relationship between ANN's performance and the depth of underground subway station. ANN model showed a high correlation between the predicted and actual measured values and it was able to predict 67∼80% of PM at 6 subway station. In addition, we found that platform shape and depth influenced the model performance. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Prediction of Tourism Demand in Iran by Using Artificial Neural Network (ANN and Supporting Vector Machine (SVR

    Directory of Open Access Journals (Sweden)

    Seyedehelham Sadatiseyedmahalleh

    2016-02-01

    Full Text Available This research examines and proves this effectiveness connected with artificial neural networks (ANNs as an alternative approach to the use of Support Vector Machine (SVR in the tourism research. This method can be used for the tourism industry to define the turism’s demands in Iran. The outcome reveals the use of ANNs in tourism research might result in better quotations when it comes to prediction bias and accuracy. Even more applications of ANNs in the context of tourism demand evaluation is needed to establish and validate the effects.

  18. USING ARTIFICIAL NEURAL NETWORKS (ANNs FOR SEDIMENT LOAD FORECASTING OF TALKHEROOD RIVER MOUTH

    Directory of Open Access Journals (Sweden)

    Vahid Nourani

    2009-01-01

    Full Text Available Without a doubt the carried sediment load by a river is the most important factor in creating and formation of the related Delta in the river mouth. Therefore, accurate forecasting of the river sediment load can play a significant role for study on the river Delta. However considering the complexity and non-linearity of the phenomenon, the classic experimental or physical-based approaches usually could not handle the problem so well. In this paper, Artificial Neural Network (ANN as a non-linear black box interpolator tool is used for modeling suspended sediment load which discharges to the Talkherood river mouth, located in northern west Iran. For this purpose, observed time series of water discharge at current and previous time steps are used as the model input neurons and the model output neuron will be the forecasted sediment load at the current time step. In this way, various schemes of the ANN approach are examined in order to achieve the best network as well as the best architecture of the model. The obtained results are also compared with the results of two other classic methods (i.e., linear regression and rating curve methods in order to approve the efficiency and ability of the proposed method.

  19. Hybrid intelligence systems and artificial neural network (ANN approach for modeling of surface roughness in drilling

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    Ch. Sanjay

    2014-12-01

    Full Text Available In machining processes, drilling operation is material removal process that has been widely used in manufacturing since industrial revolution. The useful life of cutting tool and its operating conditions largely controls the economics of machining operations. Drilling is most frequently performed material removing process and is used as a preliminary step for many operations, such as reaming, tapping, and boring. Drill wear has a bad effect on the surface finish and dimensional accuracy of the work piece. The surface finish of a machined part is one of the most important quality characteristics in manufacturing industries. The primary objective of this research is the prediction of suitable parameters for surface roughness in drilling. Cutting speed, cutting force, and machining time were given as inputs to the adaptive fuzzy neural network and neuro-fuzzy analysis for estimating the values of surface roughness by using 2, 3, 4, and 5 membership functions. The best structures were selected based on minimum of summation of square with the actual values with the estimated values by artificial neural fuzzy inference system (ANFIS and neuro-fuzzy systems. For artificial neural network (ANN analysis, the number of neurons was selected from 1, 2, 3, … , 20. The learning rate was selected as .5 and .5 smoothing factor was used. The inputs were selected as cutting speed, feed, machining time, and thrust force. The best structures of neural networks were selected based on the criteria as the minimum of summation of square with the actual value of surface roughness. Drilling experiments with 10 mm size were performed at two cutting speeds and feeds. Comparative analysis has been done between the actual values and the estimated values obtained by ANFIS, neuro-fuzzy, and ANN analysis.

  20. SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu; Chao, KSC; Parashar, Bhupesh; Chang, Jenghwa [Weill Cornell Medical College, NY, NY (United States)

    2014-06-01

    Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT, status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation.

  1. SU-E-T-206: Improving Radiotherapy Toxicity Based On Artificial Neural Network (ANN) for Head and Neck Cancer Patients

    International Nuclear Information System (INIS)

    Cho, Daniel D; Wernicke, A Gabriella; Nori, Dattatreyudu; Chao, KSC; Parashar, Bhupesh; Chang, Jenghwa

    2014-01-01

    Purpose/Objective(s): The aim of this study is to build the estimator of toxicity using artificial neural network (ANN) for head and neck cancer patients Materials/Methods: An ANN can combine variables into a predictive model during training and considered all possible correlations of variables. We constructed an ANN based on the data from 73 patients with advanced H and N cancer treated with external beam radiotherapy and/or chemotherapy at our institution. For the toxicity estimator we defined input data including age, sex, site, stage, pathology, status of chemo, technique of external beam radiation therapy (EBRT), length of treatment, dose of EBRT, status of post operation, length of follow-up, the status of local recurrences and distant metastasis. These data were digitized based on the significance and fed to the ANN as input nodes. We used 20 hidden nodes (for the 13 input nodes) to take care of the correlations of input nodes. For training ANN, we divided data into three subsets such as training set, validation set and test set. Finally, we built the estimator for the toxicity from ANN output. Results: We used 13 input variables including the status of local recurrences and distant metastasis and 20 hidden nodes for correlations. 59 patients for training set, 7 patients for validation set and 7 patients for test set and fed the inputs to Matlab neural network fitting tool. We trained the data within 15% of errors of outcome. In the end we have the toxicity estimation with 74% of accuracy. Conclusion: We proved in principle that ANN can be a very useful tool for predicting the RT outcomes for high risk H and N patients. Currently we are improving the results using cross validation

  2. Application of Artificial Neural Networks (ANNs for Weight Predictions of Blue Crabs (Callinectes sapidus RATHBUN, 1896 Using Predictor Variables

    Directory of Open Access Journals (Sweden)

    C. TURELI BILEN

    2011-10-01

    Full Text Available An evaluation of the performance of artificial networks (ANNs to estimate the weights of blue crab (Callinectes sapidus catches in Yumurtalık Cove (Iskenderun Bay that uses measured predictor variables is presented, including carapace width (CW, sex (male, female and female with eggs, and sampling month. Blue crabs (n=410 were collected each month between 15 September 1996 and 15 May 1998. Sex, CW, and sampling month were used and specified in the input layer of the network. The weights of the blue crabs were utilized in the output layer of the network. A multi-layer perception architecture model was used and was calibrated with the Levenberg Marguardt (LM algorithm. Finally, the values were determined by the ANN model using the actual data. The mean square error (MSE was measured as 3.3, and the best results had a correlation coefficient (R of 0.93. We compared the predictive capacity of the general linear model (GLM versus the Artificial Neural Network model (ANN for the estimation of the weights of blue crabs from independent field data. The results indicated the higher performance capacity of the ANN to predict weights compared to the GLM (R=0.97 vs. R=0.95, raw variable when evaluated against independent field data.

  3. Anne K. Bang: Islamic Sufi Networks in the Western Indian Ocean (c. 1880-1940. Ripples of Reform.

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    Angelika Brodersen

    2015-03-01

    Full Text Available This contribution offers a review of Anne K. Bang's book: Islamic Sufi Networks in the Western Indian Ocean (c. 1880-1940. Ripples of Reform. Islam in Africa, Volume 16. Leiden: Brill 2014. xiv + 227 pages, € 104.00, ISBN 978-900-425-1342.

  4. Technologies for Home Networking

    DEFF Research Database (Denmark)

    A broad overview of the home networking field, ranging from wireless technologies to practical applications. In the future, it is expected that private networks (e.g. home networks) will become part of the global network ecosystem, participating in sharing their own content, running IP...

  5. Comparative study of landslides susceptibility mapping methods: Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN)

    Science.gov (United States)

    Salleh, S. A.; Rahman, A. S. A. Abd; Othman, A. N.; Mohd, W. M. N. Wan

    2018-02-01

    As different approach produces different results, it is crucial to determine the methods that are accurate in order to perform analysis towards the event. This research aim is to compare the Rank Reciprocal (MCDM) and Artificial Neural Network (ANN) analysis techniques in determining susceptible zones of landslide hazard. The study is based on data obtained from various sources such as local authority; Dewan Bandaraya Kuala Lumpur (DBKL), Jabatan Kerja Raya (JKR) and other agencies. The data were analysed and processed using Arc GIS. The results were compared by quantifying the risk ranking and area differential. It was also compared with the zonation map classified by DBKL. The results suggested that ANN method gives better accuracy compared to MCDM with 18.18% higher accuracy assessment of the MCDM approach. This indicated that ANN provides more reliable results and it is probably due to its ability to learn from the environment thus portraying realistic and accurate result.

  6. Artificial Neural Network (ANN) Model to Predict Depression among Geriatric Population at a Slum in Kolkata, India.

    Science.gov (United States)

    Sau, Arkaprabha; Bhakta, Ishita

    2017-05-01

    Depression is one of the most important causes of mortality and morbidity among the geriatric population. Although, the aging brain is more vulnerable to depression, it cannot be considered as physiological and an inevitable part of ageing. Various sociodemographic and morbidity factors are responsible for the depression among them. Using Artificial Neural Network (ANN) model depression can be predicted from various sociodemographic variables and co morbid conditions even at community level by the grass root level health care workers. To predict depression among geriatric population from sociodemographic and morbidity attributes using ANN. An observational descriptive study with cross-sectional design was carried out at a slum under the service area of Bagbazar Urban Health and Training Centre (UHTC) in Kolkata. Among 126 elderlies under Bagbazar UHTC, 105 were interviewed using predesigned and pretested schedule. Depression status was assessed using 30 item Geriatric Depression Scale. WEKA 3.8.0 was used to develop the ANN model and test its performance. Prevalence of depression among the study population was 45.7%. Various sociodemographic variables like age, gender, literacy, living spouse, working status, personal income, family type, substance abuse and co morbid conditions like visual problem, mobility problem, hearing problem and sleeping problem were taken into consideration to develop the model. Prediction accuracy of this ANN model was 97.2%. Depression among geriatric population can be predicted accurately using ANN model from sociodemographic and morbidity attributes.

  7. Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN Technique

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    Awatif Soaded Alsaqqar

    2016-06-01

    Full Text Available In this research an Artificial Neural Network (ANN technique was applied for the prediction of Ryznar Index (RI of the flowing water from WTPs in Al-Karakh side (left side in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3 have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For Al-Dora WTP, ANN 3 model could be used as R was 92.8%.

  8. The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

    Science.gov (United States)

    Kuçak, R. A.; Özdemir, E.; Erol, S.

    2017-05-01

    Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

  9. THE SEGMENTATION OF POINT CLOUDS WITH K-MEANS AND ANN (ARTIFICAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. A. Kuçak

    2017-05-01

    Full Text Available Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM which is a type of ANN (Artificial Neural Network segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

  10. Artificial Neural Networks and Instructional Technology.

    Science.gov (United States)

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  11. Prediction of moving bed biofilm reactor (MBBR) performance for the treatment of aniline using artificial neural networks (ANN)

    Energy Technology Data Exchange (ETDEWEB)

    Delnavaz, M. [Tarbiat Modares University, Civil Engineering Department, Environmental Engineering Division, Tehran (Iran, Islamic Republic of); Ayati, B., E-mail: ayati_bi@modares.ac.ir [Tarbiat Modares University, Civil Engineering Department, Environmental Engineering Division, Tehran (Iran, Islamic Republic of); Ganjidoust, H. [Tarbiat Modares University, Civil Engineering Department, Environmental Engineering Division, Tehran (Iran, Islamic Republic of)

    2010-07-15

    In this study, the results of 1-year efficiency forecasting using artificial neural networks (ANN) models of a moving bed biofilm reactor (MBBR) for a toxic and hard biodegradable aniline removal were investigated. The reactor was operated in an aerobic batch and continuous condition with 50% by volume which was filled with light expanded clay aggregate (LECA) as carrier. Efficiency evaluation of the reactors was obtained at different retention time (RT) of 8, 24, 48 and 72 h with an influent COD from 100 to 4000 mg/L. Exploratory data analysis was used to detect relationships between the data and dependent evaluated one. The appropriate architecture of the neural network models was determined using several steps of training and testing of the models. The ANN-based models were found to provide an efficient and a robust tool in predicting MBBR performance for treating aromatic amine compounds.

  12. Prediction by Artificial Neural Networks (ANN of the diffusivity, mass, moisture, volume and solids on osmotically dehydrated yacon (Smallantus sonchifolius

    Directory of Open Access Journals (Sweden)

    Julio Rojas Naccha

    2012-09-01

    Full Text Available The predictive ability of Artificial Neural Network (ANN on the effect of the concentration (30, 40, 50 y 60 % w/w and temperature (30, 40 y 50°C of fructooligosaccharides solution, in the mass, moisture, volume and solids of osmodehydrated yacon cubes, and in the coefficients of the water means effective diffusivity with and without shrinkage was evaluated. The Feedforward type ANN with the Backpropagation training algorithms and the Levenberg-Marquardt weight adjustment was applied, using the following topology: 10-5 goal error, 0.01 learning rate, 0.5 moment coefficient, 2 input neurons, 6 output neurons, one hidden layer with 18 neurons, 15 training stages and logsig-pureline transfer functions. The overall average error achieved by the ANN was 3.44% and correlation coefficients were bigger than 0.9. No significant differences were found between the experimental values and the predicted values achieved by the ANN and with the predicted values achieved by a statistical model of second-order polynomial regression (p > 0.95.

  13. Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

    International Nuclear Information System (INIS)

    Taghavifar, Hamid; Mardani, Aref

    2014-01-01

    This paper examines the prediction of energy efficiency indices of driven wheels (i.e. traction coefficient and tractive power efficiency) as affected by wheel load, slippage and forward velocity at three different levels with three replicates to form a total of 162 data points. The pertinent experiments were carried out in the soil bin testing facility. A feed-forward ANN (artificial neural network) with standard BP (back propagation) algorithm was practiced to construct a supervised representation to predict the energy efficiency indices of driven wheels. It was deduced, in view of the statistical performance criteria (i.e. MSE (mean squared error) and R 2 ), that a supervised ANN with 3-8-10-2 topology and Levenberg–Marquardt training algorithm represented the optimal model. Modeling implementations indicated that ANN is a powerful technique to prognosticate the stochastic energy efficiency indices as affected by soil-wheel interactions with MSE of 0.001194 and R 2 of 0.987 and 0.9772 for traction coefficient and tractive power efficiency. It was found that traction coefficient and tractive power efficiency increase with increased slippage. A similar trend is valid for the influence of wheel load on the objective parameters. Wherein increase of velocity led to an increment of tractive power efficiency, velocity had no significant effect on traction coefficient. - Highlights: • Energy efficiency indexes were assessed as affected by tire parameters. • ANN was applied for prognostication of the objective parameters. • A 3-8-10-2 ANN with MSE of 0.001194 and R 2 of 0.987 and 0.9772 was designated as optimal model. • Optimal values of learning rate and momentum were found 0.9 and 0.5, respectively

  14. The modelling of lead removal from water by deep eutectic solvents functionalized CNTs: artificial neural network (ANN) approach.

    Science.gov (United States)

    Fiyadh, Seef Saadi; AlSaadi, Mohammed Abdulhakim; AlOmar, Mohamed Khalid; Fayaed, Sabah Saadi; Hama, Ako R; Bee, Sharifah; El-Shafie, Ahmed

    2017-11-01

    The main challenge in the lead removal simulation is the behaviour of non-linearity relationships between the process parameters. The conventional modelling technique usually deals with this problem by a linear method. The substitute modelling technique is an artificial neural network (ANN) system, and it is selected to reflect the non-linearity in the interaction among the variables in the function. Herein, synthesized deep eutectic solvents were used as a functionalized agent with carbon nanotubes as adsorbents of Pb 2+ . Different parameters were used in the adsorption study including pH (2.7 to 7), adsorbent dosage (5 to 20 mg), contact time (3 to 900 min) and Pb 2+ initial concentration (3 to 60 mg/l). The number of experimental trials to feed and train the system was 158 runs conveyed in laboratory scale. Two ANN types were designed in this work, the feed-forward back-propagation and layer recurrent; both methods are compared based on their predictive proficiency in terms of the mean square error (MSE), root mean square error, relative root mean square error, mean absolute percentage error and determination coefficient (R 2 ) based on the testing dataset. The ANN model of lead removal was subjected to accuracy determination and the results showed R 2 of 0.9956 with MSE of 1.66 × 10 -4 . The maximum relative error is 14.93% for the feed-forward back-propagation neural network model.

  15. Simulation of CO2 Solubility in Polystyrene-b-Polybutadieneb-Polystyrene (SEBS) by artificial intelligence network (ANN) method

    Science.gov (United States)

    Sharudin, R. W.; AbdulBari Ali, S.; Zulkarnain, M.; Shukri, M. A.

    2018-05-01

    This study reports on the integration of Artificial Neural Network (ANNs) with experimental data in predicting the solubility of carbon dioxide (CO2) blowing agent in SEBS by generating highest possible value for Regression coefficient (R2). Basically, foaming of thermoplastic elastomer with CO2 is highly affected by the CO2 solubility. The ability of ANN in predicting interpolated data of CO2 solubility was investigated by comparing training results via different method of network training. Regards to the final prediction result for CO2 solubility by ANN, the prediction trend (output generate) was corroborated with the experimental results. The obtained result of different method of training showed the trend of output generated by Gradient Descent with Momentum & Adaptive LR (traingdx) required longer training time and required more accurate input to produce better output with final Regression Value of 0.88. However, it goes vice versa with Levenberg-Marquardt (trainlm) technique as it produced better output in quick detention time with final Regression Value of 0.91.

  16. Applying of the Artificial Neural Networks (ANN) to Identify and Characterize Sweet Spots in Shale Gas Formations

    Science.gov (United States)

    Puskarczyk, Edyta

    2018-03-01

    The main goal of the study was to enhance and improve information about the Ordovician and Silurian gas-saturated shale formations. Author focused on: firstly, identification of the shale gas formations, especially the sweet spots horizons, secondly, classification and thirdly, the accurate characterization of divisional intervals. Data set comprised of standard well logs from the selected well. Shale formations are represented mainly by claystones, siltstones, and mudstones. The formations are also partially rich in organic matter. During the calculations, information about lithology of stratigraphy weren't taken into account. In the analysis, selforganizing neural network - Kohonen Algorithm (ANN) was used for sweet spots identification. Different networks and different software were tested and the best network was used for application and interpretation. As a results of Kohonen networks, groups corresponding to the gas-bearing intervals were found. The analysis showed diversification between gas-bearing formations and surrounding beds. It is also shown that internal diversification in sweet spots is present. Kohonen algorithm was also used for geological interpretation of well log data and electrofacies prediction. Reliable characteristic into groups shows that Ja Mb and Sa Fm which are usually treated as potential sweet spots only partially have good reservoir conditions. It is concluded that ANN appears to be useful and quick tool for preliminary classification of members and sweet spots identification.

  17. A novel and generalized approach in the inversion of geoelectrical resistivity data using Artificial Neural Networks (ANN)

    Science.gov (United States)

    Raj, A. Stanley; Srinivas, Y.; Oliver, D. Hudson; Muthuraj, D.

    2014-03-01

    The non-linear apparent resistivity problem in the subsurface study of the earth takes into account the model parameters in terms of resistivity and thickness of individual subsurface layers using the trained synthetic data by means of Artificial Neural Networks (ANN). Here we used a single layer feed-forward neural network with fast back propagation learning algorithm. So on proper training of back propagation networks it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data with reference to the synthetic data trained in the appropriate network. During training, the weights and biases of the network are iteratively adjusted to make network performance function level more efficient. On adequate training, errors are minimized and the best result is obtained using the artificial neural networks. The network is trained with more number of VES data and this trained network is demonstrated by the field data. The accuracy of inversion depends upon the number of data trained. In this novel and specially designed algorithm, the interpretation of the vertical electrical sounding has been done successfully with the more accurate layer model.

  18. Application of back-propagation artificial neural network (ANN) to predict crystallite size and band gap energy of ZnO quantum dots

    Science.gov (United States)

    Pelicano, Christian Mark; Rapadas, Nick; Cagatan, Gerard; Magdaluyo, Eduardo

    2017-12-01

    Herein, the crystallite size and band gap energy of zinc oxide (ZnO) quantum dots were predicted using artificial neural network (ANN). Three input factors including reagent ratio, growth time, and growth temperature were examined with respect to crystallite size and band gap energy as response factors. The generated results from neural network model were then compared with the experimental results. Experimental crystallite size and band gap energy of ZnO quantum dots were measured from TEM images and absorbance spectra, respectively. The Levenberg-Marquardt (LM) algorithm was used as the learning algorithm for the ANN model. The performance of the ANN model was then assessed through mean square error (MSE) and regression values. Based on the results, the ANN modelling results are in good agreement with the experimental data.

  19. A call for water-efficient technologies (an interview with dr. Anne Elings)

    NARCIS (Netherlands)

    Elings, A.

    2012-01-01

    During the recent International Flower Trade Expo in Nairobi, Wageningen UR Greenhouse Horticulture project leader and greenhouse horticulture specialist Anne Elings pointed out that Kenya is not a water scarce country but management of the same is wanting. HortiNews had a chat with him.

  20. Neuropathological findings processed by artificial neural networks (ANNs can perfectly distinguish Alzheimer's patients from controls in the Nun Study

    Directory of Open Access Journals (Sweden)

    Snowdon David

    2007-06-01

    Full Text Available Abstract Background Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs analysis Methods The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. Results By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance

  1. Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study.

    Science.gov (United States)

    Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

    2007-06-21

    Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus. The results of this study

  2. Mobile infostation network technology

    Science.gov (United States)

    Rajappan, Gowri; Acharya, Joydeep; Liu, Hongbo; Mandayam, Narayan; Seskar, Ivan; Yates, Roy

    2006-05-01

    Inefficient use of network resources on the battlefield is a serious liability: if an asset communicates with the network command for data-a terrain map, for instance-it ties up the end-to-end network resources. When many such assets contend for data simultaneously, traffic is limited by the slowest link along the path from the network command to the asset. A better approach is for a local server, known as an infostation, to download data on an anticipated-need basis when the network load is low. The infostation can then dump data when needed to the assets over a high-speed wireless connection. The infostation serves the local assets over an OFDM-based wireless data link that has MIMO enhancements for high data rate and robustness. We aim for data rate in excess of 100 Mbps, spectral efficiency in excess of 5 bits/sec/Hz, and robustness to poor channel conditions and jammers. We propose an adaptive physical layer that determines power levels, modulation schemes, and the MIMO enhancements to use based on the channel state and the level of interference in the system. We also incorporate the idea of superuser: a user who is allowed preferential use of the high data rate link. We propose a MAC that allows for this priority-based bandwidth allocation scheme. The proposed infostation MAC is integrated tightly with the physical layer through a cross-layer design. We call the proposed infostation PHY, MAC, and network technology, collectively, as the Mobile Infostation Network Technology (MINT).

  3. Statistical optimization of the phytoremediation of arsenic by Ludwigia octovalvis- in a pilot reed bed using response surface methodology (RSM) versus an artificial neural network (ANN).

    Science.gov (United States)

    Titah, Harmin Sulistiyaning; Halmi, Mohd Izuan Effendi Bin; Abdullah, Siti Rozaimah Sheikh; Hasan, Hassimi Abu; Idris, Mushrifah; Anuar, Nurina

    2018-06-07

    In this study, the removal of arsenic (As) by plant, Ludwigia octovalvis, in a pilot reed bed was optimized. A Box-Behnken design was employed including a comparative analysis of both Response Surface Methodology (RSM) and an Artificial Neural Network (ANN) for the prediction of maximum arsenic removal. The predicted optimum condition using the desirability function of both models was 39 mg kg -1 for the arsenic concentration in soil, an elapsed time of 42 days (the sampling day) and an aeration rate of 0.22 L/min, with the predicted values of arsenic removal by RSM and ANN being 72.6% and 71.4%, respectively. The validation of the predicted optimum point showed an actual arsenic removal of 70.6%. This was achieved with the deviation between the validation value and the predicted values being within 3.49% (RSM) and 1.87% (ANN). The performance evaluation of the RSM and ANN models showed that ANN performs better than RSM with a higher R 2 (0.97) close to 1.0 and very small Average Absolute Deviation (AAD) (0.02) and Root Mean Square Error (RMSE) (0.004) values close to zero. Both models were appropriate for the optimization of arsenic removal with ANN demonstrating significantly higher predictive and fitting ability than RSM.

  4. Prediction ofWater Quality Parameters (NO3, CL in Karaj Riverby Usinga Combinationof Wavelet Neural Network, ANN and MLRModels

    Directory of Open Access Journals (Sweden)

    T. Rajaee

    2016-10-01

    Full Text Available IntroductionThe water quality is an issue of ongoing concern. Evaluation of the quantity and quality of running waters is considerable in hydro-environmental management.The prediction and control of the quality of Karaj river water, as one of the important needed water supply sources of Tehran, possesses great importance. In this study, Performance of Artificial Neural Network (ANN, Wavelet Neural Network combination (WANN and multi linear regression (MLR models, to predict next month the Nitrate (NO3 and Chloride (CL ions of "gate ofBylaqan sluice" station located in Karaj River has been evaluated. Materials and MethodsIn this research two separate ANN models for prediction of NO3 and CL has been expanded. Each one of the parameters for prediction (NO3 / CL has been put related to the past amounts of the same time series (NO3 / CL and its amounts of Q in past months.From astatisticalperiod of10yearswas usedforthe input of the models. Hence 80% of entire data from (96 initial months of data as training set, next 10% of data (12 months and 10% of the end of time series (terminal 12 months were considered as for validation and test of the models, respectively. In WANNcombination model, the real monthly observed time series of river discharge (Q and mentioned qualityparameters(NO3 / CL were decomposed to some sub-time series at different levels by wavelet analysis.Then the decomposed quality parameters to predict and Q time series were used at different levels as inputs to the ANN technique for predicting one-step-ahead Nitrate and Chloride. These time series play various roles in the original time series and the behavior of each is distinct, so the contribution to the original time series varies from each other. In addition, prediction of high NO3 and CL values greater than mean of data that have great importancewere investigated by the models. The capability of the models was evaluated by Coefficient of Efficiency (E and the Root Mean Square

  5. Anne Fine

    Directory of Open Access Journals (Sweden)

    Philip Gaydon

    2015-04-01

    Full Text Available An interview with Anne Fine with an introduction and aside on the role of children’s literature in our lives and development, and our adult perceptions of the suitability of childhood reading material. Since graduating from Warwick in 1968 with a BA in Politics and History, Anne Fine has written over fifty books for children and eight for adults, won the Carnegie Medal twice (for Goggle-Eyes in 1989 and Flour Babies in 1992, been a highly commended runner-up three times (for Bill’s New Frock in 1989, The Tulip Touch in 1996, and Up on Cloud Nine in 2002, been shortlisted for the Hans Christian Andersen Award (the highest recognition available to a writer or illustrator of children’s books, 1998, undertaken the positon of Children’s Laureate (2001-2003, and been awarded an OBE for her services to literature (2003. Warwick presented Fine with an Honorary Doctorate in 2005. Philip Gaydon’s interview with Anne Fine was recorded as part of the ‘Voices of the University’ oral history project, co-ordinated by Warwick’s Institute of Advanced Study.

  6. Social Networks and Technology Adoption

    OpenAIRE

    Hogset, Heidi

    2005-01-01

    This study analyzes social network effects on Kenyan smallholders' decision to adopt improved natural resource management techniques. These effects are decomposed into effects from social influence and learning through networks (strong ties), group effects, weak ties effects, informal finance, and conflicts arising from technological externalities, controlling for non-network effects.

  7. Classifying Sources Influencing Indoor Air Quality (IAQ Using Artificial Neural Network (ANN

    Directory of Open Access Journals (Sweden)

    Shaharil Mad Saad

    2015-05-01

    Full Text Available Monitoring indoor air quality (IAQ is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC, base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity.

  8. Optimization of thermal conductivity lightweight brick type AAC (Autoclaved Aerated Concrete) effect of Si & Ca composition by using Artificial Neural Network (ANN)

    Science.gov (United States)

    Zulkifli; Wiryawan, G. P.

    2018-03-01

    Lightweight brick is the most important component of building construction, therefore it is necessary to have lightweight thermal, mechanical and aqustic thermal properties that meet the standard, in this paper which is discussed is the domain of light brick thermal conductivity properties. The advantage of lightweight brick has a low density (500-650 kg/m3), more economical, can reduce the load 30-40% compared to conventional brick (clay brick). In this research, Artificial Neural Network (ANN) is used to predict the thermal conductivity of lightweight brick type Autoclaved Aerated Concrete (AAC). Based on the training and evaluation that have been done on 10 model of ANN with number of hidden node 1 to 10, obtained that ANN with 3 hidden node have the best performance. It is known from the mean value of MSE (Mean Square Error) validation for three training times of 0.003269. This ANN was further used to predict the thermal conductivity of four light brick samples. The predicted results for each of the AAC1, AAC2, AAC3 and AAC4 light brick samples were 0.243 W/m.K, respectively; 0.29 W/m.K; 0.32 W/m.K; and 0.32 W/m.K. Furthermore, ANN is used to determine the effect of silicon composition (Si), Calcium (Ca), to light brick thermal conductivity. ANN simulation results show that the thermal conductivity increases with increasing Si composition. Si content is allowed maximum of 26.57%, while the Ca content in the range 20.32% - 30.35%.

  9. Exact estimation of biodiesel cetane number (CN) from its fatty acid methyl esters (FAMEs) profile using partial least square (PLS) adapted by artificial neural network (ANN)

    International Nuclear Information System (INIS)

    Hosseinpour, Soleiman; Aghbashlo, Mortaza; Tabatabaei, Meisam; Khalife, Esmail

    2016-01-01

    Highlights: • Estimating the biodiesel CN from its FAMEs profile using ANN-based PLS approach. • Comparing the capability of ANN-adapted PLS approach with the standard PLS model. • Exact prediction of biodiesel CN from it FAMEs profile using ANN-based PLS method. • Developing an easy-to-use software using ANN-PLS model for computing the biodiesel CN. - Abstract: Cetane number (CN) is among the most important properties of biodiesel because it quantifies combustion speed or in better words, ignition quality. Experimental measurement of biodiesel CN is rather laborious and expensive. However, the high proportionality of biodiesel fatty acid methyl esters (FAMEs) profile with its CN is very appealing to develop straightforward and inexpensive computerized tools for biodiesel CN estimation. Unfortunately, correlating the chemical structure of biodiesel to its CN using conventional statistical and mathematical approaches is very difficult. To solve this issue, partial least square (PLS) adapted by artificial neural network (ANN) was introduced and examined herein as an innovative approach for the exact estimation of biodiesel CN from its FAMEs profile. In the proposed approach, ANN paradigm was used for modeling the inner relation between the input and the output PLS score vectors. In addition, the capability of the developed method in predicting the biodiesel CN was compared with the basal PLS method. The accuracy of the developed approaches for computing the biodiesel CN was assessed using three statistical criteria, i.e., coefficient of determination (R"2), mean-squared error (MSE), and percentage error (PE). The ANN-adapted PLS method predicted the biodiesel CN with an R"2 value higher than 0.99 demonstrating the fidelity of the developed model over the classical PLS method with a markedly lower R"2 value of about 0.85. In order to facilitate the use of the proposed model, an easy-to-use computer program was also developed on the basis of ANN-adapted PLS

  10. Artificial Neural Network (ANN) design for Hg-Se interactions and their effect on reduction of Hg uptake by radish plant

    International Nuclear Information System (INIS)

    Kumar Rohit Raj; Abhishek Kardam; Shalini Srivastava; Jyoti Kumar Arora

    2010-01-01

    The tendency of selenium to interact with heavy metals in presence of naturally occurring species has been exploited for the development of green bioremediation of toxic metals from soil using Artificial Neural Network (ANN) modeling. The cross validation of the data for the reduction in uptake of Hg(II) ions in the plant R. sativus grown in soil and sand culture in presence of selenium has been used for ANN modeling. ANN model based on the combination of back propagation and principal component analysis was able to predict the reduction in Hg uptake with a sigmoid axon transfer function. The data of fifty laboratory experimental sets were used for structuring single layer ANN model. Series of experiments resulted into the performance evaluation based on considering 20% data for testing and 20% data for cross validation at 1,500 Epoch with 0.70 momentums The Levenberg-Marquardt algorithm (LMA) was found as the best of BP algorithms with a minimum mean squared error at the eighth place of the decimal for training (MSE) and cross validation. (author)

  11. Network speech systems technology program

    Science.gov (United States)

    Weinstein, C. J.

    1981-09-01

    This report documents work performed during FY 1981 on the DCA-sponsored Network Speech Systems Technology Program. The two areas of work reported are: (1) communication system studies in support of the evolving Defense Switched Network (DSN) and (2) design and implementation of satellite/terrestrial interfaces for the Experimental Integrated Switched Network (EISN). The system studies focus on the development and evaluation of economical and endurable network routing procedures. Satellite/terrestrial interface development includes circuit-switched and packet-switched connections to the experimental wideband satellite network. Efforts in planning and coordination of EISN experiments are reported in detail in a separate EISN Experiment Plan.

  12. A Historical Analysis of Media Practices and Technologies in Protest Movements: A Review of Crisis and Critique by Anne Kaun

    Directory of Open Access Journals (Sweden)

    Anne Laajalahti

    2017-05-01

    Full Text Available Dr. Anne Kaun’s book, Crisis and Critique: A Brief History of Media Participation in Times of Crisis (London: Zed Books, 2016, 131 pp., ISBN: 978-1-78360-736-5, is a concise but comprehensive analysis of the changing media practices and technologies in protest movements. The book overviews the topic within the context of major economic crises and scrutinises three richly detailed case studies in the United States: (a the unemployed workers’ movement during the Great Depression in the 1930s, (b the tenants’ rent strike movement of the early 1970s, and (c the Occupy Wall Street movement following the Great Recession of 2008. Kaun begins her book with an introduction to economic crises and protest movements and highlights the relationship of crisis and critique to media practices. She goes on to investigate historical forms of media participation in protest movements from three different perspectives: (a protest time, (b protest space, and (c protest speed. The book contributes to the recent discussion on the emerging role of social media in protest by providing a historically nuanced analysis of the media participation in times of crisis. As a whole, the book is valuable to anyone interested in media and social activism.

  13. Networked Constellation Communications Technologies

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop communications architectures and enabling technologies for mission concepts relying on multiple spatially distributed spacecraft to perform coordinated...

  14. 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.

  15. Simulation of Snowmelt Runoff Using SRM Model and Comparison With Neural Networks ANN and ANFIS (Case Study: Kardeh dam basin

    Directory of Open Access Journals (Sweden)

    morteza akbari

    2017-03-01

    of the basin with 2962 meters above sea level. Kardeh dam was primarily constructed on the Kardehriver for providing drinking and agriculture water demand with an annual volume rate of 21.23 million cubic meters. Satellite image: To estimate the level of snow cover, the satellite Landsat ETM+ data at path 35-159, rows 34-159 over the period 2001-2002 were used. Surfaces covered with snow were separated bysnow distinction normalized index (NDSI, But due to the lack of training data for image classification (areas with snow and no snow, the k-means unsupervised classification algorithm was used. Extracting the data from the meteorological and hydrological Since only a gauging station exists at the Kardeh dam site, the daily discharge data recorded at these stations was used. To extract meteorological parameters such as precipitation and temperature data, the records of the three stations Golmakan, Mashhad and Ghouchan, as the stations closest to the dam basin Kardeh were used. The purpose of this study was to simulate snowmelt runoff using SRM hydrological models and to compare the results with the outputs of the neural network models such as the ANN and the ANFIS model. Flow simulation was carried out using SRM, ANN model with the Multilayer Perceptron with back-propagation algorithm, and Sugeno type ANFIS. To evaluate the performance of the models in addition to the standard statistics such as mean square error or mean absolute percentage error, the regression coefficient measures and the difference in volume were used. The results showed that all three models are almost similar in terms of statistical parameters MSE and R and the differences were negligible. SRM model: SRM model is a daily hydrological model. This equation is composed of different components including 14 parameters. The input values were calculated based on the equations of degree-day factor. The evaluation of the model was performed with flow subside factor, coefficient and subtracting volume

  16. Performance evaluation of an irreversible Miller cycle comparing FTT (finite-time thermodynamics) analysis and ANN (artificial neural network) prediction

    International Nuclear Information System (INIS)

    Mousapour, Ashkan; Hajipour, Alireza; Rashidi, Mohammad Mehdi; Freidoonimehr, Navid

    2016-01-01

    In this paper, the first and second-laws efficiencies are applied to performance analysis of an irreversible Miller cycle. In the irreversible cycle, the linear relation between the specific heat of the working fluid and its temperature, the internal irreversibility described using the compression and expansion efficiencies, the friction loss computed according to the mean velocity of the piston and the heat-transfer loss are considered. The effects of various design parameters, such as the minimum and maximum temperatures of the working fluid and the compression ratio on the power output and the first and second-laws efficiencies of the cycle are discussed. In the following, a procedure named ANN is used for predicting the thermal efficiency values versus the compression ratio, and the minimum and maximum temperatures of the Miller cycle. Nowadays, Miller cycle is widely used in the automotive industry and the obtained results of this study will provide some significant theoretical grounds for the design optimization of the Miller cycle. - Highlights: • The performance of an irreversible Miller cycle is investigated using FFT. • The effects of design parameters on the performance of the cycle are investigated. • ANN is applied to predict the thermal efficiency and the power output values. • There is an excellent correlation between FTT and ANN data. • ANN can be applied to predict data where FTT analysis has not been performed.

  17. Determining degree of roasting in cocoa beans by artificial neural network (ANN)-based electronic nose system and gas chromatography/mass spectrometry (GC/MS).

    Science.gov (United States)

    Tan, Juzhong; Kerr, William L

    2018-08-01

    Roasting is a critical step in chocolate processing, where moisture content is decreased and unique flavors and texture are developed. The determination of the degree of roasting in cocoa beans is important to ensure the quality of chocolate. Determining the degree of roasting relies on human specialists or sophisticated chemical analyses that are inaccessible to small manufacturers and farmers. In this study, an electronic nose system was constructed consisting of an array of gas sensors and used to detect volatiles emanating from cocoa beans roasted for 0, 20, 30 and 40 min. The several signals were used to train a three-layer artificial neural network (ANN). Headspace samples were also analyzed by gas chromatography/mass spectrometry (GC/MS), with 23 select volatiles used to train a separate ANN. Both ANNs were used to predict the degree of roasting of cocoa beans. The electronic nose had a prediction accuracy of 94.4% using signals from sensors TGS 813, 826, 822, 830, 830, 2620, 2602 and 2610. In comparison, the GC/MS predicted the degree of roasting with an accuracy of 95.8%. The electronic nose system is able to predict the extent of roasting, as well as a more sophisticated approach using GC/MS. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

  18. Performance Parameters Analysis of an XD3P Peugeot Engine Using Artificial Neural Networks (ANN) Concept in MATLAB

    Science.gov (United States)

    Rangaswamy, T.; Vidhyashankar, S.; Madhusudan, M.; Bharath Shekar, H. R.

    2015-04-01

    The current trends of engineering follow the basic rule of innovation in mechanical engineering aspects. For the engineers to be efficient, problem solving aspects need to be viewed in a multidimensional perspective. One such methodology implemented is the fusion of technologies from other disciplines in order to solve the problems. This paper mainly deals with the application of Neural Networks in order to analyze the performance parameters of an XD3P Peugeot engine (used in Ministry of Defence). The basic propaganda of the work is divided into two main working stages. In the former stage, experimentation of an IC engine is carried out in order to obtain the primary data. In the latter stage the primary database formed is used to design and implement a predictive neural network in order to analyze the output parameters variation with respect to each other. A mathematical governing equation for the neural network is obtained. The obtained polynomial equation describes the characteristic behavior of the built neural network system. Finally, a comparative study of the results is carried out.

  19. Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells.

    Science.gov (United States)

    Yetilmezsoy, Kaan; Demirel, Sevgi

    2008-05-30

    A three-layer artificial neural network (ANN) model was developed to predict the efficiency of Pb(II) ions removal from aqueous solution by Antep pistachio (Pistacia Vera L.) shells based on 66 experimental sets obtained in a laboratory batch study. The effect of operational parameters such as adsorbent dosage, initial concentration of Pb(II) ions, initial pH, operating temperature, and contact time were studied to optimise the conditions for maximum removal of Pb(II) ions. On the basis of batch test results, optimal operating conditions were determined to be an initial pH of 5.5, an adsorbent dosage of 1.0 g, an initial Pb(II) concentration of 30 ppm, and a temperature of 30 degrees C. Experimental results showed that a contact time of 45 min was generally sufficient to achieve equilibrium. After backpropagation (BP) training combined with principal component analysis (PCA), the ANN model was able to predict adsorption efficiency with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and a linear transfer function (purelin) at output layer. The Levenberg-Marquardt algorithm (LMA) was found as the best of 11 BP algorithms with a minimum mean squared error (MSE) of 0.000227875. The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of about 0.936 for five model variables used in this study.

  20. Building secure network by integrated technology

    International Nuclear Information System (INIS)

    An Dehai; Xu Rongsheng; Liu Baoxu

    2000-01-01

    The author introduces a method which can realize the most powerful network security prevention by the network security integrated technologies such as firewall, realtime monitor, network scanner, Web detection and security, etc

  1. CCTV networking and digital technology

    CERN Document Server

    Damjanovski, Vlado

    2005-01-01

    Closed circuit television (CCTV) is experiencing a leap in technology using digital techniques, networking and the Internet. The new edition of this high-level professional reference retains the particulars that made the first edition a success, including the details of CCD cameras, lenses, coaxial cables, fiber-optics, and system design, but it is expanded to cover all video compression techniques used in the ever increasing assortment of digital video recorders (DVRs) available on the market today. This new edition of the book CCTV demystifies DVR technology. It also serves to clarify the te

  2. Research on NGN network control technology

    Science.gov (United States)

    Li, WenYao; Zhou, Fang; Wu, JianXue; Li, ZhiGuang

    2004-04-01

    Nowadays NGN (Next Generation Network) is the hotspot for discussion and research in IT section. The NGN core technology is the network control technology. The key goal of NGN is to realize the network convergence and evolution. Referring to overlay network model core on Softswitch technology, circuit switch network and IP network convergence realized. Referring to the optical transmission network core on ASTN/ASON, service layer (i.e. IP layer) and optical transmission convergence realized. Together with the distributing feature of NGN network control technology, on NGN platform, overview of combining Softswitch and ASTN/ASON control technology, the solution whether IP should be the NGN core carrier platform attracts general attention, and this is also a QoS problem on NGN end to end. This solution produces the significant practical meaning on equipment development, network deployment, network design and optimization, especially on realizing present network smooth evolving to the NGN. This is why this paper puts forward the research topic on the NGN network control technology. This paper introduces basics on NGN network control technology, then proposes NGN network control reference model, at the same time describes a realizable network structure of NGN. Based on above, from the view of function realization, NGN network control technology is discussed and its work mechanism is analyzed.

  3. Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

    Science.gov (United States)

    Balabin, Roman M; Lomakina, Ekaterina I

    2011-04-21

    In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

  4. Comparison between Possibilistic c-Means (PCM and Artificial Neural Network (ANN Classification Algorithms in Land use/ Land cover Classification

    Directory of Open Access Journals (Sweden)

    Ganchimeg Ganbold

    2017-03-01

    Full Text Available There are several statistical classification algorithms available for landuse/land cover classification. However, each has a certain bias orcompromise. Some methods like the parallel piped approach in supervisedclassification, cannot classify continuous regions within a feature. Onthe other hand, while unsupervised classification method takes maximumadvantage of spectral variability in an image, the maximally separableclusters in spectral space may not do much for our perception of importantclasses in a given study area. In this research, the output of an ANNalgorithm was compared with the Possibilistic c-Means an improvementof the fuzzy c-Means on both moderate resolutions Landsat8 and a highresolution Formosat 2 images. The Formosat 2 image comes with an8m spectral resolution on the multispectral data. This multispectral imagedata was resampled to 10m in order to maintain a uniform ratio of1:3 against Landsat 8 image. Six classes were chosen for analysis including:Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC, the six features reflecteddifferently in the infrared region with wheat producing the brightestpixel values. Signature collection per class was therefore easily obtainedfor all classifications. The output of both ANN and FCM, were analyzedseparately for accuracy and an error matrix generated to assess the qualityand accuracy of the classification algorithms. When you compare theresults of the two methods on a per-class-basis, ANN had a crisperoutput compared to PCM which yielded clusters with pixels especiallyon the moderate resolution Landsat 8 imagery.

  5. Mass storage technology in networks

    Science.gov (United States)

    Ishii, Katsunori; Takeda, Toru; Itao, Kiyoshi; Kaneko, Reizo

    1990-08-01

    Trends and features of mass storage subsystems in network are surveyed and their key technologies spotlighted. Storage subsystems are becoming increasingly important in new network systems in which communications and data processing are systematically combined. These systems require a new class of high-performance mass-information storage in order to effectively utilize their processing power. The requirements of high transfer rates, high transactional rates and large storage capacities, coupled with high functionality, fault tolerance and flexibility in configuration, are major challenges in storage subsystems. Recent progress in optical disk technology has resulted in improved performance of on-line external memories to optical disk drives, which are competing with mid-range magnetic disks. Optical disks are more effective than magnetic disks in using low-traffic random-access file storing multimedia data that requires large capacity, such as in archive use and in information distribution use by ROM disks. Finally, it demonstrates image coded document file servers for local area network use that employ 130mm rewritable magneto-optical disk subsystems.

  6. Predicting fuelwood prices in Greece with the use of ARIMA models, artificial neural networks and a hybrid ARIMA-ANN model

    International Nuclear Information System (INIS)

    Koutroumanidis, Theodoros; Ioannou, Konstantinos; Arabatzis, Garyfallos

    2009-01-01

    Throughout history, energy resources have acquired a strategic significance for the economic growth and social welfare of any country. The large-scale oil crisis of 1973 coupled with various environmental protection issues, have led many countries to look for new, alternative energy sources. Biomass and fuelwood in particular, constitutes a major renewable energy source (RES) that can make a significant contribution, as a substitute for oil. This paper initially provides a description of the contribution of renewable energy sources to the production of electricity, and also examines the role of forests in the production of fuelwood in Greece. Following this, autoregressive integrated moving average (ARIMA) models, artificial neural networks (ANN) and a hybrid model are used to predict the future selling prices of the fuelwood (from broadleaved and coniferous species) produced by Greek state forest farms. The use of the ARIMA-ANN hybrid model provided the optimum prediction results, thus enabling decision-makers to proceed with a more rational planning for the production and fuelwood market. (author)

  7. The use of artificial neural networks (ANN) for modeling of decolorization of textile dye solution containing C. I. Basic Yellow 28 by electrocoagulation process

    International Nuclear Information System (INIS)

    Daneshvar, N.; Khataee, A.R.; Djafarzadeh, N.

    2006-01-01

    In this paper, electrocoagulation has been used for removal of color from solution containing C. I. Basic Yellow 28. The effect of operational parameters such as current density, initial pH of the solution, time of electrolysis, initial dye concentration, distance between the electrodes, retention time and solution conductivity were studied in an attempt to reach higher removal efficiency. Our results showed that the increase of current density up to 80 A m -2 enhanced the color removal efficiency, the electrolysis time was 7 min and the range of pH was determined 5-8. It was found that for achieving a high color removal percent, the conductivity of the solution and the initial concentration of dye should be 10 mS cm -1 and 50 mg l -1 , respectively. An artificial neural networks (ANN) model was developed to predict the performance of decolorization efficiency by EC process based on experimental data obtained in a laboratory batch reactor. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The model can describe the color removal percent under different conditions

  8. The use of artificial neural networks (ANN) for modeling of decolorization of textile dye solution containing C. I. Basic Yellow 28 by electrocoagulation process

    Energy Technology Data Exchange (ETDEWEB)

    Daneshvar, N. [Water and Wastewater Treatment Research Laboratory, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz (Iran, Islamic Republic of)]. E-mail: nezam_daneshvar@yahoo.com; Khataee, A.R. [Water and Wastewater Treatment Research Laboratory, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz (Iran, Islamic Republic of)]. E-mail: ar_khataee@yahoo.com; Djafarzadeh, N. [Water and Wastewater Treatment Research Laboratory, Department of Applied Chemistry, Faculty of Chemistry, University of Tabriz, Tabriz (Iran, Islamic Republic of)]. E-mail: n.jafarzadeh@gmail.com

    2006-10-11

    In this paper, electrocoagulation has been used for removal of color from solution containing C. I. Basic Yellow 28. The effect of operational parameters such as current density, initial pH of the solution, time of electrolysis, initial dye concentration, distance between the electrodes, retention time and solution conductivity were studied in an attempt to reach higher removal efficiency. Our results showed that the increase of current density up to 80 A m{sup -2} enhanced the color removal efficiency, the electrolysis time was 7 min and the range of pH was determined 5-8. It was found that for achieving a high color removal percent, the conductivity of the solution and the initial concentration of dye should be 10 mS cm{sup -1} and 50 mg l{sup -1}, respectively. An artificial neural networks (ANN) model was developed to predict the performance of decolorization efficiency by EC process based on experimental data obtained in a laboratory batch reactor. A comparison between the predicted results of the designed ANN model and experimental data was also conducted. The model can describe the color removal percent under different conditions.

  9. Network technology for depot modernization

    Energy Technology Data Exchange (ETDEWEB)

    Hostick, C.J.

    1990-12-01

    This report was prepared by the Pacific Northwest Laboratory to summarize existing and emerging information system technology and standards applicable to Depot System Command (DESCOM) modernization efforts. The intent of this summarization is to provide the Revitalization of Army Depots for the Year 2000 (READY 2000) team a clear understanding of the enabling information system technologies required to support effective modernization activities. Much of the information contained in this report was acquired during the last year in support of the US Army Armament, Munitions, and Chemical Command (AMCCOM) Facility Integrated Manufacturing Management System (FIMMS) project at PNL, which is targeting the modernization of plant-wide information systems at Army Ammunition Plants. The objective of information system modernization is to improve the effectiveness of an organization in performing its mission. Information system modernization strives to meet this objective by creating an environment where data is electronically captured near the source and readily available to all areas of the organization. Advanced networks, together with related information system technology, are the enabling mechanisms that make modern information system infrastructures possible. The intent of this paper is to present an overview of advanced information system network technology to support depot modernization planners in making technology management decisions. Existing and emerging Open System Interconnection (OSI) and Government Open System Interconnection Profile (GOSIP) standards are explained, as well as a brief assessment of existing products compliant with these standards. Finally, recommendations for achieving plant-wide integration using existing products are presented, and migration strategies for full OSI compliance are introduced. 5 refs., 16 figs. (JF)

  10. Technological Developments in Networking, Education and Automation

    CERN Document Server

    Elleithy, Khaled; Iskander, Magued; Kapila, Vikram; Karim, Mohammad A; Mahmood, Ausif

    2010-01-01

    "Technological Developments in Networking, Education and Automation" includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the following areas: Computer Networks: Access Technologies, Medium Access Control, Network architectures and Equipment, Optical Networks and Switching, Telecommunication Technology, and Ultra Wideband Communications. Engineering Education and Online Learning: including development of courses and systems for engineering, technical and liberal studies programs; online laboratories; intelligent

  11. Support vector machine regression (LS-SVM)--an alternative to artificial neural networks (ANNs) for the analysis of quantum chemistry data?

    Science.gov (United States)

    Balabin, Roman M; Lomakina, Ekaterina I

    2011-06-28

    A multilayer feed-forward artificial neural network (MLP-ANN) with a single, hidden layer that contains a finite number of neurons can be regarded as a universal non-linear approximator. Today, the ANN method and linear regression (MLR) model are widely used for quantum chemistry (QC) data analysis (e.g., thermochemistry) to improve their accuracy (e.g., Gaussian G2-G4, B3LYP/B3-LYP, X1, or W1 theoretical methods). In this study, an alternative approach based on support vector machines (SVMs) is used, the least squares support vector machine (LS-SVM) regression. It has been applied to ab initio (first principle) and density functional theory (DFT) quantum chemistry data. So, QC + SVM methodology is an alternative to QC + ANN one. The task of the study was to estimate the Møller-Plesset (MPn) or DFT (B3LYP, BLYP, BMK) energies calculated with large basis sets (e.g., 6-311G(3df,3pd)) using smaller ones (6-311G, 6-311G*, 6-311G**) plus molecular descriptors. A molecular set (BRM-208) containing a total of 208 organic molecules was constructed and used for the LS-SVM training, cross-validation, and testing. MP2, MP3, MP4(DQ), MP4(SDQ), and MP4/MP4(SDTQ) ab initio methods were tested. Hartree-Fock (HF/SCF) results were also reported for comparison. Furthermore, constitutional (CD: total number of atoms and mole fractions of different atoms) and quantum-chemical (QD: HOMO-LUMO gap, dipole moment, average polarizability, and quadrupole moment) molecular descriptors were used for the building of the LS-SVM calibration model. Prediction accuracies (MADs) of 1.62 ± 0.51 and 0.85 ± 0.24 kcal mol(-1) (1 kcal mol(-1) = 4.184 kJ mol(-1)) were reached for SVM-based approximations of ab initio and DFT energies, respectively. The LS-SVM model was more accurate than the MLR model. A comparison with the artificial neural network approach shows that the accuracy of the LS-SVM method is similar to the accuracy of ANN. The extrapolation and interpolation results show that LS-SVM is

  12. Networking Technologies and the Rate of Technological Change

    Directory of Open Access Journals (Sweden)

    Charles Mitchell

    2005-12-01

    Full Text Available Network technology is changing rapidly and those adept at ICT analysis need resolve rate of change issues. Developments in networking now are in the direction of heuristic intelligence. Since about 1980, networking techniques have encouraged combining bits of information with imagination cognitively to improve ideas about reality. ICT enterprise projects utilize networking to sustain requisite imagination. Assumptions and misassuptions of project builders are rationally comprehended as networking sustains creative processes. The monopolization of valuable network techniques influences in the direction of esoteric networking. Data presents that substantial knowledge and networking is now occurring globally. As a netaphor, networking

  13. ANN multiscale model of anti-HIV drugs activity vs AIDS prevalence in the US at county level based on information indices of molecular graphs and social networks.

    Science.gov (United States)

    González-Díaz, Humberto; Herrera-Ibatá, Diana María; Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Orbegozo-Medina, Ricardo Alfredo; Pazos, Alejandro

    2014-03-24

    This work is aimed at describing the workflow for a methodology that combines chemoinformatics and pharmacoepidemiology methods and at reporting the first predictive model developed with this methodology. The new model is able to predict complex networks of AIDS prevalence in the US counties, taking into consideration the social determinants and activity/structure of anti-HIV drugs in preclinical assays. We trained different Artificial Neural Networks (ANNs) using as input information indices of social networks and molecular graphs. We used a Shannon information index based on the Gini coefficient to quantify the effect of income inequality in the social network. We obtained the data on AIDS prevalence and the Gini coefficient from the AIDSVu database of Emory University. We also used the Balaban information indices to quantify changes in the chemical structure of anti-HIV drugs. We obtained the data on anti-HIV drug activity and structure (SMILE codes) from the ChEMBL database. Last, we used Box-Jenkins moving average operators to quantify information about the deviations of drugs with respect to data subsets of reference (targets, organisms, experimental parameters, protocols). The best model found was a Linear Neural Network (LNN) with values of Accuracy, Specificity, and Sensitivity above 0.76 and AUROC > 0.80 in training and external validation series. This model generates a complex network of AIDS prevalence in the US at county level with respect to the preclinical activity of anti-HIV drugs in preclinical assays. To train/validate the model and predict the complex network we needed to analyze 43,249 data points including values of AIDS prevalence in 2,310 counties in the US vs ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4,856 protocols, and 10 possible experimental measures.

  14. Artificial neural network (ANN) method for modeling of sunset yellow dye adsorption using zinc oxide nanorods loaded on activated carbon: Kinetic and isotherm study

    Science.gov (United States)

    Maghsoudi, M.; Ghaedi, M.; Zinali, A.; Ghaedi, A. M.; Habibi, M. H.

    2015-01-01

    In this research, ZnO nanoparticle loaded on activated carbon (ZnO-NPs-AC) was synthesized simply by a low cost and nontoxic procedure. The characterization and identification have been completed by different techniques such as SEM and XRD analysis. A three layer artificial neural network (ANN) model is applicable for accurate prediction of dye removal percentage from aqueous solution by ZnO-NRs-AC following conduction of 270 experimental data. The network was trained using the obtained experimental data at optimum pH with different ZnO-NRs-AC amount (0.005-0.015 g) and 5-40 mg/L of sunset yellow dye over contact time of 0.5-30 min. The ANN model was applied for prediction of the removal percentage of present systems with Levenberg-Marquardt algorithm (LMA), a linear transfer function (purelin) at output layer and a tangent sigmoid transfer function (tansig) in the hidden layer with 6 neurons. The minimum mean squared error (MSE) of 0.0008 and coefficient of determination (R2) of 0.998 were found for prediction and modeling of SY removal. The influence of parameters including adsorbent amount, initial dye concentration, pH and contact time on sunset yellow (SY) removal percentage were investigated and optimal experimental conditions were ascertained. Optimal conditions were set as follows: pH, 2.0; 10 min contact time; an adsorbent dose of 0.015 g. Equilibrium data fitted truly with the Langmuir model with maximum adsorption capacity of 142.85 mg/g for 0.005 g adsorbent. The adsorption of sunset yellow followed the pseudo-second-order rate equation.

  15. Biotreatment of zinc-containing wastewater in a sulfidogenic CSTR: Performance and artificial neural network (ANN) modelling studies

    International Nuclear Information System (INIS)

    Sahinkaya, Erkan

    2009-01-01

    Sulfidogenic treatment of sulfate (2-10 g/L) and zinc (65-677 mg/L) containing simulated wastewater was studied in a mesophilic (35 deg. C) CSTR. Ethanol was supplemented (COD/sulfate = 0.67) as carbon and energy source for sulfate-reducing bacteria (SRB). The robustness of the system was studied by increasing Zn, COD and sulfate loadings. Sulfate removal efficiency, which was 70% at 2 g/L feed sulfate concentration, steadily decreased with increasing feed sulfate concentration and reached 40% at 10 g/L. Over 99% Zn removal was attained due to the formation of zinc-sulfide precipitate. COD removal efficiency at 2 g/L feed sulfate concentration was over 94%, whereas, it steadily decreased due to the accumulation of acetate at higher loadings. Alkalinity produced from acetate oxidation increased wastewater pH remarkably when feed sulfate concentration was 5 g/L or lower. Electron flow from carbon oxidation to sulfate reduction averaged 83 ± 13%. The rest of the electrons were most likely coupled with fermentative reactions as the amount of methane production was insignificant. The developed ANN model was very successful as an excellent to reasonable match was obtained between the measured and the predicted concentrations of sulfate (R = 0.998), COD (R = 0.993), acetate (R = 0.976) and zinc (R = 0.827) in the CSTR effluent

  16. Social networking services: technologies and applications

    OpenAIRE

    Puzyrnyy, Oleksandr

    2011-01-01

    Puzyrnyy, Oleksandr. 2011. Social networking services: technologies and applications. Bachelor's Thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 52. The aim of this thesis is to describe the concept of social networking, its technological base, business opportunities and future perspectives. The study discovers how social networks are made and which different purposes they might have. In addition, social networking is viewed as a part of business strategy o...

  17. Survey of network and information security technology

    International Nuclear Information System (INIS)

    Liu Baoxu; Wang Xiaozhen

    2007-01-01

    With the rapidly development of the computer network technology and informationize working of our Country, Network and Information Security issues becomes the focal point problem that people shows solicitude for. On the basis analysing security threat and challenge of network information and their developing trend. This paper briefly analyses and discusses the main relatively study direction and content about the theory, technology and practice of Network and Information Security. (authors)

  18. Ann tuleb Rakverest Võrru

    Index Scriptorium Estoniae

    2009-01-01

    Võru kultuurimajas Kannel etendub 17. aprillil Rakvere teatri noortelavastus "Kuidas elad? ...Ann?!" Aidi Valliku jutustuse põhjal. Lavastaja Sven Heiberg. Mängivad ka Viljandi Kultuuriakadeemia teatritudengid

  19. Handbook of social network technologies and applications

    CERN Document Server

    Furht, Borko

    2010-01-01

    Social networking is a concept that has existed for a long time; however, with the explosion of the Internet, social networking has become a tool for people to connect and communicate in ways that were impossible in the past. The recent development of Web 2.0 has provided many new applications, such as Myspace, Facebook, and LinkedIn. The purpose of ""Handbook of Social Networks: Technologies and Applications"" is to provide comprehensive guidelines on the current and future trends in social network technologies and applications in the field of Web-based Social Networks. This handbook includes

  20. Latest Trends in Home Networking Technologies

    Science.gov (United States)

    Tsutsui, Akihiro

    Broadband access service, including FTTH, is now in widespread use in Japan. More than half of the households that have broadband Internet access construct local area networks (home networks) in their homes. In addition, information appliances such as personal computers, networked audio, and visual devices and game machines are connected to home networks, and many novel service applications are provided via the Internet. However, it is still difficult to install and incorporate these devices and services because networked devices have been developed in different communities. I briefly explain the current status of information appliances and home networking technologies and services and discuss some of the problems in this and their solutions.

  1. A novel framework for intelligent signal detection via artificial neural networks for cyclic voltammetry in pyroprocessing technology

    International Nuclear Information System (INIS)

    Rakhshan Pouri, Samaneh; Manic, Milos; Phongikaroon, Supathorn

    2018-01-01

    Highlights: •First time ANN implementation toward pyroprocessing safeguards. •Real time monitoring in terms of intelligent materials detection and accountability. •CV simulation via ANN showing a high accuracy of prediction for the unseen situation. •Elimination of trial and error approach to avoid overfitting in learning. -- Abstract: Electrorefiner (ER) is the heart of pyroprocessing technology which contains different fission, rare-earth, and transuranic chloride compositions during the operation. This is still a developing technology that needs to be advanced for the commercial reprocessing design of used nuclear fuel (UNF) in terms of intelligent materials detection and accountability towards safeguards. A novel signal detection, artificial neural network (ANN), has been proposed in this study to apply on massive ER systemic parameters to simulate cyclic voltammetry (CV) graphs for the unseen situation. ANN could be trained to mimic the system by driving the data sets interrelation between variables to provide current and potential simulated data sets with a high accuracy of prediction. For this purpose, over 230,000 experimental data points reported in literature have been explored—0.5–5 wt% of zirconium chloride (ZrCl 4 ) in LiCl-KCl molten salt with different scan rates at 773 K. This study has illustrated a new framework of ANN implementation to eliminate trial and error approach by comparing the average error of one to three hidden layers with different number of neurons. In addition, this framework results in finding a preferable balance between underfitting and overfitting in deep learning. Furthermore, simulated CV graphs were compared with the experimental data and illustrated a reasonable prediction. The results reveal two structures with three hidden layers providing a good prediction with a low average error. The outcomes indicate that ANN has a strong potential in applying toward safeguards for pyroprocessing technology.

  2. Empirical modeling of a dewaxing system of lubricant oil using Artificial Neural Network (ANN); Modelagem empirica de um sistema de desparafinacao de oleo lubrificante usando redes neurais artificiais

    Energy Technology Data Exchange (ETDEWEB)

    Fontes, Cristiano Hora de Oliveira; Medeiros, Ana Claudia Gondim de; Silva, Marcone Lopes; Neves, Sergio Bello; Carvalho, Luciene Santos de; Guimaraes, Paulo Roberto Britto; Pereira, Magnus; Vianna, Regina Ferreira [Universidade Salvador (UNIFACS), Salvador, BA (Brazil). Dept. de Engenharia e Arquitetura]. E-mail: paulorbg@unifacs.br; Santos, Nilza Maria Querino dos [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil)]. E-mail: nilzaq@petrobras.com.br

    2003-07-01

    The MIBK (m-i-b-ketone) dewaxing unit, located at the Landulpho Alves refinery, allows two different operating modes: dewaxing ND oil removal. The former is comprised of an oil-wax separation process, which generates a wax stream with 2 - 5% oil. The latter involves the reprocessing of the wax stream to reduce its oil content. Both involve a two-stage filtration process (primary and secondary) with rotative filters. The general aim of this research is to develop empirical models to predict variables, for both unit-operating modes, to be used in control algorithms, since many data are not available during normal plant operation and therefore need to be estimated. Studies have suggested that the oil content is an essential variable to develop reliable empirical models and this work is concerned with the development of an empirical model for the prediction of the oil content in the wax stream leaving the primary filters. The model is based on a feed forward Artificial Neural Network (ANN) and tests with one and two hidden layers indicate very good agreement between experimental and predicted values. (author)

  3. iAnn

    DEFF Research Database (Denmark)

    Jimenez, Rafael C; Albar, Juan P; Bhak, Jong

    2013-01-01

    We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add...... submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically...

  4. Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

    International Nuclear Information System (INIS)

    Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

    2011-01-01

    With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

  5. Networking Technologies for Future Home Networks Using 60 GHz Radio

    NARCIS (Netherlands)

    Wang, J.

    2010-01-01

    Networking technologies have been changing the life of people in their private residential space. With the arrival of high definition (HD) multimedia services and broadband communications into the living space, future home networks are expected to support high speed device-to-device connectivity

  6. 78 FR 17418 - Rural Health Information Technology Network Development Grant

    Science.gov (United States)

    2013-03-21

    ... Information Technology Network Development Grant AGENCY: Health Resources and Services Administration (HRSA...-competitive replacement award under the Rural Health Information Technology Network Development Grant (RHITND... relinquishing its fiduciary responsibilities for the Rural Health Information Technology Network Development...

  7. Anne-Ly Reimaa : "Suhtlemisel on oluline avatus" / Anne-Ly Reimaa ; interv. Tiia Linnard

    Index Scriptorium Estoniae

    Reimaa, Anne-Ly

    2005-01-01

    Ilmunud ka: Severnoje Poberezhje : Subbota 3. september lk. 5. Intervjueeritav oma tööst Brüsselis, kus esindab Eesti linnade liitu ja Eesti maaomavalitsuste liitu. Arvamust avaldavad Anne Jundas ja Kaia Kaldvee. Lisa: CV

  8. Software Defined Networking Demands on Software Technologies

    DEFF Research Database (Denmark)

    Galinac Grbac, T.; Caba, Cosmin Marius; Soler, José

    2015-01-01

    Software Defined Networking (SDN) is a networking approach based on a centralized control plane architecture with standardised interfaces between control and data planes. SDN enables fast configuration and reconfiguration of the network to enhance resource utilization and service performances....... This new approach enables a more dynamic and flexible network, which may adapt to user needs and application requirements. To this end, systemized solutions must be implemented in network software, aiming to provide secure network services that meet the required service performance levels. In this paper......, we review this new approach to networking from an architectural point of view, and identify and discuss some critical quality issues that require new developments in software technologies. These issues we discuss along with use case scenarios. Here in this paper we aim to identify challenges...

  9. DESIGN OF A VISUAL INTERFACE FOR ANN BASED SYSTEMS

    Directory of Open Access Journals (Sweden)

    Ramazan BAYINDIR

    2008-01-01

    Full Text Available Artificial intelligence application methods have been used for control of many systems with parallel of technological development besides conventional control techniques. Increasing of artificial intelligence applications have required to education in this area. In this paper, computer based an artificial neural network (ANN software has been presented to learning and understanding of artificial neural networks. By means of the developed software, the training of the artificial neural network according to the inputs provided and a test action can be performed by changing the components such as iteration number, momentum factor, learning ratio, and efficiency function of the artificial neural networks. As a result of the study a visual education set has been obtained that can easily be adapted to the real time application.

  10. Visionary network 2030. Technology vision for future distribution network

    International Nuclear Information System (INIS)

    Kumpulainen, L.; Laaksonen, H.; Komulainen, R.

    2006-11-01

    Objective of this research was to create the long term vision of a distribution network technology to be used for the near future rebuild and necessary R and D efforts. Present status of the grid was briefly handled and created scenarios for the operational environment changes and available technology International view was used for getting familiar with the present solutions and future expectations in other countries. Centralised power generation is supposed to form the majority, but also the distributed generation will play more and more important role, which is hard to predict due to the uncertainty of the development of the regulation. Higher reliability and safety in major faults are expected from the future network with the reasonable costs. Impact of the climate change and impregnant using restrictions cause difficulties especially for the overhead lines in the forests. In the rural network also the ageing is the problem. For the urban networks the land usage and environmental issues get more challenging and the network reinforcement is necessary due to the increased use of electricity. As a result several technical solutions are available. Additions to the technology today, several new solutions were introduced. Important solutions in the future network are supposed to be the wide range of underground cable, high degree utilisation of the communication and network automation solutions, considerable shorter protection zones and new layout solution. In a long run the islanding enabled by the distributed energy systems and totally new network structures and solutions based on power electronics are supposed to improve the power quality and profitability. Separate quality classes in network design principally are also supposed to be approved. Getting into the vision needs also the Roadmap project, which coordinates and focuses the development of the industry. So the limited national development resources can be effectively utilised. A coordinated national

  11. Mobile Networking Technology Within INSC

    National Research Council Canada - National Science Library

    Macker, Joseph P

    2003-01-01

    We provide an overview of the INSC Mobility Task area efforts including: a brief overview of technology areas investigated, a discussion of research developments, and example results from experimentation and demonstration...

  12. Networking Technologies for Future Home Networks Using 60 GHz Radio

    OpenAIRE

    Wang, J.

    2010-01-01

    Networking technologies have been changing the life of people in their private residential space. With the arrival of high definition (HD) multimedia services and broadband communications into the living space, future home networks are expected to support high speed device-to-device connectivity with Quality-of-Service (QoS) provisioning. There is no prize for guessing that it has to be wireless communication which creates maximal freedom. Nevertheless, it is doubtful that today's home networ...

  13. Network operating system focus technology

    Science.gov (United States)

    1985-01-01

    An activity structured to provide specific design requirements and specifications for the Space Station Data Management System (DMS) Network Operating System (NOS) is outlined. Examples are given of the types of supporting studies and implementation tasks presently underway to realize a DMS test bed capability to develop hands-on understanding of NOS requirements as driven by actual subsystem test beds participating in the overall Johnson Space Center test bed program. Classical operating system elements and principal NOS functions are listed.

  14. Networking and Information Technology Workforce Study: Final Report

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — This report presents the results of a study of the global Networking and Information Technology NIT workforce undertaken for the Networking and Information...

  15. Wireless Cognitive Networks Technologies and Protocols

    OpenAIRE

    Loscri , Valeria; Maskooki , Arash; Mitton , Nathalie; Vegni , Anna Maria

    2015-01-01

    International audience; Software Defined Radio and Cognitive Radio applied to Wireless Sensor Networks and Body Area Networks represent an intriguing and really recent paradigm, which represents an objective of study of several researchers. In order to make this technology effective, it is necessary to consider an analytical model of communication capacity, energy consumption and congestion, to effectively exploit the Software Defined Radio and Cognitive Radio in this type of systems. This ch...

  16. Technology development in market networks

    International Nuclear Information System (INIS)

    Olerup, B.

    2001-01-01

    Technology procurement is used as an environmental control means in Sweden to promote the manufacturing and sale of energy-efficient technologies. The public authority in charge makes use of the market mechanism in alternating co-operative and competitive elements. The fragmented market, with its standardised products for many small customers, is brought together to specify desired product developments. These demands also include other qualities besides energy efficiency. A contest is announced in which a possible future market is indicated to manufacturers. Efforts are made to enlarge the market to motivate their investment and to keep down the unit cost. Each side in the deal is thus given an incentive to act in the desired direction. (author)

  17. Wireless local area network. A new technology of network

    International Nuclear Information System (INIS)

    Wu Yunjun; Zhao Zongtao

    2003-01-01

    This paper introduces Wireless Local Area Network (WLAN), including the concept, history, characters and the foreground of its development, it also narrates in detail the several key techniques used to implement IEEE802.11 WLAN, and ideas on key technology of future progress in wireless LAN field have also been presented. (authors)

  18. Autonomous vision networking: miniature wireless sensor networks with imaging technology

    Science.gov (United States)

    Messinger, Gioia; Goldberg, Giora

    2006-09-01

    The recent emergence of integrated PicoRadio technology, the rise of low power, low cost, System-On-Chip (SOC) CMOS imagers, coupled with the fast evolution of networking protocols and digital signal processing (DSP), created a unique opportunity to achieve the goal of deploying large-scale, low cost, intelligent, ultra-low power distributed wireless sensor networks for the visualization of the environment. Of all sensors, vision is the most desired, but its applications in distributed sensor networks have been elusive so far. Not any more. The practicality and viability of ultra-low power vision networking has been proven and its applications are countless, from security, and chemical analysis to industrial monitoring, asset tracking and visual recognition, vision networking represents a truly disruptive technology applicable to many industries. The presentation discusses some of the critical components and technologies necessary to make these networks and products affordable and ubiquitous - specifically PicoRadios, CMOS imagers, imaging DSP, networking and overall wireless sensor network (WSN) system concepts. The paradigm shift, from large, centralized and expensive sensor platforms, to small, low cost, distributed, sensor networks, is possible due to the emergence and convergence of a few innovative technologies. Avaak has developed a vision network that is aided by other sensors such as motion, acoustic and magnetic, and plans to deploy it for use in military and commercial applications. In comparison to other sensors, imagers produce large data files that require pre-processing and a certain level of compression before these are transmitted to a network server, in order to minimize the load on the network. Some of the most innovative chemical detectors currently in development are based on sensors that change color or pattern in the presence of the desired analytes. These changes are easily recorded and analyzed by a CMOS imager and an on-board DSP processor

  19. Nuclear technology databases and information network systems

    International Nuclear Information System (INIS)

    Iwata, Shuichi; Kikuchi, Yasuyuki; Minakuchi, Satoshi

    1993-01-01

    This paper describes the databases related to nuclear (science) technology, and information network. Following contents are collected in this paper: the database developed by JAERI, ENERGY NET, ATOM NET, NUCLEN nuclear information database, INIS, NUclear Code Information Service (NUCLIS), Social Application of Nuclear Technology Accumulation project (SANTA), Nuclear Information Database/Communication System (NICS), reactor materials database, radiation effects database, NucNet European nuclear information database, reactor dismantling database. (J.P.N.)

  20. Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

    Science.gov (United States)

    Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

    2017-08-15

    Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

  1. Ann Tenno salapaigad / Margit Tõnson

    Index Scriptorium Estoniae

    Tõnson, Margit, 1978-

    2011-01-01

    Fotograaf Ann Tenno aiandushuvist, pildistamisest maailma erinevates paikades. Uutest suundadest (fototöötlus, fractal art, soojuskaameraga pildistamine) tema loomingus. Katkendeid Ann Tenno 2010. aastal ilmunud proosaraamatust "Üle unepiiri"

  2. Transport Network Technologies – Study and Testing

    DEFF Research Database (Denmark)

    Bozorgebrahimi, K.; Channegowda, M.; Colmenero, A.

    Following on from the theoretical research into Carrier Class Transport Network Technologies (CCTNTs) documented in DJ1.1.1, this report describes the extensive testing performed by JRA1 Task 1. The tests covered EoMPLS, Ethernet OAM, Synchronous Ethernet, PBB-TE, MPLS-TP, OTN and GMPLS...

  3. Integrating neural network technology and noise analysis

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Oak Ridge National Lab., TN

    1995-01-01

    The integrated use of neural network and noise analysis technologies offers advantages not available by the use of either technology alone. The application of neural network technology to noise analysis offers an opportunity to expand the scope of problems where noise analysis is useful and unique ways in which the integration of these technologies can be used productively. The two-sensor technique, in which the responses of two sensors to an unknown driving source are related, is used to demonstration such integration. The relationship between power spectral densities (PSDs) of accelerometer signals is derived theoretically using noise analysis to demonstrate its uniqueness. This relationship is modeled from experimental data using a neural network when the system is working properly, and the actual PSD of one sensor is compared with the PSD of that sensor predicted by the neural network using the PSD of the other sensor as an input. A significant deviation between the actual and predicted PSDs indicate that system is changing (i.e., failing). Experiments carried out on check values and bearings illustrate the usefulness of the methodology developed. (Author)

  4. Outdoor Lighting Networks: Market, Technologies and Standards

    NARCIS (Netherlands)

    Cavalcanti, D.; Wang, J.; Chen, R.; Jiang , D.; Yang, Y.

    2012-01-01

    Providing the right amount of light where and when it is needed is an opportunity to transform today’s cities into smart and livable urban spaces. New technologies are being introduced, such are adaptivecontrols and outdoor lighting networks, which can deliver energy andcost savings through adaptive

  5. Using Citation Network Analysis in Educational Technology

    Science.gov (United States)

    Cho, Yonjoo; Park, Sunyoung

    2012-01-01

    Previous reviews in the field of Educational Technology (ET) have revealed some publication patterns according to authors, institutions, and affiliations. However, those previous reviews focused only on the rankings of individual authors and institutions, and did not provide qualitative details on relations and networks of scholars and scholarly…

  6. Biogas engine performance estimation using ANN

    Directory of Open Access Journals (Sweden)

    Yusuf Kurtgoz

    2017-12-01

    Full Text Available Artificial neural network (ANN method was used to estimate the thermal efficiency (TE, brake specific fuel consumption (BSFC and volumetric efficiency (VE values of a biogas engine with spark ignition at different methane (CH4 ratios and engine load values. For this purpose, the biogas used in the biogas engine was produced by the anaerobic fermentation method from bovine manure and different CH4 contents (51%, 57%, 87% were obtained by purification of CO2 and H2S. The data used in the ANN models were obtained experimentally from a 4-stroke four-cylinder, spark ignition engine, at constant speed for different load and CH4 ratios. Using some of the obtained experimental data, ANN models were developed, and the rest was used to test the developed models. In the ANN models, the CH4 ratio of the fuel, engine load, inlet air temperature (Tin, air fuel ratio and the maximum cylinder pressure are chosen as the input parameters. TE, BSFC and VE are used as the output parameters. Root mean square error (RMSE, mean absolute percentage error (MAPE and correlation coefficient (R performance indicators are used to compare measured and predicted values. It has been shown that ANN models give good results in spark ignition biogas engines with high correlation and low error rates for TE, BSFC and VE values.

  7. Feature Selection and ANN Solar Power Prediction

    Directory of Open Access Journals (Sweden)

    Daniel O’Leary

    2017-01-01

    Full Text Available A novel method of solar power forecasting for individuals and small businesses is developed in this paper based on machine learning, image processing, and acoustic classification techniques. Increases in the production of solar power at the consumer level require automated forecasting systems to minimize loss, cost, and environmental impact for homes and businesses that produce and consume power (prosumers. These new participants in the energy market, prosumers, require new artificial neural network (ANN performance tuning techniques to create accurate ANN forecasts. Input masking, an ANN tuning technique developed for acoustic signal classification and image edge detection, is applied to prosumer solar data to improve prosumer forecast accuracy over traditional macrogrid ANN performance tuning techniques. ANN inputs tailor time-of-day masking based on error clustering in the time domain. Results show an improvement in prediction to target correlation, the R2 value, lowering inaccuracy of sample predictions by 14.4%, with corresponding drops in mean average error of 5.37% and root mean squared error of 6.83%.

  8. An ANN application for water quality forecasting.

    Science.gov (United States)

    Palani, Sundarambal; Liong, Shie-Yui; Tkalich, Pavel

    2008-09-01

    Rapid urban and coastal developments often witness deterioration of regional seawater quality. As part of the management process, it is important to assess the baseline characteristics of the marine environment so that sustainable development can be pursued. In this study, artificial neural networks (ANNs) were used to predict and forecast quantitative characteristics of water bodies. The true power and advantage of this method lie in its ability to (1) represent both linear and non-linear relationships and (2) learn these relationships directly from the data being modeled. The study focuses on Singapore coastal waters. The ANN model is built for quick assessment and forecasting of selected water quality variables at any location in the domain of interest. Respective variables measured at other locations serve as the input parameters. The variables of interest are salinity, temperature, dissolved oxygen, and chlorophyll-alpha. A time lag up to 2Delta(t) appeared to suffice to yield good simulation results. To validate the performance of the trained ANN, it was applied to an unseen data set from a station in the region. The results show the ANN's great potential to simulate water quality variables. Simulation accuracy, measured in the Nash-Sutcliffe coefficient of efficiency (R(2)), ranged from 0.8 to 0.9 for the training and overfitting test data. Thus, a trained ANN model may potentially provide simulated values for desired locations at which measured data are unavailable yet required for water quality models.

  9. Group colocation behavior in technological social networks.

    Directory of Open Access Journals (Sweden)

    Chloë Brown

    Full Text Available We analyze two large datasets from technological networks with location and social data: user location records from an online location-based social networking service, and anonymized telecommunications data from a European cellphone operator, in order to investigate the differences between individual and group behavior with respect to physical location. We discover agreements between the two datasets: firstly, that individuals are more likely to meet with one friend at a place they have not visited before, but tend to meet at familiar locations when with a larger group. We also find that groups of individuals are more likely to meet at places that their other friends have visited, and that the type of a place strongly affects the propensity for groups to meet there. These differences between group and solo mobility has potential technological applications, for example, in venue recommendation in location-based social networks.

  10. Kõnelused Tartus / Anne Untera

    Index Scriptorium Estoniae

    Untera, Anne, 1951-

    2007-01-01

    8.-10. V Tartus toimunud eesti, läti ja saksa kunstiteadlaste ühisseminarist. Alexander Knorre rääkis Karl August Senffi, Ilona Audere Friedrich Ludwig von Maydelli, Mai Levin Karl Alexander von Winkleri, Kristiana Abele Johann Walter-Kurau (1869-1932), Anne Untera Konstantin ja Sally von Kügelgeni, Epp Preem Julie Hagen-Schwartzi, Friedrich Gross Eduard von Gebhardti ja Katharina Hadding Ida Kerkoviuse (1879-1970) loomingust

  11. Preliminary Study on Application of Artificial Neural Networks (ANN) for Determining the Peroxide Value of Three Commercial Palm Oil Based FTIR Spectrum)

    International Nuclear Information System (INIS)

    Azwan Mat Lazim; Musa Ahmad; Zuriati Zakaria; Mohd Suzeren Jamil; Suria Ramli; Faiz Zainuddin; Mohd Nasir Taib; Mat Nasir Mat Arip

    2013-01-01

    Peroxide value is one of the measurements that being used to determine the peroxide in oil samples produce from the peroxide compound and hydroperoxide group at the primary level of lipid oxidation. In this study, 3 commercial palm cooking oils were selected and labeled as A, B and C. Two different conditions were applied to the samples. First, the oil sample was exposed to the air for three months (labeled as A) while samples B and C were used for frying for many times. Two inputs from FTIR spectra (3444 cm -1 and 3450 cm -1 ) were chosen for the ANN training. The suitable architecture for this training is 2:20:1. The prediction made by ANN was very accurate and compatible to the result which obtained from the standard method. A low average error (0.48) was obtained when the hidden neuron (20) and the epochs (300) were used. (author)

  12. On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

    Science.gov (United States)

    Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

    2017-10-01

    Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

  13. LON Technology in Wireless Sensor Networking Applications

    Directory of Open Access Journals (Sweden)

    Ryszard Golanski

    2006-01-01

    Full Text Available In the paper a discussion on how to optimize LonWorks/EIA-709 sensornetworking technology for wireless applications, in presented. Main solutions offered byLocal Operating Networks (LON, LonWorks platform attractive for wirelesscommunication, that is, the send-on-delta concept and the sleep mode, are displayed. Thepredictive p-persistent CSMA MAC protocol constituting the heart of the communicationcapability of LON networks is analysed in detail. Next, the message services are described,and the analytical evaluation of delivery reliability is derived. Performance evaluation basedon simulation results for unicast traffic is presented first. In order to highlight the robustnessof the predictive CSMA to overload situations, the saturation performance for a general caseload scenario including multicast transactions is reported. The methods of effectivemanagement of energy consumption in LonWorks networks are discussed. Finally, the LONdesign tradeoffs are summarized.

  14. Development of IT-based data communication network technology

    International Nuclear Information System (INIS)

    Hong, Seok Boong; Jeong, K. I.; Yoo, Y. R.

    2010-10-01

    - Developing broadband high-reliability real-time communications technology for NPP - Developing reliability and performance validation technology for communications network - Developing security technology for NPP communications network - Developing field communications network for harsh environment of NPP - International standard registration(Oct. 28, 2009, IEC 61500

  15. Network Gateway Technology: The Issue of Redundancy towards ...

    African Journals Online (AJOL)

    The Internet has provided advancement in the areas of network and networking facilities. Everyone connected to the Internet is concerned about two basic things: the availability of network services and the speed of the network. Network gateway redundancy technology falls within these categories and happens to be one of ...

  16. Optimizing the Removal of Rhodamine B in Aqueous Solutions by Reduced Graphene Oxide-Supported Nanoscale Zerovalent Iron (nZVI/rGO Using an Artificial Neural Network-Genetic Algorithm (ANN-GA

    Directory of Open Access Journals (Sweden)

    Xuedan Shi

    2017-06-01

    Full Text Available Rhodamine B (Rh B is a toxic dye that is harmful to the environment, humans, and animals, and thus the discharge of Rh B wastewater has become a critical concern. In the present study, reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO was used to treat Rh B aqueous solutions. The nZVI/rGO composites were synthesized with the chemical deposition method and were characterized using scanning electron microscopy (SEM, X-ray diffraction (XRD, Raman spectroscopy, N2-sorption, and X-ray photoelectron spectroscopy (XPS analysis. The effects of several important parameters (initial pH, initial concentration, temperature, and contact time on the removal of Rh B by nZVI/rGO were optimized by response surface methodology (RSM and artificial neural network hybridized with genetic algorithm (ANN-GA. The results suggest that the ANN-GA model was more accurate than the RSM model. The predicted optimum value of Rh B removal efficiency (90.0% was determined using the ANN-GA model, which was compatible with the experimental value (86.4%. Moreover, the Langmuir, Freundlich, and Temkin isotherm equations were applied to fit the adsorption equilibrium data, and the Freundlich isotherm was the most suitable model for describing the process for sorption of Rh B onto the nZVI/rGO composites. The maximum adsorption capacity based on the Langmuir isotherm was 87.72 mg/g. The removal process of Rh B could be completed within 20 min, which was well described by the pseudo-second order kinetic model.

  17. Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID) and Artificial Neural Network Models (ANNs).

    Science.gov (United States)

    Hernández Suárez, Marcos; Astray Dopazo, Gonzalo; Larios López, Dina; Espinosa, Francisco

    2015-01-01

    There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA) or Factor Analysis (FA) have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID) algorithm and Artificial Neural Network (ANN) models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain). Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID) tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness between 44 and 100

  18. Identification of Relevant Phytochemical Constituents for Characterization and Authentication of Tomatoes by General Linear Model Linked to Automatic Interaction Detection (GLM-AID and Artificial Neural Network Models (ANNs.

    Directory of Open Access Journals (Sweden)

    Marcos Hernández Suárez

    Full Text Available There are a large number of tomato cultivars with a wide range of morphological, chemical, nutritional and sensorial characteristics. Many factors are known to affect the nutrient content of tomato cultivars. A complete understanding of the effect of these factors would require an exhaustive experimental design, multidisciplinary scientific approach and a suitable statistical method. Some multivariate analytical techniques such as Principal Component Analysis (PCA or Factor Analysis (FA have been widely applied in order to search for patterns in the behaviour and reduce the dimensionality of a data set by a new set of uncorrelated latent variables. However, in some cases it is not useful to replace the original variables with these latent variables. In this study, Automatic Interaction Detection (AID algorithm and Artificial Neural Network (ANN models were applied as alternative to the PCA, AF and other multivariate analytical techniques in order to identify the relevant phytochemical constituents for characterization and authentication of tomatoes. To prove the feasibility of AID algorithm and ANN models to achieve the purpose of this study, both methods were applied on a data set with twenty five chemical parameters analysed on 167 tomato samples from Tenerife (Spain. Each tomato sample was defined by three factors: cultivar, agricultural practice and harvest date. General Linear Model linked to AID (GLM-AID tree-structured was organized into 3 levels according to the number of factors. p-Coumaric acid was the compound the allowed to distinguish the tomato samples according to the day of harvest. More than one chemical parameter was necessary to distinguish among different agricultural practices and among the tomato cultivars. Several ANN models, with 25 and 10 input variables, for the prediction of cultivar, agricultural practice and harvest date, were developed. Finally, the models with 10 input variables were chosen with fit's goodness

  19. Application of ANN and fuzzy logic algorithms for streamflow ...

    Indian Academy of Sciences (India)

    1Department of Soil and Water Engineering, College of Technology and Engineering, Maharana Pratap. University of ... It was found that, ANN model performance improved with increasing .... algorithm uses supervised learning that provides.

  20. Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

    Science.gov (United States)

    Yu, Peigen; Low, Mei Yin; Zhou, Weibiao

    2018-01-01

    In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by dosing solutions of 0.1% green tea extract with differing concentrations of eight flavour keys deemed to be important for green tea aroma and taste, based on a D-optimal experimental design, before undergoing commercial sterilisation. Sensory evaluation of the green tea model system was carried out using an untrained consumer panel to obtain hedonic liking scores of the samples. Regression models were subsequently trained to objectively predict the consumer liking scores of the green tea model systems. A linear partial least squares (PLS) regression model was developed to describe the effects of the eight flavour keys on consumer liking, with a coefficient of determination (R 2 ) of 0.733, and a root-mean-square error (RMSE) of 3.53%. The PLS model was further augmented with an artificial neural network (ANN) to establish a PLS-ANN hybrid model. The established hybrid model was found to give a better prediction of consumer liking scores, based on its R 2 (0.875) and RMSE (2.41%). Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Estimation of the chemical-induced eye injury using a weight-of-evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part I: irritation potential.

    Science.gov (United States)

    Verma, Rajeshwar P; Matthews, Edwin J

    2015-03-01

    Evaluation of potential chemical-induced eye injury through irritation and corrosion is required to ensure occupational and consumer safety for industrial, household and cosmetic ingredient chemicals. The historical method for evaluating eye irritant and corrosion potential of chemicals is the rabbit Draize test. However, the Draize test is controversial and its use is diminishing - the EU 7th Amendment to the Cosmetic Directive (76/768/EEC) and recast Regulation now bans marketing of new cosmetics having animal testing of their ingredients and requires non-animal alternative tests for safety assessments. Thus, in silico and/or in vitro tests are advocated. QSAR models for eye irritation have been reported for several small (congeneric) data sets; however, large global models have not been described. This report describes FDA/CFSAN's development of 21 ANN c-QSAR models (QSAR-21) to predict eye irritation using the ADMET Predictor program and a diverse training data set of 2928 chemicals. The 21 models had external (20% test set) and internal validation and average training/verification/test set statistics were: 88/88/85(%) sensitivity and 82/82/82(%) specificity, respectively. The new method utilized multiple artificial neural network (ANN) molecular descriptor selection functionalities to maximize the applicability domain of the battery. The eye irritation models will be used to provide information to fill the critical data gaps for the safety assessment of cosmetic ingredient chemicals. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. Application of UDWDM technology in FTTH networks

    Science.gov (United States)

    Lamperski, Jan; Stepczak, Piotr

    2015-12-01

    In the paper we presented results of investigation of an original ultra dense wavelength division technology based on optical comb generator and its implementation for FTTH networks. The optical comb generator used a ring configuration with an acousto-optic frequency shifter (AOFS) which ensured obtaining very stable optical carrier frequency distances. Properties of an optical comb generator module determined stability of the UDWDM transmitter. Key properties of a selective components based on all fiber Fabry-Perot resonant cavity were presented. Operation of direct and coherent detection DWDM systems were shown. New configurations of FTTH UDWDM architecture have been proposed.

  3. Optimising training data for ANNs with Genetic Algorithms

    OpenAIRE

    Kamp , R. G.; Savenije , H. H. G.

    2006-01-01

    International audience; Artificial Neural Networks (ANNs) have proved to be good modelling tools in hydrology for rainfall-runoff modelling and hydraulic flow modelling. Representative datasets are necessary for the training phase in which the ANN learns the model's input-output relations. Good and representative training data is not always available. In this publication Genetic Algorithms (GA) are used to optimise training datasets. The approach is tested with an existing hydraulic model in ...

  4. Optimising training data for ANNs with Genetic Algorithms

    OpenAIRE

    R. G. Kamp; R. G. Kamp; H. H. G. Savenije

    2006-01-01

    Artificial Neural Networks (ANNs) have proved to be good modelling tools in hydrology for rainfall-runoff modelling and hydraulic flow modelling. Representative datasets are necessary for the training phase in which the ANN learns the model's input-output relations. Good and representative training data is not always available. In this publication Genetic Algorithms (GA) are used to optimise training datasets. The approach is tested with an existing hydraulic model in The Netherlands. An...

  5. Ad hoc laser networks component technology for modular spacecraft

    Science.gov (United States)

    Huang, Xiujun; Shi, Dele; Shen, Jingshi

    2017-10-01

    Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

  6. Network Gateway Technology: The Issue of Redundancy towards ...

    African Journals Online (AJOL)

    Everyone connected to the Internet is concerned about two basic things: the availability of network services and the speed of the network. Network gateway redundancy technology falls within these categories and happens to be one of the newest technologies which only few companies, such as mobile companies and ...

  7. Application of neural networks to group technology

    Science.gov (United States)

    Caudell, Thomas P.; Smith, Scott D. G.; Johnson, G. C.; Wunsch, Donald C., II

    1991-08-01

    Adaptive resonance theory (ART) neural networks are being developed for application to the industrial engineering problem of group technology--the reuse of engineering designs. Two- and three-dimensional representations of engineering designs are input to ART-1 neural networks to produce groups or families of similar parts. These representations, in their basic form, amount to bit maps of the part, and can become very large when the part is represented in high resolution. This paper describes an enhancement to an algorithmic form of ART-1 that allows it to operate directly on compressed input representations and to generate compressed memory templates. The performance of this compressed algorithm is compared to that of the regular algorithm on real engineering designs and a significant savings in memory storage as well as a speed up in execution is observed. In additions, a `neural database'' system under development is described. This system demonstrates the feasibility of training an ART-1 network to first cluster designs into families, and then to recall the family when presented a similar design. This application is of large practical value to industry, making it possible to avoid duplication of design efforts.

  8. Conference on "Mathematical Technology of Networks"

    CERN Document Server

    2015-01-01

    Bringing together leading researchers in the fields of functional analysis, mathematical physics and graph theory, as well as natural scientists using networks as a tool in their own research fields, such as neuroscience and machine learning, this volume presents recent advances in functional, analytical, probabilistic, and spectral aspects in the study of graphs, quantum graphs, and complex networks. The contributors to this volume explore the interplay between theoretical and applied aspects of discrete and continuous graphs. Their work helps to close the gap between different avenues of research on graphs, including metric graphs and ramified structures. All papers were presented at the conference "Mathematical Technology of Networks," held December 4–7, 2013 at the Zentrum für interdisziplinäre Forschung (ZiF) in Bielefeld, Germany, and are supplemented with detailed figures illustrating both abstract concepts as well as their real-world applications. Dynamical models on graphs or random graphs a...

  9. Space-based Networking Technology Developments in the Interplanetary Network Directorate Information Technology Program

    Science.gov (United States)

    Clare, Loren; Clement, B.; Gao, J.; Hutcherson, J.; Jennings, E.

    2006-01-01

    Described recent development of communications protocols, services, and associated tools targeted to reduce risk, reduce cost and increase efficiency of IND infrastructure and supported mission operations. Space-based networking technologies developed were: a) Provide differentiated quality of service (QoS) that will give precedence to traffic that users have selected as having the greatest importance and/or time-criticality; b) Improve the total value of information to users through the use of QoS prioritization techniques; c) Increase operational flexibility and improve command-response turnaround; d) Enable new class of networked and collaborative science missions; e) Simplify applications interfaces to communications services; and f) Reduce risk and cost from a common object model and automated scheduling and communications protocols. Technologies are described in three general areas: communications scheduling, middleware, and protocols. Additionally developed simulation environment, which provides comprehensive, quantitative understanding of the technologies performance within overall, evolving architecture, as well as ability to refine & optimize specific components.

  10. The German competence network on nuclear technology

    International Nuclear Information System (INIS)

    Kuczera, B.; Fritz, P.

    2004-01-01

    Full text: The present German energy policy is based on the phase-out of nuclear electricity generation, which means that the last of the currently operating eighteen German nuclear power plants will run until about 2022. While the plants will be shut down one after the other, decommissioning will start together with interim storage of the radioactive waste. The safe waste disposal in a final repository is planned to start around 2030 and may take another two decades, i.e., in Germany nuclear competence is further needed, at least until the mid of this century. Against this background, a high-ranking commission under the direction of the Federal Ministry of Economy and Technology evaluated the publicly funded nuclear safety related research and development (R and D) activities in Germany. One of the recommendations made by the commission was the foundation of a Competence Network on Nuclear Technology for an optimum coordination of the remaining nuclear activities including aspects of future human resources in this area. This Network was established in March 2000 with the following member institutions: Research Centre Juelich, Research Centre Karlsruhe, Research Centre Rossendorf and the Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) in Munich and their neighbouring Technical Universities. The strategic objectives of the Competence Network include: Trend investigations on job development and on university education capacities in the nuclear technology sector; Enhanced cooperation of the Research Centres with universities in the nuclear field and support of international education initiatives (e.g. ENEN, WNU); Coordination and bundling of the activities in publicly funded reactor safety and waste management R and D programmes; Support of qualified young scientists and engineers (pre-doctoral students) - also by third-party funds; Participation in and collaboration with international projects and activities for advancements of international nuclear safety

  11. A survey on the wireless sensor network technology

    International Nuclear Information System (INIS)

    Kim, Jae Hee; Jun, Hyeong Seop; Lee, Jae Cheol; Choi, Yoo Rak

    2007-12-01

    Wireless sensor technology is required in the safety inspection for safety-critical unit of nuclear power plant. This report describes wireless sensor technology related with the project named 'Development of a remote care system of NPP components based on the network and safety database'. This report includes contents of methodology and status of sensor network construction, status of zigbee sensor network, problem of security and sensor battery. Energy harvesting technology will be mentioned on the next report

  12. Survey of Promising Technologies for 5G Networks

    OpenAIRE

    Le, Nam Tuan; Hossain, Mohammad Arif; Islam, Amirul; Kim, Do-yun; Choi, Young-June; Jang, Yeong Min

    2016-01-01

    As an enhancement of cellular networks, the future-generation 5G network can be considered an ultra-high-speed technology. The proposed 5G network might include all types of advanced dominant technologies to provide remarkable services. Consequently, new architectures and service management schemes for different applications of the emerging technologies need to be recommended to solve issues related to data traffic capacity, high data rate, and reliability for ensuring QoS. Cloud computing, I...

  13. Proceedings of a Conference on Telecommunication Technologies, Networkings and Libraries

    Science.gov (United States)

    Knight, N. K.

    1981-12-01

    Current and developing technologies for digital transmission of image data likely to have an impact on the operations of libraries and information centers or provide support for information networking are reviewed. Technologies reviewed include slow scan television, teleconferencing, and videodisc technology and standards development for computer network interconnection through hardware and software, particularly packet switched networks computer network protocols for library and information service applications, the structure of a national bibliographic telecommunications network; and the major policy issues involved in the regulation or deregulation of the common communications carriers industry.

  14. An Overview of Computer Network security and Research Technology

    OpenAIRE

    Rathore, Vandana

    2016-01-01

    The rapid development in the field of computer networks and systems brings both convenience and security threats for users. Security threats include network security and data security. Network security refers to the reliability, confidentiality, integrity and availability of the information in the system. The main objective of network security is to maintain the authenticity, integrity, confidentiality, availability of the network. This paper introduces the details of the technologies used in...

  15. Design and value of service oriented technologies for smart business networking

    NARCIS (Netherlands)

    Alt, R.; Smits, M.T.; Beverungen, D.; Tuunanen, T.; Wijnhoven, F.

    2014-01-01

    Business networks that effectively use technologies and outperform competing networks are known as smart business networks. Theory hypothesizes that smart business networking requires a ‘Networked Business Operating System’ (NBOS), a technological architecture consisting of business logic, that

  16. Research on Network Defense Strategy Based on Honey Pot Technology

    Science.gov (United States)

    Hong, Jianchao; Hua, Ying

    2018-03-01

    As a new network security technology of active defense, The honeypot technology has become a very effective and practical method of decoy attackers. The thesis discusses the theory, structure, characteristic, design and implementation of Honeypot in detail. Aiming at the development of means of attack, put forward a kind of network defense technology based on honeypot technology, constructing a virtual Honeypot demonstrate the honeypot’s functions.

  17. A Sensitive ANN Based Differential Relay for Transformer Protection with Security against CT Saturation and Tap Changer Operation

    OpenAIRE

    KHORASHADI-ZADEH, Hassan; LI, Zuyi

    2014-01-01

    This paper presents an artificial neural network (ANN) based scheme for fault identification in power transformer protection. The proposed scheme is featured by the application of ANN to identifying system patterns, the unique choice of harmonics of positive sequence differential currents as ANN inputs, the effective handling of current transformer (CT) saturation with an ANN based approach, and the consideration of tap changer position for correcting secondary CT current. Performanc...

  18. Mobile Computing and Ubiquitous Networking: Concepts, Technologies and Challenges.

    Science.gov (United States)

    Pierre, Samuel

    2001-01-01

    Analyzes concepts, technologies and challenges related to mobile computing and networking. Defines basic concepts of cellular systems. Describes the evolution of wireless technologies that constitute the foundations of mobile computing and ubiquitous networking. Presents characterization and issues of mobile computing. Analyzes economical and…

  19. Curriculum Assessment Using Artificial Neural Network and Support Vector Machine Modeling Approaches: A Case Study. IR Applications. Volume 29

    Science.gov (United States)

    Chen, Chau-Kuang

    2010-01-01

    Artificial Neural Network (ANN) and Support Vector Machine (SVM) approaches have been on the cutting edge of science and technology for pattern recognition and data classification. In the ANN model, classification accuracy can be achieved by using the feed-forward of inputs, back-propagation of errors, and the adjustment of connection weights. In…

  20. Security Technologies for Open Networking Environments (STONE)

    Energy Technology Data Exchange (ETDEWEB)

    Muftic, Sead

    2005-03-31

    Under this project SETECS performed research, created the design, and the initial prototype of three groups of security technologies: (a) middleware security platform, (b) Web services security, and (c) group security system. The results of the project indicate that the three types of security technologies can be used either individually or in combination, which enables effective and rapid deployment of a number of secure applications in open networking environments. The middleware security platform represents a set of object-oriented security components providing various functions to handle basic cryptography, X.509 certificates, S/MIME and PKCS No.7 encapsulation formats, secure communication protocols, and smart cards. The platform has been designed in the form of security engines, including a Registration Engine, Certification Engine, an Authorization Engine, and a Secure Group Applications Engine. By creating a middleware security platform consisting of multiple independent components the following advantages have been achieved - Object-oriented, Modularity, Simplified Development, and testing, Portability, and Simplified extensions. The middleware security platform has been fully designed and a preliminary Java-based prototype has been created for the Microsoft Windows operating system. The Web services security system, designed in the project, consists of technologies and applications that provide authentication (i.e., single sign), authorization, and federation of identities in an open networking environment. The system is based on OASIS SAML and XACML standards for secure Web services. Its topology comprises three major components: Domain Security Server (DSS) is the main building block of the system Secure Application Server (SAS) Secure Client In addition to the SAML and XACML engines, the authorization system consists of two sets of components An Authorization Administration System An Authorization Enforcement System Federation of identities in multi

  1. Plans & Policies for Technology in Education: A Compendium. A Technology Leadership Network Special Report.

    Science.gov (United States)

    National School Boards Association, Alexandria, VA. Inst. for the Transfer of Technology to Education.

    This document shows how education leaders nationwide--many of them part of the National School Boards Association's 345-district Technology Leadership Network--have addressed technology-related policy issues such as copyright, purchasing, network/Internet use, and ethics as well as technology planning topics including staff development, classroom…

  2. Organizational Application of Social Networking Information Technologies

    Science.gov (United States)

    Reppert, Jeffrey R.

    2012-01-01

    The focus of this qualitative research study using the Delphi method is to provide a framework for leaders to develop their own social networks. By exploring concerns in four areas, leaders may be able to better plan, implement, and manage social networking systems in organizations. The areas addressed are: (a) social networking using…

  3. Survey of Promising Technologies for 5G Networks

    Directory of Open Access Journals (Sweden)

    Nam Tuan Le

    2016-01-01

    Full Text Available As an enhancement of cellular networks, the future-generation 5G network can be considered an ultra-high-speed technology. The proposed 5G network might include all types of advanced dominant technologies to provide remarkable services. Consequently, new architectures and service management schemes for different applications of the emerging technologies need to be recommended to solve issues related to data traffic capacity, high data rate, and reliability for ensuring QoS. Cloud computing, Internet of things (IoT, and software-defined networking (SDN have become some of the core technologies for the 5G network. Cloud-based services provide flexible and efficient solutions for information and communications technology by reducing the cost of investing in and managing information technology infrastructure. In terms of functionality, SDN is a promising architecture that decouples control planes and data planes to support programmability, adaptability, and flexibility in ever-changing network architectures. However, IoT combines cloud computing and SDN to achieve greater productivity for evolving technologies in 5G by facilitating interaction between the physical and human world. The major objective of this study provides a lawless vision on comprehensive works related to enabling technologies for the next generation of mobile systems and networks, mainly focusing on 5G mobile communications.

  4. Application of wireless sensor network technology in logistics information system

    Science.gov (United States)

    Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

    2017-04-01

    This paper introduces the basic concepts of active RFID (WSN-ARFID) based on wireless sensor networks and analyzes the shortcomings of the existing RFID-based logistics monitoring system. Integrated wireless sensor network technology and the scrambling point of RFID technology. A new real-time logistics detection system based on WSN and RFID, a model of logistics system based on WSN-ARFID is proposed, and the feasibility of this technology applied to logistics field is analyzed.

  5. Resilient Disaster Network Based on Software Defined Cognitive Wireless Network Technology

    Directory of Open Access Journals (Sweden)

    Goshi Sato

    2015-01-01

    Full Text Available In order to temporally recover the information network infrastructure in disaster areas from the Great East Japan Earthquake in 2011, various wireless network technologies such as satellite IP network, 3G, and Wi-Fi were effectively used. However, since those wireless networks are individually introduced and installed but not totally integrated, some of networks were congested due to the sudden network traffic generation and unbalanced traffic distribution, and eventually the total network could not effectively function. In this paper, we propose a disaster resilient network which integrates various wireless networks into a cognitive wireless network that users can use as an access network to the Internet at the serious disaster occurrence. We designed and developed the disaster resilient network based on software defined network (SDN technology to automatically select the best network link and route among the possible access networks to the Internet by periodically monitoring their network states and evaluate those using extended AHP method. In order to verify the usefulness of our proposed system, a prototype system is constructed and its performance is evaluated.

  6. 75 FR 57521 - Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010...

    Science.gov (United States)

    2010-09-21

    ... NATIONAL SCIENCE FOUNDATION Networking and Information Technology Research and Development (NITRD...) for Networking and Information Technology Research and Development (NITRD). ACTION: Notice, request.... SUMMARY: With this notice, the National Coordination Office for Networking and Information Technology...

  7. Creation of a European network dedicated to technology transfer

    CERN Multimedia

    2008-01-01

    The CERN Council recently approved the creation of a technology transfer network, whose aim will be to improve European industry’s access to the technologies developed by the particle physics community in the Member States. The gas detectors for the TOTEM experiment (GEM) offer potential for fruitful collaboration within the framework of the TT network. Many other technologies are going down the same road.The desire to set up a technology transfer network follows on from the European Strategy for Particle Physics, approved by the CERN Council on 14 July 2006 in Lisbon. In this context, special emphasis was laid on European industry’s participation in the implementation of particle physics programmes and, in particular, its access to the new technologies developed by the scientific community. It was recognised that effort needs to be put into improving the efficiency of technology transfer...

  8. Enabling Technologies for Cognitive Optical Networks

    DEFF Research Database (Denmark)

    Borkowski, Robert

    Cognition is a new paradigm for optical networking, in which the network has capabilities to observe, plan, decide, and act autonomously in order to optimize the end-to-end performance and minimize the need for human supervision. This PhD thesis expands the state of the art on cognitive optical......, and machine learning algorithms that make cognition possible. Secondly, advanced optical performance monitoring (OPM) capabilities performed via digital signal processing (DSP) that provide CONs with necessary feedback information allowing for autonomous network optimization. The research results presented...... in this thesis were carried out in the framework of the EU project Cognitive Heterogeneous Reconfigurable Optical Network (CHRON), whose aim was to develop an architecture and implement a testbed of a cognitive network able to self-configure and self-optimize to efficiently use available resources. In order...

  9. Flow forecast by SWAT model and ANN in Pracana basin, Portugal

    NARCIS (Netherlands)

    Demirel, M.C.; Venancio, Anabela; Kahya, Ercan

    2009-01-01

    This study provides a unique opportunity to analyze the issue of flow forecast based on the soil and water assessment tool (SWAT) and artificial neural network (ANN) models. In last two decades, the ANNs have been extensively applied to various water resources system problems. In this study, the

  10. The Role of Electronic Learning Technology in Networks Systems

    International Nuclear Information System (INIS)

    Abd ELhamid, A.; Ayad, N.M.A.; Fouad, Y.; Abdelkader, T.

    2016-01-01

    Recently, Electronic Learning Technology (ELT) has been widely spread as one of the new technologies in the world through using Information and Communication Technology (ICT). One of the strategies of ELT is Simulation, for instance Military and Medical simulations that are used to avoid risks and reduce Costs. A wireless communication network refers to any network not physically connected by cables, which enables the desired convenience and mobility for the user. Wireless communication networks have been useful in areas such as commerce, education and defense. According to the nature of a particular application, they can be used in home-based and industrial systems or in commercial and military environments. Historically, Mobile Ad-hoc Networks (MANET) have primarily been used for tactical military network related applications to improve battlefield communications/ survivability. MANET is a collection of wireless nodes that can dynamically be set up anywhere and anytime without using any pre-existing network infrastructure. Mobility in wireless networks basically refers to nodes changing its point of attachment to the network. Also, how the end terminals can move, there are many mobility models described the movement of nodes, many researchers use the Random Way point Mobility Model (RWPM). In this paper, a Graphical User Interface (GUI) for RWPM simulation is introduced as a proposal to be used through ELT Project. In the research area of computer and communications networks, simulation is a very useful technique for the behavior of networks

  11. WiMAX technology and network evolution

    CERN Document Server

    Etemad, Kamran

    2010-01-01

    WiMAX, the Worldwide Interoperability for Microwave Access, represents a paradigm shift in telecommunications technology. It offers the promise of cheaper, smaller, and simpler technology compared to existing broadband options such as DSL, cable, fiber, and 3G wireless.

  12. Ado Vabbe preemia Anne Parmastole

    Index Scriptorium Estoniae

    2003-01-01

    Tartu Kunstimajas Tartu kunsti aastalõpunäitus. Kujundaja Mari Nõmmela. Anne Parmastole A. Vabbe, Silja Salmistule E-Kunstisalongi, Lii Jürgensonile EDA, Jüri Marranile Wilde kohviku, Sami Makkonenile AS Vunder ja Tartu Õlletehase A. Le Coq ning Eda Lõhmusele AS Merko Tartu preemia

  13. Cyber-physical system design with sensor networking technologies

    CERN Document Server

    Zeadally, Sherali

    2016-01-01

    This book describes how wireless sensor networking technologies can help in establishing and maintaining seamless communications between the physical and cyber systems to enable efficient, secure, reliable acquisition, management, and routing of data.

  14. Future networks and technologies supporting innovative communications

    DEFF Research Database (Denmark)

    Prasad, Ramjee

    2012-01-01

    -communications (WISDOM) that combines the aspects of personal- and cognitive radio- networks to let seamlessly bridge the virtual and physical worlds offering a constant level of all-senses, context-based, rich communication experience over fixed and wireless networks for the end users while realizing a new generation......Within a fully interconnected world, the distinct relationship between end users, consumers and providers rapidly changes towards a scenario of collaboration and competition of multiple parties within one system. ‘Convergence’, ‘ubiquitous’ and ‘smart’ are key words describing future networks...

  15. Cognitive Heterogeneous Reconfigurable Optical Networks (CHRON): Enabling Technologies and Techniques

    DEFF Research Database (Denmark)

    Tafur Monroy, Idelfonso; Zibar, Darko; Guerrero Gonzalez, Neil

    2011-01-01

    We present the approach of cognition applied to heterogeneous optical networks developed in the framework of the EU project CHRON: Cognitive Heterogeneous Reconfigurable Optical Network. We introduce and discuss in particular the technologies and techniques that will enable a cognitive optical...... network to observe, act, learn and optimizes its performance, taking into account its high degree of heterogeneity with respect to quality of service, transmission and switching techniques....

  16. Applications of artificial neural networks in medical science.

    Science.gov (United States)

    Patel, Jigneshkumar L; Goyal, Ramesh K

    2007-09-01

    Computer technology has been advanced tremendously and the interest has been increased for the potential use of 'Artificial Intelligence (AI)' in medicine and biological research. One of the most interesting and extensively studied branches of AI is the 'Artificial Neural Networks (ANNs)'. Basically, ANNs are the mathematical algorithms, generated by computers. ANNs learn from standard data and capture the knowledge contained in the data. Trained ANNs approach the functionality of small biological neural cluster in a very fundamental manner. They are the digitized model of biological brain and can detect complex nonlinear relationships between dependent as well as independent variables in a data where human brain may fail to detect. Nowadays, ANNs are widely used for medical applications in various disciplines of medicine especially in cardiology. ANNs have been extensively applied in diagnosis, electronic signal analysis, medical image analysis and radiology. ANNs have been used by many authors for modeling in medicine and clinical research. Applications of ANNs are increasing in pharmacoepidemiology and medical data mining. In this paper, authors have summarized various applications of ANNs in medical science.

  17. Knowledge network for medical technology management in Mexico.

    Science.gov (United States)

    Licona, Fabiola Martínez; Leehan, Joaquín Azpiroz; Méndez, Miguel Cadena; Yuriar, Salvador Duarte; Salazar, Raúl Molina; Gilmore, Amador Terán

    2009-10-01

    The role of biomedical engineers (BMEs) has changed widely over the years, from managing a group of technicians to the planning of large installations and the management of medical technology countrywide. As the technology has advanced, the competence of BMEs has been challenged because it is no longer possible to be an expert in every component of the technology involved in running a hospital. Our approach has been to form a network of professionals that are experts in different fields related to medical technology, where work is coordinated to provide high quality services at the planning and execution stages of projects related to medical technology. A study of the procedures involved in the procurement of medical technology has been carried out over the years. These experiences have been compared with several case studies where the approach to problem solving in this area has been multidisciplinary. Planning and execution phases of projects involving medical technology management have been identified. After several instances of collaboration among experts from different fields, a network for management of healthcare technology has been formed at our institution that incorporates the experience from different departments that were dealing separately with projects involving medical technology. This network has led us to propose this approach to solve medical technology management projects, where the strengths of each subgroup complement each other. This structure will lead to a more integrated approach to healthcare technology management and will ensure higher quality solutions.

  18. Anne-Ly Võlli: Iga inimene ja asutus vajab omamoodi lähenemist / Anne-Ly Võlli ; intervjueerinud Jaanika Kressa

    Index Scriptorium Estoniae

    Võlli, Anne-Ly, 1976-

    2009-01-01

    MTÜ Jõgevamaa Omavalitsuste Aktiviseerimiskeskus kinnitas avaliku konkursi tulemusel juhatuse liikmeks Anne-Ly Võlli, kelle ülesandeks on keskuse tegevuse juhtimine ja koostöö arendamine partneromavalitsuste ja teiste koostööpartnerite vahel

  19. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 2: Fiber optic technology and long distance networks

    Science.gov (United States)

    1986-10-01

    The study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the Executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  20. LFC based adaptive PID controller using ANN and ANFIS techniques

    Directory of Open Access Journals (Sweden)

    Mohamed I. Mosaad

    2014-12-01

    Full Text Available This paper presents an adaptive PID Load Frequency Control (LFC for power systems using Neuro-Fuzzy Inference Systems (ANFIS and Artificial Neural Networks (ANN oriented by Genetic Algorithm (GA. PID controller parameters are tuned off-line by using GA to minimize integral error square over a wide-range of load variations. The values of PID controller parameters obtained from GA are used to train both ANFIS and ANN. Therefore, the two proposed techniques could, online, tune the PID controller parameters for optimal response at any other load point within the operating range. Testing of the developed techniques shows that the adaptive PID-LFC could preserve optimal performance over the whole loading range. Results signify superiority of ANFIS over ANN in terms of performance measures.

  1. Playing tag with ANN: boosted top identification with pattern recognition

    International Nuclear Information System (INIS)

    Almeida, Leandro G.; Backović, Mihailo; Cliche, Mathieu; Lee, Seung J.; Perelstein, Maxim

    2015-01-01

    Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a “digital image" of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p T in the 1100–1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

  2. Playing tag with ANN: boosted top identification with pattern recognition

    Energy Technology Data Exchange (ETDEWEB)

    Almeida, Leandro G. [Institut de Biologie de l’École Normale Supérieure (IBENS), Inserm 1024- CNRS 8197,46 rue d’Ulm, 75005 Paris (France); Backović, Mihailo [Center for Cosmology, Particle Physics and Phenomenology - CP3,Universite Catholique de Louvain,Louvain-la-neuve (Belgium); Cliche, Mathieu [Laboratory for Elementary Particle Physics, Cornell University,Ithaca, NY 14853 (United States); Lee, Seung J. [Department of Physics, Korea Advanced Institute of Science and Technology,335 Gwahak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); School of Physics, Korea Institute for Advanced Study,Seoul 130-722 (Korea, Republic of); Perelstein, Maxim [Laboratory for Elementary Particle Physics, Cornell University,Ithaca, NY 14853 (United States)

    2015-07-17

    Many searches for physics beyond the Standard Model at the Large Hadron Collider (LHC) rely on top tagging algorithms, which discriminate between boosted hadronic top quarks and the much more common jets initiated by light quarks and gluons. We note that the hadronic calorimeter (HCAL) effectively takes a “digital image' of each jet, with pixel intensities given by energy deposits in individual HCAL cells. Viewed in this way, top tagging becomes a canonical pattern recognition problem. With this motivation, we present a novel top tagging algorithm based on an Artificial Neural Network (ANN), one of the most popular approaches to pattern recognition. The ANN is trained on a large sample of boosted tops and light quark/gluon jets, and is then applied to independent test samples. The ANN tagger demonstrated excellent performance in a Monte Carlo study: for example, for jets with p{sub T} in the 1100–1200 GeV range, 60% top-tag efficiency can be achieved with a 4% mis-tag rate. We discuss the physical features of the jets identified by the ANN tagger as the most important for classification, as well as correlations between the ANN tagger and some of the familiar top-tagging observables and algorithms.

  3. Gigabit network technology. Final technical report

    Energy Technology Data Exchange (ETDEWEB)

    Davenport, C.M.C. [ed.

    1996-10-01

    Current digital networks are evolving toward distributed multimedia with a wide variety of applications with individual data rates ranging from kb/sec to tens and hundreds of Mb/sec. Link speed requirements are pushing into the Gb/sec range and beyond the envelop of electronic networking capabilities. There is a vast amount of untapped bandwidth available in the low-attenuation communication bands of an optical fiber. The capacity in one fiber thread is enough to carry more than two thousand times as much information as all the current radio and microwave frequencies. And while fiber optics has replaced copper wire as the transmission medium of choice, the communication capacity of conventional fiber optic networks is ultimately limited by electronic processing speeds.

  4. Digital video technologies and their network requirements

    Energy Technology Data Exchange (ETDEWEB)

    R. P. Tsang; H. Y. Chen; J. M. Brandt; J. A. Hutchins

    1999-11-01

    Coded digital video signals are considered to be one of the most difficult data types to transport due to their real-time requirements and high bit rate variability. In this study, the authors discuss the coding mechanisms incorporated by the major compression standards bodies, i.e., JPEG and MPEG, as well as more advanced coding mechanisms such as wavelet and fractal techniques. The relationship between the applications which use these coding schemes and their network requirements are the major focus of this study. Specifically, the authors relate network latency, channel transmission reliability, random access speed, buffering and network bandwidth with the various coding techniques as a function of the applications which use them. Such applications include High-Definition Television, Video Conferencing, Computer-Supported Collaborative Work (CSCW), and Medical Imaging.

  5. Technology assessment, expectations and networks : An illustration using new materials

    NARCIS (Netherlands)

    Den Hond, Frank; Groenewegen, Peter; Vergragt, Philip

    1990-01-01

    This presents an approach to forecasting and identifying the positive and negative consequences of a new technology. It outlines aspects of the theory of actor networks, and shows how it can help the analysis. As a specific example, to aid communication, it considers new materials technology

  6. Perspectives on next-generation technology for environmental sensor networks

    Science.gov (United States)

    Barbara J. Benson; Barbara J. Bond; Michael P. Hamilton; Russell K. Monson; Richard Han

    2009-01-01

    Sensor networks promise to transform and expand environmental science. However, many technological difficulties must be overcome to achieve this potential. Partnerships of ecologists with computer scientists and engineers are critical in meeting these challenges. Technological issues include promoting innovation in new sensor design, incorporating power optimization...

  7. Annely Peebo kutsus presidendi kontserdile / Maria Ulfsak

    Index Scriptorium Estoniae

    Ulfsak, Maria, 1981-

    2003-01-01

    Laulja Anneli Peebo kohtus president Arnold Rüütliga, et anda üle kutse Andrea Bocelli ja Annely Peebo ühiskontserdile. Vt. samas: Andrea Bocelli ja Annely Peebo kontsert Tallinna lauluväljakul 23. augustil; Andrea Bocelli

  8. Applying Trusted Network Technology To Process Control Systems

    Science.gov (United States)

    Okhravi, Hamed; Nicol, David

    Interconnections between process control networks and enterprise networks expose instrumentation and control systems and the critical infrastructure components they operate to a variety of cyber attacks. Several architectural standards and security best practices have been proposed for industrial control systems. However, they are based on older architectures and do not leverage the latest hardware and software technologies. This paper describes new technologies that can be applied to the design of next generation security architectures for industrial control systems. The technologies are discussed along with their security benefits and design trade-offs.

  9. Organized technology. Networks and innovation in technical systems

    International Nuclear Information System (INIS)

    Shrum, W.

    1985-01-01

    The book is based on a study of radioactive waste and solar cell research. Social network methods are used to illuminate the differences between technologies such as nuclear waste disposal, dominated by the federal government, and potentially profitable technologies such as photovoltaics, where the private sector plays a larger role. The book examines the interaction of government agencies, national laboratories, private firms, universities, regulatory agencies, Congress, and public-interest groups in the technology development process

  10. Damage level prediction of non-reshaped berm breakwater using ANN, SVM and ANFIS models

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; SubbaRao; Harish, N.; Lokesha

    Marine Structures Laboratory, Department of Applied Mechanics and Hydraulics, NITK, Surathkal, India. Soft computing techniques like Artificial Neural Network (ANN), Support Vector Machine (SVM) and Adaptive Neuro Fuzzy Inference system (ANFIS) models...

  11. Application of local area network technology in an engineering environment

    International Nuclear Information System (INIS)

    Powell, A.D.; Sokolowski, M.A.

    1990-01-01

    This paper reports on the application of local area network technology in an engineering environment. Mobil Research and Development Corporation Engineering, Dallas, texas has installed a local area network (LAN) linking over 85 microcomputers. This network, which has been in existence for more than three years, provides common access by all engineers to quality output devices such as laser printers and multi-color pen plotters; IBM mainframe connections; electronic mail and file transfer; and common engineering program. The network has been expanded via a wide area ethernet network to link the Dallas location with a functionally equivalent LAN of over 400 microcomputers in Princeton, N.J. Additionally, engineers on assignment at remote areas in Europe, U.S., Africa and project task forces have dial-in access to the network via telephone lines

  12. A Network Analysis Model for Selecting Sustainable Technology

    Directory of Open Access Journals (Sweden)

    Sangsung Park

    2015-09-01

    Full Text Available Most companies develop technologies to improve their competitiveness in the marketplace. Typically, they then patent these technologies around the world in order to protect their intellectual property. Other companies may use patented technologies to develop new products, but must pay royalties to the patent holders or owners. Should they fail to do so, this can result in legal disputes in the form of patent infringement actions between companies. To avoid such situations, companies attempt to research and develop necessary technologies before their competitors do so. An important part of this process is analyzing existing patent documents in order to identify emerging technologies. In such analyses, extracting sustainable technology from patent data is important, because sustainable technology drives technological competition among companies and, thus, the development of new technologies. In addition, selecting sustainable technologies makes it possible to plan their R&D (research and development efficiently. In this study, we propose a network model that can be used to select the sustainable technology from patent documents, based on the centrality and degree of a social network analysis. To verify the performance of the proposed model, we carry out a case study using actual patent data from patent databases.

  13. Networks dynamics in the case of emerging technologies

    Energy Technology Data Exchange (ETDEWEB)

    Rotolo, D

    2016-07-01

    This research in progress aims at increasing our understanding of how collaborative networks form, evolve and are configured in the case of emerging technologies. The architecture of the relationships among the variety of organisational actors involved in the emergence process exerts a significant influence in shaping technological change in certain directions rather than others, especially in the early stage of emergence. As a result, socially optimal or desirable technological trajectories may be ‘opportunistically’ rejected. Our empirical analysis is based on a case-study of an emerging medical technology, namely ‘microneedles’. On the basis of co-authorship data reported in 1,943 publications on the topic from 1990 to 2014, longitudinal collaboration (co-authorship) networks were built at two levels: affiliation and author. We examined the dynamics of co-authorship networks by building on recent methodological advancements in network analysis, i.e. Exponential Random Graph Models (ERGMs). These models enable us to make statistical inferences about on the extent to which a network configuration occurs more than could be expected by chance and to identify which social mechanisms may be shaping the network in certain configurations. The findings of the statistical analyses (currently in progress) combined with the qualitative understanding of the case will increase our understanding of which mechanisms are more likely to drive the network dynamics in the case of emerging technologies. These include evidence of the extent to which the likelihood of forming, maintaining, or terminating ties among actors (authors or affiliations) is affected by actors’ covariates such as types of organisations, diversity/specialisation of the research undertaken, and status. These findings have potential to provide important inputs for policymaking process in the case of emerging technologies. (Author)

  14. Networks dynamics in the case of emerging technologies

    International Nuclear Information System (INIS)

    Rotolo, D

    2016-01-01

    This research in progress aims at increasing our understanding of how collaborative networks form, evolve and are configured in the case of emerging technologies. The architecture of the relationships among the variety of organisational actors involved in the emergence process exerts a significant influence in shaping technological change in certain directions rather than others, especially in the early stage of emergence. As a result, socially optimal or desirable technological trajectories may be ‘opportunistically’ rejected. Our empirical analysis is based on a case-study of an emerging medical technology, namely ‘microneedles’. On the basis of co-authorship data reported in 1,943 publications on the topic from 1990 to 2014, longitudinal collaboration (co-authorship) networks were built at two levels: affiliation and author. We examined the dynamics of co-authorship networks by building on recent methodological advancements in network analysis, i.e. Exponential Random Graph Models (ERGMs). These models enable us to make statistical inferences about on the extent to which a network configuration occurs more than could be expected by chance and to identify which social mechanisms may be shaping the network in certain configurations. The findings of the statistical analyses (currently in progress) combined with the qualitative understanding of the case will increase our understanding of which mechanisms are more likely to drive the network dynamics in the case of emerging technologies. These include evidence of the extent to which the likelihood of forming, maintaining, or terminating ties among actors (authors or affiliations) is affected by actors’ covariates such as types of organisations, diversity/specialisation of the research undertaken, and status. These findings have potential to provide important inputs for policymaking process in the case of emerging technologies. (Author)

  15. An Experimental Investigation into the Optimal Processing Conditions for the CO2 Laser Cladding of 20 MnCr5 Steel Using Taguchi Method and ANN

    Science.gov (United States)

    Mondal, Subrata; Bandyopadhyay, Asish.; Pal, Pradip Kumar

    2010-10-01

    This paper presents the prediction and evaluation of laser clad profile formed by means of CO2 laser applying Taguchi method and the artificial neural network (ANN). Laser cladding is one of the surface modifying technologies in which the desired surface characteristics of any component can be achieved such as good corrosion resistance, wear resistance and hardness etc. Laser is used as a heat source to melt the anti-corrosive powder of Inconel-625 (Super Alloy) to give a coating on 20 MnCr5 substrate. The parametric study of this technique is also attempted here. The data obtained from experiments have been used to develop the linear regression equation and then to develop the neural network model. Moreover, the data obtained from regression equations have also been used as supporting data to train the neural network. The artificial neural network (ANN) is used to establish the relationship between the input/output parameters of the process. The established ANN model is then indirectly integrated with the optimization technique. It has been seen that the developed neural network model shows a good degree of approximation with experimental data. In order to obtain the combination of process parameters such as laser power, scan speed and powder feed rate for which the output parameters become optimum, the experimental data have been used to develop the response surfaces.

  16. Disruptive technologies and networking in telecom industries

    DEFF Research Database (Denmark)

    Madsen, Erik Strøjer; Hartington, Simon

    in the telecommunication industry and finds significant similarities between the industry development and the literature on disruptive technology, which finds that incumbent companies are not able to react in a successful way when disruptions occur in their industry. By studying how the telecommunication industry...

  17. Towards the systematic development of medical networking technology.

    Science.gov (United States)

    Faust, Oliver; Shetty, Ravindra; Sree, S Vinitha; Acharya, Sripathi; Acharya U, Rajendra; Ng, E Y K; Poo, Chua Kok; Suri, Jasjit

    2011-12-01

    Currently, there is a disparity in the availability of doctors between urban and rural areas of developing countries. Most experienced doctors and specialists, as well as advanced diagnostic technologies, are available in urban areas. People living in rural areas have less or sometimes even no access to affordable healthcare facilities. Increasing the number of doctors and charitable medical hospitals or deploying advanced medical technologies in these areas might not be economically feasible, especially in developing countries. We need to mobilize science and technology to master this complex, large scale problem in an objective, logical, and professional way. This can only be achieved with a collaborative effort where a team of experts works on both technical and non-technical aspects of this health care divide. In this paper we use a systems engineering framework to discuss hospital networks which might be solution for the problem. We argue that with the advancement in communication and networking technologies, economically middle class people and even some rural poor have access to internet and mobile communication systems. Thus, Hospital Digital Networking Technologies (HDNT), such as telemedicine, can be developed to utilize internet, mobile and satellite communication systems to connect primitive rural healthcare centers to well advanced modern urban setups and thereby provide better consultation and diagnostic care to the needy people. This paper describes requirements and limitations of the HDNTs. It also presents the features of telemedicine, the implementation issues and the application of wireless technologies in the field of medical networking.

  18. Emergent technologies, networks that lurks the sociability

    Directory of Open Access Journals (Sweden)

    Luis Gregorio Iglesias Sahagún

    2018-05-01

    Full Text Available This paper highlights several symptoms that can be observed in multiple societies since the installation of so called “emergent technologies”, especially technologies of information and communication. Supported on the idea that this technological capacity provokes an alteration of the culture, which becomes a connectionist neo-capitalism, we suggest that besides the constriction of the “field of the possible” produced by the system of a central market economy, the appliances and technological devices – the portable ones particularly-, exerts a new constriction and, actually, re-organization, of this “field of the possible”“. We find this as disturbing signs of loss of autonomy, such as a reduction in margins for the exercise of autonomy by individuals and collectivities. We will argue that the situation becomes sophisticated in societies with a high installed capacity of communication, information and transportation technologies. In such societies, in fact, reticular forms are lavished in multiple areas: production, provision of services (shared economy, neighborhood, school, university, etc. No doubt “the network” is the metaphor that best conveys much of what happens and the ways it happens in our daily lives. Starting from a conception of sociability, understood as the form that concurrences can adopt, the form of “doing something together”, the forms of “putting something in common”, the forms of “doing about that something put in common “, we hypothesized that with emergent technologies and social reticulation, a vector of centrifugal component that blocks, hinders or inhibits sociability has also been set in motion.

  19. Technology Licensing Strategy for Network Product in a Service Industry

    Directory of Open Access Journals (Sweden)

    Xianpei Hong

    2015-01-01

    Full Text Available Technology licensing has gained significant attention in literature and practice as a rapid and effective way to improve firm’s capability of technology innovation. In this paper, we investigate a duopolistic service provider competition market, where service providers develop and sell a kind of network product. In this setting, we analyze the innovating service provider’s four licensing strategies: no licensing, fixed fee licensing, royalty licensing, and two-part tariff licensing. The literature suggests that when the network products can be completely substituted, two-part tariff licensing is the optimal strategy of the innovating service provider. We find that when the network products cannot be completely substituted, two-part tariff licensing is not always optimal. The degree of the product differentiation, the intensity of the network effects, and the R&D cost of the potential licensee play a key role in determining the innovating service provider’s optimal licensing strategies.

  20. Privacy and technology challenges for ubiquitous social networking

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Seet, Boon-Chong

    2015-01-01

    towards important challenges such as social sensing, enabling social networking and privacy protection. In this paper we firstly investigate the methods and technologies for acquisition of the relevant context for promotion of sociability among inhabitants of USN environments. Afterwards, we review...... architectures and techniques for enabling social interactions between participants. Finally, we identify privacy as the major challenge for networking in USN environments. Consequently, we depict design guidelines and review privacy protection models for facilitating personal information disclosure....

  1. MUPBED - interworking challenges in a multi-domain and multi-technology network environment

    DEFF Research Database (Denmark)

    Foisel, Hans-Martin; Spaeth, Jan; Cavazzoni, Carlo

    2007-01-01

    Todays data transport networks are evolving continuously towards customer oriented and application aware networks. This evolution happens in Europe in a highly diverse network environment, covering multiple network domains, layers, technologies, control and management approaches. In this paper...

  2. Router Agent Technology for Policy-Based Network Management

    Science.gov (United States)

    Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston

    2011-01-01

    This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

  3. Cognitive wireless networks using the CSS technology

    CERN Document Server

    Li, Meiling; Pan, Jeng-Shyang

    2016-01-01

    The aim of this book is to provide some useful methods to improve the spectrum sensing performance in a systematic way, and point out an effective method for the application of cognitive radio technology in wireless communications. The book gives a state-of-the-art survey and proposes some new cooperative spectrum sensing (CSS) methods attempting to achieve better performance. For each CSS, the main idea and corresponding algorithm design are elaborated in detail. This book covers the fundamental concepts and the core technologies of CSS, especially its latest developments. Each chapter is presented in a self-sufficient and independent way so that the reader can select the chapters interesting to them. The methodologies are described in detail so that the readers can repeat the corresponding experiments easily. It will be a useful book for researchers helping them to understand the classifications of CSS, inspiring new ideas about the novel CSS technology for CR, and learning new ideas from the current status...

  4. A brief review of advances in complex networks of nuclear science and technology field

    International Nuclear Information System (INIS)

    Fang Jinqing

    2010-01-01

    A brief review of advances in complex networks of nuclear science and technology field at home and is given and summarized. These complex networks include: nuclear energy weapon network, network centric warfare, beam transport networks, continuum percolation evolving network associated with nuclear reactions, global nuclear power station network, (nuclear) chemistry reaction networks, radiological monitoring and anti-nuclear terror networks, and so on. Some challenge issues and development prospects of network science are pointed out finally. (authors)

  5. Control of coupled oscillator networks with application to microgrid technologies.

    Science.gov (United States)

    Skardal, Per Sebastian; Arenas, Alex

    2015-08-01

    The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable synchronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

  6. Control of coupled oscillator networks with application to microgrid technologies

    Science.gov (United States)

    Arenas, Alex

    The control of complex systems and network-coupled dynamical systems is a topic of vital theoretical importance in mathematics and physics with a wide range of applications in engineering and various other sciences. Motivated by recent research into smart grid technologies, we study the control of synchronization and consider the important case of networks of coupled phase oscillators with nonlinear interactions-a paradigmatic example that has guided our understanding of self-organization for decades. We develop a method for control based on identifying and stabilizing problematic oscillators, resulting in a stable spectrum of eigenvalues, and in turn a linearly stable syn- chronized state. The amount of control, that is, number of oscillators, required to stabilize the network is primarily dictated by the coupling strength, dynamical heterogeneity, and mean degree of the network, and depends little on the structural heterogeneity of the network itself.

  7. Do social networks and technological capabilities help knowledge management?

    Directory of Open Access Journals (Sweden)

    Encarnación García-Sánchez

    2017-12-01

    Full Text Available Dynamic capabilities are currently becoming an important extension of the theory of resources and capabilities that enables companies to adapt better in the current competitive environment. This paper examines how knowledge management, a dynamic function related to management or administration of a set of knowledge flows, develops thanks to the greater dynamism of social networks. It then shows how this relationship is especially strengthened by different technological capabilities. To achieve these goals, the paper examines the main tools that permit companies to develop an ability to achieve competitive advantage relative to the technological capabilities of managers and workers, social networks and knowledge management.

  8. 75 FR 55360 - Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010...

    Science.gov (United States)

    2010-09-10

    ... NATIONAL SCIENCE FOUNDATION Networking and Information Technology Research and Development (NITRD... Information Technology Research and Development (NITRD). ACTION: Notice, request for public comment. FOR..., the National Coordination Office for Networking and Information Technology Research and Development...

  9. Bridging the Gap from Networking Technologies to Applications: Workshop Report

    Science.gov (United States)

    Johnson, Marjory J.; desJardins, Richard

    2000-01-01

    The objective of the Next Generation Internet (NGI) Federal program is threefold, encompassing development of networking technologies, high-performance network testbeds, and revolutionary applications. There have been notable advances in emerging network technologies and several nationwide testbeds have been established, but the integration of emerging technologies into applications is lagging. To help bridge this gap between developers of NGI networking technologies and developers of NGI applications, the NASA Research and Education Network (NREN) project hosted a two-day workshop at NASA Ames Research Center in August 1999. This paper presents a summary of the results of this workshop and also describes some of the challenges NREN is facing while incorporating new technologies into HPCC and other NASA applications. The workshop focused on three technologies - Quality of Service (QoS), advanced multicast, and security-and five major NGI application areas - telemedicine, digital earth, digital video, distributed data-intensive applications, and computational infrastructure applications. Network technology experts, application developers, and NGI testbed representatives came together at the workshop to promote cross-fertilization between the groups. Presentations on the first day, including an overview of the three technologies, application case studies and testbed status reports, laid the foundation for discussions on the second day. The objective of these latter discussions, held within smaller breakout groups, was to establish a coherent picture of the current status of the various pieces of each of the three technologies, to create a roadmap outlining future technology development, and to offer technological guidance to application developers. In this paper we first present a brief overview of the NGI applications that were represented at the workshop, focusing on the identification of technological advances that have successfully been incorporated in each

  10. Annäherung Approaching

    Directory of Open Access Journals (Sweden)

    Carola Hilmes

    2007-03-01

    Full Text Available Das von Stefan Moses zusammengestellte „Bilderbuch“ zeigt Fotos von Ilse Aichinger. Sie selbst kommt durch eine Reihe von Geschichten und Gedichten zu Wort. In diesen intimen Dialog werden auch die Leser/-innen einbezogen. Das ermöglicht Annäherung.This “Picture Book”, compiled by Stefan Moses, displays photographs of Ilse Aichinger. She is also given voice through a series of stories and poems. The reader is also drawn into this intimate dialogue, thus making it possible for image, text, and reader to converge.

  11. Software-Defined Networks as a Stage of the Network Technology Evolution

    Directory of Open Access Journals (Sweden)

    A. A. Krasotin

    2013-01-01

    Full Text Available The authors of the article focus on the concept of a software defined network. In the beginning, the brief historical account is given concerning software defined networks as a scientific concept, its formation and technological and scientific meaning. The software defined network concept is treated in the article not as the final state-of-the-art in networking, but rather as a possible step and direction in the development of a networking paradigm. The article touches on pros and cons as well of the software defined networking and gives an account of possible stages of development of this technology in the context of other technologies, considering its hybrid with MPLS, as an example. OpenFlow protocol constitutes the main part of the article. The authors further discuss various kinds of existing libraries realizing programmable management routines for a software defined network using OpenFlow. All of these libraries provide API for building modular applications for software defined network management. Touching on practical side of implementation the results of comparative tests of throughput and latency, achieved with these libraries are shown.

  12. Reconfiguring global pharmaceutical value networks through targeted technology interventions

    OpenAIRE

    Harrington, Tomas Seosamh; Phillips, MA; Srai, Jagjit Singh

    2016-01-01

    Targeting a series of advanced manufacturing technology (AMT) ‘interventions’ provides the potential for significant step changes across the pharmaceutical value chain, from early stage ‘system discovery’ and clinical trials, through to novel service supply models. This research explores future value network configurations which, when aligned with disruptive shifts in technology (process and digital), may enable alternative routes to medicines production and the delivery of additional value t...

  13. Comparison of Conventional and ANN Models for River Flow Forecasting

    Science.gov (United States)

    Jain, A.; Ganti, R.

    2011-12-01

    Hydrological models are useful in many water resources applications such as flood control, irrigation and drainage, hydro power generation, water supply, erosion and sediment control, etc. Estimates of runoff are needed in many water resources planning, design development, operation and maintenance activities. River flow is generally estimated using time series or rainfall-runoff models. Recently, soft artificial intelligence tools such as Artificial Neural Networks (ANNs) have become popular for research purposes but have not been extensively adopted in operational hydrological forecasts. There is a strong need to develop ANN models based on real catchment data and compare them with the conventional models. In this paper, a comparative study has been carried out for river flow forecasting using the conventional and ANN models. Among the conventional models, multiple linear, and non linear regression, and time series models of auto regressive (AR) type have been developed. Feed forward neural network model structure trained using the back propagation algorithm, a gradient search method, was adopted. The daily river flow data derived from Godavari Basin @ Polavaram, Andhra Pradesh, India have been employed to develop all the models included here. Two inputs, flows at two past time steps, (Q(t-1) and Q(t-2)) were selected using partial auto correlation analysis for forecasting flow at time t, Q(t). A wide range of error statistics have been used to evaluate the performance of all the models developed in this study. It has been found that the regression and AR models performed comparably, and the ANN model performed the best amongst all the models investigated in this study. It is concluded that ANN model should be adopted in real catchments for hydrological modeling and forecasting.

  14. Elastic optical networks architectures, technologies, and control

    CERN Document Server

    Velasco, Luis

    2016-01-01

    This book addresses challenges and potential solutions surrounding the dramatic yearly increases in bandwidth demand. The editors discuss the predicament surrounding current growth, which is predicted to continue because of the proliferation of disruptive, high bandwidth applications like video and cloud applications. They also discuss that in addition to growth, traffic will become much more dynamic, both in time and direction. The contributors show how large changes in traffic magnitude during a 24-hour period can be observed, as day-time business users have very different demands to evening-time residential customers, and how this plays into addressing future challenges. In addition, they discuss potential solutions for the issues surrounding situations where multiple content and cloud service providers offer competing services, causing the traffic direction to become more dynamic. The contributors discuss that although the WDM transponder technology can be upgraded to 100Gb/s in the short to medium term, ...

  15. Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

    Directory of Open Access Journals (Sweden)

    Maytham S. Ahmed

    2016-09-01

    Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

  16. Effect of network topology on the spreading of technologies

    International Nuclear Information System (INIS)

    Kocsis, G.; Kun, F.

    2007-01-01

    statistics. We showed that the topology of social contacts of agents plays a significant role in the spreading of telecommunication technologies. To make the model more realistic we considered networks of agents with small-world and scale-free properties. Based on computer simulations we showed that a complex system of a large number of local communities is more favorable for the spreading of technologies than a fully interconnected one

  17. Secure, Mobile, Wireless Network Technology Designed, Developed, and Demonstrated

    Science.gov (United States)

    Ivancic, William D.; Paulsen, Phillip E.

    2004-01-01

    The inability to seamlessly disseminate data securely over a high-integrity, wireless broadband network has been identified as a primary technical barrier to providing an order-of-magnitude increase in aviation capacity and safety. Secure, autonomous communications to and from aircraft will enable advanced, automated, data-intensive air traffic management concepts, increase National Air Space (NAS) capacity, and potentially reduce the overall cost of air travel operations. For the first time ever, secure, mobile, network technology was designed, developed, and demonstrated with state-ofthe- art protocols and applications by a diverse, cooperative Government-industry team led by the NASA Glenn Research Center. This revolutionary technology solution will make fundamentally new airplane system capabilities possible by enabling secure, seamless network connections from platforms in motion (e.g., cars, ships, aircraft, and satellites) to existing terrestrial systems without the need for manual reconfiguration. Called Mobile Router, the new technology autonomously connects and configures networks as they traverse from one operating theater to another. The Mobile Router demonstration aboard the Neah Bay, a U.S. Coast Guard vessel stationed in Cleveland, Ohio, accomplished secure, seamless interoperability of mobile network systems across multiple domains without manual system reconfiguration. The Neah Bay was chosen because of its low cost and communications mission similarity to low-Earth-orbiting satellite platforms. This technology was successfully advanced from technology readiness level (TRL) 2 (concept and/or application formation) to TRL 6 (system model or prototype demonstration in a relevant environment). The secure, seamless interoperability offered by the Mobile Router and encryption device will enable several new, vehicle-specific and systemwide technologies to perform such things as remote, autonomous aircraft performance monitoring and early detection and

  18. Projekt "Baltenet - The Baltic Technology Network" / Leonid Pai

    Index Scriptorium Estoniae

    Pai, Leonid

    2005-01-01

    Baltenet - The Baltic Technology Network on projekt, mille alusel teevad koostööd tehniliste erialade koolituse arendamiseks Baltimere äärsetes riikides neli kutseõppeasutust Soomest, Rootsist, Lätis ja Eestist. Projekti rahastab Euroopa Liidu Leonardo da Vinci programm

  19. TECHNOLOGY TRANSFER NETWORKS ON PAPAYA PRODUCTION WITH TRANSITIONAL GROWERS

    Directory of Open Access Journals (Sweden)

    Octavio Cano-Reyes

    2012-11-01

    Full Text Available Social networks analysis applied to rural innovation processes becomes a very useful technology transfer tool, since it helps to understand the complexity of social relationships among people and/or institutions in their environment, and it also defines those innovation networks given in specific working groups or regions. This study was conducted from April to May 2011 to determine those networks and key players present in the group of growers associated as “Productora y Comercializadora de Papaya de Cotaxtla S.P.R. de R.L.”, that influence the technology transfer process in Cotaxtla, Veracruz, Mexico. Data were analyzed using UCINET 6 software. Three centrality measures were obtained: range, degree of mediation and closeness. Of 32 network players, 27 actively diffuse innovations according to their interests; alliances must be established with them to transfer technology. Four growers stand out as central actors, which along with the Instituto Nacional de Investigaciones Forestales Agricolas y Pecuarias, the Colegio de Postgraduados and the growers’ organization itself, could be the most appropriate actors to establish a technology transfer program to accelerate the diffusion and adoption of innovations. Wholesalers, middlemen and credit institutions do not participate in this process, but having capital they could be incorporated in the innovation diffusion process.

  20. Solar radiation modelling using ANNs for different climates in China

    International Nuclear Information System (INIS)

    Lam, Joseph C.; Wan, Kevin K.W.; Yang, Liu

    2008-01-01

    Artificial neural networks (ANNs) were used to develop prediction models for daily global solar radiation using measured sunshine duration for 40 cities covering nine major thermal climatic zones and sub-zones in China. Coefficients of determination (R 2 ) for all the 40 cities and nine climatic zones/sub-zones are 0.82 or higher, indicating reasonably strong correlation between daily solar radiation and the corresponding sunshine hours. Mean bias error (MBE) varies from -3.3 MJ/m 2 in Ruoqiang (cold climates) to 2.19 MJ/m 2 in Anyang (cold climates). Root mean square error (RMSE) ranges from 1.4 MJ/m 2 in Altay (severe cold climates) to 4.01 MJ/m 2 in Ruoqiang. The three principal statistics (i.e., R 2 , MBE and RMSE) of the climatic zone/sub-zone ANN models are very close to the corresponding zone/sub-zone averages of the individual city ANN models, suggesting that climatic zone ANN models could be used to estimate global solar radiation for locations within the respective zones/sub-zones where only measured sunshine duration data are available. (author)

  1. AFRA Network for Education in Nuclear Science and Technology

    International Nuclear Information System (INIS)

    Hashim, O.N.; Wanjala, F.

    2017-01-01

    The Africa Regional Cooperative Agreement for Research Development and Training related to Science and Technology (AFRA) established the AFRA Network for Education in Nuclear Science and Technology (AFRA-NEST) in order to implement AFRA strategy on Human Resource Development (HRD) and Nuclear Knowledge Management (NKM). The strategies for implementing the objectives are: to use ICT for web-based education and training; recognition of Regional Designated Centres (RDCs) for professional nuclear education in nuclear science and technology, and organization of harmonized and accredited programs at tertiary levels and awarding of fellowships/scholarships to young and brilliant students for teaching and research in the various nuclear disciplines

  2. [Anne Arold. Kontrastive Analyse...] / Paul Alvre

    Index Scriptorium Estoniae

    Alvre, Paul, 1921-2008

    2001-01-01

    Arvustus: Arold, Anne. Kontrastive analyse der Wortbildungsmuster im Deutschen und im Estnischen (am Beispiel der Aussehensadjektive). Tartu, 2000. (Dissertationes philologiae germanicae Universitatis Tartuensis)

  3. Educational Technology Network: a computer conferencing system dedicated to applications of computers in radiology practice, research, and education.

    Science.gov (United States)

    D'Alessandro, M P; Ackerman, M J; Sparks, S M

    1993-11-01

    Educational Technology Network (ET Net) is a free, easy to use, on-line computer conferencing system organized and funded by the National Library of Medicine that is accessible via the SprintNet (SprintNet, Reston, VA) and Internet (Merit, Ann Arbor, MI) computer networks. It is dedicated to helping bring together, in a single continuously running electronic forum, developers and users of computer applications in the health sciences, including radiology. ET Net uses the Caucus computer conferencing software (Camber-Roth, Troy, NY) running on a microcomputer. This microcomputer is located in the National Library of Medicine's Lister Hill National Center for Biomedical Communications and is directly connected to the SprintNet and the Internet networks. The advanced computer conferencing software of ET Net allows individuals who are separated in space and time to unite electronically to participate, at any time, in interactive discussions on applications of computers in radiology. A computer conferencing system such as ET Net allows radiologists to maintain contact with colleagues on a regular basis when they are not physically together. Topics of discussion on ET Net encompass all applications of computers in radiological practice, research, and education. ET Net has been in successful operation for 3 years and has a promising future aiding radiologists in the exchange of information pertaining to applications of computers in radiology.

  4. Advanced Communication and Networking Technologies for Mars Exploration

    Science.gov (United States)

    Bhasin, Kul; Hayden, Jeff; Agre, Jonathan R.; Clare, Loren P.; Yan, Tsun-Yee

    2001-01-01

    Next-generation Mars communications networks will provide communications and navigation services to a wide variety of Mars science vehicles including: spacecraft that are arriving at Mars, spacecraft that are entering and descending in the Mars atmosphere, scientific orbiter spacecraft, spacecraft that return Mars samples to Earth, landers, rovers, aerobots, airplanes, and sensing pods. In the current architecture plans, the communication services will be provided using capabilities deployed on the science vehicles as well as dedicated communication satellites that will together make up the Mars network. This network will evolve as additional vehicles arrive, depart or end their useful missions. Cost savings and increased reliability will result from the ability to share communication services between missions. This paper discusses the basic architecture that is needed to support the Mars Communications Network part of NASA's Space Science Enterprise (SSE) communications architecture. The network may use various networking technologies such as those employed in the terrestrial Internet, as well as special purpose deep-space protocols to move data and commands autonomously between vehicles, at disparate Mars vicinity sites (on the surface or in near-Mars space) and between Mars vehicles and earthbound users. The architecture of the spacecraft on-board local communications is being reconsidered in light of these new networking requirements. The trend towards increasingly autonomous operation of the spacecraft is aimed at reducing the dependence on resource scheduling provided by Earth-based operators and increasing system fault tolerance. However, these benefits will result in increased communication and software development requirements. As a result, the envisioned Mars communications infrastructure requires both hardware and protocol technology advancements. This paper will describe a number of the critical technology needs and some of the ongoing research

  5. Single Frequency Network Based Distributed Passive Radar Technology

    Directory of Open Access Journals (Sweden)

    Wan Xian-rong

    2015-01-01

    Full Text Available The research and application of passive radar are heading from single transmitter-receiver pair to multiple transmitter-receiver pairs. As an important class of the illuminators of opportunity, most of modern digital broadcasting and television systems work on Single Frequency Network (SFN, which intrinsically determines that the passive radar based on such illuminators must be distributed and networked. In consideration of the remarkable working and processing mode of passive radar under SFN configuration, this paper proposes the concept of SFN-based Distributed Passive Radar (SDPR. The main characteristics and key problems of SDPR are first described. Then several potential solutions are discussed for part of the key technologies. The feasibility of SDPR is demonstrated by preliminary experimental results. Finally, the concept of four network convergence that includes the broadcast based passive radar network is conceived, and its application prospects are discussed.

  6. Enhancement of RWSN Lifetime via Firework Clustering Algorithm Validated by ANN

    Directory of Open Access Journals (Sweden)

    Ahmad Ali

    2018-03-01

    Full Text Available Nowadays, wireless power transfer is ubiquitously used in wireless rechargeable sensor networks (WSNs. Currently, the energy limitation is a grave concern issue for WSNs. However, lifetime enhancement of sensor networks is a challenging task need to be resolved. For addressing this issue, a wireless charging vehicle is an emerging technology to expand the overall network efficiency. The present study focuses on the enhancement of overall network lifetime of the rechargeable wireless sensor network. To resolve the issues mentioned above, we propose swarm intelligence based hard clustering approach using fireworks algorithm with the adaptive transfer function (FWA-ATF. In this work, the virtual clustering method has been applied in the routing process which utilizes the firework optimization algorithm. Still now, an FWA-ATF algorithm yet not applied by any researcher for RWSN. Furthermore, the validation study of the proposed method using the artificial neural network (ANN backpropagation algorithm incorporated in the present study. Different algorithms are applied to evaluate the performance of proposed technique that gives the best results in this mechanism. Numerical results indicate that our method outperforms existing methods and yield performance up to 80% regarding energy consumption and vacation time of wireless charging vehicle.

  7. Home Network Technologies and Automating Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    McParland, Charles

    2009-12-01

    sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

  8. Gigabit Satellite Network for NASA's Advanced Communication Technology Satellite (ACTS)

    Science.gov (United States)

    Hoder, Douglas; Bergamo, Marcos

    1996-01-01

    The advanced communication technology satellite (ACTS) gigabit satellite network provides long-haul point-to-point and point-to-multipoint full-duplex SONET services over NASA's ACTS. at rates up to 622 Mbit/s (SONET OC-12), with signal quality comparable to that obtained with terrestrial fiber networks. Data multiplexing over the satellite is accomplished using time-division multiple access (TDMA) techniques coordinated with the switching and beam hopping facilities provided by ACTS. Transmissions through the satellite are protected with Reed-Solomon encoding. providing virtually error-free transmission under most weather conditions. Unique to the system are a TDMA frame structure and satellite synchronization mechanism that allow: (a) very efficient utilization of the satellite capacity: (b) over-the-satellite dosed-loop synchronization of the network in configurations with up to 64 ground stations: and (c) ground station initial acquisition without collisions with existing signalling or data traffic. The user interfaces are compatible with SONET standards, performing the function of conventional SONET multiplexers and. as such. can be: readily integrated with standard SONET fiber-based terrestrial networks. Management of the network is based upon the simple network management protocol (SNMP). and includes an over-the-satellite signalling network and backup terrestrial internet (IP-based) connectivity. A description of the ground stations is also included.

  9. Work of scientific and technological information under network environment

    International Nuclear Information System (INIS)

    Chen Yingxi; Huang Daifu; Yang Lifeng

    2010-01-01

    With the development of internet and information technology, the work of scientific and technological information is faced with great challenge. This article expounds the new changes of scientific and technological information in enterprise under network environment by giving a minute description on the situation the work faced and characteristic of the work. Not only does it carry out enthusiastic discussion upon problems which are present in the work of scientific and technological information in the company, but puts forward proposals and specific measures as well. Service theory is also offered by adjusting and reforming the resources construction, service ways and the job of providing contents. We should take vigorous action to the research work of scientific and technological information, changing the information directional service into knowledge providing service. (authors)

  10. Science of the science, drug discovery and artificial neural networks.

    Science.gov (United States)

    Patel, Jigneshkumar

    2013-03-01

    Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

  11. Applicability of new radio technologies for advanced UMTS networks

    Directory of Open Access Journals (Sweden)

    A. Dekorsy

    2004-01-01

    Full Text Available An expanded effort is under the way to support the evolution of UMTS (Universal Mobile Telecommunication System. Apart from delivering high data rates, future UMTS releases will also require to provide high network performance in terms of system capacity, low radiated power, and high coverage. Well promising performance-enhancing technologies are smart antennas as well as multiuser detection. Although these new radio technologies have recently been subject to intense research, main UMTS network integration aspects with their specific constraints have been neglected in many cases. Especially the interaction with UMTS radio resource control being required to meet Quality of Service (QoS constraints has to be included to assess the applicability of these technologies for UMTS. In this paper, we study the interaction of beamforming concepts as well as multiuser detection with load and power control. We also work out UMTS specific constraints like signal-to-interference-plus-noise ratio (SINR operating points, pilot power pollution or channel estimation, all strongly limiting network performance. Results are shown for capacity gains and power reduction for all beamforming concepts of interest as well as linear multiuser detection schemes. The results show that fix as well as user-specific beamforming significantly improves network performance gains in downlink. In uplink multiuser detection indicates fairly modest system capacity gains, while it reduces tremendously mobile station power.

  12. Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

    International Nuclear Information System (INIS)

    Peter, Josephine; Doloi, B.; Bhattacharyya, B.

    2011-01-01

    The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actual experimental observations.

  13. Evaluation of High-Performance Network Technologies for ITER

    Energy Technology Data Exchange (ETDEWEB)

    Zagar, K.; Kolaric, P.; Sabjan, R.; Zagar, A. [Cosylab d.d., Ljubljana (Slovenia); Hunt, S. [Alceli Hunt Beratung, Meisterschwanden (Switzerland)

    2009-07-01

    To facilitate fast feedback control of plasma, ITER's Control, Data Access and Communication system (CODAC) will need to provide a mechanism for hard real-time communication between its distributed nodes. In particular, four types of high-performance communication have been identified. Synchronous Databus Network (SDN) is to provide an ability to distribute parameters of plasma (estimated to about 5000 double-valued signals) across the system to allow for 1 ms control cycles. Event Distribution Network (EDN) and Time Communication Network (TCN) are to allow synchronization of node I/O operations to 10 ns. Finally, the Audio Video Network (AVN) is to provide sufficient bandwidth for streaming of surveillance and diagnostics video at a high resolution (1024*1024) and frame rate (30 Hz). In this article, we present some combinations of common off-the-shelf (COTS) technologies that allow the above requirements to be met. Also, we present the performances achieved in a practical (though small scale) technology demonstrator, which involved a real-time LINUS operating running on National Instruments' PXI platform, UDP communication implemented directly atop the Ethernet network adapter, CISCO switches, Micro Research Finland's timing and event solution, and GigE audio-video streaming. This document is composed of an abstract followed by the presentation transparencies. (authors)

  14. Evaluation of high-performance network technologies for ITER

    Energy Technology Data Exchange (ETDEWEB)

    Zagar, K., E-mail: klemen.zagar@cosylab.co [Cosylab d.d., 1000 Ljubljana (Slovenia); Hunt, S. [Alceli Hunt Beratung, 5616 Meisterschwanden (Switzerland); Kolaric, P.; Sabjan, R.; Zagar, A.; Dedic, J. [Cosylab d.d., 1000 Ljubljana (Slovenia)

    2010-07-15

    For the fast feedback plasma controllers, ITER's Control, Data Access and Communication system (CODAC) will need to provide a mechanism for hard real-time communication between its distributed nodes. In particular, the ITER CODAC team identified four types of high-performance communication applications. Synchronous Databus Network (SDN) is to provide an ability to distribute parameters of plasma (estimated to about 5000 double-valued signals) across the system to allow for 1 ms control cycles. Event Distribution Network (EDN) and Time Communication Network (TCN) are to allow synchronization of node I/O operations to 10 ns. Finally, the Audio-Video Network (AVN) is to provide sufficient bandwidth for streaming of surveillance and diagnostics video at a high resolution (1024 x 1024) and frame rate (30 Hz). In this article, we present some combinations of common-off-the-shelf (COTS) technologies that allow the above requirements to be met. Also, we present the performances achieved in a practical (though small scale) technology demonstrator, which involved a real-time Linux operating running on National Instruments' PXI platform, UDP communication implemented directly atop the Ethernet network adapter, CISCO switches, Micro Research Finland's timing and event solution, and GigE audio-video streaming.

  15. Evaluation of high-performance network technologies for ITER

    International Nuclear Information System (INIS)

    Zagar, K.; Hunt, S.; Kolaric, P.; Sabjan, R.; Zagar, A.; Dedic, J.

    2010-01-01

    For the fast feedback plasma controllers, ITER's Control, Data Access and Communication system (CODAC) will need to provide a mechanism for hard real-time communication between its distributed nodes. In particular, the ITER CODAC team identified four types of high-performance communication applications. Synchronous Databus Network (SDN) is to provide an ability to distribute parameters of plasma (estimated to about 5000 double-valued signals) across the system to allow for 1 ms control cycles. Event Distribution Network (EDN) and Time Communication Network (TCN) are to allow synchronization of node I/O operations to 10 ns. Finally, the Audio-Video Network (AVN) is to provide sufficient bandwidth for streaming of surveillance and diagnostics video at a high resolution (1024 x 1024) and frame rate (30 Hz). In this article, we present some combinations of common-off-the-shelf (COTS) technologies that allow the above requirements to be met. Also, we present the performances achieved in a practical (though small scale) technology demonstrator, which involved a real-time Linux operating running on National Instruments' PXI platform, UDP communication implemented directly atop the Ethernet network adapter, CISCO switches, Micro Research Finland's timing and event solution, and GigE audio-video streaming.

  16. ANN based optimization of a solar assisted hybrid cooling system in Turkey

    Energy Technology Data Exchange (ETDEWEB)

    Ozgur, Arif; Yetik, Ozge; Arslan, Oguz [Mechanical Eng. Dept., Engineering Faculty, Dumlupinar University (Turkey)], email: maozgur@dpu.edu.tr, email: ozgeyetik@dpu.edu.tr, email: oarslan@dpu.edu.tr

    2011-07-01

    This study achieved optimization of a solar assisted hybrid cooling system with refrigerants such as R717, R141b, R134a and R123 using an artificial neural network (ANN) model based on average total solar radiation, ambient temperature, generator temperature, condenser temperature, intercooler temperature and fluid types. ANN is a new tool; it works rapidly and can thus be a solution for design and optimization of complex power cycles. A unique flexible ANN algorithm was introduced to evaluate the solar ejector cooling systems because of the nonlinearity of neural networks. The conclusion was that the best COPs value obtained with the ANN is 1.35 and COPc is 3.03 when the average total solar radiation, ambient temperature, generator temperature, condenser temperature, intercooler temperature and algorithm are respectively 674.72 W/m2, 17.9, 80, 15 and 13 degree celsius and LM with 14 neurons in single hidden layer, for R717.

  17. Mary Anne Chambers | IDRC - International Development Research ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    A former Member of Provincial Parliament, Mary Anne served as Minister of Training, Colleges and Universities, and Minister of Children and Youth Services in the Government of Ontario. She is also a former senior vice-president of Scotiabank. A graduate of the University of Toronto, Mary Anne has received honorary ...

  18. Using Internet of Things technologies for wireless sensor networks

    Science.gov (United States)

    Martinez, K.; Hart, J. K.; Basford, P. J.; Bragg, G. M.; Ward, T.

    2013-12-01

    Numerous authors have envisioned the future internet where anything will be connected: the Internet of Things (IoT). The idea is an extrapolation of the spread of networked devices such as phones, tablets etc. Each device is expected to have its own Internet address and thus be easy to access. The key building blocks of any IoT system are networking, hardware platforms and node software - so they are similar to wireless sensor network requirements. Most existing IoT demonstrators and applications have been gadget-style objects where power and connectivity problems are not too restricting. Environmental sensor networks can benefit from using some of the technologies involved in IoT development. However it is expected that tuning the networking and power management will be necessary to make them as efficient as state of the art wireless sensor networks. Some IoT assumptions such as always-connected nodes and full IP capability need to be considered. This paper will illustrate the advantages and disadvantages of IoT techniques for environment sensing drawing on a range of employment scenarios. We also describe a glacial 'Internet of things' project, which aims to monitor glacial processes. In particular we describe the IoT developments in a deployment in Iceland to examine glacier seismicity, velocity and provide camera images.

  19. Assessment of ANN and SVM models for estimating normal direct irradiation (H_b)

    International Nuclear Information System (INIS)

    Santos, Cícero Manoel dos; Escobedo, João Francisco; Teramoto, Érico Tadao; Modenese Gorla da Silva, Silvia Helena

    2016-01-01

    Highlights: • The performance of SVM and ANN in estimating Normal Direct Irradiation (H_b) was evaluated. • 12 models using different input variables are developed (hourly and daily partitions). • The most relevant input variables for DNI are kt, H_s_c and insolation ratio (r′ = n/N). • Support Vector Machine (SVM) provides accurate estimates and outperforms the Artificial Neural Network (ANN). - Abstract: This study evaluates the estimation of hourly and daily normal direct irradiation (H_b) using machine learning techniques (ML): Artificial Neural Network (ANN) and Support Vector Machine (SVM). Time series of different meteorological variables measured over thirteen years in Botucatu were used for training and validating ANN and SVM. Seven different sets of input variables were tested and evaluated, which were chosen based on statistical models reported in the literature. Relative Mean Bias Error (rMBE), Relative Root Mean Square Error (rRMSE), determination coefficient (R"2) and “d” Willmott index were used to evaluate ANN and SVM models. When compared to statistical models which use the same set of input variables (R"2 between 0.22 and 0.78), ANN and SVM show higher values of R"2 (hourly models between 0.52 and 0.88; daily models between 0.42 and 0.91). Considering the input variables, atmospheric transmissivity of global radiation (kt), integrated solar constant (H_s_c) and insolation ratio (n/N, n is sunshine duration and N is photoperiod) were the most relevant in ANN and SVM models. The rMBE and rRMSE values in the two time partitions of SVM models are lower than those obtained with ANN. Hourly ANN and SVM models have higher rRMSE values than daily models. Optimal performance with hourly models was obtained with ANN4"h (rMBE = 12.24%, rRMSE = 23.99% and “d” = 0.96) and SVM4"h (rMBE = 1.75%, rRMSE = 20.10% and “d” = 0.96). Optimal performance with daily models was obtained with ANN2"d (rMBE = −3.09%, rRMSE = 18.95% and “d” = 0

  20. Intelligent MRTD testing for thermal imaging system using ANN

    Science.gov (United States)

    Sun, Junyue; Ma, Dongmei

    2006-01-01

    The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task, for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type, the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP, but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly, we use frame grabber to capture the 4-bar target image data. Then according to image gray scale, we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets, along with known target visibility, are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm, demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.

  1. A Hybrid FEM-ANN Approach for Slope Instability Prediction

    Science.gov (United States)

    Verma, A. K.; Singh, T. N.; Chauhan, Nikhil Kumar; Sarkar, K.

    2016-09-01

    Assessment of slope stability is one of the most critical aspects for the life of a slope. In any slope vulnerability appraisal, Factor Of Safety (FOS) is the widely accepted index to understand, how close or far a slope from the failure. In this work, an attempt has been made to simulate a road cut slope in a landslide prone area in Rudrapryag, Uttarakhand, India which lies near Himalayan geodynamic mountain belt. A combination of Finite Element Method (FEM) and Artificial Neural Network (ANN) has been adopted to predict FOS of the slope. In ANN, a three layer, feed- forward back-propagation neural network with one input layer and one hidden layer with three neurons and one output layer has been considered and trained using datasets generated from numerical analysis of the slope and validated with new set of field slope data. Mean absolute percentage error estimated as 1.04 with coefficient of correlation between the FOS of FEM and ANN as 0.973, which indicates that the system is very vigorous and fast to predict FOS for any slope.

  2. The Networking and Information Technology Research and Development NITRD Program 2012 Strategic Plan

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — Information technology IT computers, wired and wireless digital networks, electronic data and information, IT devices and systems, and software applications?today...

  3. Research of the key technology in satellite communication networks

    Science.gov (United States)

    Zeng, Yuan

    2018-02-01

    According to the prediction, in the next 10 years the wireless data traffic will be increased by 500-1000 times. Not only the wireless data traffic will be increased exponentially, and the demand for diversified traffic will be increased. Higher requirements for future mobile wireless communication system had brought huge market space for satellite communication system. At the same time, the space information networks had been greatly developed with the depth of human exploration of space activities, the development of space application, the expansion of military and civilian application. The core of spatial information networks is the satellite communication. The dissertation presented the communication system architecture, the communication protocol, the routing strategy, switch scheduling algorithm and the handoff strategy based on the satellite communication system. We built the simulation platform of the LEO satellites networks and simulated the key technology using OPNET.

  4. Strategic Management of Technology and the Structuring of Industrial Networks

    DEFF Research Database (Denmark)

    Sørensen, Ole H.

    The thesis explores the following question: 'How do actants in industrial companies partake in the enactment of locally embedded and globally reaching industrial networks through participation in technology development activities?' It draws on Actor Netwok Theories and analyses three case stories...... from the hearing aid industry. In one of the case stories is shown how three Danish companies became a 'centre of translation' by collaborating on the development of the software standard NOAH....

  5. Prediction of scour below submerged pipeline crossing a river using ANN.

    Science.gov (United States)

    Azamathulla, H M; Zakaria, Nor Azazi

    2011-01-01

    The process involved in the local scour below pipelines is so complex that it makes it difficult to establish a general empirical model to provide accurate estimation for scour. This paper describes the use of artificial neural networks (ANN) to estimate the pipeline scour depth. The data sets of laboratory measurements were collected from published works and used to train the network or evolve the program. The developed networks were validated by using the observations that were not involved in training. The performance of ANN was found to be more effective when compared with the results of regression equations in predicting the scour depth around pipelines.

  6. Formal Variability of Terms in the Sphere of Network Technologies

    Directory of Open Access Journals (Sweden)

    Roman Viktorovich Deniko

    2015-09-01

    Full Text Available The article addresses the problem of formal variability of terms in the sphere of network terminology in the Russian language. The research is based on data from the Internet communication in the sphere of network technologies. Such formal variability types as graphical, phonemic, word building and complex (graphic and phonetic, morphologic and accentual are discussed in this article. The authors reveal the reasons for graphic variability of foreign origin terms making up the international terminological fund. These reasons cover such aspects as the use of graphics of source language and recipient language; the presence or absence of hyphenation, etc. It is determined that the phonemic variants of terms appear as a result of oral or written borrowings. The existence of such variants is also connected with the stage of their adaptation in the Russian language after borrowing. In this case the variants are related with soft or hard pronunciation of consonants. There are also some cases of phonemic variability on the graphic level. The complex variability is regarded as a part of active processes taking place in the modern Russian language, and these processes involve both native and foreign origin terms. The particular attention is paid to the word-building variants – word-building affixes the variability of which is peculiar of network technologies. The results of the research show that the variability of professional units belonging to the network technologies sublanguage is caused by the active process of borrowing of specialpurpose vocabulary into the Russian language. The process is due to the intensification of intercultural communication in the professional spheres.

  7. PREFACE: Complex Networks: from Biology to Information Technology

    Science.gov (United States)

    Barrat, A.; Boccaletti, S.; Caldarelli, G.; Chessa, A.; Latora, V.; Motter, A. E.

    2008-06-01

    The field of complex networks is one of the most active areas in contemporary statistical physics. Ten years after seminal work initiated the modern study of networks, interest in the field is in fact still growing, as indicated by the ever increasing number of publications in network science. The reason for such a resounding success is most likely the simplicity and broad significance of the approach that, through graph theory, allows researchers to address a variety of different complex systems within a common framework. This special issue comprises a selection of contributions presented at the workshop 'Complex Networks: from Biology to Information Technology' held in July 2007 in Pula (Cagliari), Italy as a satellite of the general conference STATPHYS23. The contributions cover a wide range of problems that are currently among the most important questions in the area of complex networks and that are likely to stimulate future research. The issue is organised into four sections. The first two sections describe 'methods' to study the structure and the dynamics of complex networks, respectively. After this methodological part, the issue proceeds with a section on applications to biological systems. The issue closes with a section concentrating on applications to the study of social and technological networks. The first section, entitled Methods: The Structure, consists of six contributions focused on the characterisation and analysis of structural properties of complex networks: The paper Motif-based communities in complex networks by Arenas et al is a study of the occurrence of characteristic small subgraphs in complex networks. These subgraphs, known as motifs, are used to define general classes of nodes and their communities by extending the mathematical expression of the Newman-Girvan modularity. The same line of research, aimed at characterising network structure through the analysis of particular subgraphs, is explored by Bianconi and Gulbahce in Algorithm

  8. The Role of Social Networks in Financing High Technology New Ventures: An Empirical Exploration

    NARCIS (Netherlands)

    Heuven, J.M.J.

    2006-01-01

    This paper focuses on the role of networks in financing high technology start-ups. We claim that the role of networks is twofold. On the one hand networks are important because network contacts can give direct access to resources. On the other hand, networks are important because being affiliated

  9. [The Identification of the Origin of Chinese Wolfberry Based on Infrared Spectral Technology and the Artificial Neural Network].

    Science.gov (United States)

    Li, Zhong; Liu, Ming-de; Ji, Shou-xiang

    2016-03-01

    The Fourier Transform Infrared Spectroscopy (FTIR) is established to find the geographic origins of Chinese wolfberry quickly. In the paper, the 45 samples of Chinese wolfberry from different places of Qinghai Province are to be surveyed by FTIR. The original data matrix of FTIR is pretreated with common preprocessing and wavelet transform. Compared with common windows shifting smoothing preprocessing, standard normal variation correction and multiplicative scatter correction, wavelet transform is an effective spectrum data preprocessing method. Before establishing model through the artificial neural networks, the spectra variables are compressed by means of the wavelet transformation so as to enhance the training speed of the artificial neural networks, and at the same time the related parameters of the artificial neural networks model are also discussed in detail. The survey shows even if the infrared spectroscopy data is compressed to 1/8 of its original data, the spectral information and analytical accuracy are not deteriorated. The compressed spectra variables are used for modeling parameters of the backpropagation artificial neural network (BP-ANN) model and the geographic origins of Chinese wolfberry are used for parameters of export. Three layers of neural network model are built to predict the 10 unknown samples by using the MATLAB neural network toolbox design error back propagation network. The number of hidden layer neurons is 5, and the number of output layer neuron is 1. The transfer function of hidden layer is tansig, while the transfer function of output layer is purelin. Network training function is trainl and the learning function of weights and thresholds is learngdm. net. trainParam. epochs=1 000, while net. trainParam. goal = 0.001. The recognition rate of 100% is to be achieved. It can be concluded that the method is quite suitable for the quick discrimination of producing areas of Chinese wolfberry. The infrared spectral analysis technology

  10. An Overview on Wireless Sensor Networks Technology and Evolution

    Directory of Open Access Journals (Sweden)

    Chiara Buratti

    2009-08-01

    Full Text Available Wireless sensor networks (WSNs enable new applications and require non-conventional paradigms for protocol design due to several constraints. Owing to the requirement for low device complexity together with low energy consumption (i.e., long network lifetime, a proper balance between communication and signal/data processing capabilities must be found. This motivates a huge effort in research activities, standardization process, and industrial investments on this field since the last decade. This survey paper aims at reporting an overview of WSNs technologies, main applications and standards, features in WSNs design, and evolutions. In particular, some peculiar applications, such as those based on environmental monitoring, are discussed and design strategies highlighted; a case study based on a real implementation is also reported. Trends and possible evolutions are traced. Emphasis is given to the IEEE 802.15.4 technology, which enables many applications of WSNs. Some example of performance characteristics of 802.15.4-based networks are shown and discussed as a function of the size of the WSN and the data type to be exchanged among nodes.

  11. FE-ANN based modeling of 3D Simple Reinforced Concrete Girders for Objective Structural Health Evaluation : Tech Transfer Summary

    Science.gov (United States)

    2017-06-01

    The objective of this study was to develop an objective, quantitative method for evaluating damage to bridge girders by using artificial neural networks (ANNs). This evaluation method, which is a supplement to visual inspection, requires only the res...

  12. Prediction of Film Cooling Effectiveness on a Gas Turbine Blade Leading Edge Using ANN and CFD

    Science.gov (United States)

    Dávalos, J. O.; García, J. C.; Urquiza, G.; Huicochea, A.; De Santiago, O.

    2018-05-01

    In this work, the area-averaged film cooling effectiveness (AAFCE) on a gas turbine blade leading edge was predicted by employing an artificial neural network (ANN) using as input variables: hole diameter, injection angle, blowing ratio, hole and columns pitch. The database used to train the network was built using computational fluid dynamics (CFD) based on a two level full factorial design of experiments. The CFD numerical model was validated with an experimental rig, where a first stage blade of a gas turbine was represented by a cylindrical specimen. The ANN architecture was composed of three layers with four neurons in hidden layer and Levenberg-Marquardt was selected as ANN optimization algorithm. The AAFCE was successfully predicted by the ANN with a regression coefficient R2<0.99 and a root mean square error RMSE=0.0038. The ANN weight coefficients were used to estimate the relative importance of the input parameters. Blowing ratio was the most influential parameter with relative importance of 40.36 % followed by hole diameter. Additionally, by using the ANN model, the relationship between input parameters was analyzed.

  13. Prediction of Splitting Tensile Strength of Concrete Containing Zeolite and Diatomite by ANN

    Directory of Open Access Journals (Sweden)

    E. Gülbandılar

    2017-01-01

    Full Text Available This study was designed to investigate with two different artificial neural network (ANN prediction model for the behavior of concrete containing zeolite and diatomite. For purpose of constructing this model, 7 different mixes with 63 specimens of the 28, 56 and 90 days splitting tensile strength experimental results of concrete containing zeolite, diatomite, both zeolite and diatomite used in training and testing for ANN systems was gathered from the tests. The data used in the ANN models are arranged in a format of seven input parameters that cover the age of samples, Portland cement, zeolite, diatomite, aggregate, water and hyper plasticizer and an output parameter which is splitting tensile strength of concrete. In the model, the training and testing results have shown that two different ANN systems have strong potential as a feasible tool for predicting 28, 56 and 90 days the splitting tensile strength of concrete containing zeolite and diatomite.

  14. Application of Artificial Neural Networks to Complex Groundwater Management Problems

    International Nuclear Information System (INIS)

    Coppola, Emery; Poulton, Mary; Charles, Emmanuel; Dustman, John; Szidarovszky, Ferenc

    2003-01-01

    As water quantity and quality problems become increasingly severe, accurate prediction and effective management of scarcer water resources will become critical. In this paper, the successful application of artificial neural network (ANN) technology is described for three types of groundwater prediction and management problems. In the first example, an ANN was trained with simulation data from a physically based numerical model to predict head (groundwater elevation) at locations of interest under variable pumping and climate conditions. The ANN achieved a high degree of predictive accuracy, and its derived state-transition equations were embedded into a multiobjective optimization formulation and solved to generate a trade-off curve depicting water supply in relation to contamination risk. In the second and third examples, ANNs were developed with real-world hydrologic and climate data for different hydrogeologic environments. For the second problem, an ANN was developed using data collected for a 5-year, 8-month period to predict heads in a multilayered surficial and limestone aquifer system under variable pumping, state, and climate conditions. Using weekly stress periods, the ANN substantially outperformed a well-calibrated numerical flow model for the 71-day validation period, and provided insights into the effects of climate and pumping on water levels. For the third problem, an ANN was developed with data collected automatically over a 6-week period to predict hourly heads in 11 high-capacity public supply wells tapping a semiconfined bedrock aquifer and subject to large well-interference effects. Using hourly stress periods, the ANN accurately predicted heads for 24-hour periods in all public supply wells. These test cases demonstrate that the ANN technology can solve a variety of complex groundwater management problems and overcome many of the problems and limitations associated with traditional physically based flow models

  15. Optical fiber cabling technologies for flexible access network

    Science.gov (United States)

    Tanji, Hisashi

    2008-07-01

    Fiber-to-the-home (FTTH) outside plant infrastructure should be so designed and constructed as to flexibly deal with increasing subscribers and system evolution to be expected in the future, taking minimization of total cost (CAPEX and OPEX) into consideration. With this in mind, fiber access architectures are reviewed and key technologies on optical fiber and cable for supporting flexible access network are presented. Low loss over wide wavelength (low water peak) and bend-insensitive single mode fiber is a future proof solution. Enhanced separable ribbon facilitates mid-span access to individual fibers in a cable installed, improving fiber utilizing efficiency and flexibility of distribution design. It also contributes to an excellent low PMD characteristic which could be required for video RF overlay system or high capacity long reach metro-access convergence network in the future. Bend-insensitive fiber based cabling technique including field installable connector greatly improves fiber/cable handling in installation and maintenance work.

  16. Integrating Space Communication Network Capabilities via Web Portal Technologies

    Science.gov (United States)

    Johnston, Mark D.; Lee, Carlyn-Ann; Lau, Chi-Wung; Cheung, Kar-Ming; Levesque, Michael; Carruth, Butch; Coffman, Adam; Wallace, Mike

    2014-01-01

    We have developed a service portal prototype as part of an investigation into the feasibility of using Java portlet technology as a means of providing integrated access to NASA communications network services. Portal servers provide an attractive platform for this role due to the various built-in collaboration applications they can provide, combined with the possibility to develop custom inter-operating portlets to extent their functionality while preserving common presentation and behavior. This paper describes various options for integration of network services related to planning and scheduling, and results based on use of a popular open-source portal framework. Plans are underway to develop an operational SCaN Service Portal, building on the experiences reported here.

  17. ACTS TDMA network control. [Advanced Communication Technology Satellite

    Science.gov (United States)

    Inukai, T.; Campanella, S. J.

    1984-01-01

    This paper presents basic network control concepts for the Advanced Communications Technology Satellite (ACTS) System. Two experimental systems, called the low-burst-rate and high-burst-rate systems, along with ACTS ground system features, are described. The network control issues addressed include frame structures, acquisition and synchronization procedures, coordinated station burst-time plan and satellite-time plan changes, on-board clock control based on ground drift measurements, rain fade control by means of adaptive forward-error-correction (FEC) coding and transmit power augmentation, and reassignment of channel capacities on demand. The NASA ground system, which includes a primary station, diversity station, and master control station, is also described.

  18. Estimation of the chemical-induced eye injury using a Weight-of-Evidence (WoE) battery of 21 artificial neural network (ANN) c-QSAR models (QSAR-21): part II: corrosion potential.

    Science.gov (United States)

    Verma, Rajeshwar P; Matthews, Edwin J

    2015-03-01

    This is part II of an in silico investigation of chemical-induced eye injury that was conducted at FDA's CFSAN. Serious eye damage caused by chemical (eye corrosion) is assessed using the rabbit Draize test, and this endpoint is an essential part of hazard identification and labeling of industrial and consumer products to ensure occupational and consumer safety. There is an urgent need to develop an alternative to the Draize test because EU's 7th amendment to the Cosmetic Directive (EC, 2003; 76/768/EEC) and recast Regulation now bans animal testing on all cosmetic product ingredients and EU's REACH Program limits animal testing for chemicals in commerce. Although in silico methods have been reported for eye irritation (reversible damage), QSARs specific for eye corrosion (irreversible damage) have not been published. This report describes the development of 21 ANN c-QSAR models (QSAR-21) for assessing eye corrosion potential of chemicals using a large and diverse CFSAN data set of 504 chemicals, ADMET Predictor's three sensitivity analyses and ANNE classification functionalities with 20% test set selection from seven different methods. QSAR-21 models were internally and externally validated and exhibited high predictive performance: average statistics for the training, verification, and external test sets of these models were 96/96/94% sensitivity and 91/91/90% specificity. Copyright © 2014 Elsevier Inc. All rights reserved.

  19. An open, interoperable, and scalable prehospital information technology network architecture.

    Science.gov (United States)

    Landman, Adam B; Rokos, Ivan C; Burns, Kevin; Van Gelder, Carin M; Fisher, Roger M; Dunford, James V; Cone, David C; Bogucki, Sandy

    2011-01-01

    Some of the most intractable challenges in prehospital medicine include response time optimization, inefficiencies at the emergency medical services (EMS)-emergency department (ED) interface, and the ability to correlate field interventions with patient outcomes. Information technology (IT) can address these and other concerns by ensuring that system and patient information is received when and where it is needed, is fully integrated with prior and subsequent patient information, and is securely archived. Some EMS agencies have begun adopting information technologies, such as wireless transmission of 12-lead electrocardiograms, but few agencies have developed a comprehensive plan for management of their prehospital information and integration with other electronic medical records. This perspective article highlights the challenges and limitations of integrating IT elements without a strategic plan, and proposes an open, interoperable, and scalable prehospital information technology (PHIT) architecture. The two core components of this PHIT architecture are 1) routers with broadband network connectivity to share data between ambulance devices and EMS system information services and 2) an electronic patient care report to organize and archive all electronic prehospital data. To successfully implement this comprehensive PHIT architecture, data and technology requirements must be based on best available evidence, and the system must adhere to health data standards as well as privacy and security regulations. Recent federal legislation prioritizing health information technology may position federal agencies to help design and fund PHIT architectures.

  20. Making Wireless Networks Secure for NASA Mission Critical Applications Using Virtual Private Network (VPN) Technology

    Science.gov (United States)

    Nichols, Kelvin F.; Best, Susan; Schneider, Larry

    2004-01-01

    With so many security issues involved with wireless networks, the technology has not been fully utilized in the area of mission critical applications. These applications would include the areas of telemetry, commanding, voice and video. Wireless networking would allow payload operators the mobility to take computers outside of the control room to their off ices and anywhere else in the facility that the wireless network was extended. But the risk is too great of having someone sit just inside of your wireless network coverage and intercept enough of your network traffic to steal proprietary data from a payload experiment or worse yet hack back into your system and do even greater harm by issuing harmful commands. Wired Equivalent Privacy (WEP) is improving but has a ways to go before it can be trusted to protect mission critical data. Today s hackers are becoming more aggressive and innovative, and in order to take advantage of the benefits that wireless networking offer, appropriate security measures need to be in place that will thwart hackers. The Virtual Private Network (VPN) offers a solution to the security problems that have kept wireless networks from being used for mission critical applications. VPN provides a level of encryption that will ensure that data is protected while it is being transmitted over a wireless local area network (LAN). The VPN allows a user to authenticate to the site that the user needs to access. Once this authentication has taken place the network traffic between that site and the user is encapsulated in VPN packets with the Triple Data Encryption Standard (3DES). 3DES is an encryption standard that uses a single secret key to encrypt and decrypt data. The length of the encryption key is 168 bits as opposed to its predecessor DES that has a 56-bit encryption key. Even though 3DES is the common encryption standard for today, the Advance Encryption Standard (AES), which provides even better encryption at a lower cycle cost is growing

  1. Research on artificial neural network applications for nuclear power plants

    International Nuclear Information System (INIS)

    Chang, Soon-Heung; Cheon, Se-Woo

    1992-01-01

    Artificial neural networks (ANNs) are an emerging computational technology which can significantly enhance a number of applications. These consist of many interconnected processing elements that exhibit human-like performance, i.e., learning, pattern recognition and associative memory skills. Several application studies on ANNs devoted to nuclear power plants have been carried out at the Korea Advanced Institute of Science and Technology since 1989. These studies include the feasibility of using ANNs for the following tasks: (1) thermal power prediction, (2) transient identification, (3) multiple alarm processing and diagnosis, (4) core thermal margin prediction, and (5) prediction of core parameters for fuel reloading. This paper introduces the back-propagation network (BPN) model which is the most commonly used algorithm, and summarizes each of the studies briefly. (author)

  2. Comparison of ANN and RKS approaches to model SCC strength

    Science.gov (United States)

    Prakash, Aravind J.; Sathyan, Dhanya; Anand, K. B.; Aravind, N. R.

    2018-02-01

    Self compacting concrete (SCC) is a high performance concrete that has high flowability and can be used in heavily reinforced concrete members with minimal compaction segregation and bleeding. The mix proportioning of SCC is highly complex and large number of trials are required to get the mix with the desired properties resulting in the wastage of materials and time. The research on SCC has been highly empirical and no theoretical relationships have been developed between the mixture proportioning and engineering properties of SCC. In this work effectiveness of artificial neural network (ANN) and random kitchen sink algorithm(RKS) with regularized least square algorithm(RLS) in predicting the split tensile strength of the SCC is analysed. Random kitchen sink algorithm is used for mapping data to higher dimension and classification of this data is done using Regularized least square algorithm. The training and testing data for the algorithm was obtained experimentally using standard test procedures and materials available. Total of 40 trials were done which were used as the training and testing data. Trials were performed by varying the amount of fine aggregate, coarse aggregate, dosage and type of super plasticizer and water. Prediction accuracy of the ANN and RKS model is checked by comparing the RMSE value of both ANN and RKS. Analysis shows that eventhough the RKS model is good for large data set, its prediction accuracy is as good as conventional prediction method like ANN so the split tensile strength model developed by RKS can be used in industries for the proportioning of SCC with tailor made property.

  3. A Survey of Key Technology of Network Public Opinion Analysis

    Directory of Open Access Journals (Sweden)

    Li Su Ying

    2016-01-01

    Full Text Available The internet has become an important base for internet users to make comments because of its interactivity and fast dissemination. The outbreak of internet public opinion has become a major risk for network information security. Domestic and foreign researchers had carried out extensive and in-depth study on public opinion. Fruitful results have achieved in the basic theory research and emergency handling and other aspects of public opinion. But research on the public opinion in China is still in the initial stage, the key technology of the public opinion analysis is still as a starting point for in-depth study and discussion.

  4. Visualising Actor Network for Cooperative Systems in Marine Technology

    DEFF Research Database (Denmark)

    Pan, Yushan; Finken, Sisse

    2016-01-01

    Awareness is a concept familiar to specialists within the field of Computer Supported Cooperative Work (CSCW). It is superior for analysing and describing some of the ad hoc work activities that unfold in cooperation. Such informal activities are outside the scope of engineers’ formal models, whi...... that shape computer systems. The aim, thus, is to portray cooperative work in a way that can be valuable for engineers implementing marine technology. We do so by way of presenting a transferring technique (2T) using insights from the CSCW field and Actor Network Theory (ANT)....

  5. Wireless body area networks technology, implementation, and applications

    CERN Document Server

    Yuce, Mehmet R

    2011-01-01

    The book provides a comprehensive overview for the latest WBAN systems, technologies, and applications. The chapters of the book have been written by various specialists who are experts in their areas of research and practice. The book starts with the basic techniques involved in designing and building WBAN systems. It explains the deployment issues and then moves into the application areas of WBAN. The remaining chapters focus on the development of hardware, signal processing algorithms, and wireless communication and network design for wearable and implantable body sensors used in WBAN appli

  6. Technology and knowledge flow the power of networks

    CERN Document Server

    Trentin, Guglielmo

    2011-01-01

    This book outlines how network technology can support, foster and enhance the Knowledge Management, Sharing and Development (KMSD) processes in professional environments through the activation of both formal and informal knowledge flows. Understanding how ICT can be made available to such flows in the knowledge society is a factor that cannot be disregarded and is confirmed by the increasing interest of companies in new forms of software-mediated social interaction. The latter factor is in relation both to the possibility of accelerating internal communication and problem solving processes, an

  7. Examining Engineering & Technology Students' Acceptance of Network Virtualization Technology Using the Technology Acceptance Model

    Science.gov (United States)

    Yousif, Wael K.

    2010-01-01

    This causal and correlational study was designed to extend the Technology Acceptance Model (TAM) and to test its applicability to Valencia Community College (VCC) Engineering and Technology students as the target user group when investigating the factors influencing their decision to adopt and to utilize VMware as the target technology. In…

  8. Utilizing HPC Network Technologies in High Energy Physics Experiments

    CERN Document Server

    AUTHOR|(CDS)2088631; The ATLAS collaboration

    2017-01-01

    Because of their performance characteristics high-performance fabrics like Infiniband or OmniPath are interesting technologies for many local area network applications, including data acquisition systems for high-energy physics experiments like the ATLAS experiment at CERN. This paper analyzes existing APIs for high-performance fabrics and evaluates their suitability for data acquisition systems in terms of performance and domain applicability. The study finds that existing software APIs for high-performance interconnects are focused on applications in high-performance computing with specific workloads and are not compatible with the requirements of data acquisition systems. To evaluate the use of high-performance interconnects in data acquisition systems a custom library, NetIO, is presented and compared against existing technologies. NetIO has a message queue-like interface which matches the ATLAS use case better than traditional HPC APIs like MPI. The architecture of NetIO is based on a interchangeable bac...

  9. The Asian Network for Education in Nuclear Technology (ANENT)

    International Nuclear Information System (INIS)

    Amin, F.; Grover, R.B.; Han, K.W.

    2004-01-01

    The per capita electricity availability in the Asian region is below the world average. Nuclear energy is considered by several countries in the region as a potential source to meet their growing energy demand. Thus, there is likely to be an expansion of nuclear power programme in the Asian region. Additionally, as the economies in the region expand, there will be an increasing role for isotope and radiation technologies in the health care, agriculture, and industrial sectors. The growing demand for power and non-power applications of nuclear technologies would require a sustainable supply of well-qualified nuclear workforce. The Asian Network for Education in Nuclear Technology, ANENT in short, was established in February 2004 in response to this need. The state of nuclear education in the region is at different levels in different countries. This diversity provides an opportunity for sharing of knowledge and resources. ANENT will facilitate cooperation in education, related research and training through: (i) sharing of information and materials on nuclear education and training; (ii) exchange of students, teachers and researchers; (iii) establishment of reference curricula and facilitating mutual recognition of degrees; and (iv) facilitating communication between ANENT member institutions and other regional and global networks. By focusing on education, ANENT complements existing activities undertaken by the International Atomic Energy Agency (IAEA) and supports IAEA activities for the preservation of nuclear knowledge. ANENT is a comprehensive initiative in education and training in that it will give equal importance to power and non-power technologies, thus meeting the diverse needs of the countries in the Asian region. (author)

  10. Improvement of radiation dose estimation due to nuclear accidents using deep neural network and GPU

    Energy Technology Data Exchange (ETDEWEB)

    Desterro, Filipe S.M.; Almeida, Adino A.H.; Pereira, Claudio M.N.A., E-mail: filipesantana18@gmail.com, E-mail: adino@ien.gov.br, E-mail: cmcoelho@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

    2017-07-01

    Recently, the use of mobile devices has been proposed for dose assessment during nuclear accidents. The idea is to support field teams, providing an approximated estimation of the dose distribution map in the vicinity of the nuclear power plant (NPP), without needing to be connected to the NPP systems. In order to provide such stand-alone execution, the use of artificial neural networks (ANN) has been proposed in substitution of the complex and time consuming physical models executed by the atmospheric dispersion radionuclide (ADR) system. One limitation observed on such approach is the very time-consuming training of the ANNs. Moreover, if the number of input parameters increases the performance of standard ANNs, like Multilayer-Perceptron (MLP) with backpropagation training, is affected leading to unreasonable training time. To improve learning, allowing better dose estimations, more complex ANN architectures are required. ANNs with many layers (much more than a typical number of layers), referred to as Deep Neural Networks (DNN), for example, have demonstrating to achieve better results. On the other hand, the training of such ANNs is very much slow. In order to allow the use of such DNNs in a reasonable training time, a parallel programming solution, using Graphic Processing Units (GPU) and Computing Unified Device Architecture (CUDA) is proposed. This work focuses on the study of computational technologies for improvement of the ANNs to be used in the mobile application, as well as their training algorithms. (author)

  11. Improvement of radiation dose estimation due to nuclear accidents using deep neural network and GPU

    International Nuclear Information System (INIS)

    Desterro, Filipe S.M.; Almeida, Adino A.H.; Pereira, Claudio M.N.A.

    2017-01-01

    Recently, the use of mobile devices has been proposed for dose assessment during nuclear accidents. The idea is to support field teams, providing an approximated estimation of the dose distribution map in the vicinity of the nuclear power plant (NPP), without needing to be connected to the NPP systems. In order to provide such stand-alone execution, the use of artificial neural networks (ANN) has been proposed in substitution of the complex and time consuming physical models executed by the atmospheric dispersion radionuclide (ADR) system. One limitation observed on such approach is the very time-consuming training of the ANNs. Moreover, if the number of input parameters increases the performance of standard ANNs, like Multilayer-Perceptron (MLP) with backpropagation training, is affected leading to unreasonable training time. To improve learning, allowing better dose estimations, more complex ANN architectures are required. ANNs with many layers (much more than a typical number of layers), referred to as Deep Neural Networks (DNN), for example, have demonstrating to achieve better results. On the other hand, the training of such ANNs is very much slow. In order to allow the use of such DNNs in a reasonable training time, a parallel programming solution, using Graphic Processing Units (GPU) and Computing Unified Device Architecture (CUDA) is proposed. This work focuses on the study of computational technologies for improvement of the ANNs to be used in the mobile application, as well as their training algorithms. (author)

  12. Social network influences on technology acceptance : A matter of tie strength, centrality and density

    NARCIS (Netherlands)

    Ten Kate, Stephan; Haverkamp, Sophie; Mahmood, Fariha; Feldberg, Frans

    2010-01-01

    This study examines social network influences on the individual technology acceptance. Since it is believed that individuals' trust, opinions and behavior are influenced by their network, an analysis of that network may help to provide some explanations on technology acceptance. However, since

  13. Social Networks As Internet-technologies in Electoral Campaigns: the International View

    Directory of Open Access Journals (Sweden)

    Александр Александрович Свинин

    2013-12-01

    Full Text Available Social networks as internet-technologies became a useful instrument for politicians during the electoral campaigns. The main reason for that is the fact that social networks today are the next step in development of communications between people. In the article the author investigates the history of social networks, different cases of application of social networks in electoral campaigns.

  14. The Role of Digital Technologies in Learning: Expectations of First Year University Students / Le rôle des technologies numériques dans l’apprentissage : les attentes des étudiants de première année universitaire

    Directory of Open Access Journals (Sweden)

    Martha Gabriel

    2012-02-01

    Full Text Available A growing literature suggests that there is a disjuncture between the instructional practices of the education system and the student body it is expected to serve, particularly with respect to the roles of digital technologies. Based on surveys and focus group interviews of first-year students at a primarily undergraduate Canadian university and focus group interviews of professors at the same institution, this study explores the gaps and intersections between students’ uses and expectations for digital technologies while learning inside the classroom and socializing outside the classroom, and the instructional uses, expectations and concerns of their professors. It concludes with recommendations for uses of digital technologies that go beyond information transmission, the need for extended pedagogical discussions to harness the learning potentials of digital technologies, and for pedagogies that embrace the social construction of knowledge as well as individual acquisition. Des études de plus en plus nombreuses suggèrent qu’il existe un écart entre les pratiques d’enseignement dans le système de l’éducation et la population étudiante desservie, notamment en ce qui concerne le rôle des technologies numériques. La présente étude, fondée sur les résultats de sondages et d’entrevues de groupe auprès des étudiants de première année inscrits à une université canadienne principalement axée sur les études de premier cycle, ainsi que sur des entrevues de groupe auprès de professeurs du même établissement, explore les écarts et les concordances entre, d’une part, l’utilisation et les attentes des étudiants relativement aux technologies numériques dans l’apprentissage en classe et dans les relations sociales en dehors des classes, et, d’autre part, l’utilisation de ces technologies dans les pratiques d’enseignement, les préoccupation et les attentes des professeurs. L’étude se conclut par des

  15. THE FEMINISM AND FEMININITY OF ANN VERONICA IN H. G. WELLS' ANN VERONICA

    Directory of Open Access Journals (Sweden)

    Liem Satya Limanta

    2002-01-01

    Full Text Available H.G. Well's Ann Veronica structurally seems to be divided into two parts; the first deals with Ann Veronica's struggle to get equality with men and freedom in most aspects of life, such as in politics, economics, education, and sexuality; the second describes much the other side of her individuality which she cannot deny, namely her femininity, such as her crave for love, marriage, maternity, and beauty. H.G. Wells describes vividly the two elements in Ann Veronica, feminism and femininity. As a feminist, Ann Veronica rebelled against her authoritative Victorian father, who regarded women only as men's property to be protected from the harsh world outside. On the other side, Ann could not deny her being a woman after she fell in love with Capes. Her femininity from the second half of the novel then is explored. Although the novel ends with the depiction of the domestic life of Ann Veronica, it does not mean that the feminism is gone altogether. The key point is that the family life Ann chooses as a `submissive' wife and good mother is her choice. It is very different if it is forced on her to do. Thus, this novel depicts both sides of Ann Veronica, her feminism and her femininity.

  16. ANN-based wavelet analysis for predicting electrical signal from photovoltaic power supply system

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Medea Univ., Medea (Algeria). Inst. of Science Engineering, Dept. of Electronics

    2007-07-01

    This study was conducted to predict different electrical signals from a photovoltaic power supply system (PVPS) using an artificial neural networks (ANN) with wavelet analysis. It involved the creation of a database of electrical signals (PV-generator current, voltage, battery current voltage, regulator current and voltage) obtained from an experimental PVPS system installed in the south of Algeria. The potential applications were for sizing and analyzing the performance of PVPS systems; control of maximum power point tracker (MPPT) in order to deliver the maximum energy from the PV-array; prediction of the optimal configuration (PV-array and battery sizing) of PVPS systems; expert configuration of PV-systems; faults diagnosis; supervision; and, control and monitoring. First, based on the wavelet analysis each electrical signal was mapped in several time frequency domains. The PV-system was then divided into 3-subsystems corresponding to ANN-PV generator model, ANN-battery model, and ANN-regulator model. An example of day-by-day prediction for each electrical signal was presented. The results of the proposed approach were in good agreement with experimental results. In addition, the accuracy of the proposed approach was more satisfactory when only ANN was used. It was concluded that this methodology offers the possibility of developing a new expert configuration of PVPS by implementing the soft computing ANN-wavelet program with a digital signal processing (DSP) circuit. 26 refs., 1 tab., 5 figs.

  17. Neutron spectrometry and dosimetry with ANNs

    International Nuclear Information System (INIS)

    Vega C, H. R.; Hernandez D, V. M.; Gallego, E.; Lorente, A.

    2009-10-01

    Artificial neural networks technology has been applied to unfold the neutron spectra and to calculate the effective dose, the ambient equivalent dose, and the personal dose equivalent for 252 Cf and 241 AmBe neutron sources. A Bonner sphere spectrometry with a 6 LiI(Eu) scintillator was utilized to measure the count rates of the spheres that were utilized as input in two artificial neural networks, one for spectrometry and another for dosimetry. Spectra and the ambient dose equivalent were also obtained with BUNKIUT code and the UTA4 response matrix. With both procedures spectra and ambient dose equivalent agrees in less than 10%. (author)

  18. Resource allocation using ANN in LTE

    Science.gov (United States)

    Yigit, Tuncay; Ersoy, Mevlut

    2017-07-01

    LTE is the 4th generation wireless network technology, which provides flexible bandwidth, higher data speeds and lower delay. Difficulties may be experienced upon an increase in the number of users in LTE. The objective of this study is to ensure a faster solution to any such resource allocation problems which might arise upon an increase in the number of users. A fast and effective solution has been obtained by making use of Artificial Neural Network. As a result, fast working artificial intelligence methods may be used in resource allocation problems during operation.

  19. Optical home network based on an N×N multimode fiber architecture and CWDM technology

    NARCIS (Netherlands)

    Richard, F.; Guignard, P.; Pizzinat, A.; Guillo, L.; Guillory, J.; Charbonnier, B; Koonen, A.M.J.; Martinez, E.O.; Tanguy, E.; Li, H.W.

    2011-01-01

    With this optical home network solution associating an N×N multimode architecture and CWDM technology, various applications and network topologies are supported by a unique multiformat infrastructure. Issues related to the use of MMF are discussed.

  20. Diversity Networks

    Science.gov (United States)

    and professional growth of women through networking, mentoring and training. We strive to ensure that will be used. National Processing Center Seniors Leader: Jo Anne Hankins Champion: Eric Milliner NO

  1. Research of the self-healing technologies in the optical communication network of distribution automation

    Science.gov (United States)

    Wang, Hao; Zhong, Guoxin

    2018-03-01

    Optical communication network is the mainstream technique of the communication networks for distribution automation, and self-healing technologies can improve the in reliability of the optical communication networks significantly. This paper discussed the technical characteristics and application scenarios of several network self-healing technologies in the access layer, the backbone layer and the core layer of the optical communication networks for distribution automation. On the base of the contrastive analysis, this paper gives an application suggestion of these self-healing technologies.

  2. 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. .

  3. Lipid Processing Technology: Building a Multilevel Modeling Network

    DEFF Research Database (Denmark)

    Diaz Tovar, Carlos Axel; Mustaffa, Azizul Azri; Hukkerikar, Amol

    2011-01-01

    of a computer aided multilevel modeling network consisting a collection of new and adopted models, methods and tools for the systematic design and analysis of processes employing lipid technology. This is achieved by decomposing the problem into four levels of modeling: 1. pure component properties; 2. mixtures...... and phase behavior; 3. unit operations; and 4. process synthesis and design. The methods and tools in each level include: For the first level, a lipid‐database of collected experimental data from the open literature, confidential data from industry and generated data from validated predictive property...... of these unit operations with respect to performance parameters such as minimum total cost, product yield improvement, operability etc., and process intensification for the retrofit of existing biofuel plants. In the fourth level the information and models developed are used as building blocks...

  4. AFRA Network for Education in Nuclear Science and Technology

    International Nuclear Information System (INIS)

    Hashim, N.; Wanjala, F.

    2017-01-01

    AFRA-NEST was Conceived at the AFRA Ministerial Conference held in Aswan in 2007. The main objective of AFRA-NEST is to facilitate operation and networking in higher education, training and related research in Nuclear Science (NS&T) in the African Region through: • Sharing of information and materials of nuclear education and training. The strategies for implementing the objectives are: the use ICT for web-based education and training,; recognition of Regional Designated Centres (RDCs) for professional nuclear education in nuclear science and technology, and organization of harmonized and accredited programs at tertiary levels for teaching and research in the various nuclear disciplines. The main function of the AFRA-NEST is to; foster sustainable human resource development and nuclear knowledge management; host the Cyber Learning Platform for Nuclear Education and Training for the AFRA region and to integrate all available higher education capabilities in Africa

  5. Proceedings of the Workshop on Advanced Network and Technology Concepts for Mobile, Micro, and Personal Communications

    Science.gov (United States)

    Paul, Lori (Editor)

    1991-01-01

    The Workshop on Advanced Network and Technology Concepts for Mobile, Micro, and Personal Communications was held at NASA's JPL Laboratory on 30-31 May 1991. It provided a forum for reviewing the development of advanced network and technology concepts for turn-of-the-century telecommunications. The workshop was organized into three main categories: (1) Satellite-Based Networks (L-band, C-band, Ku-band, and Ka-band); (2) Terrestrial-Based Networks (cellular, CT2, PCN, GSM, and other networks); and (3) Hybrid Satellite/Terrestrial Networks. The proceedings contain presentation papers from each of the above categories.

  6. Artificial neural networks as a tool in urban storm drainage

    DEFF Research Database (Denmark)

    Loke, E.; Warnaars, E.A.; Jacobsen, P.

    1997-01-01

    The introduction of Artificial Neural Networks (ANNs) as a tool in the field of urban storm drainage is discussed. Besides some basic theory on the mechanics of ANNs and a general classification of the different types of ANNs, two ANN application examples are presented: The prediction of runoff...

  7. Identification of drought in Dhalai river watershed using MCDM and ANN models

    Science.gov (United States)

    Aher, Sainath; Shinde, Sambhaji; Guha, Shantamoy; Majumder, Mrinmoy

    2017-03-01

    An innovative approach for drought identification is developed using Multi-Criteria Decision Making (MCDM) and Artificial Neural Network (ANN) models from surveyed drought parameter data around the Dhalai river watershed in Tripura hinterlands, India. Total eight drought parameters, i.e., precipitation, soil moisture, evapotranspiration, vegetation canopy, cropping pattern, temperature, cultivated land, and groundwater level were obtained from expert, literature and cultivator survey. Then, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) were used for weighting of parameters and Drought Index Identification (DII). Field data of weighted parameters in the meso scale Dhalai River watershed were collected and used to train the ANN model. The developed ANN model was used in the same watershed for identification of drought. Results indicate that the Limited-Memory Quasi-Newton algorithm was better than the commonly used training method. Results obtained from the ANN model shows the drought index developed from the study area ranges from 0.32 to 0.72. Overall analysis revealed that, with appropriate training, the ANN model can be used in the areas where the model is calibrated, or other areas where the range of input parameters is similar to the calibrated region for drought identification.

  8. Development and Application of ANN Model for Worker Assignment into Virtual Cells of Large Sized Configurations

    International Nuclear Information System (INIS)

    Murali, R. V.; Fathi, Khalid; Puri, A. B.

    2010-01-01

    This paper presents an extended version of study already undertaken on development of an artificial neural networks (ANNs) model for assigning workforce into virtual cells under virtual cellular manufacturing systems (VCMS) environments. Previously, the same authors have introduced this concept and applied it to virtual cells of two-cell configuration and the results demonstrated that ANNs could be a worth applying tool for carrying out workforce assignments. In this attempt, three-cell configurations problems are considered for worker assignment task. Virtual cells are formed under dual resource constraint (DRC) context in which the number of available workers is less than the total number of machines available. Since worker assignment tasks are quite non-linear and highly dynamic in nature under varying inputs and conditions and, in parallel, ANNs have the ability to model complex relationships between inputs and outputs and find similar patterns effectively, an attempt was earlier made to employ ANNs into the above task. In this paper, the multilayered perceptron with feed forward (MLP-FF) neural network model has been reused for worker assignment tasks of three-cell configurations under DRC context and its performance at different time periods has been analyzed. The previously proposed worker assignment model has been reconfigured and cell formation solutions available for three-cell configuration in the literature are used in combination to generate datasets for training ANNs framework. Finally, results of the study have been presented and discussed.

  9. Trends in Energy Management Technology: BCS Integration Technologies - Open Communications Networking

    Energy Technology Data Exchange (ETDEWEB)

    Webster, Tom

    2002-09-18

    Our overall purpose in writing this series of articles is to provide Federal energy managers some basic informational tools to assist their decision making process relative to energy management systems design, specification, procurement, and energy savings potential. Since Federal buildings rely on energy management systems more than their commercial counterparts, it is important for energy practitioners to have a high level of knowledge and understanding of these complex systems. This is the second article in a series and will focus on building control system (BCS) networking fundamentals and an assessment of current approaches to open communications protocols. This is important because networking is a complex subject and the networks form the basic infrastructure for energy management functions and for integrating a wide variety of OEM equipment into a complete EMCIS. The first article [1] covered enabling technologies for emerging energy management systems. Future topics will concentrate on more practical aspects including applications software, product offerings, networking strategies, and case studies of actual installations. Please refer to the first article for a more complete overview of the purpose and background for this series.

  10. Technological Cooperation Networks at Bio-Manguinhos: the Role of Information and Communication Technologies

    Directory of Open Access Journals (Sweden)

    Lázaro Pereira de Oliveira

    2015-01-01

    Full Text Available This article identifies and discusses the contribution of information and communication technologies (ICTs to the technological cooperation projects of Bio-Manguinhos, a pharmaceutical manufacturer that belongs to Osvaldo Cruz Foundation (FIOCRUZ, responsible for producing vaccines, reagents and biopharmaceuticals, with priority on meeting the needs of the Brazilian public health system. It is a case study with a qualitative approach for descriptive and explanatory purposes. The data were collected from 14 interviews conducted with managers of research and development (R&D projects with high relevance to the organization. The results allow concluding that the ICTs requiring greater interdependence between partners and two-way knowledge flows have not yet been used. They also show the importance of closer cooperation between the information technology (IT and R&D areas. A future positioning of Bio-Manguinhos as a technological center focused on discovery and sale of new active ingredients can favor the use of tools that promote greater integration between the partners of technology cooperation networks.

  11. Theory Study and Application of the BP-ANN Method for Power Grid Short-Term Load Forecasting

    Institute of Scientific and Technical Information of China (English)

    Xia Hua; Gang Zhang; Jiawei Yang; Zhengyuan Li

    2015-01-01

    Aiming at the low accuracy problem of power system short⁃term load forecasting by traditional methods, a back⁃propagation artifi⁃cial neural network (BP⁃ANN) based method for short⁃term load forecasting is presented in this paper. The forecast points are re⁃lated to prophase adjacent data as well as the periodical long⁃term historical load data. Then the short⁃term load forecasting model of Shanxi Power Grid (China) based on BP⁃ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP⁃ANN method is simple and with higher precision and practicality.

  12. Heterogeneous Wireless Mesh Network Technology Evaluation for Space Proximity and Surface Applications

    Science.gov (United States)

    DeCristofaro, Michael A.; Lansdowne, Chatwin A.; Schlesinger, Adam M.

    2014-01-01

    NASA has identified standardized wireless mesh networking as a key technology for future human and robotic space exploration. Wireless mesh networks enable rapid deployment, provide coverage in undeveloped regions. Mesh networks are also self-healing, resilient, and extensible, qualities not found in traditional infrastructure-based networks. Mesh networks can offer lower size, weight, and power (SWaP) than overlapped infrastructure-perapplication. To better understand the maturity, characteristics and capability of the technology, we developed an 802.11 mesh network consisting of a combination of heterogeneous commercial off-the-shelf devices and opensource firmware and software packages. Various streaming applications were operated over the mesh network, including voice and video, and performance measurements were made under different operating scenarios. During the testing several issues with the currently implemented mesh network technology were identified and outlined for future work.

  13. Investigations on an environmental technology transfer information network; Kankyo gijutsu iten joho network chosa

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    With developing countries (APEC countries) as the main objects, investigations were carried out to issue environmental technology transfer information that Japan has accumulated, and advance exchanges of technical information with persons related inside and outside Japan. As a result of the investigations, it was found that the environmental technology information that serves more effectively for the developing countries is the technical information that has been developed by repeating improvements, has provided actual results in work sites, and is actually used, rather than the state-of-art technologies. Based on this result, business entities having factories and operation centers located in Mie Prefecture and the city of Yokkaichi were asked to provide data for the actually used environmental technologies. Out of 51 items provided by 17 companies, nine items were selected to be used as prototype database materials for an information network. The objects of information sources will be expanded to a nationwide scale in the future to improve the contents of the database. Problems of handling information copyrights and technical know-hows were presented in the course of data collection, urging the necessity of due considerations on the matter. Necessity was indicated on maintenance and management of data base as well as its quantitative expansion. 1 ref., 4 figs.

  14. Innovation and communicative action: health management networks and technologies.

    Science.gov (United States)

    Rivera, Francisco Javier Uribe; Artmann, Elizabeth

    2016-11-03

    This article discusses elements of a theory of innovation from the perspective of innovation networks and social construction of technology, based on Habermas' Theory of Communicative Action and authors from the Sociology of Innovation. Based on the theoretical framework of the communicative production of scientific facts, we focus on innovation management as a basic dimension that must meet some organizational and methodological requirements in order to power its results. We present and discuss instruments such as Situational Planning, Prospective Analysis, Strategic Portfolio Management, and Networks Management that can help deal with the challenge of innovation and exploration of the future. We conclude that network organizational formats centered on reflexivity of interdisciplinary groups and planning approaches that encourage innovation criteria in assessing the attractiveness of activities and that help anticipate forms of innovation through systematic prospective analysis can potentiate the process of generating innovation as a product of networks. Resumo: No artigo são discutidos elementos de uma teoria da inovação numa perspectiva de redes de inovação e de construção social da tecnologia, a partir da Teoria do Agir Comunicativo de Habermas e de autores da Sociologia da Inovação. Com base no marco teórico da produção comunicativa de fatos científicos, focamos a gestão da inovação como uma dimensão fundamental que deve contemplar alguns requisitos, tanto de natureza organizacional quanto metodológica, para potencializar seus resultados. Apresentamos e discutimos instrumentos como o Planejamento Situacional, a Análise Prospectiva, a Gestão Estratégica de Portfólios e a Gestão de Redes que podem contribuir para o desafio da inovação e exploração do futuro. Conclui-se que formas organizativas em rede, centradas na reflexividade de grupos interdisciplinares, e enfoques de planejamento que estimulem o uso de critérios de inovação na

  15. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 3: Advanced networks and economics

    Science.gov (United States)

    1986-10-01

    This study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  16. Prediction of IRI in short and long terms for flexible pavements: ANN and GMDH methods

    NARCIS (Netherlands)

    Ziari, H.; Sobhani, J.; Ayoubinejad, J.; Hartmann, Timo

    2015-01-01

    Prediction of pavement condition is one of the most important issues in pavement management systems. In this paper, capabilities of artificial neural networks (ANNs) and group method of data handling (GMDH) methods in predicting flexible pavement conditions were analysed in three levels: in 1 year,

  17. Do technologies have politics? The new paradigm and pedagogy in networked learning

    OpenAIRE

    Jones, Chris

    2001-01-01

    This paper explores the relationships between the technologies deployed in networked and e-Learning and the pedagogies and politics associated with them. Networked learning and the related move to e-Learning are coincident with the globalisation, commodification and massification of Higher Education. It examines the hard and soft forms of technological determinism (TD) found in the current advocacy of technological futures for Higher Education. Hard TD claims that new technologies bring about...

  18. Application of Ann for Prediction of Co2+, Cd2+ and Zn2+ Ions Uptake by R. Squarrosus Biomass in Single and Binary Mixtures

    Directory of Open Access Journals (Sweden)

    Nemeček Peter

    2014-06-01

    Full Text Available Discharge of heavy metals into aquatic ecosystems has become a matter of concern over the last few decades. The search for new technologies involving the removal of toxic metals from wastewaters has directed the attention to biosorption, based on metal binding capacities of various biological materials. Degree of sorbent affinity for the sorbate determines its distribution between the solid and liquid phases and this behavior can be described by adsorption isotherm models (Freundlich and Langmuir isotherm models representing the classical approach. In this study, an artificial neural network (ANN was proposed to predict the sorption efficiency in single and binary component solutions of Cd2+, Zn2+ and Co2+ ions by biosorbent prepared from biomass of moss Rhytidiadelphus squarrosus. Calculated non-linear ANN models presented in this paper are advantageous for its capability of successful prediction, which can be problematic in the case of classical isotherm approach. Quality of prediction was proved by strong agreement between calculated and measured data, expressed by the coefficient of determination in both, single and binary metal systems (R2= 0.996 and R2= 0.987, respectively. Another important benefit of these models is necessity of significantly smaller amount of data (about 50% for the model calculation. Also, it is possible to calculate Qeq for all studied metals by one combined ANN model, which totally overcomes a classical isotherm approach

  19. Obituary: Anne Barbara Underhill, 1920-2003

    Science.gov (United States)

    Roman, Nancy Grace

    2003-12-01

    Anne was born in Vancouver, British Columbia on 12 June 1920. Her parents were Frederic Clare Underhill, a civil engineer and Irene Anna (née Creery) Underhill. She had a twin brother and three younger brothers. As a young girl she was active in Girl Guides and graduated from high school winning the Lieutenant Governor's medal as one of the top students in the Province. She also excelled in high school sports. Her mother died when Anne was 18 and, while undertaking her university studies, Anne assisted in raising her younger brothers. Her twin brother was killed in Italy during World War II (1944), a loss that Anne felt deeply. Possibly because of fighting to get ahead in astronomy, a field overwhelming male when she started, she frequently appeared combative. At the University of British Columbia, Anne obtained a BA (honors) in Chemistry (1942), followed by a MA in 1944. After working for the NRC in Montreal for a year, she studied at the University of Toronto prior to entering the University of Chicago in 1946 to obtain her PhD. Her thesis was the first model computed for a multi-layered stellar atmosphere (1948). During this time she worked with Otto Struve, developing a lifetime interest in hot stars and the analysis of their high dispersion spectra. She received two fellowships from the University Women of Canada. She received a U.S. National Research Fellowship to work at the Copenhagen Observatory, and upon its completion, she returned to British Columbia to work at the Dominion Astrophysical Observatory as a research scientist from 1949--1962. During this period she spent a year at Harvard University as a visiting professor and at Princeton where she used their advanced computer to write the first code for modeling stellar atmospheres. Anne was invited to the University of Utrecht (Netherlands) as a full professor in 1962. She was an excellent teacher, well liked by the students in her classes, and by the many individuals that she guided throughout her

  20. Ann Arbor Session I: Breaking Ground.

    Science.gov (United States)

    Music Educators Journal, 1979

    1979-01-01

    Summarizes the first session of the National Symposium on the Applications of Psychology to the Teaching and Learning of Music held at Ann Arbor from October 30 to November 2, 1978. Sessions concerned auditory perception, motor learning, child development, memory and information processing, and affect and motivation. (SJL)

  1. Ilmus artiklikogumik "Eesti teadlased paguluses" / Anne Valmas

    Index Scriptorium Estoniae

    Valmas, Anne, 1941-2017

    2009-01-01

    TLÜ AR väliseesti kirjanduse keskuse ja TTÜ Raamatukogu koostöös 24.03.2009 toimunud konverentsist "Eesti teadlased paguluses", mis tutvustas väliseesti teadlaste osa maailmateaduses. Ettekannete põhjal valminud artiklikogumikust "Eesti teadlased paguluses", koostajad Vahur Mägi ja Anne Valmas. Tallinn : Tallinna Ülikooli Kirjastus, 2009

  2. Research on optical access network remote management technology

    Science.gov (United States)

    Wang, Wayne; Zou, Chen; Luo, Wenyi

    2008-11-01

    This paper goal is to provide a framework for the remote configuration and management of services for PON (Passive Optical Network) access and fiber access. Also it defines how Auto-Configuration Servers (ACS) in the network can remotely configure, troubleshoot and manage a Passive Optical Network (PON) optical network termination (ONT) with layer 3 capabilities using the CPE WAN management protocol, TR-069.

  3. A study of the security technology and a new security model for WiFi network

    Science.gov (United States)

    Huang, Jing

    2013-07-01

    The WiFi network is one of the most rapidly developing wireless communication networks, which makes wireless office and wireless life possible and greatly expands the application form and scope of the internet. At the same time, the WiFi network security has received wide attention, and this is also the key factor of WiFi network development. This paper makes a systematic introduction to the WiFi network and WiFi network security problems, and the WiFi network security technology are reviewed and compared. In order to solve the security problems in WiFi network, this paper presents a new WiFi network security model and the key exchange algorithm. Experiments are performed to test the performance of the model, the results show that the new security model can withstand external network attack and ensure stable and safe operation of WiFi network.

  4. Networking activities in technology-based entrepreneurial teams

    DEFF Research Database (Denmark)

    Neergaard, Helle

    2005-01-01

    Based on social network theoy, this article investigates the distribution of networking roles and responsibilities in entrepreneurial founding teams. Its focus is on the team as a collection of individuals, thus allowing the research to address differences in networking patterns. It identifies six...... central networking activities and shows that not all founding team members are equally active 'networkers'. The analyses show that team members prioritize different networking activities and that one member in particular has extensive networking activities whereas other memebrs of the team are more...

  5. Effectiveness of ANN for seismic behaviour prediction considering geometric configuration effect in concrete gravity dams

    Directory of Open Access Journals (Sweden)

    Mohd. Saqib

    2016-09-01

    Full Text Available In this study, an Artificial Neural Networks (ANN model is built and verified for quick estimation of the structural parameter obtained for a concrete gravity dam section due to seismic excitation. The database of numerous inputs and outputs obtained through Abaqus which are further converted into dimensionless forms in the statistical software (MATLAB to build the ANN model. The developed model can be used for accurate estimation of this parameter. The results showed an excellent capability of the model to predict the outputs with high accuracy and reduced computational time.

  6. Application of network technology to Remote Monitoring System

    International Nuclear Information System (INIS)

    Johnson, C.S.; Sorokowski, D.L.; Veevers, K.

    1994-01-01

    The Australian Safeguards Office (ASO) and the US Department of Energy (DOE) have sponsored work under a bilateral agreement to implement a Remote Monitoring System (RMS) at an Australian nuclear site operated by the Australian Nuclear Science and Technology Organization (ANSTO). The RMS, designed by Sandia National Laboratories (SNL), was installed in February 1994 at the Dry Spent Fuel Storage Facility (DSFSF) located at Lucas Heights, Australia. The RMS was designed to test a number of different concepts that would be useful for unattended remote monitoring activities. The DSFSF located in Building 27 is a very suitable test site for a RMS. The RMS uses a network of low cost nodes to collect data from a number of different sensors and security devices. Different sensors and detection devices have been installed to study how they can be used to complement each other for C/S applications. The data collected from the network will allow a comparison of how the various types of sensors perform under the same set of conditions. A video system using digital compression collects digital images and stores them on a hard drive and a digital optical disk. Data and images from the storage area are remotely monitored via telephone from Canberra, Australia and Albuquerque, NM, USA. These remote monitoring stations operated by ASO and SNL respectively, can retrieve data and images from the RMS computer at the DSFSF. The data and images are encrypted before transmission. The Remote Monitoring System field tests have been operational for six months with good test results. Sensors have performed well and the digital images have excellent resolution. The hardware and software have performed reliably without any major difficulties. This paper summarizes the highlights of the prototype system and the ongoing field tests

  7. The application of somputer and network technology in the realm of petroleum

    International Nuclear Information System (INIS)

    Liu Wei

    2003-01-01

    In the our country petroleum industry inside, the computer and network technology have become the important tools of exploring and developing new oil fields. Using jumped-up and most advanced computer and network technology will carve out wider foreground for the development of the petroleum realm. (authors)

  8. Assessing Community Informatics: A Review of Methodological Approaches for Evaluating Community Networks and Community Technology Centers.

    Science.gov (United States)

    O'Neil, Dara

    2002-01-01

    Analyzes the emerging community informatics evaluation literature to develop an understanding of the indicators used to gauge project impacts in community networks and community technology centers. The study finds that community networks and community technology center assessments fall into five key areas: strong democracy; social capital;…

  9. Une année d’immersion dans un dispositif de formation aux technologies : prise de conscience du potentiel éducatif des TICE, intentions d’action et changement de pratique

    Directory of Open Access Journals (Sweden)

    Daniel Peraya

    2012-01-01

    Full Text Available Cette contribution traite des effets d’un dispositif de formation hybride destiné à des étudiants de première année de psychologie et des sciences de l’éducation. La recherche se base sur une analyse qualitative de 66 rapports réflexifs d’étudiants rédigés dans le cadre d’un dispositif dont l’approche pédagogique se veut immersive et située. Cette approche favorise une meilleure compréhension du potentiel des TICE (médiation épistémique ainsi que, dans certains cas, un changement d’attitude par rapport à celles-ci (médiation posturale et, dans d’autres cas, un transfert d’usage à diverses sphères d’activité : académique, professionnelle ou personnelle (médiation praxéologique.

  10. Deployment of a Testbed in a Brazilian Research Network using IPv6 and Optical Access Technologies

    Science.gov (United States)

    Martins, Luciano; Ferramola Pozzuto, João; Olimpio Tognolli, João; Chaves, Niudomar Siqueira De A.; Reggiani, Atilio Eduardo; Hortêncio, Claudio Antonio

    2012-04-01

    This article presents the implementation of a testbed and the experimental results obtained with it on the Brazilian Experimental Network of the government-sponsored "GIGA Project." The use of IPv6 integrated to current and emerging optical architectures and technologies, such as dense wavelength division multiplexing and 10-gigabit Ethernet on the core and gigabit capable passive optical network and optical distribution network on access, were tested. These protocols, architectures, and optical technologies are promising and part of a brand new worldwide technological scenario that has being fairly adopted in the networks of enterprises and providers of the world.

  11. Control of GMA Butt Joint Welding Based on Neural Networks

    DEFF Research Database (Denmark)

    Christensen, Kim Hardam; Sørensen, Torben

    2004-01-01

    This paper presents results from an experimentally based research on Gas Metal Arc Welding (GMAW), controlled by the artificial neural network (ANN) technology. A system has been developed for modeling and online adjustment of welding parameters, appropriate to guarantee a high degree of quality......-linear least square error minimization, has been used with the back-propagation algorithm for training the network, while a Bayesian regularization technique has been successfully applied for minimizing the risk of inexpedient over-training....

  12. Novel Formulation of Adaptive MPC as EKF Using ANN Model: Multiproduct Semibatch Polymerization Reactor Case Study.

    Science.gov (United States)

    Kamesh, Reddi; Rani, Kalipatnapu Yamuna

    2017-12-01

    In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation over control horizon based on minimizing the deviation of model output predictions from set points along the prediction horizon. An industrial case study for temperature control of a multiproduct semibatch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANN-EKFMPC strategy at supervisory level as a cascade control configuration along with proportional integral controller [ANN-EKFMPC with PI (ANN-EKFMPC-PI)]. The proposed approach is formulated incorporating all aspects of MPC including move suppression factor for control effort minimization and constraint-handling capability including terminal constraints. The nominal stability analysis and offset-free tracking capabilities of the proposed controller are proved. Its performance is evaluated by comparison with a standard MPC-based cascade control approach using the same adaptive ANN model. The ANN-EKFMPC-PI control configuration has shown better controller performance in terms of temperature tracking, smoother input profiles, as well as constraint-handling ability compared with the ANN-MPC with PI approach for two products in summer and winter. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.

  13. Fault diagnosis in nuclear power plants using an artificial neural network technique

    International Nuclear Information System (INIS)

    Chou, H.P.; Prock, J.; Bonfert, J.P.

    1993-01-01

    Application of artificial intelligence (AI) computational techniques, such as expert systems, fuzzy logic, and neural networks in diverse areas has taken place extensively. In the nuclear industry, the intended goal for these AI techniques is to improve power plant operational safety and reliability. As a computerized operator support tool, the artificial neural network (ANN) approach is an emerging technology that currently attracts a large amount of interest. The ability of ANNs to extract the input/output relation of a complicated process and the superior execution speed of a trained ANN motivated this study. The goal was to develop neural networks for sensor and process faults diagnosis with the potential of implementing as a component of a real-time operator support system LYDIA, early sensor and process fault detection and diagnosis

  14. Anne-Mette Langes plan for ADHD kongressen

    DEFF Research Database (Denmark)

    Lange, Anne-Mette

    2017-01-01

    http://medicinsktidsskrift.dk/behandlinger/psykiatri/699-anne-mette-langes-plan-for-adhd-kongressen.html......http://medicinsktidsskrift.dk/behandlinger/psykiatri/699-anne-mette-langes-plan-for-adhd-kongressen.html...

  15. Application of modern technology for fieldwork support in network operations

    International Nuclear Information System (INIS)

    Eggen, Arnt Ove; Langdal, Bjoern Inge

    2006-04-01

    Demands for rational and efficient operation and management in several business sectors such as power-, oil- and gas industry, telecommunication, water and multi-utility has lead to big changes for personnel in charge of managing the infrastructure and for the field-workers. Contractors providing services for the large power network companies do not have the local knowledge about construction projects, and there are increased demands on efficiency related to completion, documentation and reporting. This implies a need for transmission of knowledge and experiences between office and the field, and support for fieldwork in the form of applications using various technological possibilities. Field solutions that have well-developed technical and organisational properties will make administration of the infrastructure more efficient, and raise the quality of the work. The choice of mobile service will always be a compromise between several different wishes and needs. The properties of hardware, software and communication options will often influence possible choices in the respective fields. As an important step in testing of hardware, software and communication, some prototypes have been developed for Pocket Pc. The prototypes 'Befaring' and 'HelikopterBefaring' have been chosen because they contain many of the elements that are important in a mobile solution. In addition a prototype for internet applications has been developed ('HelikopterBefaringMottak') and a Windows application ('HelikopterBefaringPresentasjon') in order to visualise the received and managed information sent from the mobile units. The technological development both in software, hardware, GPS and mobile telephones is extremely rapid, and the first mobile solutions with Pocket Pc, mobile telephone and GPS in one integrated unit is already on the market (ml)

  16. Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Driver And Dispatcher Perceptions Of AATA'S Advanced Operating System

    Science.gov (United States)

    1999-01-01

    In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

  17. Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Transfer And On-Time Performance Study : Before And After AOS Implementation, October 1996 - May 1999

    Science.gov (United States)

    1999-01-01

    In 1997, the Ann Arbor (Michigan) Transportation Authority began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such technolog...

  18. Modelling and automatic reactive power control of isolated wind-diesel hybrid power systems using ANN

    International Nuclear Information System (INIS)

    Bansal, R.C.

    2008-01-01

    This paper presents an artificial neural network (ANN) based approach to tune the parameters of the static var compensator (SVC) reactive power controller over a wide range of typical load model parameters. The gains of PI (proportional integral) based SVC are optimised for typical values of the load voltage characteristics (n q ) by conventional techniques. Using the generated data, the method of multi-layer feed forward ANN with error back propagation training is employed to tune the parameters of the SVC. An ANN tuned SVC controller has been applied to control the reactive power of a variable slip/speed isolated wind-diesel hybrid power system. It is observed that the maximum deviations of all parameters are more for larger values of n q . It has been shown that initially synchronous generator supplies the reactive power required by the induction generator and/or load, and the latter reactive power is purely supplied by the SVC

  19. Quick and reliable estimation of power distribution in a PHWR by ANN

    International Nuclear Information System (INIS)

    Dubey, B.P.; Jagannathan, V.; Kataria, S.K.

    1998-01-01

    Knowledge of the distribution of power in all the channels of a Pressurised Heavy Water Reactor (PHWR) as a result of a perturbation caused by one or more of the regulating devices is very important from the operation and maintenance point of view of the reactor. Theoretical design codes available for this purpose take several minutes to calculate the channel power distribution on modern PCs. Artificial Neural networks (ANNs) have been employed in predicting channel power distribution of Indian PHWRs for any given configuration of regulating devices of the reactor. ANNs produce the result much faster and with good accuracy. This paper describes the methodology of ANN, its reliability, the validation range, and scope for its possible on-line use in the actual reactor

  20. Modelling and automatic reactive power control of isolated wind-diesel hybrid power systems using ANN

    Energy Technology Data Exchange (ETDEWEB)

    Bansal, R.C. [Electrical and Electronics Engineering Division, School of Engineering and Physics, The University of the South Pacific, Suva (Fiji)

    2008-02-15

    This paper presents an artificial neural network (ANN) based approach to tune the parameters of the static var compensator (SVC) reactive power controller over a wide range of typical load model parameters. The gains of PI (proportional integral) based SVC are optimised for typical values of the load voltage characteristics (n{sub q}) by conventional techniques. Using the generated data, the method of multi-layer feed forward ANN with error back propagation training is employed to tune the parameters of the SVC. An ANN tuned SVC controller has been applied to control the reactive power of a variable slip/speed isolated wind-diesel hybrid power system. It is observed that the maximum deviations of all parameters are more for larger values of n{sub q}. It has been shown that initially synchronous generator supplies the reactive power required by the induction generator and/or load, and the latter reactive power is purely supplied by the SVC. (author)

  1. Korean efforts for education and training network in nuclear technology

    International Nuclear Information System (INIS)

    Han, Kyong-Won; Lee, Eui-Jin

    2007-01-01

    Nuclear energy has been a backbone for Korea's remarkable economic growth, and will continue its essential role with 18 nuclear power plants in operation, 2 more units under construction, 6 more units in planning. Korea is operating its own designed nuclear power plants, such as KSNP, 1400, as well as self-design and operation of 30 MW Hanaro research reactor. Korea makes strong efforts to develop future nuclear technology. They are the System-Integrated Modular Advanced Reactor, SMART, Korea Advanced Liquid Metal reactor, KALIMER, Hydrogen Production reactor, and Proliferation-resistant Nuclear Fuel Cycle. In parallel, Korea is establishing an Advanced Radiation Technology R and D Center and a High Power Proton Accelerator Center. International, next generation nuclear power technologies are being developed through projects such as the IAEA Innovative Nuclear Reactors and Fuel Cycle, INPRO, Generation IV International Forum, GIF, and International thermonuclear Experimental reactor, ITER. In the new millennium, Korea expects that radiation technology combined with bio, nano, and space technology will sustain our civilization. About 21,000 qualified nuclear human resources are engaged in power and non-power fields such as design and manufacturing of equipment, plant operation and maintenance, safety, RI production, R and D, etc. However, it is recognized that the first generation of nuclear work force is getting older and retired, less of our youth are studying nuclear science and engineering. Korean Government has established a promotion program on nuclear human resources development, which is needed until 2010. For the sustainable development of nuclear science and technology, it calls for more qualified human resources. We ought to encourage our youth to become more interested in nuclear studies and careers. Korea is making strong efforts to support nuclear education and training for young generations. It is believed that internationally accepted advanced

  2. Using ANN and EPR models to predict carbon monoxide concentrations in urban area of Tabriz

    Directory of Open Access Journals (Sweden)

    Mohammad Shakerkhatibi

    2015-09-01

    Full Text Available Background: Forecasting of air pollutants has become a popular topic of environmental research today. For this purpose, the artificial neural network (AAN technique is widely used as a reliable method for forecasting air pollutants in urban areas. On the other hand, the evolutionary polynomial regression (EPR model has recently been used as a forecasting tool in some environmental issues. In this research, we compared the ability of these models to forecast carbon monoxide (CO concentrations in the urban area of Tabriz city. Methods: The dataset of CO concentrations measured at the fixed stations operated by the East Azerbaijan Environmental Office along with meteorological data obtained from the East Azerbaijan Meteorological Bureau from March 2007 to March 2013, were used as input for the ANN and EPR models. Results: Based on the results, the performance of ANN is more reliable in comparison with EPR. Using the ANN model, the correlation coefficient values at all monitoring stations were calculated above 0.85. Conversely, the R2 values for these stations were obtained <0.41 using the EPR model. Conclusion: The EPR model could not overcome the nonlinearities of input data. However, the ANN model displayed more accurate results compared to the EPR. Hence, the ANN models are robust tools for predicting air pollutant concentrations.

  3. Simulation model of ANN based maximum power point tracking controller for solar PV system

    Energy Technology Data Exchange (ETDEWEB)

    Rai, Anil K.; Singh, Bhupal [Department of Electrical and Electronics Engineering, Ajay Kumar Garg Engineering College, Ghaziabad 201009 (India); Kaushika, N.D.; Agarwal, Niti [School of Research and Development, Bharati Vidyapeeth College of Engineering, A-4 Paschim Vihar, New Delhi 110063 (India)

    2011-02-15

    In this paper the simulation model of an artificial neural network (ANN) based maximum power point tracking controller has been developed. The controller consists of an ANN tracker and the optimal control unit. The ANN tracker estimates the voltages and currents corresponding to a maximum power delivered by solar PV (photovoltaic) array for variable cell temperature and solar radiation. The cell temperature is considered as a function of ambient air temperature, wind speed and solar radiation. The tracker is trained employing a set of 124 patterns using the back propagation algorithm. The mean square error of tracker output and target values is set to be of the order of 10{sup -5} and the successful convergent of learning process takes 1281 epochs. The accuracy of the ANN tracker has been validated by employing different test data sets. The control unit uses the estimates of the ANN tracker to adjust the duty cycle of the chopper to optimum value needed for maximum power transfer to the specified load. (author)

  4. Neural Networks to model the innovativeness perception of co-creative firms

    DEFF Research Database (Denmark)

    Tanev, Stoyan

    2012-01-01

    contribution is to make a quantitative analysis in order to assess the relationship between value co-creation and innovation in technology-driven firms: we are using Artificial Neural Network (ANN) to investigate the relationship between value co-creation and innovativeness, and Self Organising Map (SOM) models...

  5. Wi-Fi Network Communication Technology Design | Onibere ...

    African Journals Online (AJOL)

    Transmission media (like Satellite, VSAT), access method used to transmit both voice and data on the networks and underlying software and hardware requirements. Also the various standards and protocol for proper wireless networks management, the various authentication and encryption techniques of Wi -Fi network ...

  6. Strategic interactions in DRAM and RISC technology: A network approach

    NARCIS (Netherlands)

    Duysters, G.M.; Vanhaverbeke, W.P.M.

    1996-01-01

    Interorganizational cooperation in some high-tech industries is no longer confined to two-company alliances, but entails industry-wide alliance networks. This article examines how industry analysis and network analysis can be combined to provide a thorough understanding of how network positions, and

  7. 网络管理中的建模技术%Modeling Technologies in Network Management

    Institute of Scientific and Technical Information of China (English)

    张鹏; 李钢; 李增智

    2000-01-01

    Modeling is an effective approach during science research or engineering development. Based on the brief introduction to basic structure of network management systems ,this paper discusses the application scope of modeling method. Subsequently, related to the development work in the project of HiTMN, a local telephone network management system, two kinds of model are built for telephone switching network. They are mathematical model and object-oriented model, built using mathematical modeling method and object modeling technology respectively. Finally ,the importance of using modeling technologies in network management is emphasized.

  8. Research on key technology of planning and design for AC/DC hybrid distribution network

    Science.gov (United States)

    Shen, Yu; Wu, Guilian; Zheng, Huan; Deng, Junpeng; Shi, Pengjia

    2018-04-01

    With the increasing demand of DC generation and DC load, the development of DC technology, AC and DC distribution network integrating will become an important form of future distribution network. In this paper, the key technology of planning and design for AC/DC hybrid distribution network is proposed, including the selection of AC and DC voltage series, the design of typical grid structure and the comprehensive evaluation method of planning scheme. The research results provide some ideas and directions for the future development of AC/DC hybrid distribution network.

  9. Semantic Technologies for User-Centric Home Network Management

    OpenAIRE

    Ibrahim Rana, Annie

    2015-01-01

    Home area network (HAN) management is problematic for ordinary home users. Lack of user expertise, potential complexity of administration tasks, extreme diversity of network devices, price pressures producing devices with minimal feature sets, and highly dynamic requirements of user applications are some of the main challenges in HANs. As networking becomes enabled in many more HAN devices, these problems are set to increase. A viable solution to address these challenges lie...

  10. Comprehensive heat transfer correlation for water/ethylene glycol-based graphene (nitrogen-doped graphene) nanofluids derived by artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS)

    Science.gov (United States)

    Savari, Maryam; Moghaddam, Amin Hedayati; Amiri, Ahmad; Shanbedi, Mehdi; Ayub, Mohamad Nizam Bin

    2017-10-01

    Herein, artificial neural network and adaptive neuro-fuzzy inference system are employed for modeling the effects of important parameters on heat transfer and fluid flow characteristics of a car radiator and followed by comparing with those of the experimental results for testing data. To this end, two novel nanofluids (water/ethylene glycol-based graphene and nitrogen-doped graphene nanofluids) were experimentally synthesized. Then, Nusselt number was modeled with respect to the variation of inlet temperature, Reynolds number, Prandtl number and concentration, which were defined as the input (design) variables. To reach reliable results, we divided these data into train and test sections to accomplish modeling. Artificial networks were instructed by a major part of experimental data. The other part of primary data which had been considered for testing the appropriateness of the models was entered into artificial network models. Finally, predictad results were compared to the experimental data to evaluate validity. Confronted with high-level of validity confirmed that the proposed modeling procedure by BPNN with one hidden layer and five neurons is efficient and it can be expanded for all water/ethylene glycol-based carbon nanostructures nanofluids. Finally, we expanded our data collection from model and could present a fundamental correlation for calculating Nusselt number of the water/ethylene glycol-based nanofluids including graphene or nitrogen-doped graphene.

  11. Attacks on public telephone networks: technologies and challenges

    Science.gov (United States)

    Kosloff, T.; Moore, Tyler; Keller, J.; Manes, Gavin W.; Shenoi, Sujeet

    2003-09-01

    Signaling System 7 (SS7) is vital to signaling and control in America's public telephone networks. This paper describes a class of attacks on SS7 networks involving the insertion of malicious signaling messages via compromised SS7 network components. Three attacks are discussed in detail: IAM flood attacks, redirection attacks and point code spoofing attacks. Depending on their scale of execution, these attacks can produce effects ranging from network congestion to service disruption. Methods for detecting these denial-of-service attacks and mitigating their effects are also presented.

  12. Application of ANN-SCE model on the evaluation of automatic generation control performance

    Energy Technology Data Exchange (ETDEWEB)

    Chang-Chien, L.R.; Lo, C.S.; Lee, K.S. [National Cheng Kung Univ., Tainan, Taiwan (China)

    2005-07-01

    An accurate evaluation of load frequency control (LFC) performance is needed to balance minute-to-minute electricity generation and demand. In this study, an artificial neural network-based system control error (ANN-SCE) model was used to assess the performance of automatic generation controls (AGC). The model was used to identify system dynamics for control references in supplementing AGC logic. The artificial neural network control error model was used to track a single area's LFC dynamics in Taiwan. The model was used to gauge the impacts of regulation control. Results of the training, evaluating, and projecting processes showed that the ANN-SCE model could be algebraically decomposed into components corresponding to different impact factors. The SCE information obtained from testing of various AGC gains provided data for the creation of a new control approach. The ANN-SCE model was used in conjunction with load forecasting and scheduled generation data to create an ANN-SCE identifier. The model successfully simulated SCE dynamics. 13 refs., 10 figs.

  13. Process Control Strategies for Dual-Phase Steel Manufacturing Using ANN and ANFIS

    Science.gov (United States)

    Vafaeenezhad, H.; Ghanei, S.; Seyedein, S. H.; Beygi, H.; Mazinani, M.

    2014-11-01

    In this research, a comprehensive soft computational approach is presented for the analysis of the influencing parameters on manufacturing of dual-phase steels. A set of experimental data have been gathered to obtain the initial database used for the training and testing of both artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS). The parameters used in the strategy were intercritical annealing temperature, carbon content, and holding time which gives off martensite percentage as an output. A fraction of the data set was chosen to train both ANN and ANFIS, and the rest was put into practice to authenticate the act of the trained networks while seeing unseen data. To compare the obtained results, coefficient of determination and root mean squared error indexes were chosen. Using artificial intelligence methods, it is not necessary to consider and establish a preliminary mathematical model and formulate its affecting parameters on its definition. In conclusion, the martensite percentages corresponding to the manufacturing parameters can be determined prior to a production using these controlling algorithms. Although the results acquired from both ANN and ANFIS are very encouraging, the proposed ANFIS has enhanced performance over the ANN and takes better effect on cost-reduction profit.

  14. The key network communication technology in large radiation image cooperative process system

    International Nuclear Information System (INIS)

    Li Zheng; Kang Kejun; Gao Wenhuan; Wang Jingjin

    1998-01-01

    Large container inspection system (LCIS) based on radiation imaging technology is a powerful tool for the customs to check the contents inside a large container without opening it. An image distributed network system is composed of operation manager station, image acquisition station, environment control station, inspection processing station, check-in station, check-out station, database station by using advanced network technology. Mass data, such as container image data, container general information, manifest scanning data, commands and status, must be on-line transferred between different stations. Advanced network communication technology is presented

  15. Application and study of advanced network technology in large container inspection system

    International Nuclear Information System (INIS)

    Li Zheng; Kang Kejun; Gao Wenhuan; Wang Jingjin

    1996-01-01

    Large Container Inspection System (LCIS) based on radiation imaging technology is a powerful tool for the customs to check the contents inside a large container without opening it. An image distributed network system is composed of center manager station, image acquisition station, environment control station, inspection processing station, check-in station, check-out station, database station by using advanced network technology. Mass data, such as container image data, container general information, manifest scanning data, commands and status, must be on-line transferred between different stations. Advanced network technology and software programming technique are presented

  16. Two-component network model in voice identification technologies

    Directory of Open Access Journals (Sweden)

    Edita K. Kuular

    2018-03-01

    Full Text Available Among the most important parameters of biometric systems with voice modalities that determine their effectiveness, along with reliability and noise immunity, a speed of identification and verification of a person has been accentuated. This parameter is especially sensitive while processing large-scale voice databases in real time regime. Many research studies in this area are aimed at developing new and improving existing algorithms for presentation and processing voice records to ensure high performance of voice biometric systems. Here, it seems promising to apply a modern approach, which is based on complex network platform for solving complex massive problems with a large number of elements and taking into account their interrelationships. Thus, there are known some works which while solving problems of analysis and recognition of faces from photographs, transform images into complex networks for their subsequent processing by standard techniques. One of the first applications of complex networks to sound series (musical and speech analysis are description of frequency characteristics by constructing network models - converting the series into networks. On the network ontology platform a previously proposed technique of audio information representation aimed on its automatic analysis and speaker recognition has been developed. This implies converting information into the form of associative semantic (cognitive network structure with amplitude and frequency components both. Two speaker exemplars have been recorded and transformed into pertinent networks with consequent comparison of their topological metrics. The set of topological metrics for each of network models (amplitude and frequency one is a vector, and together  those combine a matrix, as a digital "network" voiceprint. The proposed network approach, with its sensitivity to personal conditions-physiological, psychological, emotional, might be useful not only for person identification

  17. Modelling flow dynamics in water distribution networks using ...

    African Journals Online (AJOL)

    One such approach is the Artificial Neural Networks (ANNs) technique. The advantage of ANNs is that they are robust and can be used to model complex linear and non-linear systems without making implicit assumptions. ANNs can be trained to forecast flow dynamics in a water distribution network. Such flow dynamics ...

  18. NETWORK-CENTRIC TECHNOLOGIES FOR CONTROL OF THREE-PHASE NETWORK OPERATION MODES

    Directory of Open Access Journals (Sweden)

    Ye. I. Sokol

    2017-06-01

    Full Text Available Purpose. The development of the control system for three-phase network is based on intelligent technologies of network-centric control of heterogeneous objects. The introduction of unmanned aerial vehicles for monitoring of three-phase network increases the efficiency of management. Methodology. The case of decomposition of the instantaneous capacities of the fixed and variable components for 3-wire system. The features of power balance for the different modes of its functioning. It should be noted that symmetric sinusoidal mode is balanced and good, but really unbalanced, if the standard reactive power is not zero. To solve the problem of compensation is sufficient knowledge of the total value of the inactive components of full power (value of the inactive power without detail. The creation of a methodology of measurement and assessment will require knowledge of the magnitudes of each inactive component separately, which leads to the development of a unified approach to the measurement and compensation of inactive components of full power and the development of a generalized theory of power. Results. Procedure for the compensation of the current of zero sequence excludes from circuit the source, as the active component of instantaneous power of zero sequence, and a vector due to a current of zero sequence. This procedure is performed without time delay as it does not require integration. Only a 3–wire system with symmetrical voltage eliminates pulsations and symmetrization of the equivalent conductances of the phases of the task. Under asymmetric voltage, the power is different, its analysis requires the creation of a vector mathematical model of the energy processes of asymmetrical modes of 3–phase systems. Originality. The proposed method extends the basis of the vector method for any zero sequence voltages and shows that the various theories of instantaneous power three wired scheme due to the choice of a basis in a two

  19. Technologies for all-optical wavelength conversion in DWDM networks

    DEFF Research Database (Denmark)

    Wolfson, David; Fjelde, Tina; Kloch, Allan

    2001-01-01

    Different techniques for all-optical wavelength conversion are reviewed and the advantages and disadvantages seen from a system perspective are highlighted. All-optical wavelength conversion will play a major role in making cost-effective network nodes in future high-speed WDM networks, where...

  20. Cloud RAN for Mobile Networks - a Technology Overview

    DEFF Research Database (Denmark)

    Checko, Aleksandra; Christiansen, Henrik Lehrmann; Yan, Ying

    2014-01-01

    Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can address a number of challenges the operators face while trying to support growing end-user’s needs. The main idea behind C-RAN is to pool the Baseband Units (BBUs) from multiple base stations into centralized BBU...

  1. Processing horizontal networks measured by integrated terrestrial and GPS technologies

    Directory of Open Access Journals (Sweden)

    Vincent Jakub

    2003-09-01

    Full Text Available Local horizontal networks in which GPS and terrestrial measurements (TER are done are often established at present. Iin other networks, the previous terrestrial measurements can be completed with quantities from contemporary GPS observations (tunnel nets, mining nets with surface and underground parts and other long-shaped nets.The processing of such heterobeneous (GPS, TER networks whose terrestrial measurements are performed as point coordinate measurements (∆X, ∆Y using (geodetic total stationIn is presented in this paper. In such network structures it is then available:- the values ∆X, ∆Y from TER observations which are transformed in the plane of S-JTSK for adjustement,- the values ∆X, ∆Y in the plane S-JTSK that can be obtained by 3D transformation of WGS84 netpoint coordinates from GPS observations to corresponding coordinates S-JTSK.For common adjusting all the ∆X, ∆Y, some elements of the network geometry (e.g. distances should be measured by both methods (GPS, TER. This approach makes possible an effective homogenisation of both network parts what is equivalent to saying that an expressive influence reduction on local frame realizations of S-JTSK in the whole network can be made.Results of network processing obtained in proposed manner are acceptable in general and they are equivalent (accuracy, reliability to results of another processing methods.

  2. Application of local computer networks in nuclear-physical experiments and technology

    International Nuclear Information System (INIS)

    Foteev, V.A.

    1986-01-01

    The bases of construction, comparative performance and potentialities of local computer networks with respect to their application in physical experiments are considered. The principle of operation of local networks is shown on the basis of the Ethernet network and the results of analysis of their operating performance are given. The examples of operating local networks in the area of nuclear-physics research and nuclear technology are presented as follows: networks of Japan Atomic Energy Research Institute, California University and Los Alamos National Laboratory, network realization according to the DECnet and Fast-bus programs, home network configurations of the USSR Academy of Sciences and JINR Neutron Physical Laboratory etc. It is shown that local networks allows significantly raise productivity in the sphere of data processing

  3. Exploring Social Networking Technologies as Tools for HIV Prevention for Men Who Have Sex With Men.

    Science.gov (United States)

    Ramallo, Jorge; Kidder, Thomas; Albritton, Tashuna; Blick, Gary; Pachankis, John; Grandelski, Valen; Grandeleski, Valen; Kershaw, Trace

    2015-08-01

    Social networking technologies are influential among men who have sex with men (MSM) and may be an important strategy for HIV prevention. We conducted focus groups with HIV positive and negative participants. Almost all participants used social networking sites to meet new friends and sexual partners. The main obstacle to effective HIV prevention campaigns in social networking platforms was stigmatization based on homosexuality as well as HIV status. Persistent stigma associated with HIV status and disclosure was cited as a top reason for avoiding HIV-related conversations while meeting new partners using social technologies. Further, social networking sites have different social etiquettes and rules that may increase HIV risk by discouraging HIV status disclosure. Overall, successful interventions for MSM using social networking technologies must consider aspects of privacy, stigma, and social norms in order to enact HIV reduction among MSM.

  4. Discussion on the Technology and Method of Computer Network Security Management

    Science.gov (United States)

    Zhou, Jianlei

    2017-09-01

    With the rapid development of information technology, the application of computer network technology has penetrated all aspects of society, changed people's way of life work to a certain extent, brought great convenience to people. But computer network technology is not a panacea, it can promote the function of social development, but also can cause damage to the community and the country. Due to computer network’ openness, easiness of sharing and other characteristics, it had a very negative impact on the computer network security, especially the loopholes in the technical aspects can cause damage on the network information. Based on this, this paper will do a brief analysis on the computer network security management problems and security measures.

  5. Comparative analysis of the application of different Low Power Wide Area Network technologies in power grid

    Science.gov (United States)

    Wang, Hao; Sui, Hong; Liao, Xing; Li, Junhao

    2018-03-01

    Low Power Wide Area Network (LPWAN) technologies developed rapidly in recent years, but the application principle of different LPWAN technologies in power grid is still not clear. This paper gives a comparative analysis of two mainstream LPWAN technologies including NB-IoT and LoRa, and gives an application suggestion of these two LPWAN technologies, which can guide the planning and construction of LPWAN in power grid.

  6. Crossing the technology adoption chasm in the presence of network externalities implications for DoD

    OpenAIRE

    Schang, Suzanne L.

    2007-01-01

    This thesis explores factors inhibiting technologies from crossing the technology diffusion "chasm" in between early and wide-scale adoption. It focuses on cost and benefit uncertainty as well as network effects applied to end-users and their organizations. Specifically, it explores Department of Defense (DoD) acquisition programs bringing promising technologies to the field defines successful technology adoption as realizing its full potential return on investment by achieving the widest ...

  7. Enabling Research Network Connectivity to Clouds with Virtual Router Technology

    Science.gov (United States)

    Seuster, R.; Casteels, K.; Leavett-Brown, CR; Paterson, M.; Sobie, RJ

    2017-10-01

    The use of opportunistic cloud resources by HEP experiments has significantly increased over the past few years. Clouds that are owned or managed by the HEP community are connected to the LHCONE network or the research network with global access to HEP computing resources. Private clouds, such as those supported by non-HEP research funds are generally connected to the international research network; however, commercial clouds are either not connected to the research network or only connect to research sites within their national boundaries. Since research network connectivity is a requirement for HEP applications, we need to find a solution that provides a high-speed connection. We are studying a solution with a virtual router that will address the use case when a commercial cloud has research network connectivity in a limited region. In this situation, we host a virtual router in our HEP site and require that all traffic from the commercial site transit through the virtual router. Although this may increase the network path and also the load on the HEP site, it is a workable solution that would enable the use of the remote cloud for low I/O applications. We are exploring some simple open-source solutions. In this paper, we present the results of our studies and how it will benefit our use of private and public clouds for HEP computing.

  8. Networking and Information Technology Research and Development. Supplement of the President's Budget for Fiscal Year 2006

    National Research Council Canada - National Science Library

    2005-01-01

    This Supplement to the President's Budget for Fiscal Year 2006 offers a brief technical outline of the 2006 budget request for the Networking and Information Technology Research and Development (NITRD) Program...

  9. Grand Challenges: Science, Engineering, and Societal Advances, Requiring Networking and Information Technology Research and Development

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — ...the U.S. Government makes critical decisions about appropriate investments in IT R and D to help society forward both socially and economically. To inform that...

  10. Collaboration on technological innovation in Danish fashion chains: A network perspective

    DEFF Research Database (Denmark)

    Tambo, Torben

    2014-01-01

    and departments stores, technology and service providers, ownership structures and local level supply chain facilities. This paper analyses theoretical and empirical views of innovation in international retail networks using lead actors in the (Danish) fashion industry as a case to highlight how this industry...... in business networks. The network comprises an innovation system that focuses on organisational learning and iterative development of the intended technologies. Implications of the current study are suggestions to brand owners, network partners and retailers on how to identify, understand, support and promote......With brand owners struggling to compete with new products, physical production processes and sourcing logistics, innovation taking place in retail networks is often overlooked. Networks in retailing are comprised by the brand owner, the varieties of single- and multi-brand stores, chains...

  11. Handbook of sensor networking advanced technologies and applications

    CERN Document Server

    Vacca, John R

    2015-01-01

    ""John R. Vacca has been a forward thinker in how omnipotent networks will work and envisioned many types of devices and functions that can be networked. His work in these areas is unsurpassed by other writers and visionaries.In this book, John has pulled together the knowledge that is needed for managers and developers to keep moving forward, and to do so faster, with sensor networking machines and devices that can perform both the mundane and complex tasks that are required for process management and production, which is necessary to propel enterprises and thus drive the global econom

  12. Cloud RAN for Mobile Networks - a Technology Overview

    OpenAIRE

    Checko, Aleksandra; Christiansen, Henrik Lehrmann; Yan, Ying; Scolari, Lara; Kardaras, Georgios; Berger, Michael Stübert; Dittmann, Lars

    2014-01-01

    Cloud Radio Access Network (C-RAN) is a novel mobile network architecture which can address a number of challenges the operators face while trying to support growing end-user’s needs. The main idea behind C-RAN is to pool the Baseband Units (BBUs) from multiple base stations into centralized BBU Pool for statistical multiplexing gain, while shifting the burden to the high-speed wireline transmission of In-phase and Quadrature (IQ) data. C-RAN enables energy efficient network operation and pos...

  13. Network Coding is the 5G Key Enabling Technology

    DEFF Research Database (Denmark)

    Compta, Pol Torres; Fitzek, Frank; Roetter, Daniel Enrique Lucani

    2015-01-01

    The exponential growth of the mobile devices market, not only smartphones, but also tablets, laptops or wearables, poses a serious challenge for 5G communications. Random Linear Network Coding (RLNC) is a promising solution for present and future networks as it has been shown to provide increased...... throughput, security, and robustness for the transmission of data through the network. Most of the analysis and the demonstrators have focused on the study of data packets with the same size (number of bytes). This constitutes a best case scenario as coded packets will incur little overhead to handle...

  14. An exploration of options and functions of climate technology centres and networks. Discussion paper

    International Nuclear Information System (INIS)

    De Coninck, H.C.; Wuertenberger, L.; Cochran, J.; Cox, S.; Benioff, R.

    2010-11-01

    This paper responds to a request to UNEP from the UNFCCC Expert Group on Technology Transfer to examine operational modalities for climate technology centres and networks. The paper first discusses possible dimensions for the climate technology centre and network, and it reviews a number of existing networks and centres. It then distinguishes five options for the organizational structure and describes potential operational characteristics for each of these options. All options examined seek to build from existing climate and non-climate-related public and private technology centres, networks, and initiatives. Consistent with the UNFCCC negotiating text and draft technology decision, the paper evaluates potential implementation options and outcomes for each of the functions tentatively assigned to the climate technology centre and network, as well as selected functions of the technology executive committee. Approaches are offered for integrating delivery of these functions through coordinated programmes, and hypothetical examples are given to explain how the technology mechanism might add value in practice. The options presented in this paper are not an exhaustive treatment of potential structures or implementation approaches, and other approaches can be considered.

  15. Kui vana on kunstnik? / Anneli Porri

    Index Scriptorium Estoniae

    Porri, Anneli, 1980-

    2003-01-01

    Rahvusvahelise kunstihariduse konverentsi "InSea on Sea" raames Kunstiakadeemia galeriis Karin Laansoo kureeritud Tallinna Kunstikooli õpilaste tööde näitus "MÄRKmed", Draakoni galeriis Mari Sobolevi kureeritud Viljandi Maagümnaasiumi kunstistuudio näitus "Sisseastumiseksam maailma", rahvusraamatukogus Anneli Porri kureeritud näitus "Kokkuvõte" EKA tänavuste lõpetajate töödest ja näitus "Leitud tagahoovist", Kullo galeriis rahvusvaheline näitus "Dialoog erinevuste vahel"

  16. Use of neural networks to monitor power plant components

    International Nuclear Information System (INIS)

    Ikonomopoulos, A.; Tsoukalas, L.H.

    1992-01-01

    A new methodology is presented for nondestructive evaluation (NDE) of check valve performance and degradation. Artificial neural network (ANN) technology is utilized for processing frequency domain signatures of check valves operating in a nuclear power plant (NPP). Acoustic signatures obtained from different locations on a check valve are transformed from the time domain to the frequency domain and then used as input to a pretrained neural network. The neural network has been trained with data sets corresponding to normal operation, therefore establishing a basis for check valve satisfactory performance. Results obtained from the proposed methodology demonstrate the ability of neural networks to perform accurate and quick evaluations of check valve performance

  17. Fractured reservoir discrete feature network technologies. Final report, March 7, 1996 to September 30, 1998

    Energy Technology Data Exchange (ETDEWEB)

    Dershowitz, William S.; Einstein, Herbert H.; LaPoint, Paul R.; Eiben, Thorsten; Wadleigh, Eugene; Ivanova, Violeta

    1998-12-01

    This report summarizes research conducted for the Fractured Reservoir Discrete Feature Network Technologies Project. The five areas studied are development of hierarchical fracture models; fractured reservoir compartmentalization, block size, and tributary volume analysis; development and demonstration of fractured reservoir discrete feature data analysis tools; development of tools for data integration and reservoir simulation through application of discrete feature network technologies for tertiary oil production; quantitative evaluation of the economic value of this analysis approach.

  18. The role of social networks in financing technology-based ventures: an empirical exploration

    NARCIS (Netherlands)

    Heuven, J.M.J.; Groen, Arend J.

    2012-01-01

    The focus of this study is on the role of networks in both identifying and accessing financial resource providers by technology-based ventures. We explore the role of networks by taking into account several specifications. We (1) acknowledge that new ventures can access financial resource providers

  19. Success Factors and Challenges of an Information Communication Technology Network in Rural Schools

    Science.gov (United States)

    Mihai, Maryke A.

    2017-01-01

    In April 2008, an interactive information communication technology (ICT) network was established in Mpumalanga, South Africa. the network involved the implementation of SMART board interactive whiteboards (IWBs) and collaboration between a leading school and several disadvantaged schools. the main purpose of the Mpumalanga IWB project was to reach…

  20. Technologies That Support Marketing and Market Development in SMEs—Evidence from Social Networks

    NARCIS (Netherlands)

    Eggers, Fabian; Hatak, Isabella; Kraus, Sascha; Niemand, Thomas

    2017-01-01

    This study builds on previous research on information technology implementation and usage in small and medium-sized enterprises (SMEs) and applies a special focus on social networks. Specifically, this research investigates antecedents of social network usage in SMEs and respective performance

  1. Ethernet access network based on free-space optic deployment technology

    Science.gov (United States)

    Gebhart, Michael; Leitgeb, Erich; Birnbacher, Ulla; Schrotter, Peter

    2004-06-01

    The satisfaction of all communication needs from single households and business companies over a single access infrastructure is probably the most challenging topic in communications technology today. But even though the so-called "Last Mile Access Bottleneck" is well known since more than ten years and many distribution technologies have been tried out, the optimal solution has not yet been found and paying commercial access networks offering all service classes are still rare today. Conventional services like telephone, radio and TV, as well as new and emerging services like email, web browsing, online-gaming, video conferences, business data transfer or external data storage can all be transmitted over the well known and cost effective Ethernet networking protocol standard. Key requirements for the deployment technology driven by the different services are high data rates to the single customer, security, moderate deployment costs and good scalability to number and density of users, quick and flexible deployment without legal impediments and high availability, referring to the properties of optical and wireless communication. We demonstrate all elements of an Ethernet Access Network based on Free Space Optic distribution technology. Main physical parts are Central Office, Distribution Network and Customer Equipment. Transmission of different services, as well as configuration, service upgrades and remote control of the network are handled by networking features over one FSO connection. All parts of the network are proven, the latest commercially available technology. The set up is flexible and can be adapted to any more specific need if required.

  2. Computer Networking Laboratory for Undergraduate Computer Technology Program

    National Research Council Canada - National Science Library

    Naghedolfeizi, Masoud

    2000-01-01

    ...) To improve the quality of education in the existing courses related to computer networks and data communications as well as other computer science courses such programming languages and computer...

  3. Using Web-Based Technologies for Network Management Tools

    National Research Council Canada - National Science Library

    Agami, Arie

    1997-01-01

    .... New solutions to current network management tools problems may be found in the increasingly popular World Wide Web, Internet tools such as Java, and remote database access through the Internet...

  4. Local area networks an introduction to the technology

    CERN Document Server

    McNamara, John E

    1985-01-01

    This concise book provides an objective introduction to local area networks - how they work, what they do, and how you can benefit from them. It outlines the pros and cons of the most common configurations so you can evaluate them in light of your own needs. You'll also learn about network software, with special emphasis on the ISO layered model of communications protocols.

  5. Mesh Networking in the Tactical Environment Using White Space Technolog

    Science.gov (United States)

    2015-12-01

    facilitate the establishment of a point to multi-point network topology . The base station node handles the compilation of data necessary to determine a...the client nodes from the base station node, the number of client nodes, and the network topology . The metrics chosen for evaluation were picked as a...model, are commonly utilized to simulate quadratic path loss across free space [22]. This model uses the following formula to calculate path loss: L

  6. Stability analysis of rubblemound breakwater using ANN

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Rao, S.; Manjunath, Y.R.; Kim, D.H.

    relation is not clear. In more practical terms networks are non-linear modeling tools and they can be used to model complex relationship between input and output system. Earlier applications of neural networks for stability analysis of rubble mound.... WORKING PRINCIPLE OF NEURAL NETWORK The feed forward neural networks have ability to approximate any continuous function or complex phenomena into a simple one. The working of neural network as described below. A feed forward neural network as shown...

  7. Network Technologies for Networked Terrorists: Assessing the Value of Information and Communication Technologies to Modern Terrorist Organizations

    National Research Council Canada - National Science Library

    Don, Bruce; Frelinger, Dave; Gerwehr, Scott; Landree, Eric; Jackson, Brian

    2007-01-01

    .... This book explores the role that these communications and computer technologies play and the net effect of their use, the purpose and manner in which the technology is used, the operational actions...

  8. Determinants of International Technology Transfer: an Empirical Analysis of the Enterprise Europe Network

    Directory of Open Access Journals (Sweden)

    Carina Araújo

    2014-09-01

    Full Text Available This paper explores the key factors that foster technology transfer within the triad university-industry-government in an international context, i.e., the Enterprise Europe Network (EEN. Based on 71 technological Partnership Agreements (PAs, estimation results indicate that PAs associated to partners that provide their collaborators with the appropriate training in technology transfer-related issues, present substantial past experience in international or technological projects, and participate in extensive networks, are those that achieve better performances in terms of international technology transfer. High levels of formal schooling per se are not a key determinant of international technology transfer; the critical factor is highly educated human resources who receive complementary training in technology transfer issues.

  9. Anneli Randla kaitses doktorikraadi Cambridge'is / Anneli Randla ; interv. Reet Varblane

    Index Scriptorium Estoniae

    Randla, Anneli, 1970-

    1999-01-01

    5. mail kaitses Cambridge'is esimese eesti kunstiteadlasena doktorikraadi Anneli Randla. Töö teema: kerjusmungaordukloostrite arhitektuur Põhja-Euroopas. Juhendaja dr. Deborah Howard. Doktorikraadile esitatavatest nõudmistest, doktoritöö kaitsmisest, magistrikraadi kaitsnu õppimisvõimalustest Cambridge's.

  10. Ensemble ANNs-PSO-GA Approach for Day-ahead Stock E-exchange Prices Forecasting

    Directory of Open Access Journals (Sweden)

    Yi Xiao

    2013-02-01

    Full Text Available Stock e-exchange prices forecasting is an important financial problem that is receiving increasing attention. This study proposes a novel three-stage nonlinear ensemble model. In the proposed model, three different types of neural-network based models, i.e. Elman network, generalized regression neural network (GRNN and wavelet neural network (WNN are constructed by three non-overlapping training sets and are further optimized by improved particle swarm optimization (IPSO. Finally, a neural-network-based nonlinear meta-model is generated by learning three neural-network based models through support vector machines (SVM neural network. The superiority of the proposed approach lies in its flexibility to account for potentially complex nonlinear relationships. Three daily stock indices time series are used for validating the forecasting model. Empirical results suggest the ensemble ANNs-PSO-GA approach can significantly improve the prediction performance over other individual models and linear combination models listed in this study.

  11. Advice Networks and Local Diffusion of Technological Innovations

    Science.gov (United States)

    Barahona, Juan Carlos; Pentland, Alex Sandy

    Classical writers such as John Stuart Mill and Karl Marx speculated that the standard of living could not rise indefinitely unless advances in technology increased the yield of the means of production. Neoclassical growth theory, based on capital accumulation, supports this intuition [1]. Digital tools increase personal productivity. Communication technologies enhance the coordination among individuals and increase the efficacy and efficiency of collective efforts. In both ways, technology contributes with wealth creation and the overall welfare of the community.

  12. European network for health technology assessment, EUnetHTA: planning, development, and implementation of a sustainable European network for health technology assessment

    DEFF Research Database (Denmark)

    Kristensen, Finn Børlum; Mäkelä, Marjukka; Neikter, Susanna Allgurin

    2009-01-01

    OBJECTIVES: The European network on Health Technology Assessment (EUnetHTA) aimed to produce tangible and practical results to be used in the various phases of health technology assessment and to establish a framework and processes to support this. This article presents the background, objectives......, and organization of EUnetHTA, which involved a total of sixty-four partner organizations. METHODS: Establishing an effective and sustainable structure for a transnational network involved many managerial, policy, and methodological tools, according to the objective of each task or Work Package. Transparency...... the use of HTA at national and regional levels. Responsiveness to political developments in Europe should be balanced with maintaining a high level of ambition to promote independent, evidence-based information and well-tested tools for best practice based on a strong network of HTA institutions....

  13. Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

    Science.gov (United States)

    Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

    2015-09-15

    The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Optimization of the Production of Extracellular Polysaccharide from the Shiitake Medicinal Mushroom Lentinus edodes (Agaricomycetes) Using Mutation and a Genetic Algorithm-Coupled Artificial Neural Network (GA-ANN).

    Science.gov (United States)

    Adeeyo, Adeyemi Ojutalayo; Lateef, Agbaje; Gueguim-Kana, Evariste Bosco

    2016-01-01

    Exopolysaccharide (EPS) production by a strain of Lentinus edodes was studied via the effects of treatments with ultraviolet (UV) irradiation and acridine orange. Furthermore, optimization of EPS production was studied using a genetic algorithm coupled with an artificial neural network in submerged fermentation. Exposure to irradiation and acridine orange resulted in improved EPS production (2.783 and 5.548 g/L, respectively) when compared with the wild strain (1.044 g/L), whereas optimization led to improved productivity (23.21 g/L). The EPS produced by various strains also demonstrated good DPPH scavenging activities of 45.40-88.90%, and also inhibited the growth of Escherichia coli and Klebsiella pneumoniae. This study shows that multistep optimization schemes involving physical-chemical mutation and media optimization can be an attractive strategy for improving the yield of bioactives from medicinal mushrooms. To the best of our knowledge, this report presents the first reference of a multistep approach to optimizing EPS production in L. edodes.

  15. Identifying and tracking attacks on networks: C3I displays and related technologies

    Science.gov (United States)

    Manes, Gavin W.; Dawkins, J.; Shenoi, Sujeet; Hale, John C.

    2003-09-01

    Converged network security is extremely challenging for several reasons; expanded system and technology perimeters, unexpected feature interaction, and complex interfaces all conspire to provide hackers with greater opportunities for compromising large networks. Preventive security services and architectures are essential, but in and of themselves do not eliminate all threat of compromise. Attack management systems mitigate this residual risk by facilitating incident detection, analysis and response. There are a wealth of attack detection and response tools for IP networks, but a dearth of such tools for wireless and public telephone networks. Moreover, methodologies and formalisms have yet to be identified that can yield a common model for vulnerabilities and attacks in converged networks. A comprehensive attack management system must coordinate detection tools for converged networks, derive fully-integrated attack and network models, perform vulnerability and multi-stage attack analysis, support large-scale attack visualization, and orchestrate strategic responses to cyber attacks that cross network boundaries. We present an architecture that embodies these principles for attack management. The attack management system described engages a suite of detection tools for various networking domains, feeding real-time attack data to a comprehensive modeling, analysis and visualization subsystem. The resulting early warning system not only provides network administrators with a heads-up cockpit display of their entire network, it also supports guided response and predictive capabilities for multi-stage attacks in converged networks.

  16. Construction and discussion of the science and technology information network of SWIP

    International Nuclear Information System (INIS)

    Wang Li; Zhang Yiming

    2010-01-01

    The digital library needs to be developed with the advancement of digitalisation and network, and the construction of digital information resource is more indispensable. This paper introduces the exploration and the work performed by the Research Office of Science and Technology Information of the Southwestern Institute of Physics with respect to preliminary construction of science and technology (S and T) information network resources and the magnitude alteration of S and T information service platform subsequently and the building of a dynamical network information service mode of its own characteristics. (authors)

  17. Simulation technologies in networking and communications selecting the best tool for the test

    CERN Document Server

    Pathan, Al-Sakib Khan; Khan, Shafiullah

    2014-01-01

    Simulation is a widely used mechanism for validating the theoretical models of networking and communication systems. Although the claims made based on simulations are considered to be reliable, how reliable they really are is best determined with real-world implementation trials.Simulation Technologies in Networking and Communications: Selecting the Best Tool for the Test addresses the spectrum of issues regarding the different mechanisms related to simulation technologies in networking and communications fields. Focusing on the practice of simulation testing instead of the theory, it presents

  18. WEPP and ANN models for simulating soil loss and runoff in a semi-arid Mediterranean region.

    Science.gov (United States)

    Albaradeyia, Issa; Hani, Azzedine; Shahrour, Isam

    2011-09-01

    This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.

  19. Prediction of groundwater levels from lake levels and climate data using ANN approach

    OpenAIRE

    Dogan, Ahmet; Demirpence, Husnu; Cobaner, Murat

    2008-01-01

    There are many environmental concerns relating to the quality and quantity of surface and groundwater. It is very important to estimate the quantity of water by using readily available climate data for managing water resources of the natural environment. As a case study an artificial neural network (ANN) methodology is developed for estimating the groundwater levels (upper Floridan aquifer levels) as a function of monthly averaged precipitation, evaporation, and measured levels of Magnolia an...

  20. Social Networking and Smart Technology: Viable Environmental Communication Tools…?

    Science.gov (United States)

    Montain, J.; Byrne, J. M.

    2010-12-01

    To what extent do popular social networking channels represent a viable means for disseminating information regarding environmental change to the general public? Are new forms of communication such as YouTube™, Facebook™, MySpace™ and Twitter™ and smart devices such as iPhone™ and BlackBerry™ useful and effective in terms motivating people into social action and behavioural modification; or do they simply pay ‘lip service’ to these pressing environmental issues? This project will explore the background connections between social networking and environmental communication and education; and outline why such tools might be an appropriate way to connect to a broad audience in an efficient and unconventional manner. Further, research will survey the current prevalence of reliable environmental change information on social networking Internet-based media; and finally, suggestions for improved strategies and new directions will be provided.

  1. Zigbee networking technology and its application in Lamost optical fiber positioning and control system

    Science.gov (United States)

    Jin, Yi; Zhai, Chao; Gu, Yonggang; Zhou, Zengxiang; Gai, Xiaofeng

    2010-07-01

    4,000 fiber positioning units need to be positioned precisely in LAMOST(Large Sky Area Multi-object Optical Spectroscopic Telescope) optical fiber positioning & control system, and every fiber positioning unit needs two stepper motors for its driven, so 8,000 stepper motors need to be controlled in the entire system. Wireless communication mode is adopted to save the installing space on the back of the focal panel, and can save more than 95% external wires compared to the traditional cable control mode. This paper studies how to use the ZigBee technology to group these 8000 nodes, explores the pros and cons of star network and tree network in order to search the stars quickly and efficiently. ZigBee technology is a short distance, low-complexity, low power, low data rate, low-cost two-way wireless communication technology based on the IEEE 802.15.4 protocol. It based on standard Open Systems Interconnection (OSI): The 802.15.4 standard specifies the lower protocol layers-the physical layer (PHY), and the media access control (MAC). ZigBee Alliance defined on this basis, the rest layers such as the network layer and application layer, and is responsible for high-level applications, testing and marketing. The network layer used here, based on ad hoc network protocols, includes the following functions: construction and maintenance of the topological structure, nomenclature and associated businesses which involves addressing, routing and security and a self-organizing-self-maintenance functions which will minimize consumer spending and maintenance costs. In this paper, freescale's 802.15.4 protocol was used to configure the network layer. A star network and a tree network topology is realized, which can build network, maintenance network and create a routing function automatically. A concise tree network address allocate algorithm is present to assign the network ID automatically.

  2. Breast Cancer Diagnosis using Artificial Neural Networks with Extreme Learning Techniques

    OpenAIRE

    Chandra Prasetyo Utomo; Aan Kardiana; Rika Yuliwulandari

    2014-01-01

    Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breast cancer diagnosis. However, the standard Gradient-Based Back Propagation Artificial Neural Networks...

  3. Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA-ANN model

    Energy Technology Data Exchange (ETDEWEB)

    Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)

    2010-12-15

    In this paper the wind speed forecasting in the Isla de Cedros in Baja California, in the Cerro de la Virgen in Zacatecas and in Holbox in Quintana Roo is presented. The time series utilized are average hourly wind speed data obtained directly from the measurements realized in the different sites during about one month. In order to do wind speed forecasting Hybrid models consisting of Autoregressive Integrated Moving Average (ARIMA) models and Artificial Neural Network (ANN) models were developed. The ARIMA models were first used to do the wind speed forecasting of the time series and then with the obtained errors ANN were built taking into account the nonlinear tendencies that the ARIMA technique could not identify, reducing with this the final errors. Once the Hybrid models were developed 48 data out of sample for each one of the sites were used to do the wind speed forecasting and the results were compared with the ARIMA and the ANN models working separately. Statistical error measures such as the mean error (ME), the mean square error (MSE) and the mean absolute error (MAE) were calculated to compare the three methods. The results showed that the Hybrid models predict the wind velocities with a higher accuracy than the ARIMA and ANN models in the three examined sites. (author)

  4. Assessment of spatial distribution of soil heavy metals using ANN-GA, MSLR and satellite imagery.

    Science.gov (United States)

    Naderi, Arman; Delavar, Mohammad Amir; Kaboudin, Babak; Askari, Mohammad Sadegh

    2017-05-01

    This study aims to assess and compare heavy metal distribution models developed using stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) based on satellite imagery. The source identification of heavy metals was also explored using local Moran index. Soil samples (n = 300) were collected based on a grid and pH, organic matter, clay, iron oxide contents cadmium (Cd), lead (Pb) and zinc (Zn) concentrations were determined for each sample. Visible/near-infrared reflectance (VNIR) within the electromagnetic ranges of satellite imagery was applied to estimate heavy metal concentrations in the soil using MSLR and ANN-GA models. The models were evaluated and ANN-GA model demonstrated higher accuracy, and the autocorrelation results showed higher significant clusters of heavy metals around the industrial zone. The higher concentration of Cd, Pb and Zn was noted under industrial lands and irrigation farming in comparison to barren and dryland farming. Accumulation of industrial wastes in roads and streams was identified as main sources of pollution, and the concentration of soil heavy metals was reduced by increasing the distance from these sources. In comparison to MLSR, ANN-GA provided a more accurate indirect assessment of heavy metal concentrations in highly polluted soils. The clustering analysis provided reliable information about the spatial distribution of soil heavy metals and their sources.

  5. Proceedings of the Neural Network Workshop for the Hanford Community

    Energy Technology Data Exchange (ETDEWEB)

    Keller, P.E.

    1994-01-01

    These proceedings were generated from a series of presentations made at the Neural Network Workshop for the Hanford Community. The abstracts and viewgraphs of each presentation are reproduced in these proceedings. This workshop was sponsored by the Computing and Information Sciences Department in the Molecular Science Research Center (MSRC) at the Pacific Northwest Laboratory (PNL). Artificial neural networks constitute a new information processing technology that is destined within the next few years, to provide the world with a vast array of new products. A major reason for this is that artificial neural networks are able to provide solutions to a wide variety of complex problems in a much simpler fashion than is possible using existing techniques. In recognition of these capabilities, many scientists and engineers are exploring the potential application of this new technology to their fields of study. An artificial neural network (ANN) can be a software simulation, an electronic circuit, optical system, or even an electro-chemical system designed to emulate some of the brain`s rudimentary structure as well as some of the learning processes that are believed to take place in the brain. For a very wide range of applications in science, engineering, and information technology, ANNs offer a complementary and potentially superior approach to that provided by conventional computing and conventional artificial intelligence. This is because, unlike conventional computers, which have to be programmed, ANNs essentially learn from experience and can be trained in a straightforward fashion to carry out tasks ranging from the simple to the highly complex.

  6. Current state of information technology use in a US primary care practice-based research network

    Directory of Open Access Journals (Sweden)

    James Andrews

    2004-02-01

    Conclusion While interest in enabling information technologies was high in KAN, adoption was variable, with use of several key technologies reported as low.The results suggest that research in this network that would be dependent on or enhanced by IT might be impeded and, generally, greater attention should be given to enhancing the IT infrastructure in primary care.

  7. Enterprise Social Networking: Technology Acceptance Related to Personality, Age, and Gender

    Science.gov (United States)

    Rochelle, Joseph

    2017-01-01

    In this dissertation, the researcher examined and added to the body of knowledge within the project change management field of technology implementation. The rationale behind the study was to evaluate technology acceptance of Enterprise Social Networking (ESN), which has been widely implemented across over 90% of the "Fortune" 500…

  8. Uranium mining and metallurgy library science and technology literature retrieval of network

    International Nuclear Information System (INIS)

    Tang Lilei

    2014-01-01

    This paper introduces the network resources and characteristics retrieve service of Beijing research Institute of Chemical Engineering of Metallurgy library, Analyzes the problems often encountered in the literature retrieval in science and technology, And puts forward the solution, Puts forward the thinking and Suggestions of science and technology literature retrieval. (author)

  9. Evaluation Of The Advanced Operating System Of The Ann Arbor Transportation Authority : Cost Study : Before, During And After AOS Implementation (October 1996-May 1999)

    Science.gov (United States)

    1999-01-01

    In 1997, the Ann Arbor (Michigan) Transportation Authority (AATA) began deploying advanced public transportation systems (APTS) technologies in its fixed route and paratransit operations. The project's concept is the integration of a range of such te...

  10. The science, technology and research network (STARNET) a searchable thematic compilation of web resources

    Science.gov (United States)

    Blados, W.R.; Cotter, G.A.; Hermann, T.

    2007-01-01

    International alliances in space efforts have resulted in a more rapid diffusion of space technology. This, in turn, increases pressure on organizations to push forward with technological developments and to take steps to maximize their inclusion into the research and development (R&D) process and the overall advancement and enhancement of space technology. To cope with this vast and rapidly growing amount of data and information that is vital to the success of the innovation, the Information Management Committee (IMC) of the Research Technology Agency (RTA) developed the science, technology and research network (STARNET). The purpose of this network is to facilitate access to worldwide information elements in terms of science, technology and overall research. It provides a virtual library with special emphasis on international security; a "one stop" information resource for policy makers, program managers, scientists, engineers, researchers and others. ?? 2007 IEEE.

  11. The research of network database security technology based on web service

    Science.gov (United States)

    Meng, Fanxing; Wen, Xiumei; Gao, Liting; Pang, Hui; Wang, Qinglin

    2013-03-01

    Database technology is one of the most widely applied computer technologies, its security is becoming more and more important. This paper introduced the database security, network database security level, studies the security technology of the network database, analyzes emphatically sub-key encryption algorithm, applies this algorithm into the campus-one-card system successfully. The realization process of the encryption algorithm is discussed, this method is widely used as reference in many fields, particularly in management information system security and e-commerce.

  12. Improving collaboration between primary care research networks using Access Grid technology

    Directory of Open Access Journals (Sweden)

    Zsolt Nagykaldi

    2008-05-01

    Full Text Available Access Grid (AG is an Internet2-driven, high performance audio_visual conferencing technology used worldwide by academic and government organisations to enhance communication, human interaction and group collaboration. AG technology is particularly promising for improving academic multi-centre research collaborations. This manuscript describes how the AG technology was utilised by the electronic Primary Care Research Network (ePCRN that is part of the National Institutes of Health (NIH Roadmap initiative to improve primary care research and collaboration among practice- based research networks (PBRNs in the USA. It discusses the design, installation and use of AG implementations, potential future applications, barriers to adoption, and suggested solutions.

  13. ATM Technology Adoption in U.S. Campus Networking.

    Science.gov (United States)

    Yao, Engui; Perry, John F.; Anderson, Larry S.; Brook, R. Dan; Hare, R. Dwight; Moore, Arnold J.; Xu, Xiaohe

    This study examined the relationships between ATM (asynchronous transfer mode) adoption in universities and four organizational variables: university size, type, finances, and information processing maturity. Another purpose of the study was to identify the current status of ATM adoption in campus networking. Subjects were university domain LAN…

  14. Incorporating network externalities into the technology acceptance model

    NARCIS (Netherlands)

    Song, Michael; Parry, Mark E.; Kawakami, Tomoko

    2009-01-01

    Research on network externalities has identified a number of product categories in which the market performance of an innovation (e.g., unit sales and revenues) is an increasing function of that innovation's installed base and the availability of complementary products. Innovation scholars have

  15. THE USE OF NEURAL NETWORK TECHNOLOGY TO MODEL SWIMMING PERFORMANCE

    Directory of Open Access Journals (Sweden)

    António José Silva

    2007-03-01

    Full Text Available The aims of the present study were: to identify the factors which are able to explain the performance in the 200 meters individual medley and 400 meters front crawl events in young swimmers, to model the performance in those events using non-linear mathematic methods through artificial neural networks (multi-layer perceptrons and to assess the neural network models precision to predict the performance. A sample of 138 young swimmers (65 males and 73 females of national level was submitted to a test battery comprising four different domains: kinanthropometric evaluation, dry land functional evaluation (strength and flexibility, swimming functional evaluation (hydrodynamics, hydrostatic and bioenergetics characteristics and swimming technique evaluation. To establish a profile of the young swimmer non-linear combinations between preponderant variables for each gender and swim performance in the 200 meters medley and 400 meters font crawl events were developed. For this purpose a feed forward neural network was used (Multilayer Perceptron with three neurons in a single hidden layer. The prognosis precision of the model (error lower than 0.8% between true and estimated performances is supported by recent evidence. Therefore, we consider that the neural network tool can be a good approach in the resolution of complex problems such as performance modeling and the talent identification in swimming and, possibly, in a wide variety of sports

  16. Technology Addiction: How Social Network Sites Impact our Lives

    Directory of Open Access Journals (Sweden)

    Natalie Gerhart

    2017-09-01

    Full Text Available Aim/Purpose: The media and research have made significant noise about young people’s addictions to technology, however the American Psychological Association (APA has reserved judgment on the clinical diagnosis of technology addiction. Research to understand technology addiction is important to the future of information systems development and behavioral usage understanding. Background: Addiction implies that there is a problem from which an IS client needs to try to recover, further implying a negative impact on life. Multiple defini-tions and outcomes of addictions have been studied in the information systems discipline, with virtually no focus on quality of life of the IS client. Methodology: This research employs a survey of students at a large southwestern United States university. Measures were adopted from previously validated sources. The final sample includes 413 usable responses analyzed using PLS. Contribution: This research broadens theoretical and practical understanding of SNS IS client perceptions by relating technology addiction to a broader impact on an individual’s life. By doing so, it provides guidance on society’s understanding of frequent technology use, as well as the development of new systems that are highly used. Findings: This research indicates diminished impulse control, distraction, social influence and satisfaction are all highly correlated with technology addiction; specifically, 55% of the variance in addiction is explained by these four indicators. However, the model further shows addiction has no significant relationship with overall satisfaction of life, indicating that IS clients do not correlate the two ideas. Recommendations for Practitioners: Heavy technology use may indicate a paradigm shift in how people inter-act, instead of a concern to be addressed by the APA. Recommendation for Researchers: Research needs to clearly define technology dependence, addiction, and overuse so that there is a strong

  17. Key technologies and concepts for beyond-3G networks

    Science.gov (United States)

    Pehkonen, Kari; Uskela, Sami; Kalliojarvi, Kari; Oksanen, Lauri; Rikkinen, Kari

    2001-10-01

    Standardization of 3rd Generation (3G) mobile communication systems has produced the first specification releases and the commercial deployment of the 3G systems has started. Whereas 1G and 2G focused on efficiently providing voice services, in 3G a lot of attention has been devoted to solutions that support both Circuit Switched (CS) and Packet Switched (PS) communication. That has called for very flexible air interface and network solutions. 3G will continue to evolve and there are already on-going standardization activities that will, for example, boost the peak data rates up to 5-10 Mbps and improve spectral efficiency by 2-4 times. In the future, 3G evolution will be going towards 10/100 Mbps peak data rates in wide/local are coverage, respectively. This will take place partly because of technical improvements of 3G radio interface solutions, but also due to network evolution which will allow the integration other radio access methods like radio LANs into the 3G system. In longer term the 3G network evolution will be going towards ALL-IP networks. As 3G evolution seems to be going towards 10 Mbps/100 Mbps peak data rates and ALL-IP networks any beyond 3G air interface or network solution should be clearly better in order to justify its technical and commercial feasibility. Given the long evolution time of 3G and integration of other radio access schemes with 3G radio we may not even see a new, complete beyond 3G system being developed. Maybe we will just witness the emergence of a new, more advanced radio access solution which will then be connected to the evolving 3G network. As 3G evolution will continue for several years to come the research targets for any beyond 3G solutions must be set very high. When it comes to air interface, we should aim at 100 Mbps peak data rates for wide area access with high mobility, and at 1 Gbps for local area access with low mobility. Regarding possible commercial launches of any beyond 3G systems or solutions they could then

  18. Deploying 5G-technologies in smart city and smart home wireless sensor networks with interferences

    DEFF Research Database (Denmark)

    Lynggaard, Per; Skouby, Knud Erik

    2015-01-01

    communication in an Internet of Things (5G) contexts. In this paper we discuss some of the key challenges that exist in the smart city and smart home networks in the light of possible 5G-solutions. Focus is on deploying cognitive radio technologies (5G) which enables the smart city networks to support......Deploying 5G technologies in a combination of smart homes and smart city opens for a new ecosystem with big potentials. The potentials lie in the creation of an advanced ICT infrastructure with support for connected and entangled services possibilities including technologies for efficient...... interconnected infrastructure elements, to handle big-data from the smart homes, and to be compatible with existing infrastructures. The considered cognitive radio technology is based on pre-coded OFDM which offers the needed flexibility to deal with the key challenges found in the smart home networks. Thus...

  19. A Survey on Quality of Service Monitoring and Analysis of Network of Agricultural Science and Technology Resources

    OpenAIRE

    Jian , Ma

    2014-01-01

    International audience; First, current situation on Network of agricultural science and technology resources is described. Then we pay much attention to the quality of service monitoring and analysis system of network resources. And finally, we come to the conclusion that the construction of Quality of service monitoring, analysis of network of agricultural science and technology resources is in great need.

  20. Technology transfer and knowledge management in cooperation networks: the Airzone case

    International Nuclear Information System (INIS)

    Benavides Velasco, C. A.; Quintana Garcia, C.

    2007-01-01

    This paper highlights the importance of cooperation networks between the public system of R and D and industry to promote technology transfer, knowledge management, and the consolidation and growth of new technology firms. Through the case of Air zone,his paper shows the significance of collaboration agreements between University and industry to enhance technology transfer and the success of entrepreneurial projects. (Author) 28 refs

  1. A network identity authentication system based on Fingerprint identification technology

    Science.gov (United States)

    Xia, Hong-Bin; Xu, Wen-Bo; Liu, Yuan

    2005-10-01

    Fingerprint verification is one of the most reliable personal identification methods. However, most of the automatic fingerprint identification system (AFIS) is not run via Internet/Intranet environment to meet today's increasing Electric commerce requirements. This paper describes the design and implementation of the archetype system of identity authentication based on fingerprint biometrics technology, and the system can run via Internet environment. And in our system the COM and ASP technology are used to integrate Fingerprint technology with Web database technology, The Fingerprint image preprocessing algorithms are programmed into COM, which deployed on the internet information server. The system's design and structure are proposed, and the key points are discussed. The prototype system of identity authentication based on Fingerprint have been successfully tested and evaluated on our university's distant education applications in an internet environment.

  2. An Examination of Application of Artificial Neural Network in Cognitive Radios

    Science.gov (United States)

    Bello Salau, H.; Onwuka, E. N.; Aibinu, A. M.

    2013-12-01

    Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined.

  3. An Examination of Application of Artificial Neural Network in Cognitive Radios

    International Nuclear Information System (INIS)

    Salau, H Bello; Onwuka, E N; Aibinu, A M

    2013-01-01

    Recent advancement in software radio technology has led to the development of smart device known as cognitive radio. This type of radio fuses powerful techniques taken from artificial intelligence, game theory, wideband/multiple antenna techniques, information theory and statistical signal processing to create an outstanding dynamic behavior. This cognitive radio is utilized in achieving diverse set of applications such as spectrum sensing, radio parameter adaptation and signal classification. This paper contributes by reviewing different cognitive radio implementation that uses artificial intelligence such as the hidden markov models, metaheuristic algorithm and artificial neural networks (ANNs). Furthermore, different areas of application of ANNs and their performance metrics based approach are also examined

  4. Microcomputer network for technological equipment monitoring and control

    International Nuclear Information System (INIS)

    Segec, O.

    1990-01-01

    The properties and purpose are characterized of a microcomputer network developed for monitoring and controlling the nuclear power plant chemistry. In the development, emphasis was put on simplicity of the components, reliability, ease of operation and availability of the components on the domestic market. So far, these criteria are only met by the DIAMO L(S) system equipped with an MH 8080 (Z80) processor. Its assets include simplicity and ruggedness, owing to which it is well suited to heavy-duty performance, whereas its drawbacks comprise a narrow extent of addressable memory and absence of any supporting software. Until now, 5 types of automated stations have been developed and submitted for test operation at the Bohunice V-2 nuclear power plant. Virtually any personal computer can be attached to the network. The system can also be installed in conventional power plants as well as beyond the power generation field. (Z.M.)

  5. Sentiment classification technology based on Markov logic networks

    Science.gov (United States)

    He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

    2016-07-01

    With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

  6. Elements of learning technologies designing of engineering networks heat

    Directory of Open Access Journals (Sweden)

    Sidorkina Irina G.

    2016-01-01

    Full Text Available Modern educational systems function as a medium fast analysis of shared information that defines them as analytical. The purpose of analytical information processing systems: working with distributed data on a global computer networks, mining and processing of semi structured information, knowledge. Existing mathematical and heuristic methods for the automated synthesis of electronic courses and their corresponding algorithms do not allow the full compliance of development realized in the form of adequate criteria for the totality of the properties distributed educational systems within acceptable time limits and characteristic. Therefore, the development of electronic educational applications must be accompanied by a variety of software support intelligent and adaptive functions. In addition, there is no theoretical justification for integrative aspects and their practical applications for intelligent and adaptive systems of designing distance learning courses. Currently, this type of problem may be considered as a potentially promising. The article presents the functionality of the e-learning course on the design engineering of thermal networks, process modeling in engineering networks with the solution of energy efficiency, detection of problem areas; identify the irrational layout of heaters and others.

  7. Implementation of ANN on CCHP system to predict trigeneration performance with consideration of various operative factors

    International Nuclear Information System (INIS)

    Anvari, Simin; Taghavifar, Hadi; Saray, Rahim Khoshbakhti; Khalilarya, Shahram; Jafarmadar, Samad

    2015-01-01

    Highlights: • ANN modeling tool was implemented on the CCHP system. • The best ANN topology was detected 10–8–9 with Levenberg–Marquadt algorithm. • The system is more sensitive of CC outlet temperature and turbine isentropic efficiency. • The lowest RMSE = 3.13e−5 and the best R 2 = 0.999 is related to lambda and second law efficiency terms, respectively. - Abstract: A detailed investigation was aimed based on numerical thermodynamic survey and artificial neural network (ANN) modeling of the trigeneration system. The results are presented in two pivotal frameworks namely the sensitivity analysis and ANN prediction capability of proposed modeling. The underlying operative parameters were chosen as input parameters from different cycles and components, while the exergy efficiency, exergy loss, coefficient of performance, heating load exergy, lambda, gas turbine power, exergy destruction, actual outlet air compressor temperature, and heat recovery gas steam generator (HRSG) outlet temperature were taken as objective output parameters for the modeling purpose. Up to now, no significant step was taken to investigate the compound power plant with thermodynamic analyses and network predictability hybrid in such a detailed oriented approach. It follows that multilayer perceptron neural network with back propagation algorithm deployed with 10–8–9 configuration results in the modeling reliability ranged within R 2 = 0.995–0.999. When dataset treated with trainlm learning algorithm and diversified neurons, the mean square error (MSE) is obtained equal to 0.2175. This denotes a powerful modeling achievement in both scientific and industrial scale to save considerable computational cost on combined cooling, heating, and power system in accomplishment of boosting the energy efficiency and system maintenance

  8. Blog and social networks: an analysis from the governmentality technologies and gender

    Directory of Open Access Journals (Sweden)

    Georgina Remondino

    2012-11-01

    Full Text Available Currently, the explosion of personal blogs, social networking and other devices and software show how certain practices that were considered exclusives of intimate and private spheres, are now enrolled in the public space of the screen. Based on this scene, in this article we consider that these technologies work as technologies of the self and as control technologies, in the sense proposed by Foucault (1990. They mediate forms of self government in their public presentation modes, while play as control technologies of the others. Technological conditions also are imposed on the possible interactions and contribute to different modes of governance of feelings and specific forms of gender performativización. In this paper we analyze these categories and share some reflections from a case of study with young women consumers of blogs and social networks in the city of Córdoba.

  9. Asian network for education in nuclear technology: An initiative to promote education and training in nuclear technology

    International Nuclear Information System (INIS)

    Kosilov, A.

    2006-01-01

    It has become increasingly clear that there is a need to consolidate the efforts of academia and industry in education and training. Partnerships of operating organizations with educational institutions and universities that provide qualified professionals for the nuclear industry should be assessed based upon medium and long term needs and strengthened where needed. In this regard the IAEA is taking the necessary action to initiate this kind of partnership through continuous networking. The paper describes the IAEA approach to promoting education and training through the Asian Network for Education in Nuclear Technology (ANENT). (author)

  10. RESEARCH OF ENGINEERING TRAFFIC IN COMPUTER UZ NETWORK USING MPLS TE TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    V. M. Pakhomovа

    2014-12-01

    Full Text Available Purpose. In railway transport of Ukraine one requires the use of computer networks of different technologies: Ethernet, Token Bus, Token Ring, FDDI and others. In combined computer networks on the railway transport it is necessary to use packet switching technology in multiprotocol networks MPLS (MultiProtocol Label Switching more effectively. They are based on the use of tags. Packet network must transmit different types of traffic with a given quality of service. The purpose of the research is development a methodology for determining the sequence of destination flows for the considered fragment of computer network of UZ. Methodology. When optimizing traffic management in MPLS networks has the important role of technology traffic engineering (Traffic Engineering, TE. The main mechanism of TE in MPLS is the use of unidirectional tunnels (MPLS TE tunnel to specify the path of the specified traffic. The mathematical model of the problem of traffic engineering in computer network of UZ technology MPLS TE was made. Computer UZ network is represented with the directed graph, their vertices are routers of computer network, and each arc simulates communication between nodes. As an optimization criterion serves the minimum value of the maximum utilization of the TE-tunnel. Findings. The six options destination flows were determined; rational sequence of flows was found, at which the maximum utilization of TE-tunnels considered a simplified fragment of a computer UZ network does not exceed 0.5. Originality. The method of solving the problem of traffic engineering in Multiprotocol network UZ technology MPLS TE was proposed; for different classes its own way is laid, depending on the bandwidth and channel loading. Practical value. Ability to determine the values of the maximum coefficient of use of TE-tunnels in computer UZ networks based on developed software model «TraffEng». The input parameters of the model: number of routers, channel capacity, the

  11. Ann Modeling for Grey Particles Produced from Interactions of Different Projectiles with Emulsion Nuclei at 4.5 AGEV/C

    International Nuclear Information System (INIS)

    El-Bakry, M.N.Y.; Basha, A.M.; Rashed, N.; Mahmoud, M.A.; Radi, A.

    2008-01-01

    Artificial Neural Network (ANN) is one of the important tools in high energy physics. In this paper, we are using ANN for modeling the multiplicity distributions of grey particles produced from interactions of P, 3 He, 4 He, 6 Li, 12 C, 24 Mg, and 32 S with emulsion nuclei, light nuclei (CNO), and heavy nuclei (Ag Br). The equations of these distributions were obtained

  12. Beyond the technological chain: Neolithic potters in social networks

    Czech Academy of Sciences Publication Activity Database

    Květina, Petr; Gomart, L.; Thér, R.; Neumannová, Klára

    2017-01-01

    Roč. 69, č. 2 (2017), s. 163-171 ISSN 0323-1267 R&D Projects: GA ČR(CZ) GA14-07062S Institutional support: RVO:67985912 Keywords : technology of pottery * chaînes opératoires * Neolithic Subject RIV: AC - Archeology, Anthropology, Ethnology OBOR OECD: Archaeology

  13. Business Value of Information Technology in Network Environments

    Science.gov (United States)

    Liu, Yucong

    2012-01-01

    Information Technology (IT) business value research is suggested as fundamental to the contribution of the IS discipline. The IS research community has accumulated a critical mass of IT business value studies, but only limited or mixed results have been found on the direct relationship between IT and firm performance. Extant studies mostly focus…

  14. Smartphone technologies and Bayesian networks to assess shorebird habitat selection

    Science.gov (United States)

    Zeigler, Sara; Thieler, E. Robert; Gutierrez, Ben; Plant, Nathaniel G.; Hines, Megan K.; Fraser, James D.; Catlin, Daniel H.; Karpanty, Sarah M.

    2017-01-01

    Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, >30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection

  15. Perbandingan Metode ANN-PSO Dan ANN-GA Dalam Pemodelan Komposisi Pakan Kambing Peranakan Etawa (PE Untuk Optimasi Kandungan Gizi

    Directory of Open Access Journals (Sweden)

    Canny Amerilyse Caesar

    2016-09-01

    Abstract Milk is one of the animal protein sources which it contains all of the substances needed by human body. The main milk producer cattle in Indonesia is dairy cow, however its milk production has not fulfilled the society needs. The alternative is the goat, the Etawa crossbreed (PE. The high quality of milk nutrients content is greatly influenced by some factors one of them, is the food factor. The PE goat livestock division of the UPT Cattle Breeding and the Cattle Food Greenery in Singosari-Malang still faces the problem, it is the low ability in giving the food composition for PE goat. This flaw affects the quality of the produced milk. It needs the artificial science of the milk nutrients contain in order to determine the food composition to produce premium milk with the optimum nutrients contain. The writer uses the method of the Artificial Neural Network (ANN and the Particle Swarm Optimization (PSO to make the modeling of goat food in optimizing the content of goat milk nutrients. In the analysis of the examination that is done with the case of 36 kg goat weight, also the food type used is the 70 % Odot grass and 30% Raja grass can increase the nutrients contain of the protein milk for 0.707% and decrease the fat nutrients contain for 0.879%. If uses the method of Artificial Neural Network (ANN and Genethic Algorithm (GA can increase the nutriens contain of the protein for 0.0852% and decrease the fat nutients contain for 2.3254%.   Key Words : Goat Milk, Optimization, Artificial Neural Network (ANN, Particle Swarm Optimization (PSO, Genetic Algorithm (GA, the food nutrients contain.

  16. Neural network wavelet technology: A frontier of automation

    Science.gov (United States)

    Szu, Harold

    1994-01-01

    Neural networks are an outgrowth of interdisciplinary studies concerning the brain. These studies are guiding the field of Artificial Intelligence towards the, so-called, 6th Generation Computer. Enormous amounts of resources have been poured into R/D. Wavelet Transforms (WT) have replaced Fourier Transforms (FT) in Wideband Transient (WT) cases since the discovery of WT in 1985. The list of successful applications includes the following: earthquake prediction; radar identification; speech recognition; stock market forecasting; FBI finger print image compression; and telecommunication ISDN-data compression.

  17. [Exploration and practice of genetics teaching assisted by network technology platform].

    Science.gov (United States)

    Li, Ya-Xuan; Zhang, Fei-Xiong; Zhao, Xin; Cai, Min-Hua; Yan, Yue-Ming; Hu, Ying-Kao

    2010-04-01

    More teaching techniques have been brought out gradually along with the development of new technologies. On the basis of those traditional teaching methods, a new platform has been set up by the network technology for teaching process. In genetics teaching, it is possible to use the network platform to guide student studying, promote student's learning interest and study independently by themselves. It has been proved, after exploring and applying for many years, that network teaching is one of the most useful methods and has inimitable advantage comparing to the traditional ones in genetics teaching. The establishment of network teaching platform, the advantage and deficiency and relevant strategies were intro-duced in this paper.

  18. Research on the framework and key technologies of panoramic visualization for smart distribution network

    Science.gov (United States)

    Du, Jian; Sheng, Wanxing; Lin, Tao; Lv, Guangxian

    2018-05-01

    Nowadays, the smart distribution network has made tremendous progress, and the business visualization becomes even more significant and indispensable. Based on the summarization of traditional visualization technologies and demands of smart distribution network, a panoramic visualization application is proposed in this paper. The overall architecture, integrated architecture and service architecture of panoramic visualization application is firstly presented. Then, the architecture design and main functions of panoramic visualization system are elaborated in depth. In addition, the key technologies related to the application is discussed briefly. At last, two typical visualization scenarios in smart distribution network, which are risk warning and fault self-healing, proves that the panoramic visualization application is valuable for the operation and maintenance of the distribution network.

  19. A Review on Radio-Over-Fiber Technology-Based Integrated (Optical/Wireless) Networks

    Science.gov (United States)

    Rajpal, Shivika; Goyal, Rakesh

    2017-06-01

    In the present paper, radio-over-fiber (RoF) technology has been proposed, which is the integration of the optical and radio networks. With a high transmission capacity, comparatively low cost and low attenuation, optical fiber provides an ideal solution for accomplishing the interconnections. In addition, a radio system enables the significant mobility, flexibility and easy access. Therefore, the system integration can meet the increasing demands of subscribers for voice, data and multimedia services that require the access network to support high data rates at any time and any place inexpensively. RoF has the potentiality to the backbone of the wireless access network and it has gained significant momentum in the last decade as a potential last-mile access scheme. This paper gives the comprehensive review of RoF technology used in the communication system. Concept, applications, advantages and limitations of RoF technology are also discussed in this paper.

  20. Wearable Device Control Platform Technology for Network Application Development

    Directory of Open Access Journals (Sweden)

    Heejung Kim

    2016-01-01

    Full Text Available Application development platform is the most important environment in IT industry. There are a variety of platforms. Although the native development enables application to optimize, various languages and software development kits need to be acquired according to the device. The coexistence of smart devices and platforms has rendered the native development approach time and cost consuming. Cross-platform development emerged as a response to these issues. These platforms generate applications for multiple devices based on web languages. Nevertheless, development requires additional implementation based on a native language because of the coverage and functions of supported application programming interfaces (APIs. Wearable devices have recently attracted considerable attention. These devices only support Bluetooth-based interdevice communication, thereby making communication and device control impossible beyond a certain range. We propose Network Application Agent (NetApp-Agent in order to overcome issues. NetApp-Agent based on the Cordova is a wearable device control platform for the development of network applications, controls input/output functions of smartphones and wearable/IoT through the Cordova and Native API, and enables device control and information exchange by external users by offering a self-defined API. We confirmed the efficiency of the proposed platform through experiments and a qualitative assessment of its implementation.

  1. Analysis of technology and business antecedents for spectrum sharing in mobile broadband networks

    OpenAIRE

    Yrjölä, S. (Seppo)

    2017-01-01

    Abstract Sharing is emerging as one of the megatrends influencing future business opportunities, and wireless communications is no exception to this development. Future mobile broadband networks will operate on different types of spectrum bands including shared spectrum, which calls for changes in the operation and management of the networks. The creation and capture of value by the different players in the mobile broadband ecosystem is expected to change due to regulation, technology, an...

  2. Mapping industrial systems - a supply network perspective on enabling technologies, processes and actors

    OpenAIRE

    Srai, Jagjit Singh

    2016-01-01

    This is the author accepted manuscript. The final version is available from InderScience Publishers via http://dx.doi.org/10.1504/IJMTM.2017.10002927 This paper develops a multi-layered multi-stage mapping approach to explore the characteristics of emerging industry supply networks (EI SNs), and how enabling production technologies and supply chain processes are supported by institutional, industrial and supply network actors. The mapping methodology involves the systematic capture of mate...

  3. OMNI: An optoelectronic multichannel network interface based on hybrid CMOS-SEED technology

    Science.gov (United States)

    Pinkston, Timothy M.

    1996-11-01

    This paper presents a hybrid CMOS-SEED multiprocessor network interface smart pixel design that implements a reservation-based channel control protocol for collisionless concurrent access to multiple optical interprocessor communication channels. An asynchronous optical token is used as the arbitration mechanism for reservation control instead of slotted access. This work demonstrates that complex network protocol functions can be implemented using optoelectronic smart pixel technology.

  4. Harnessing social networks for promoting adoption of energy technologies in the domestic sector

    International Nuclear Information System (INIS)

    Bale, Catherine S.E.; McCullen, Nicholas J.; Foxon, Timothy J.; Rucklidge, Alastair M.; Gale, William F.

    2013-01-01

    This paper presents results from modelling work investigating the effects of social networks on the adoption of energy technologies in the domestic sector. This work concerns ideas on social network interventions which have been successfully applied in other domains but which have seldom been applied to energy policy questions. We employ a dynamical multi-parameter network model where households are represented as nodes on a network for which the uptake of technologies is influenced by both personal benefit and social influences. This is applied to demonstrate the usefulness of this type of model in assessing the likely success of different roll-out strategies that a local authority could pursue in promoting the uptake of domestic energy technologies. Local authorities can play a key role in the retrofit of energy-efficiency and low-carbon energy-generation technologies in order to realise carbon reductions and alleviate fuel poverty. Scenarios are modelled for different local authority interventions that target network interactions and uptake threshold effects, and the results provide insights for policy. The potential for the use of this type of modelling in understanding the adoption of energy innovations in the domestic sector and designing local-level interventions is demonstrated. - Highlights: • We model energy-technology adoption of households connected on a social network. • Adoption depends on both personal and social benefits to the household. • We investigate interventions that a local authority could take to increase uptake. • Increased uptake results from both threshold and network intervention scenarios. • Insights should be incorporated into design of local-level domestic interventions

  5. [Attachment theory and baby slings/carriers: technological network formation].

    Science.gov (United States)

    Lu, Zxy-Yann Jane; Lin, Wan-Shiuan

    2011-12-01

    Healthcare providers recognize the important role played by attachment theory in explaining the close relationship between mental health and social behavior in mothers and their children. This paper uses attachment theory in a socio-cultural context to ascertain the mechanism by which baby slings/carriers, a new technology, produced and reproduced the scientific motherhood. It further applies a social history of technology perspective to understand how baby carriers and attachment theory are socially constructed and historically contingent on three major transformations. These transformations include the use of attachment theory-based baby carriers to further scientific motherhood; the use of baby slings/carriers to further the medicalization of breastfeeding and enhance mother-infant attachment; and the use of baby slings/carriers to transform woman's identities by integrating scientific motherhood, independence and fashion. Implications for nursing clinical policy are suggested.

  6. INTELLIGENT NETWORKS, SMART GRIDS CONCEPT, CRUCIAL TECHNOLOGIES FOR SUSTAINABLE DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Constantin RADU

    2011-05-01

    Full Text Available In this article is presented the concept of smart grids, a very important technology for sustainable development. In the context of globalization of the world lives in an increasingly complex security environment, with rapid changes, some obvious, others less obvious implications in the short, medium or long term, international, national, local and up to every citizen. All countries in the globalized world economy is facing energy problems in terms of climate change have intensified in the twentieth century.

  7. artificial neural network (ann) approach to electrical load

    African Journals Online (AJOL)

    2004-08-18

    Aug 18, 2004 ... self organizing feature map; which is back-propagating in nature. ... distribution scheduling. ... electricity demand with lead times that range from ... become increasingly vital since the rise of the ... implemented for advanced control, data and sensor ... inspired methods of computing are thought to be the.

  8. On The Comparison of Artificial Neural Network (ANN) and ...

    African Journals Online (AJOL)

    PROF. OLIVER OSUAGWA

    prediction of student achievement is one way to enhance the quality level and provide better ... model performance measure in solving different real life problems ranging from management sciences, business schools, and others [10], [12],.

  9. FPGA implementation of adaptive ANN controller for speed regulation of permanent magnet stepper motor drives

    Energy Technology Data Exchange (ETDEWEB)

    Hasanien, Hany M., E-mail: Hanyhasanien@ieee.or [Dept. of Elec. Power and Machines, Faculty of Eng., Ain Shams Univ., Cairo (Egypt)

    2011-02-15

    This paper presents a novel adaptive artificial neural network (ANN) controller, which applies on permanent magnet stepper motor (PMSM) for regulating its speed. The dynamic response of the PMSM with the proposed controller is studied during the starting process under the full load torque and under load disturbance. The effectiveness of the proposed adaptive ANN controller is then compared with that of the conventional PI controller. The proposed methodology solves the problem of nonlinearities and load changes of PMSM drives. The proposed controller ensures fast and accurate dynamic response with an excellent steady state performance. Matlab/Simulink tool is used for this dynamic simulation study. The main contribution of this work is the implementation of the proposed controller on field programmable gate array (FPGA) hardware to drive the stepper motor. The driver is built on FPGA Spartan-3E Starter from Xilinx. Experimental results are presented to demonstrate the validity and effectiveness of the proposed control scheme.

  10. Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain.

    Science.gov (United States)

    Hussain, Amjad; Syed, Muhammad Ali; Abbas, Nasir; Hanif, Sana; Arshad, Muhammad Sohail; Bukhari, Nadeem Irfan; Hussain, Khalid; Akhlaq, Muhammad; Ahmad, Zeeshan

    2016-06-01

    A novel mucoadhesive buccal tablet containing flurbiprofen (FLB) and lidocaine HCl (LID) was prepared to relieve dental pain. Tablet formulations (F1-F9) were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC) and sodium alginate (SA). The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN) approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release), which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach.

  11. Development of an ANN optimized mucoadhesive buccal tablet containing flurbiprofen and lidocaine for dental pain

    Directory of Open Access Journals (Sweden)

    Hussain Amjad

    2016-06-01

    Full Text Available A novel mucoadhesive buccal tablet containing flurbiprofen (FLB and lidocaine HCl (LID was prepared to relieve dental pain. Tablet formulations (F1-F9 were prepared using variable quantities of mucoadhesive agents, hydroxypropyl methyl cellulose (HPMC and sodium alginate (SA. The formulations were evaluated for their physicochemical properties, mucoadhesive strength and mucoadhesion time, swellability index and in vitro release of active agents. Release of both drugs depended on the relative ratio of HPMC:SA. However, mucoadhesive strength and mucoadhesion time were better in formulations, containing higher proportions of HPMC compared to SA. An artificial neural network (ANN approach was applied to optimise formulations based on known effective parameters (i.e., mucoadhesive strength, mucoadhesion time and drug release, which proved valuable. This study indicates that an effective buccal tablet formulation of flurbiprofen and lidocaine can be prepared via an optimized ANN approach.

  12. Application of ann-based decision making pattern recognition to fishing operations

    Energy Technology Data Exchange (ETDEWEB)

    Akhlaghinia, M.; Torabi, F.; Wilton, R.R. [University of Regina, Saskatchewan (Canada). Faculty of Engineering. Dept. of Petroleum Engineering], e-mail: Farshid.Torabi@uregina.ca

    2010-10-15

    Decision making is a crucial part of fishing operations. Proper decisions should be made to prevent wasted time and associated costs on unsuccessful operations. This paper presents a novel model to help drilling managers decide when to commence and when to quit a fishing operation. A decision making model based on Artificial Neural Network (ANN) has been developed that utilizes Pattern Recognition based on 181 fishing incidents from one of the most fish-prone fields of the southwest of Iran. All parameters chosen to train the ANN-Based Pattern Recognition Tool are assumed to play a role in the success of the fishing operation and are therefore used to decide whether a fishing operation should be performed or not. If the tool deems the operation suitable for consideration, a cost analysis of the fishing operation can then be performed to justify its overall cost. (author)

  13. ANN based controller for three phase four leg shunt active filter for power quality improvement

    Directory of Open Access Journals (Sweden)

    J. Jayachandran

    2016-03-01

    Full Text Available In this paper, an artificial neural network (ANN based one cycle control (OCC strategy is proposed for the DSTATCOM shunted across the load in three phase four wire distribution system. The proposed control strategy mitigates harmonic/reactive currents, ensures balanced and sinusoidal source current from the supply mains that are nearly in phase with the supply voltage and compensates neutral current under varying source and load conditions. The proposed control strategy is superior over conventional methods as it eliminates, the sensors needed for sensing load current and coupling inductor current, in addition to the multipliers and the calculation of reference currents. ANN controllers are implemented to maintain voltage across the capacitor and as a compensator to compensate neutral current. The DSTATCOM performance is validated for all possible conditions of source and load by simulation using MATLAB software and simulation results prove the efficacy of the proposed control over conventional control strategy.

  14. FPGA implementation of adaptive ANN controller for speed regulation of permanent magnet stepper motor drives

    International Nuclear Information System (INIS)

    Hasanien, Hany M.

    2011-01-01

    This paper presents a novel adaptive artificial neural network (ANN) controller, which applies on permanent magnet stepper motor (PMSM) for regulating its speed. The dynamic response of the PMSM with the proposed controller is studied during the starting process under the full load torque and under load disturbance. The effectiveness of the proposed adaptive ANN controller is then compared with that of the conventional PI controller. The proposed methodology solves the problem of nonlinearities and load changes of PMSM drives. The proposed controller ensures fast and accurate dynamic response with an excellent steady state performance. Matlab/Simulink tool is used for this dynamic simulation study. The main contribution of this work is the implementation of the proposed controller on field programmable gate array (FPGA) hardware to drive the stepper motor. The driver is built on FPGA Spartan-3E Starter from Xilinx. Experimental results are presented to demonstrate the validity and effectiveness of the proposed control scheme.

  15. Technologies, Methodologies and Challenges in Network Intrusion Detection and Prevention Systems

    Directory of Open Access Journals (Sweden)

    Nicoleta STANCIU

    2013-01-01

    Full Text Available This paper presents an overview of the technologies and the methodologies used in Network Intrusion Detection and Prevention Systems (NIDPS. Intrusion Detection and Prevention System (IDPS technologies are differentiated by types of events that IDPSs can recognize, by types of devices that IDPSs monitor and by activity. NIDPSs monitor and analyze the streams of network packets in order to detect security incidents. The main methodology used by NIDPSs is protocol analysis. Protocol analysis requires good knowledge of the theory of the main protocols, their definition, how each protocol works.

  16. The Hugging Team: The Role of Technology in Business Networking Practices

    DEFF Research Database (Denmark)

    Thorsø Sørensen, Anne; Shklovski, Irina

    2011-01-01

    Technological devices for social networking are produced in droves and networking through media seems to be the way of getting ahead in business. We examine what role technology plays in the creation, development and maintenance of business relationships among entrepreneurs in Copenhagen. We find...... that mediated communication is useful in all stages of relational maintenance but only in a supportive role in relational development where co-presence and shared personal experiences take center-stage, generating trust necessary for business relationships to work. These trust-developing experiences take effort...

  17. An agent-based model of centralized institutions, social network technology, and revolution.

    Science.gov (United States)

    Makowsky, Michael D; Rubin, Jared

    2013-01-01

    This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change.

  18. Latest generation interconnect technologies in APEnet+ networking infrastructure

    Science.gov (United States)

    Ammendola, Roberto; Biagioni, Andrea; Cretaro, Paolo; Frezza, Ottorino; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Stanislao Paolucci, Pier; Pastorelli, Elena; Rossetti, Davide; Simula, Francesco; Vicini, Piero

    2017-10-01

    In this paper we present the status of the 3rd generation design of the APEnet board (V5) built upon the 28nm Altera Stratix V FPGA; it features a PCIe Gen3 x8 interface and enhanced embedded transceivers with a maximum capability of 12.5Gbps each. The network architecture is designed in accordance to the Remote DMA paradigm. The APEnet+ V5 prototype is built upon the Stratix V DevKit with the addition of a proprietary, third party IP core implementing multi-DMA engines. Support for zero-copy communication is assured by the possibility of DMA-accessing either host and GPU memory, offloading the CPU from the chore of data copying. The current implementation plateaus to a bandwidth for memory read of 4.8GB/s. Here we describe the hardware optimization to the memory write process which relies on the use of two independent DMA engines and an improved TLB.

  19. Community and Social Network Sites as Technology Enhanced Learning Environments

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Christiansen, Ellen

    2008-01-01

    This paper examines the affordance of the Danish social networking site Mingler.dk for peer-to-peer learning and development. With inspiration from different theoretical frameworks, the authors argue how learning and development in such social online systems can be conceptualised and analysed....... Theoretically the paper defines development in accordance with Vygotsky's concept of the zone of proximal development, and learning in accordance with Wenger's concept of communities of practice. The authors suggest analysing the learning and development taking place on Mingler.dk by using these concepts...... supplemented by the notion of horizontal learning adopted from Engestrm and Wenger. Their analysis shows how horizontal learning happens by crossing boundaries between several sites of engagement, and how the actors' multiple membership enables the community members to draw on a vast amount of resources from...

  20. Situation awareness of active distribution network: roadmap, technologies, and bottlenecks

    DEFF Research Database (Denmark)

    Lin, Jin; Wan, Can; Song, Yonghua

    2016-01-01

    With the rapid development of local generation and demand response, the active distribution network (ADN), which aggregates and manages miscellaneous distributed resources, has moved from theory to practice. Secure and optimal operations now require an advanced situation awareness (SA) system so...... in the project of developing an SA system as the basic component of a practical active distribution management system (ADMS) deployed in Beijing, China, is presented. This paper reviews the ADN’s development roadmap by illustrating the changes that are made in elements, topology, structure, and control scheme....... Taking into consideration these hardware changes, a systematic framework is proposed for the main components and the functional hierarchy of an SA system for the ADN. The SA system’s implementation bottlenecks are also presented, including, but not limited to issues in big data platform, distribution...

  1. Online Expansion Technology for Dynamic Topology Changing ZigBee Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Md. Emdadul Haque

    2014-03-01

    Full Text Available In ZigBee, the router capable devices have restriction to accept a number of devices as children devices. A router capable device can not allow any new device to join as a child device if it reaches to the maximum capacity of children or depth limit. According to ZigBee specification each device has a permanent 64-bit MAC address. If a device joins a ZigBee network, it receives a short 16-bit MAC address from the parent device. If a device can not join a network, it isolates from the network and becomes an orphan node even though address spaces are available in the network. The orphan problem becomes worse when the topology of the network changes dynamically. In this paper we propose an online expansion technology to connect the maximum number of devices specially for dynamic topology changing ZigBee wireless sensor networks. The proposed technology shares available address spaces of the router devices to reduce the number of orphan nodes in the network.

  2. Policy gaps and technological deficiencies in social networking environments: Implications for information sharing

    Directory of Open Access Journals (Sweden)

    Stephen M. Mutula

    2013-06-01

    Full Text Available Background: With the growing adoption and acceptance of social networking, there are increased concerns about the violation of the users’ legitimate rights such as privacy, confidentiality, trust, security, safety, content ownership, content accuracy, integrity, access and accessibility to computer and digital networks amongst others.Objectives: The study sought to investigate the following research objectives to: (1 describe the types of social networks, (2 examine global penetration of the social networks, (3 outline the users’ legitimate rights that must be protected in the social networking sites (SNS, (4 determine the methods employed by SNS to protect the users’ legitimate rights and (5 identify the policy gaps and technological deficiencies in the protection of the users’ legitimate rights in the SNS.Method: A literature survey and content analysis of the SNS user policies were used to address objective four and objective five respectively.Results: The most actively used sites were Facebook and Twitter. Asian markets were leading in participation and in creating content than any other region. Business, education, politics and governance sectors were actively using social networking sites. Social networking sites relied upon user trust and internet security features which however, were inefficient and inadequate.Conclusion: Whilst SNS were impacting people of varying ages and of various professional persuasions, there were increased concerns about the violation and infringement of the users’ legitimate rights. Reliance on user trust and technological security features SNS to protect the users’ legitimate rights seemed ineffectual and inadequate.

  3. Application of artificial neural networks in analysis of CHF experimental data in round tubes

    International Nuclear Information System (INIS)

    Huang Yanping; Chen Bingde; Lang Xuemei; Wang Xiaojun; Shan Jianqiang; Jia Dounan

    2004-01-01

    Artificial neural networks (ANNs) are applied successfully to analyze the critical heat flux (CHF) experimental data from some round tubes in this paper. A set of software adopting artificial neural network method for predicting CHF in round tube and a set of CHF database are gotten. Comparing with common CHF correlations and CHF look-up table, ANN method has stronger ability of allow-wrong and nice robustness. The CHF predicting software adopting artificial neural network technology can improve the predicting accuracy in a wider parameter range, and is easier to update and to use. The artificial neural network method used in this paper can be applied to some similar physical problems. (authors)

  4. Efficient computation in adaptive artificial spiking neural networks

    NARCIS (Netherlands)

    D. Zambrano (Davide); R.B.P. Nusselder (Roeland); H.S. Scholte; S.M. Bohte (Sander)

    2017-01-01

    textabstractArtificial Neural Networks (ANNs) are bio-inspired models of neural computation that have proven highly effective. Still, ANNs lack a natural notion of time, and neural units in ANNs exchange analog values in a frame-based manner, a computationally and energetically inefficient form of

  5. Aspects of artificial neural networks and experimental noise

    NARCIS (Netherlands)

    Derks, E.P.P.A.

    1997-01-01

    About a decade ago, artificial neural networks (ANN) have been introduced to chemometrics for solving problems in analytical chemistry. ANN are based on the functioning of the brain and can be used for modeling complex relationships within chemical data. An ANN-model can be obtained by earning or

  6. Network communication for remote technology and NDT controls on current nuclear power plants

    International Nuclear Information System (INIS)

    Capitaine, A.

    2001-01-01

    Among the most important targets for ''UTILITIES'' are to increase nuclear power plant availability and reduce the workers dosimetry. A possible way to reach these targets is to reduce the duration of the refueling period and to limit the number of operators in the work areas It is necessary to use remote technology and to provide much equipment to support the main activities during refueling. Remote technology is a possible solution to remove operators from the maintenance area. The main activities concerned are the NDT inspection on the primary components and fuel handling system. Recent progress on remote technology made by the electronic industry and network communication has increased their capacities. It is easier now to use them, and more and more people are familiar with these technologies. Internet, manufacturing, supervision, and surgery use these technologies. Now it seems appropriate to examine these technologies for current maintenance in nuclear plants. Remote technologies and communication network can help to solve current difficulties in the maintenance field and dosimetry limits. For a long time, many people thought that the cost and the difficulty of applying new technologies would be not extremely expensive, but this is no longer the case. Now with the first feed back we can show that these technologies are a good answer for increased availability and reduction of dosimetry. (author)

  7. Network communication for remote technology and NDT controls on current nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Capitaine, A. [Electricite de France, 92 - Clamart (France). Service Etudes et Projets Thermiques et Nucleaires

    2001-07-01

    Among the most important targets for ''UTILITIES'' are to increase nuclear power plant availability and reduce the workers dosimetry. A possible way to reach these targets is to reduce the duration of the refueling period and to limit the number of operators in the work areas It is necessary to use remote technology and to provide much equipment to support the main activities during refueling. Remote technology is a possible solution to remove operators from the maintenance area. The main activities concerned are the NDT inspection on the primary components and fuel handling system. Recent progress on remote technology made by the electronic industry and network communication has increased their capacities. It is easier now to use them, and more and more people are familiar with these technologies. Internet, manufacturing, supervision, and surgery use these technologies. Now it seems appropriate to examine these technologies for current maintenance in nuclear plants. Remote technologies and communication network can help to solve current difficulties in the maintenance field and dosimetry limits. For a long time, many people thought that the cost and the difficulty of applying new technologies would be not extremely expensive, but this is no longer the case. Now with the first feed back we can show that these technologies are a good answer for increased availability and reduction of dosimetry. (author)

  8. Exploring QSARs of the interaction of flavonoids with GABA (A) receptor using MLR, ANN and SVM techniques.

    Science.gov (United States)

    Deeb, Omar; Shaik, Basheerulla; Agrawal, Vijay K

    2014-10-01

    Quantitative Structure-Activity Relationship (QSAR) models for binding affinity constants (log Ki) of 78 flavonoid ligands towards the benzodiazepine site of GABA (A) receptor complex were calculated using the machine learning methods: artificial neural network (ANN) and support vector machine (SVM) techniques. The models obtained were compared with those obtained using multiple linear regression (MLR) analysis. The descriptor selection and model building were performed with 10-fold cross-validation using the training data set. The SVM and MLR coefficient of determination values are 0.944 and 0.879, respectively, for the training set and are higher than those of ANN models. Though the SVM model shows improvement of training set fitting, the ANN model was superior to SVM and MLR in predicting the test set. Randomization test is employed to check the suitability of the models.

  9. Strategic planning for minimizing CO2 emissions using LP model based on forecasted energy demand by PSO Algorithm and ANN

    Energy Technology Data Exchange (ETDEWEB)

    Yousefi, M.; Omid, M.; Rafiee, Sh. [Department of Agricultural Machinery Engineering, University of Tehran, Karaj (Iran, Islamic Republic of); Ghaderi, S. F. [Department of Industrial Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

    2013-07-01

    Iran's primary energy consumption (PEC) was modeled as a linear function of five socioeconomic and meteorological explanatory variables using particle swarm optimization (PSO) and artificial neural networks (ANNs) techniques. Results revealed that ANN outperforms PSO model to predict test data. However, PSO technique is simple and provided us with a closed form expression to forecast PEC. Energy demand was forecasted by PSO and ANN using represented scenario. Finally, adapting about 10% renewable energy revealed that based on the developed linear programming (LP) model under minimum CO2 emissions, Iran will emit about 2520 million metric tons CO2 in 2025. The LP model indicated that maximum possible development of hydropower, geothermal and wind energy resources will satisfy the aim of minimization of CO2 emissions. Therefore, the main strategic policy in order to reduce CO2 emissions would be exploitation of these resources.

  10. Strategic planning for minimizing CO2 emissions using LP model based on forecasted energy demand by PSO Algorithm and ANN

    Energy Technology Data Exchange (ETDEWEB)

    Yousefi, M.; Omid, M.; Rafiee, Sh. [Department of Agricultural Machinery Engineering, University of Tehran, Karaj (Iran, Islamic Republic of); Ghaderi, S.F. [Department of Industrial Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

    2013-07-01

    Iran's primary energy consumption (PEC) was modeled as a linear function of five socioeconomic and meteorological explanatory variables using particle swarm optimization (PSO) and artificial neural networks (ANNs) techniques. Results revealed that ANN outperforms PSO model to predict test data. However, PSO technique is simple and provided us with a closed form expression to forecast PEC. Energy demand was forecasted by PSO and ANN using represented scenario. Finally, adapting about 10% renewable energy revealed that based on the developed linear programming (LP) model under minimum CO2 emissions, Iran will emit about 2520 million metric tons CO2 in 2025. The LP model indicated that maximum possible development of hydropower, geothermal and wind energy resources will satisfy the aim of minimization of CO2 emissions. Therefore, the main strategic policy in order to reduce CO2 emissions would be exploitation of these resources.

  11. Daily reservoir inflow forecasting combining QPF into ANNs model

    Science.gov (United States)

    Zhang, Jun; Cheng, Chun-Tian; Liao, Sheng-Li; Wu, Xin-Yu; Shen, Jian-Jian

    2009-01-01

    Daily reservoir inflow predictions with lead-times of several days are essential to the operational planning and scheduling of hydroelectric power system. The demand for quantitative precipitation forecasting (QPF) is increasing in hydropower operation with the dramatic advances in the numerical weather prediction (NWP) models. This paper presents a simple and an effective algorithm for daily reservoir inflow predictions which solicits the observed precipitation, forecasted precipitation from QPF as predictors and discharges in following 1 to 6 days as predicted targets for multilayer perceptron artificial neural networks (MLP-ANNs) modeling. An improved error back-propagation algorithm with self-adaptive learning rate and self-adaptive momentum coefficient is used to make the supervised training procedure more efficient in both time saving and search optimization. Several commonly used error measures are employed to evaluate the performance of the proposed model and the results, compared with that of ARIMA model, show that the proposed model is capable of obtaining satisfactory forecasting not only in goodness of fit but also in generalization. Furthermore, the presented algorithm is integrated into a practical software system which has been severed for daily inflow predictions with lead-times varying from 1 to 6 days of more than twenty reservoirs operated by the Fujian Province Grid Company, China.

  12. A Plane Target Detection Algorithm in Remote Sensing Images based on Deep Learning Network Technology

    Science.gov (United States)

    Shuxin, Li; Zhilong, Zhang; Biao, Li

    2018-01-01

    Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.

  13. Using neural networks for prediction of nuclear parameters

    Energy Technology Data Exchange (ETDEWEB)

    Pereira Filho, Leonidas; Souto, Kelling Cabral, E-mail: leonidasmilenium@hotmail.com, E-mail: kcsouto@bol.com.br [Instituto Federal de Educacao, Ciencia e Tecnologia do Rio de Janeiro (IFRJ), Rio de Janeiro, RJ (Brazil); Machado, Marcelo Dornellas, E-mail: dornemd@eletronuclear.gov.br [Eletrobras Termonuclear S.A. (GCN.T/ELETRONUCLEAR), Rio de Janeiro, RJ (Brazil). Gerencia de Combustivel Nuclear

    2013-07-01

    Dating from 1943, the earliest work on artificial neural networks (ANN), when Warren Mc Cullock and Walter Pitts developed a study on the behavior of the biological neuron, with the goal of creating a mathematical model. Some other work was done until after the 80 witnessed an explosion of interest in ANNs, mainly due to advances in technology, especially microelectronics. Because ANNs are able to solve many problems such as approximation, classification, categorization, prediction and others, they have numerous applications in various areas, including nuclear. Nodal method is adopted as a tool for analyzing core parameters such as boron concentration and pin power peaks for pressurized water reactors. However, this method is extremely slow when it is necessary to perform various core evaluations, for example core reloading optimization. To overcome this difficulty, in this paper a model of Multi-layer Perceptron (MLP) artificial neural network type backpropagation will be trained to predict these values. The main objective of this work is the development of Multi-layer Perceptron (MLP) artificial neural network capable to predict, in very short time, with good accuracy, two important parameters used in the core reloading problem - Boron Concentration and Power Peaking Factor. For the training of the neural networks are provided loading patterns and nuclear data used in cycle 19 of Angra 1 nuclear power plant. Three models of networks are constructed using the same input data and providing the following outputs: 1- Boron Concentration and Power Peaking Factor, 2 - Boron Concentration and 3 - Power Peaking Factor. (author)

  14. Using neural networks for prediction of nuclear parameters

    International Nuclear Information System (INIS)

    Pereira Filho, Leonidas; Souto, Kelling Cabral; Machado, Marcelo Dornellas

    2013-01-01

    Dating from 1943, the earliest work on artificial neural networks (ANN), when Warren Mc Cullock and Walter Pitts developed a study on the behavior of the biological neuron, with the goal of creating a mathematical model. Some other work was done until after the 80 witnessed an explosion of interest in ANNs, mainly due to advances in technology, especially microelectronics. Because ANNs are able to solve many problems such as approximation, classification, categorization, prediction and others, they have numerous applications in various areas, including nuclear. Nodal method is adopted as a tool for analyzing core parameters such as boron concentration and pin power peaks for pressurized water reactors. However, this method is extremely slow when it is necessary to perform various core evaluations, for example core reloading optimization. To overcome this difficulty, in this paper a model of Multi-layer Perceptron (MLP) artificial neural network type backpropagation will be trained to predict these values. The main objective of this work is the development of Multi-layer Perceptron (MLP) artificial neural network capable to predict, in very short time, with good accuracy, two important parameters used in the core reloading problem - Boron Concentration and Power Peaking Factor. For the training of the neural networks are provided loading patterns and nuclear data used in cycle 19 of Angra 1 nuclear power plant. Three models of networks are constructed using the same input data and providing the following outputs: 1- Boron Concentration and Power Peaking Factor, 2 - Boron Concentration and 3 - Power Peaking Factor. (author)

  15. Alice-Anne Martin (1926 - 2016)

    CERN Multimedia

    2016-01-01

    Alice-Anne Martin, known as “Schu” from her maiden name Schubert, passed away on 8 January 2016.   (Image: Gérard Bertin) Hired the year CERN was founded, 1954, when the construction of the Laboratory had not even begun, Schu first worked at the Villa de Cointrin (a historic building now within the grounds of Geneva airport) as a secretary. In this role, she typed the convention between CERN and the Swiss Confederation, prepared by Stéphanie Tixier, as well as some of the "Yellow Reports" that have marked key points in the Laboratory’s history. For example, using a special typewriter with two keyboards – Latin and Greek – she typed the Yellow Report on the KAM theorem by Rolf Hagedorn. Schu also worked with Felix Bloch, the first Director-General of CERN, and later became the secretary of Herbert Coblenz, the first CERN librarian. She was head of the team that edited the proceedings of the ...

  16. Sustainable Technology Analysis of Artificial Intelligence Using Bayesian and Social Network Models

    Directory of Open Access Journals (Sweden)

    Juhwan Kim

    2018-01-01

    Full Text Available Recent developments in artificial intelligence (AI have led to a significant increase in the use of AI technologies. Many experts are researching and developing AI technologies in their respective fields, often submitting papers and patent applications as a result. In particular, owing to the characteristics of the patent system that is used to protect the exclusive rights to registered technology, patent documents contain detailed information on the developed technology. Therefore, in this study, we propose a statistical method for analyzing patent data on AI technology to improve our understanding of sustainable technology in the field of AI. We collect patent documents that are related to AI technology, and then analyze the patent data to identify sustainable AI technology. In our analysis, we develop a statistical method that combines social network analysis and Bayesian modeling. Based on the results of the proposed method, we provide a technological structure that can be applied to understand the sustainability of AI technology. To show how the proposed method can be applied to a practical problem, we apply the technological structure to a case study in order to analyze sustainable AI technology.

  17. Investments on a Rugged Landscape: The Effect of Investor Population, Network Structure, and Complexity on Technological Change

    DEFF Research Database (Denmark)

    Hain, Daniel; Mas Tur, Elena

    In this paper, we investigate which characteristics of technological and financial systems might be conductive for technological change. We are particularly in how the interplay between capabilities, resources and networks among investors with the complexity and maturity of technologies affect...... rates of technological change and diversity, and prevents technologies from getting stuck in the financial “valley of death”. In a next step, we introduce investor networks and allow agents to co-invest together in order to pool financial resources and get access to their forecasting capability...... in a specific technological domain. We compare which investor network structures lead to the high rates of technological change and diversity on a given technology landscape. Results from a Monte Carlo simulation indicate networked investor population to outperform the case of isolated stand-alone investors...

  18. Fighting the Network: A Critique of the Network as a Security Technology

    NARCIS (Netherlands)

    de Goede, M.

    2012-01-01

    It is difficult to think about global connectivity without confronting the importance of the network as a metaphor and a model of contemporary social life and transnational danger. From the dispersed global terrorism threat, to the spread of (computer) viruses, from the identification of organized

  19. Optimization Study of Hydrogen Gas Adsorption on Zig-zag Single-walled Carbon Nanotubes: The Artificial Neural Network Analysis

    Science.gov (United States)

    Nasruddin; Lestari, M.; Supriyadi; Sholahudin

    2018-03-01

    The use of hydrogen gas in fuel cell technology has a huge opportunity to be applied in upcoming vehicle technology. One of the most important problems in fuel cell technology is the hydrogen storage. The adsorption of hydrogen in carbon-based materials attracts a lot of attention because of its reliability. This study investigated the adsorption of hydrogen gas in Single-walled Carbon Nano Tubes (SWCNT) with chilarity of (0, 12), (0, 15), and (0, 18) to find the optimum chilarity. Artificial Neural Networks (ANN) can be used to predict the hydrogen storage capacity at different pressure and temperature conditions appropriately, using simulated series of data. The Artificial Neural Network is modeled as a predictor of the hydrogen adsorption capacity which provides solutions to some deficiencies in molecular dynamics (MD) simulations. In a previous study, ANN configurations have been developed for 77k, 233k, and 298k temperatures in hydrogen gas storage. To prepare this prediction, ANN is modeled to find out the configurations that exist in the set of training and validation of specified data selection, the distance between data, and the number of neurons that produce the smallest error. This configuration is needed to make an accurate artificial neural network. The configuration of neural network was then applied to this research. The neural network analysis results show that the best configuration of artificial neural network in hydrogen storage is at 233K temperature i.e. on SWCNT with chilarity of (0.12).

  20. Network support, technology use, depression, and ART adherence among HIV-positive MSM of color.

    Science.gov (United States)

    Holloway, I W; Tan, D; Dunlap, S L; Palmer, L; Beougher, S; Cederbaum, J A

    2017-09-01

    Depression is associated with poor antiretroviral therapy (ART) adherence among people living with HIV/AIDS. This relationship may be moderated by an individual's social network characteristics. Our study sought to examine social network correlates of treatment adherence among HIV-positive men recruited from social service agencies throughout Los Angeles County (N = 150) to inform technology-driven social support interventions for this population. We administered egocentric social network and computer-assisted survey interviews focused on demographic characteristics, health history, depressive symptoms, and ART adherence, where adherence was assessed by the number of reasons participants missed taking their medication, if ever. Significant univariate correlates of adherence were included in a multivariable regression analysis, where the moderating effect of having a network member who reminds participants to take their HIV medication on the relationship between depression and adherence was tested. Over 60% of participants reported clinically significant depressive symptoms; this was significantly associated with lower adherence among those without someone in their social network to remind them about taking their HIV medication, even after adjusting for covariates in an ordinary least squares regression (adjusted mean difference b = -1.61, SE = 0.42, p = 0.0003). Having a network member who reminds participants to take their ART medication significantly ameliorated the negative association between depression and treatment adherence, especially for those reporting greater depressive symptoms (p = 0.0394). Additionally, participants demonstrated high rates of technology use to communicate with social network members. In order to achieve the aims of the National HIV/AIDS Strategy, innovative interventions addressing mental health to improve ART adherence are needed. Network strategies that leverage technology may be helpful for improving ART

  1. Seafloor classification using acoustic backscatter echo-waveform - Artificial neural network applications

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Mahale, V.; Navelkar, G.S.; Desai, R.G.P.

    In this paper seafloor classifications system based on artificial neural network (ANN) has been designed. The ANN architecture employed here is a combination of Self Organizing Feature Map (SOFM) and Linear Vector Quantization (LVQ1). Currently...

  2. Integration of multi-technology on oil spill emergency preparedness.

    Science.gov (United States)

    Liao, Zhenliang; Hannam, Phillip M; Xia, Xiaowei; Zhao, Tingting

    2012-10-01

    This paper focuses on the integration of technologies including Case-Based Reasoning (CBR), Genetic Algorithm (GA) and Artificial Neural Network (ANN) for establishing emergency preparedness for oil spill accidents. In CBR, the Frame method is used to define case representation, and the HEOM (Heterogeneous Euclidean-Overlap Metric) is improved to define the similarity of case properties. In GA, we introduce an Improved Genetic Algorithm (IGA) that achieves case adaptation, in which technologies include the Multi-Parameter Cascade Code method, the Small Section method for generation of an initial population, the Multi-Factor Integrated Fitness Function, and Niche technology for genetic operations including selection, crossover, and mutation. In ANN, a modified back-propagation algorithm is employed to train the algorithm to quickly improve system preparedness. Through the analysis of 32 fabricated oil spill cases, an oil spill emergency preparedness system based on the integration of CBR, GA and ANN is introduced. In particular, the development of ANN is presented and analyzed. The paper also discusses the efficacy of our integration approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Usability and use reference in the social network facebook: a netnographic analysis of technological users

    Directory of Open Access Journals (Sweden)

    Naiara Silva Ferreira

    2015-10-01

    Full Text Available This article presents a study about the preference of use in virtual social networks, using Facebook as object of study, to identify the motivational factors for the usability of this technology platform. The social network Facebook has been chosen to present a technological scenario of high sociability and virtual interaction. The methodology used was the netnography, being made through the collection of discussions in North American sites of news and forums online, where there is a large critical user participation on the internet, about the gains and frustrations in this context. The content analysis was performed comparing the categories of users found in the literature about values that motivate consumer technology, describing the hedonic, social, utilitarian values and perceptions of risk in consumption when related to lack of privacy. The results show two main groups of users of this technology and 7 subgroups. Therefore, the contribution of the study is that the formation of these groups may reflect technological usability of user groups around the world. The study also brings to the discussion issues related to the behaviors of the users of virtual networks which can be useful for businesses and their relationships with consumers and also the development of new knowledge from such criticism and demands that digital consumers expose about the technologies.

  4. FLASH-FLOOD MODELLING WITH ARTIFICIAL NEURAL NETWORKS USING RADAR RAINFALL ESTIMATES

    Directory of Open Access Journals (Sweden)

    Dinu Cristian

    2017-09-01

    Full Text Available The use of artificial neural networks (ANNs in modelling the hydrological processes has become a common approach in the last two decades, among side the traditional methods. In regard to the rainfall-runoff modelling, in both traditional and ANN models the use of ground rainfall measurements is prevalent, which can be challenging in areas with low rain gauging station density, especially in catchments where strong focused rainfall can generate flash-floods. The weather radar technology can prove to be a solution for such areas by providing rain estimates with good time and space resolution. This paper presents a comparison between different ANN setups using as input both ground and radar observations for modelling the rainfall-runoff process for Bahluet catchment, with focus on a flash-flood observed in the catchment.

  5. WEB 2.0 SERVICES AS A TECHNOLOGICAL FOUNDATION OF A NETWORK PROJECT

    Directory of Open Access Journals (Sweden)

    Tatiana Ivanovna Kanyanina

    2015-02-01

    Full Text Available In the light of the requirements of the federal state educational standard increases the value of the network design based on the use of Web 2.0 services. The article outlines the range of technological challenges faced by the developer of the network project, such as the choice of the network platform of the project, design tools and tools for project results placement, project coordination and organization of communication lines, the choice of instruments for the promotion of the project on the Internet. The main attention is focused on the examples of network services that address these challenges, and describe their features. The authors rely on the specific network projects implemented in Nizhny Novgorod region. The paper analyzes the possible project’s network sites (network environment. The article gives a general description of each environment, marks its distinctive features, advantages and disadvantages. The article presents project tasks’ examples, designed on the basis of the variety of Web 2.0 services that functionally meet the requirements of a particular task, examples of services to represent the project products and to summarize its results. Attention is paid to the organization of the lines of communication of the project participants and organizers and to the role of network services in the project promotion on the Internet.

  6. Dynamical assessment for evolutions of Atomic-Multinology (AM) in technology innovation using social network theory

    International Nuclear Information System (INIS)

    Woo, Taeho

    2012-01-01

    Highlights: ► The popularity of AM is analyzed by the social network theory. ► The graphical and colorful configurations are used for the meaning of the incident. ► The new industrial field is quantified by dynamical investigations. ► AM can be successfully used in nuclear industry for technology innovation. ► The method could be used for other industries. - Abstract: The technology evolution is investigated. The proposed Atomic Multinology (AM) is quantified by the dynamical method incorporated with Monte-Carlo method. There are three kinds of the technologies as the info-technology (IT), nano-technology (NT), and bio-technology (BT), which are applied to the nuclear technology. AM is initiated and modeled for the dynamic quantifications. The social network algorithm is used in the dynamical simulation for the management of the projects. The result shows that the successfulness of the AM increases, where the 60 years are the investigated period. The values of the dynamical simulation increase in later stage, which means that the technology is matured as time goes on.

  7. Final Technical Report, Wind Generator Project (Ann Arbor)

    Energy Technology Data Exchange (ETDEWEB)

    Geisler, Nathan [City of Ann Arbor, MI (United States)

    2017-03-20

    A Final Technical Report (57 pages) describing educational exhibits and devices focused on wind energy, and related outreach activities and programs. Project partnership includes the City of Ann Arbor, MI and the Ann Arbor Hands-on Museum, along with additional sub-recipients, and U.S. Department of Energy/Office of Energy Efficiency and Renewable Energy (EERE). Report relays key milestones and sub-tasks as well as numerous graphics and images of five (5) transportable wind energy demonstration devices and five (5) wind energy exhibits designed and constructed between 2014 and 2016 for transport and use by the Ann Arbor Hands-on Museum.

  8. The Design of Wireless Sensor Network System Based on ZigBee Technology for Greenhouse

    International Nuclear Information System (INIS)

    Zhu, Y W; Zhong, X X; Shi, J F

    2006-01-01

    Wireless sensor network is a new research field. It can be used in some special situation for signal collection, processing and transmitting. Zigbee is a new Wireless sensor network technology characteristic of less distance and low speed. It is a new wireless network protocol stack of IEEE 802.15.4. Lately traditional system to collects parameters for Greenhouse is widely used in agriculture. The traditional system adopts wired way wiring, which makes the system complex and expensive. Generally modern Greenhouse has hundreds of square meters and they may plant variety of plants depending on different seasons. So we need to adjust the sensors which collect parameters for Greenhouse to a better place to work more efficient. Adopting wireless way wiring is convenient and economical. This paper developed a wireless sensor network system based on ZigBee technology for greenhouse. It offers flexibility and mobility to save cost and energy spent on wiring. The framework hardware and software structure, related programming are also discussed in this paper. Comparing the system which uses ZigBee technology with traditional wired network system for greenhouse, it has advantage of low cost..low power and wider coverage. Additionally it complies with IEEE802.15.4 protocol, which makes it convenient to communicate with other products that comply with the protocol too

  9. Report on investigation in fiscal 2000 of industrial technology exchange with international networking organizations; 2000 nendo kokusaitekina network gata soshiki tono sangyo gijutsu koryu chosa hokokusho

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-03-01

    With an objective to promote exchange of industrial technologies, investigations and analyses were made on identification of the current status of networking organizations in different countries working as windows for industrial technology exchange, and on the actual status of technology commercialization methods in overseas incubators. Activities were taken in the following three fields: 1) the current status of networking organizations and incubators in different countries, 2) typology of technology commercialization, technical fields, and success factors, and 3) possibility of the use of technology information in the networking organizations. In Item 1), investigations were performed on the current status and actual activity status of the networking organizations including research parks and individual incubators intended of information exchange, mainly in the United States, UK, and Finland. In Item 2), considerations are given on the points related to technology incubation based on the information about the networking organizations and incubators in each country, and the way the industry-academia cooperation should be. In Item 3), discussions were given on the roles of the networking organizations and the possibility of utilization of technological information in the networking organizations in Japan. (NEDO)

  10. Cohesive subgroup formation : enabling and constraining effects of social capital in strategic technology alliance networks

    NARCIS (Netherlands)

    Duysters, G.M.; Lemmens, C.E.A.V.

    2002-01-01

    In this paper we will examine the role of embeddedness and social capital in the process of cohesive subgroup formation in strategic technology alliance networks. More in particular, we will investigate the social mechanisms that enable and enforce cohesive subgroup formation. We will argue that the

  11. Making Choices in the Virtual World: The New Model at United Technologies Information Network.

    Science.gov (United States)

    Gulliford, Bradley

    1998-01-01

    Describes changes in services of the United Technologies Corporation Information Network from a traditional library system to a virtual system of World Wide Web sites, a document-delivery unit, telephone and e-mail reference, and desktop technical support to provide remote access. Staff time, security, and licensing issues are addressed.…

  12. Social Media and Networking Technologies: An Analysis of Collaborative Work and Team Communication

    Science.gov (United States)

    Okoro, Ephraim A.; Hausman, Angela; Washington, Melvin C.

    2012-01-01

    Digital communication increases students' learning outcomes in higher education. Web 2.0 technologies encourages students' active engagement, collaboration, and participation in class activities, facilitates group work, and encourages information sharing among students. Familiarity with organizational use and sharing in social networks aids…

  13. Connected to Learn: Teachers' Experiences with Networked Technologies in the Classroom

    Science.gov (United States)

    Johnson, Matthew; Riel, Richard; Germain-Froese, Bernie

    2016-01-01

    To get a better understanding of how networked technologies are impacting teachers and their teaching practices, in 2015 MediaSmarts partnered with the Canadian Teachers' Federation to survey 4,043 K-12 teachers and school administrators who were teaching in classroom settings across the country. The survey explored the extent to which networked…

  14. A Co-Citation Network of Young Children's Learning with Technology

    Science.gov (United States)

    Tang, Kai-Yu; Li, Ming-Chaun; Hsin, Ching-Ting; Tsai, Chin-Chung

    2016-01-01

    This paper used a novel literature review approach--co-citation network analysis--to illuminate the latent structure of 87 empirical papers in the field of young children's learning with technology (YCLT). Based on the document co-citation analysis, a total of 206 co-citation relationships among the 87 papers were identified and then graphically…

  15. Investment and Usage of New Technologies : Evidence from a Shared ATM Network

    NARCIS (Netherlands)

    Ferrari, S.; Verboven, F.L.; Degryse, H.A.

    2007-01-01

    When new technologies become available, it is not only essential that firms have the correct investment incentives, but often also that consumers make the proper usage decisions. This paper studies investment and usage in a shared ATM network. Be- cause all banks coordinate their ATM investment

  16. Investment and Usage of New Technologies : Evidence from a Shared ATM Network

    NARCIS (Netherlands)

    Ferrari, S.; Verboven, F.L.; Degryse, H.A.

    2008-01-01

    When new technologies become available, it is not only essential that firms have the correct investment incentives, but often also that consumers make the proper usage decisions. This paper studies investment and usage in a shared ATM network. Be- cause all banks coordinate their ATM investment

  17. Using home networks to create atmospheres in the home: Technology push or (latent) user need?

    NARCIS (Netherlands)

    Kuiper-Hoyng, L.L.M.L.; Beusmans, J.W.F.

    2004-01-01

    The Atmosphere Controller is an implementation of home networking technology that could make life at home a totally new experience. An atmosphere is created by combining light (intensity and colour), music and wallpaper projection. To find out if is this type of experience fits into everyday life of

  18. Low-Power RF SOI-CMOS Technology for Distributed Sensor Networks

    Science.gov (United States)

    Dogan, Numan S.

    2003-01-01

    The objective of this work is to design and develop Low-Power RF SOI-CMOS Technology for Distributed Sensor Networks. We briefly report on the accomplishments in this work. We also list the impact of this work on graduate student research training/involvement.

  19. Key Technologies in the Context of Future Networks: Operational and Management Requirements

    Directory of Open Access Journals (Sweden)

    Lorena Isabel Barona López

    2016-12-01

    Full Text Available The concept of Future Networks is based on the premise that current infrastructures require enhanced control, service customization, self-organization and self-management capabilities to meet the new needs in a connected society, especially of mobile users. In order to provide a high-performance mobile system, three main fields must be improved: radio, network, and operation and management. In particular, operation and management capabilities are intended to enable business agility and operational sustainability, where the addition of new services does not imply an excessive increase in capital or operational expenditures. In this context, a set of key-enabled technologies have emerged in order to aid in this field. Concepts such as Software Defined Network (SDN, Network Function Virtualization (NFV and Self-Organized Networks (SON are pushing traditional systems towards the next 5G network generation.This paper presents an overview of the current status of these promising technologies and ongoing works to fulfill the operational and management requirements of mobile infrastructures. This work also details the use cases and the challenges, taking into account not only SDN, NFV, cloud computing and SON but also other paradigms.

  20. Object-Oriented Bayesian Networks (OOBN) for Aviation Accident Modeling and Technology Portfolio Impact Assessment

    Science.gov (United States)

    Shih, Ann T.; Ancel, Ersin; Jones, Sharon M.

    2012-01-01

    The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.

  1. New Technology Changing The Face of Mobile Seismic Networks

    Science.gov (United States)

    Brisbourne, A.; Denton, P.; Seis-Uk

    SEIS-UK, a seismic equipment pool and data management facility run by a consortium of four UK universities (Leicester, Leeds, Cambridge and Royal Holloway, London) completed its second phase in 2001. To compliment the existing broadband equipment pool, which has been deployed to full capacity to date, the consortium undertook a tender evaluation process for low-power, lightweight sensors and recorders, for use on both controlled source and passive seismic experiments. The preferred option, selected by the consortium, was the Guralp CMG-6TD system, with 150 systems ordered. The CMG-6TD system is a new concept in temporary seismic equipment. A 30s- 100Hz force-feedback sensor, integral 24bit digitiser and 3-4Gbyte of solid-state memory are all housed in a single unit. Use of the most recent technologies has kept the power consumption to below 1W and the weight to 3.5Kg per unit. The concept of the disk-swap procedure for obtaining data from the field has been usurped by a fast data download technique using firewire technology. This allows for rapid station servicing, essential when 150 stations are in use, and also ensures the environmental integrity of the system by removing the requirement for a disk access port and envi- ronmentally exposed data disk. The system therefore meets the criteria for controlled source and passive seismic experiments: (1) the single unit concept and low-weight is designed for rapid deployment on short-term projects; (2) the low power consumption reduces the power-supply requirements facilitating deployment; (3) the low self-noise and bandwidth of the sensor make it applicable to passive experiments involving nat- ural sources. Further to this acquisition process, in collaboration with external groups, the SEIS- UK data management procedures have been streamlined with the integration of the Guralp GCF format data into the PASSCAL PDB software. This allows for rapid dissemination of field data and the production of archive-ready datasets

  2. Interpretable neural networks with BP-SOM

    NARCIS (Netherlands)

    Weijters, A.J.M.M.; Bosch, van den A.P.J.; Pobil, del A.P.; Mira, J.; Ali, M.

    1998-01-01

    Artificial Neural Networks (ANNS) are used successfully in industry and commerce. This is not surprising since neural networks are especially competitive for complex tasks for which insufficient domain-specific knowledge is available. However, interpretation of models induced by ANNS is often

  3. The Influence of Social Networking Technologies on Female Religious Veil-Wearing Behavior in Iran

    Science.gov (United States)

    Shakiba, Abbas; Kwok, Justin; Montazeri, Mohammad Sadegh

    2014-01-01

    Abstract Social networking technologies can influence attitudes, behaviors, and social norms. Research on this topic has been conducted primarily among early adopters of technology and within the United States. However, it is important to evaluate how social media might affect people's behaviors in international settings, especially among countries with longstanding, government recommended, cultural and religious traditions and behaviors, such as Iran. This study seeks to assess whether Iranian women who have been using social networking technologies for a longer time (compared to those who have recently joined) would be less likely to cover themselves with a veil and be more comfortable publicly displaying pictures of this behavior on Facebook. Iranian females (N=253) were selected through snowball sampling from nongovernmental organizations in November 2011 and asked to complete a survey assessing their use of Facebook, concerns about not wearing a veil in Facebook pictures, and their actual likelihood of wearing a veil. Items were combined to measure lack of interest in wearing a veil. Length of time as a Facebook user was significantly associated with not wearing a veil (b=0.16, pbehavior of wearing a veil (b=−0.45, pSocial networking technologies can affect attitudes and behaviors internationally. We discuss methods of using social media for self-presentation and expression, as well as the difficulties (and importance) of studying use of technologies, such as social media, internationally. PMID:24611768

  4. Analysis of several digital network technologies for hard real-time communications in nuclear plant

    International Nuclear Information System (INIS)

    Song, Ki Sang; No, Hee Chun

    1999-01-01

    Applying digital network technology for advanced nuclear plant requires deterministic communication for tight safety requirements, timely and reliable data delivery for operation critical and mission-critical characteristics of nuclear plant. Communication protocols, such as IEEE 802/4 Tiken Bus, IEEE 802/5 Token Ring, FDDI, and ARCnet, which have deterministic communication capability are partially applied to several nuclear power plants. Although digital communication technologies have many advantages, it is necessary to consider the noise immunity form electromagnetic interference (EMI), electrical interference, impulse noise, and heat noise before selecting specific digital network technology for nuclear plant. In this paper, we consider the token frame loss and data frame loss rate due to the link error event, frame size, and link data rate in different protocols, and evaluate the possibility of failure to meet the hard real-time requirement in nuclear plant. (author). 11 refs., 3 figs., 4 tabs

  5. Professor Anne Khademian named National Academy of Public Administration Fellow

    OpenAIRE

    Chadwick, Heather Riley

    2009-01-01

    Anne Khademian, professor with Virginia Tech's Center for Public Administration and Policy, School of Public and International Affairs, at the Alexandria, Va., campus has been elected a National Academy of Public Administration (NAPA) Fellow.

  6. Anne-Marie Sargueil: ilu on kasulik / intervjueerinud Emilie Toomela

    Index Scriptorium Estoniae

    Sargueil, Anne-Marie

    2015-01-01

    Prantsuse Disainiinstituudi juht Anne-Marie Sargueil rääkis prantsuse ja skandinaavia disainist, prantslaste disainieelistustest, uutest suundadest disaini valdkonnas, Eesti Tarbekunsti- ja Disainimuuseumis avatud näitusest "20 prantsuse disainiikooni"

  7. The Royal Summer Palace, Ferdinand I and Anne

    Czech Academy of Sciences Publication Activity Database

    Dobalová, Sylva

    2015-01-01

    Roč. 7, č. 2 (2015), s. 162-175 ISSN 1804-1132 Institutional support: RVO:68378033 Keywords : Anne of Jagiello * Prague Castle * Ferdinand I of Habsburg * olive tree * dynasticism Subject RIV: AL - Art, Architecture, Cultural Heritage

  8. Ehe seep Eesti moodi / Anneli Aasmäe

    Index Scriptorium Estoniae

    Aasmäe, Anneli, 1973-

    2008-01-01

    Produtsent Kristian Taska Kalev Spordis näidatav Venezuela seebiseriaali Eesti oludele mugandatud variant "Kalevi naised" : lavastaja Ingomar Vihman : osades Andrus Vaarik, Anne Reemann, Piret Kalda, Ken Saan jt.

  9. Mentoring Entrepreneurial Networks: mapping conceptions of participants in technological-based business incubators in Brazil.

    Directory of Open Access Journals (Sweden)

    Pontes Regis, Helder

    2007-12-01

    Full Text Available The recent entrepreneurship research agenda includes the analysis of cognitive structures of successful entrepreneurs, revealing an important tool for the examination of an entrepreneurial career. Using techniques of cognitive maps, this study explores the concepts of a successful career and the network itself, as a whole, for career development. Fifty-three entrepreneurs were studied, in seven technological incubators in the city of Recife, Pernambuco, Brazil. Specifically, this study aimed to map the shared meanings of the incubated entrepreneurs regarding informal support networks. Such networks support the entrepreneurial career and the present study explores the characteristics and the conceptual model that underlies the networks. The data collection was achieved through interviews through a free evocation technique. The shared meanings indicate the existence of inherent thought categories that support network context in the incubator environment, mainly the mentoring networks. The results endorse the interpretation of an informal mentoring model emerging from the dominant evocations concerning a successful career and of the network itself as promoter of career development.

  10. Information communications technologies that surpass the global communications network. Sekai tsushinmo o koeru joho tsushin gijutsu

    Energy Technology Data Exchange (ETDEWEB)

    1990-05-01

    Development of information communications technologies that surpass the global communications network is being pushed forward in order to establish the global village that McLuhan foretold in 1964. Effects of hybrid intensification with the intensification of communications technologies and computer technologies have become evident as facsimiles, automated teller machines of banks, home videos, automatic response telephones with synthetic voices, compact disks, portable telephones, video games and high-definition televisions were developed and put to use in a wide range. Intensification and integration of computer technologies and communications technologies has every possibility, but it also has a peculiar aspect of lacking guiding principles. Uncertain factors of the values of informations in the market are ever increasing, and their true values are yet to be found. Anyhow, it is a long way to the goal of the global village.

  11. Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification

    Directory of Open Access Journals (Sweden)

    Vijay G. S.

    2012-01-01

    Full Text Available The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR and reducing the root-mean-square error (RMSE. In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN and the Support Vector Machine (SVM, for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher’s Criterion (FC. Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

  12. Comparing SVM and ANN based Machine Learning Methods for Species Identification of Food Contaminating Beetles.

    Science.gov (United States)

    Bisgin, Halil; Bera, Tanmay; Ding, Hongjian; Semey, Howard G; Wu, Leihong; Liu, Zhichao; Barnes, Amy E; Langley, Darryl A; Pava-Ripoll, Monica; Vyas, Himansu J; Tong, Weida; Xu, Joshua

    2018-04-25

    Insect pests, such as pantry beetles, are often associated with food contaminations and public health risks. Machine learning has the potential to provide a more accurate and efficient solution in detecting their presence in food products, which is currently done manually. In our previous research, we demonstrated such feasibility where Artificial Neural Network (ANN) based pattern recognition techniques could be implemented for species identification in the context of food safety. In this study, we present a Support Vector Machine (SVM) model which improved the average accuracy up to 85%. Contrary to this, the ANN method yielded ~80% accuracy after extensive parameter optimization. Both methods showed excellent genus level identification, but SVM showed slightly better accuracy  for most species. Highly accurate species level identification remains a challenge, especially in distinguishing between species from the same genus which may require improvements in both imaging and machine learning techniques. In summary, our work does illustrate a new SVM based technique and provides a good comparison with the ANN model in our context. We believe such insights will pave better way forward for the application of machine learning towards species identification and food safety.

  13. Estimation of Costs and Durations of Construction of Urban Roads Using ANN and SVM

    Directory of Open Access Journals (Sweden)

    Igor Peško

    2017-01-01

    Full Text Available Offer preparation has always been a specific part of a building process which has significant impact on company business. Due to the fact that income greatly depends on offer’s precision and the balance between planned costs, both direct and overheads, and wished profit, it is necessary to prepare a precise offer within required time and available resources which are always insufficient. The paper presents a research of precision that can be achieved while using artificial intelligence for estimation of cost and duration in construction projects. Both artificial neural networks (ANNs and support vector machines (SVM are analysed and compared. The best SVM has shown higher precision, when estimating costs, with mean absolute percentage error (MAPE of 7.06% compared to the most precise ANNs which has achieved precision of 25.38%. Estimation of works duration has proved to be more difficult. The best MAPEs were 22.77% and 26.26% for SVM and ANN, respectively.

  14. Measurement and ANN prediction of pH-dependent solubility of nitrogen-heterocyclic compounds.

    Science.gov (United States)

    Sun, Feifei; Yu, Qingni; Zhu, Jingke; Lei, Lecheng; Li, Zhongjian; Zhang, Xingwang

    2015-09-01

    Based on the solubility of 25 nitrogen-heterocyclic compounds (NHCs) measured by saturation shake-flask method, artificial neural network (ANN) was employed to the study of the quantitative relationship between the structure and pH-dependent solubility of NHCs. With genetic algorithm-multivariate linear regression (GA-MLR) approach, five out of the 1497 molecular descriptors computed by Dragon software were selected to describe the molecular structures of NHCs. Using the five selected molecular descriptors as well as pH and the partial charge on the nitrogen atom of NHCs (QN) as inputs of ANN, a quantitative structure-property relationship (QSPR) model without using Henderson-Hasselbalch (HH) equation was successfully developed to predict the aqueous solubility of NHCs in different pH water solutions. The prediction model performed well on the 25 model NHCs with an absolute average relative deviation (AARD) of 5.9%, while HH approach gave an AARD of 36.9% for the same model NHCs. It was found that QN played a very important role in the description of NHCs and, with QN, ANN became a potential tool for the prediction of pH-dependent solubility of NHCs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Prediction of Frequency for Simulation of Asphalt Mix Fatigue Tests Using MARS and ANN

    Directory of Open Access Journals (Sweden)

    Ali Reza Ghanizadeh

    2014-01-01

    Full Text Available Fatigue life of asphalt mixes in laboratory tests is commonly determined by applying a sinusoidal or haversine waveform with specific frequency. The pavement structure and loading conditions affect the shape and the frequency of tensile response pulses at the bottom of asphalt layer. This paper introduces two methods for predicting the loading frequency in laboratory asphalt fatigue tests for better simulation of field conditions. Five thousand (5000 four-layered pavement sections were analyzed and stress and strain response pulses in both longitudinal and transverse directions was determined. After fitting the haversine function to the response pulses by the concept of equal-energy pulse, the effective length of the response pulses were determined. Two methods including Multivariate Adaptive Regression Splines (MARS and Artificial Neural Network (ANN methods were then employed to predict the effective length (i.e., frequency of tensile stress and strain pulses in longitudinal and transverse directions based on haversine waveform. It is indicated that, under controlled stress and strain modes, both methods (MARS and ANN are capable of predicting the frequency of loading in HMA fatigue tests with very good accuracy. The accuracy of ANN method is, however, more than MARS method. It is furthermore shown that the results of the present study can be generalized to sinusoidal waveform by a simple equation.

  16. ANN-PSO Integrated Optimization Methodology for Intelligent Control of MMC Machining

    Science.gov (United States)

    Chandrasekaran, Muthumari; Tamang, Santosh

    2017-08-01

    Metal Matrix Composites (MMC) show improved properties in comparison with non-reinforced alloys and have found increased application in automotive and aerospace industries. The selection of optimum machining parameters to produce components of desired surface roughness is of great concern considering the quality and economy of manufacturing process. In this study, a surface roughness prediction model for turning Al-SiCp MMC is developed using Artificial Neural Network (ANN). Three turning parameters viz., spindle speed ( N), feed rate ( f) and depth of cut ( d) were considered as input neurons and surface roughness was an output neuron. ANN architecture having 3 -5 -1 is found to be optimum and the model predicts with an average percentage error of 7.72 %. Particle Swarm Optimization (PSO) technique is used for optimizing parameters to minimize machining time. The innovative aspect of this work is the development of an integrated ANN-PSO optimization method for intelligent control of MMC machining process applicable to manufacturing industries. The robustness of the method shows its superiority for obtaining optimum cutting parameters satisfying desired surface roughness. The method has better convergent capability with minimum number of iterations.

  17. Estimating SPT-N Value Based on Soil Resistivity using Hybrid ANN-PSO Algorithm

    Science.gov (United States)

    Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

    2018-04-01

    Standard Penetration Resistance (N value) is used in many empirical geotechnical engineering formulas. Meanwhile, soil resistivity is a measure of soil’s resistance to electrical flow. For a particular site, usually, only a limited N value data are available. In contrast, resistivity data can be obtained extensively. Moreover, previous studies showed evidence of a correlation between N value and resistivity value. Yet, no existing method is able to interpret resistivity data for estimation of N value. Thus, the aim is to develop a method for estimating N-value using resistivity data. This study proposes a hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) method to estimate N value using resistivity data. Five different ANN-PSO models based on five boreholes were developed and analyzed. The performance metrics used were the coefficient of determination, R2 and mean absolute error, MAE. Analysis of result found that this method can estimate N value (R2 best=0.85 and MAEbest=0.54) given that the constraint, Δ {\\bar{l}}ref, is satisfied. The results suggest that ANN-PSO method can be used to estimate N value with good accuracy.

  18. An analysis of communications and networking technologies for the smart grid

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Hernandez, Joaquin [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico)

    2013-03-01

    The Smart Grid concept has been foreseen as the integration of the electrical generation, transmission and distribution network and the data communications network. Although, traditional communications interfaces, protocols and standards has been used in the electrical grid in an isolated manner, modern communications network is considered as the fundamental enabling technology within the future Smart Grid. Modern communications technologies, protocol architectures and standards can help to build a common communications network infrastructure for data transport between customer premises, power substations, and power distribution systems, utility control centers and utility data centers. The Smart Grid will support traditional applications such as SCADA, distribution automation (DA), energy management systems (EMS), demand site management (DSM) and automatic meter reading (AMR), etc., as well as new applications like advanced metering infrastructure (AMI), substation automation (SA), microgrids, distributed generation, grid monitoring and control, data storage and analysis, among others. To make this possible, the Smart Grid requires a two-way wide area communications network between different dispersed areas, from generation, to distribution to consumer premises. In fact, it will consist of many different types of communications networks such as wide area networks, local area network, home area networks, etc. This requires a new architectural approach to implement a common communications infrastructure that provides the reliability, scalability, security and interoperability to support multiple applications. In addition, open standards addressing interoperability, are key for the development and deployment of the Smart Grid as a true integrated network. A communications backbone is necessary to provide interoperability. To achieve the level of networking, interoperability and security that meets the technical requirements of the Smart Grid, its data communications

  19. Citizen Management of Technology: A Science and Technology Studies approach to wireless networks and urban governance trough guifi.net

    Directory of Open Access Journals (Sweden)

    Yann Bona Beauvois

    2011-03-01

    Full Text Available Thesis presented at the Departament de Psicologia Social de la UAB by Yann Bona on December, 2010. Directed by Dr. Joan Pujol Tarrés.This dissertation explores the many ways in which citizens aiming to manage technologies in urban scape relate to public administrations. To accomplish it's task, it brings forward certain STS notions such as cosmopolitics, hybrid composition or technical democracy. On a general level, this thesis seeks an answer to Bruno Latour concern with what does it mean to conceive the technical as political?. We offer a set of conclusions based on what we choose to name a Sociotechnique of Public Policy .Our work relies on a case study focused on a free and open wireless network (located in Catalunya for the most part and called guifi.net that emerged from the desire and will of Civil Society wich, up to date, turns out to be the world's biggest free wireless network.

  20. Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

    Science.gov (United States)

    Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

    2017-12-01

    The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

  1. Modelling the spectral irradiance distribution in sunny inland locations using an ANN-based methodology

    International Nuclear Information System (INIS)

    Torres-Ramírez, M.; Elizondo, D.; García-Domingo, B.; Nofuentes, G.; Talavera, D.L.

    2015-01-01

    This work is aimed at verifying that in sunny inland locations artificial intelligence techniques may provide an estimation of the spectral irradiance with adequate accuracy for photovoltaic applications. An ANN (artificial neural network) based method was developed, trained and tested to model the spectral distributions between wavelengths ranging from 350 to 1050 nm. Only commonly available input data such as geographical information regarding location, specific date and time together with horizontal global irradiance and ambient temperature are required. Historical information from a 24-month experimental campaign carried out in Jaén (Spain) provided the necessary data to train and test the ANN tool. A Kohonen self-organized map was used as innovative technique to classify the whole input dataset and build a small and representative training dataset. The shape of the spectral irradiance distribution, the in-plane global irradiance (G T ) and irradiation (H T ) and the APE (average photon energy) values obtained through the ANN method were statistically compared to the experimental ones. In terms of shape distribution fitting, the mean relative deformation error stays below 4.81%. The root mean square percentage error is around 6.89% and 0.45% when estimating G T and APE, respectively. Regarding H T , errors lie below 3.18% in all cases. - Highlights: • ANN-based model to estimate the spectral irradiance distribution in sunny inland locations. • MRDE value stay below 4.81% in spectral irradiance distribution shape fitting. • RMSPE is about 6.89% for the in-plane global irradiance and 0.45% for the average photon energy. • Errors stay below 3.18% for all the months of the year in incident irradiation terms. • Improvement of assessment of the impact of the solar spectrum in the performance of a PV module

  2. Research and application of ARP protocol vulnerability attack and defense technology based on trusted network

    Science.gov (United States)

    Xi, Huixing

    2017-03-01

    With the continuous development of network technology and the rapid spread of the Internet, computer networks have been around the world every corner. However, the network attacks frequently occur. The ARP protocol vulnerability is one of the most common vulnerabilities in the TCP / IP four-layer architecture. The network protocol vulnerabilities can lead to the intrusion and attack of the information system, and disable or disable the normal defense function of the system [1]. At present, ARP spoofing Trojans spread widely in the LAN, the network security to run a huge hidden danger, is the primary threat to LAN security. In this paper, the author summarizes the research status and the key technologies involved in ARP protocol, analyzes the formation mechanism of ARP protocol vulnerability, and analyzes the feasibility of the attack technique. Based on the summary of the common defensive methods, the advantages and disadvantages of each defense method. At the same time, the current defense method is improved, and the advantage of the improved defense algorithm is given. At the end of this paper, the appropriate test method is selected and the test environment is set up. Experiment and test are carried out for each proposed improved defense algorithm.

  3. Policy gaps and technological deficiencies in social networking environments: Implications for information sharing

    Directory of Open Access Journals (Sweden)

    Stephen M. Mutula

    2013-06-01

    Objectives: The study sought to investigate the following research objectives to: (1 describe the types of social networks, (2 examine global penetration of the social networks, (3 outline the users’ legitimate rights that must be protected in the social networking sites (SNS, (4 determine the methods employed by SNS to protect the users’ legitimate rights and (5 identify the policy gaps and technological deficiencies in the protection of the users’ legitimate rights in the SNS. Method: A literature survey and content analysis of the SNS user policies were used to address objective four and objective five respectively. Results: The most actively used sites were Facebook and Twitter. Asian markets were leading in participation and in creating content than any other region. Business, education, politics and governance sectors were actively using social networking sites. Social networking sites relied upon user trust and internet security features which however, were inefficient and inadequate. Conclusion: Whilst SNS were impacting people of varying ages and of various professional persuasions, there were increased concerns about the violation and infringement of the users’ legitimate rights. Reliance on user trust and technological security features SNS to protect the users’ legitimate rights seemed ineffectual and inadequate.

  4. From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

    Science.gov (United States)

    Ross, Muriel D.

    1991-01-01

    The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

  5. Internal evaluation of the European network for health technology assessment project.

    Science.gov (United States)

    Håheim, Lise Lund; Imaz, Iñaki; Loud, Marlène Läubli; Gasparetto, Teresa; González-Enriquez, Jesús; Dahlgren, Helena; Trofimovs, Igor; Berti, Elena; Mørland, Berit

    2009-12-01

    The internal evaluation studied the development of the European network for Health Technology Assessment (EUnetHTA) Project in achieving the general objective of establishing an effective and a sustainable network of health technology assessment (HTA) in Europe. The Work Package 3 group was dedicated to this task and performed the work. Information on activities during the project was collected from three sources. First, three yearly cross-sectional studies surveyed the participants' opinions. Responses were by individuals or by institutions. The last round included surveys to the Steering Committee, the Stakeholder Forum, and the Secretariat. Second, the Work Package Lead Partners were interviewed bi-annually, five times in total, to update the information on the Project's progress. Third, additional information was sought in available documents. The organizational structure remained stable. The Project succeeded in developing tools aimed at providing common methodology with intent to establish a standard of conducting and reporting HTA and to facilitate greater collaboration among agencies. The participants/agencies expressed their belief in a network and in maintaining local/national autonomy. The Work Package Leaders expressed a strong belief in the solid base of the Project for a future network on which to build, but were aware of the need for funding and governmental support. Participants and Work Package Leaders have expressed support for a future network that will improve national and international collaboration in HTA based on the experience from the EUnetHTA project.

  6. Smart Home Communication Technologies and Applications: Wireless Protocol Assessment for Home Area Network Resources

    Directory of Open Access Journals (Sweden)

    Tiago D. P. Mendes

    2015-07-01

    Full Text Available The paper discusses Home Area Networks (HAN communication technologies for smart home and domestic application integration. The work is initiated by identifying the application areas that can benefit from this integration. A broad and inclusive home communication interface is analysed utilizing as a key piece a Gateway based on machine-to-machine (M2M communications that interacts with the surrounding environment. Then, the main wireless networks are thoroughly assessed, and later, their suitability to the requirements of HAN considering the application area is analysed. Finally, a qualitative analysis is portrayed.

  7. Canadian CO2 Capture and Storage Technology Network : promoting zero emissions technologies

    International Nuclear Information System (INIS)

    2004-11-01

    This brochure provided information on some Canadian initiatives in carbon dioxide (CO 2 ) capture and storage. There has been growing interest in the implementation of components of CO 2 capture, storage and utilization technologies in Canada. Technology developments by the CANMET Energy Technology Centre concerning CO 2 capture using oxy-fuel combustion and amine separation were examined. Techniques concerning gasification of coal for electricity production and CO 2 capture were reviewed. Details of a study of acid gas underground injection were presented. A review of monitoring technologies in CO 2 storage in enhanced oil recovery was provided. Issues concerning the enhancement of methane recovery through the monitoring of CO 2 injected into deep coal beds were discussed. Storage capacity assessment of Canadian sedimentary basins, coal seams and oil and gas reservoirs were reviewed, in relation to their suitability for CO 2 sequestration. Details of the International Test Centre for Carbon Dioxide Capture in Regina, Saskatchewan were presented, as well as issues concerning the sequestration of CO 2 in oil sands tailings streams. A research project concerning the geologic sequestration of CO 2 and simultaneous CO 2 and methane production from natural gs hydrate reservoirs was also discussed. 12 figs.

  8. Fiber in access technologies and network convergence: an opportunity for optical integration

    Science.gov (United States)

    Ghiggino, Pierpaolo C.

    2008-11-01

    Broadband networks are among the fastest growing segment in telecom. The initial and still very significant push originated with xDSL technologies and indeed a significant amount of research and development is still occurring in this field with impressive results and allowing for a remarkable use of the installed copper infrastructure way beyond its originally planned bandwidth capabilities. However it is clear that ultimately a more suitable fiber based infrastructure will be needed in order to reduce both operational and network technology costs. Such cost reduction in inevitable as the added value to end users is only related to services and these cannot be priced outside a sensible window, whilst the related bandwidth increase is much more dramatic and its huge variability must be met with little or no cost impact by the network and its operation. Fiber in access has indeed the potential to cope with a huge bandwidth demand for many years to come as its inherent bandwidth capabilities are only just tapped by current service requirements. However the whole technology supply chain must follow in line. In particular optical technology must brace itself to cope with the required much larger deployment and greater cost effectiveness, whilst at the same time deliver performance suitable to the bandwidth increase offered in the longer term by the fiber medium. This paper looks at this issues and debates the opportunities for a new class of optical devices making use of the progress in optical integration

  9. Informatics technology mimics ecology: dense, mutualistic collaboration networks are associated with higher publication rates.

    Directory of Open Access Journals (Sweden)

    Marco D Sorani

    Full Text Available Information technology (IT adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT from the literature.We selected seven programming languages and four types of HIT. We performed PubMed searches to identify publications since 2001. We calculated summary statistics and analyzed spatiotemporal relationships. Then, we assessed ecological models of specialization, cooperativity, competition, evolution, biodiversity, and stability associated with publications.Adoption of HIT has been variable, while scripting languages have experienced rapid adoption. Hospital systems had the largest HIT research corpus, while Perl had the largest language corpus. Scripting languages represented the largest connected network components. The relationship between edges and nodes was linear, though Bioconductor had more edges than expected and Perl had fewer. Spatiotemporal relationships were weak. Most languages shared a bioinformatics specialization and appeared mutualistic or competitive. HIT specializations varied. Specialization was highest for Bioconductor and radiology systems. Specialization and cooperativity were positively correlated among languages but negatively correlated among HIT. Rates of language evolution were similar. Biodiversity among languages grew in the first half of the decade and stabilized, while diversity among HIT was variable but flat. Compared with publications in 2001, correlation with publications one year later was positive while correlation after ten years was weak and negative.Adoption of new technologies can be unpredictable. Spatiotemporal relationships facilitate adoption but are not sufficient. As with ecosystems, dense

  10. Informatics technology mimics ecology: dense, mutualistic collaboration networks are associated with higher publication rates.

    Science.gov (United States)

    Sorani, Marco D

    2012-01-01

    Information technology (IT) adoption enables biomedical research. Publications are an accepted measure of research output, and network models can describe the collaborative nature of publication. In particular, ecological networks can serve as analogies for publication and technology adoption. We constructed network models of adoption of bioinformatics programming languages and health IT (HIT) from the literature.We selected seven programming languages and four types of HIT. We performed PubMed searches to identify publications since 2001. We calculated summary statistics and analyzed spatiotemporal relationships. Then, we assessed ecological models of specialization, cooperativity, competition, evolution, biodiversity, and stability associated with publications.Adoption of HIT has been variable, while scripting languages have experienced rapid adoption. Hospital systems had the largest HIT research corpus, while Perl had the largest language corpus. Scripting languages represented the largest connected network components. The relationship between edges and nodes was linear, though Bioconductor had more edges than expected and Perl had fewer. Spatiotemporal relationships were weak. Most languages shared a bioinformatics specialization and appeared mutualistic or competitive. HIT specializations varied. Specialization was highest for Bioconductor and radiology systems. Specialization and cooperativity were positively correlated among languages but negatively correlated among HIT. Rates of language evolution were similar. Biodiversity among languages grew in the first half of the decade and stabilized, while diversity among HIT was variable but flat. Compared with publications in 2001, correlation with publications one year later was positive while correlation after ten years was weak and negative.Adoption of new technologies can be unpredictable. Spatiotemporal relationships facilitate adoption but are not sufficient. As with ecosystems, dense, mutualistic

  11. Artificial neural networks: an efficient tool for modelling and optimization of biofuel production (a mini review)

    International Nuclear Information System (INIS)

    Sewsynker-Sukai, Yeshona; Faloye, Funmilayo; Kana, Evariste Bosco Gueguim

    2016-01-01

    In view of the looming energy crisis as a result of depleting fossil fuel resources and environmental concerns from greenhouse gas emissions, the need for sustainable energy sources has secured global attention. Research is currently focused towards renewable sources of energy due to their availability and environmental friendliness. Biofuel production like other bioprocesses is controlled by several process parameters including pH, temperature and substrate concentration; however, the improvement of biofuel production requires a robust process model that accurately relates the effect of input variables to the process output. Artificial neural networks (ANNs) have emerged as a tool for modelling complex, non-linear processes. ANNs are applied in the prediction of various processes; they are useful for virtual experimentations and can potentially enhance bioprocess research and development. In this study, recent findings on the application of ANN for the modelling and optimization of biohydrogen, biogas, biodiesel, microbial fuel cell technology and bioethanol are reviewed. In addition, comparative studies on the modelling efficiency of ANN and other techniques such as the response surface methodology are briefly discussed. The review highlights the efficiency of ANNs as a modelling and optimization tool in biofuel process development

  12. Arabic Handwriting Recognition Using Neural Network Classifier

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... an OCR using Neural Network classifier preceded by a set of preprocessing .... Artificial Neural Networks (ANNs), which we adopt in this research, consist of ... advantage and disadvantages of each technique. In [9],. Khemiri ...

  13. Neural Network Based Load Frequency Control for Restructuring ...

    African Journals Online (AJOL)

    Neural Network Based Load Frequency Control for Restructuring Power Industry. ... an artificial neural network (ANN) application of load frequency control (LFC) of a Multi-Area power system by using a neural network controller is presented.

  14. Visible technologies, invisible organisations: An empirical study of public beliefs about electricity supply networks

    International Nuclear Information System (INIS)

    Devine-Wright, Patrick; Devine-Wright, Hannah; Sherry-Brennan, Fionnguala

    2010-01-01

    Reducing carbon emissions in the energy system poses significant challenges to electricity transmission and distribution networks. Whilst these challenges are as much social as economic or technical, to date few research studies have investigated public beliefs about electricity supply networks. This research aimed to address this gap by means of a nationally representative study of UK adults (n=1041), probing beliefs about how electricity reaches the home, responsibility for electricity supply, associations with the words 'National Grid', as well as beliefs about the planning of new infrastructure. Findings suggest that electricity networks are represented predominantly in terms of technologies rather than organisations, specifically in terms of familiar, visible components such as cables or wires, rather than more systemic concepts such as networks. Transmission and distribution network operators were largely invisible to members of the public. In terms of planning new lines, most respondents assumed that government ministers were involved in decision-making, while local residents were widely perceived to have little influence; moreover, there was strong public support for placing new power lines underground, regardless of the cost. In conclusion, organisational invisibility, coupled with low expectations of participatory involvement, could provoke public opposition and delay siting new network infrastructure.

  15. Combined wavelet transform-artificial neural network use in tablet active content determination by near-infrared spectroscopy.

    Science.gov (United States)

    Chalus, Pascal; Walter, Serge; Ulmschneider, Michel

    2007-05-22

    The pharmaceutical industry faces increasing regulatory pressure to optimize quality control. Content uniformity is a basic release test for solid dosage forms. To accelerate test throughput and comply with the Food and Drug Administration's process analytical technology initiative, attention is increasingly turning to nondestructive spectroscopic techniques, notably near-infrared (NIR) spectroscopy (NIRS). However, validation of NIRS using requisite linearity and standard error of prediction (SEP) criteria remains a challenge. This study applied wavelet transformation of the NIR spectra of a commercial tablet to build a model using conventional partial least squares (PLS) regression and an artificial neural network (ANN). Wavelet coefficients in the PLS and ANN models reduced SEP by up to 60% compared to PLS models using mathematical spectra pretreatment. ANN modeling yielded high-linearity calibration and a correlation coefficient exceeding 0.996.

  16. Optimum coagulant forecasting by modeling jar test experiments using ANNs

    Science.gov (United States)

    Haghiri, Sadaf; Daghighi, Amin; Moharramzadeh, Sina

    2018-01-01

    Currently, the proper utilization of water treatment plants and optimizing their use is of particular importance. Coagulation and flocculation in water treatment are the common ways through which the use of coagulants leads to instability of particles and the formation of larger and heavier particles, resulting in improvement of sedimentation and filtration processes. Determination of the optimum dose of such a coagulant is of particular significance. A high dose, in addition to adding costs, can cause the sediment to remain in the filtrate, a dangerous condition according to the standards, while a sub-adequate dose of coagulants can result in the reducing the required quality and acceptable performance of the coagulation process. Although jar tests are used for testing coagulants, such experiments face many constraints with respect to evaluating the results produced by sudden changes in input water because of their significant costs, long time requirements, and complex relationships among the many factors (turbidity, temperature, pH, alkalinity, etc.) that can influence the efficiency of coagulant and test results. Modeling can be used to overcome these limitations; in this research study, an artificial neural network (ANN) multi-layer perceptron (MLP) with one hidden layer has been used for modeling the jar test to determine the dosage level of used coagulant in water treatment processes. The data contained in this research have been obtained from the drinking water treatment plant located in Ardabil province in Iran. To evaluate the performance of the model, the mean squared error (MSE) and correlation coefficient (R2) parameters have been used. The obtained values are within an acceptable range that demonstrates the high accuracy of the models with respect to the estimation of water-quality characteristics and the optimal dosages of coagulants; so using these models will allow operators to not only reduce costs and time taken to perform experimental jar tests

  17. Performance measurement of plate fin heat exchanger by exploration: ANN, ANFIS, GA, and SA

    Directory of Open Access Journals (Sweden)

    A.K. Gupta

    2017-01-01

    Full Text Available An experimental work is conducted on counter flow plate fin compact heat exchanger using offset strip fin under different mass flow rates. The training, testing, and validation set of data has been collected by conducting experiments. Next, artificial neural network merged with Genetic Algorithm (GA utilized to measure the performance of plate-fin compact heat exchanger. The main aim of present research is to measure the performance of plate-fin compact heat exchanger and to provide full explanations. An artificial neural network predicted simulated data, which verified with experimental data under 10–20% error. Then, the authors examined two well-known global search techniques, simulated annealing and the genetic algorithm. The proposed genetic algorithm and Simulated Annealing (SA results have been summarized. The parameters are impartially important for good results. With the emergence of a new data-driven modeling technique, Neuro-fuzzy based systems are established in academic and practical applications. The neuro-fuzzy interference system (ANFIS has also been examined to undertake the problem related to plate-fin heat exchanger performance measurement under various parameters. Moreover, Parallel with ANFIS model and Artificial Neural Network (ANN model has been created with emphasizing the accuracy of the different techniques. A wide range of statistical indicators used to assess the performance of the models. Based on the comparison, it was revealed that technical ANFIS improve the accuracy of estimates in the small pool and tropical ANN.

  18. Leadership Under Challenge: Information Technology R&D in a Competitive World. An Assessment of the Federal Networking and Information Technology R&D Program

    National Research Council Canada - National Science Library

    Marburger, John H; Kvamme, E. F; Scalise, George; Reed, Daniel A

    2007-01-01

    ...).That leadership is essential to U.S. economic prosperity, security, and quality of life. This report presents a formal assessment of the Federal Networking and Information Technology R&D (NITRD...

  19. Perspectives on Advanced Learning Technologies and Learning Networks and Future Aerospace Workforce Environments

    Science.gov (United States)

    Noor, Ahmed K. (Compiler)

    2003-01-01

    An overview of the advanced learning technologies is given in this presentation along with a brief description of their impact on future aerospace workforce development. The presentation is divided into five parts (see Figure 1). In the first part, a brief historical account of the evolution of learning technologies is given. The second part describes the current learning activities. The third part describes some of the future aerospace systems, as examples of high-tech engineering systems, and lists their enabling technologies. The fourth part focuses on future aerospace research, learning and design environments. The fifth part lists the objectives of the workshop and some of the sources of information on learning technologies and learning networks.

  20. An ANN-based approach to predict blast-induced ground vibration of Gol-E-Gohar iron ore mine, Iran

    Directory of Open Access Journals (Sweden)

    Mahdi Saadat

    2014-02-01

    Full Text Available Blast-induced ground vibration is one of the inevitable outcomes of blasting in mining projects and may cause substantial damage to rock mass as well as nearby structures and human beings. In this paper, an attempt has been made to present an application of artificial neural network (ANN to predict the blast-induced ground vibration of the Gol-E-Gohar (GEG iron mine, Iran. A four-layer feed-forward back propagation multi-layer perceptron (MLP was used and trained with Levenberg–Marquardt algorithm. To construct ANN models, the maximum charge per delay, distance from blasting face to monitoring point, stemming and hole depth were taken as inputs, whereas peak particle velocity (PPV was considered as an output parameter. A database consisting of 69 data sets recorded at strategic and vulnerable locations of GEG iron mine was used to train and test the generalization capability of ANN models. Coefficient of determination (R2 and mean square error (MSE were chosen as the indicators of the performance of the networks. A network with architecture 4-11-5-1 and R2 of 0.957 and MSE of 0.000722 was found to be optimum. To demonstrate the supremacy of ANN approach, the same 69 data sets were used for the prediction of PPV with four common empirical models as well as multiple linear regression (MLR analysis. The results revealed that the proposed ANN approach performs better than empirical and MLR models.