A Contribution to the Study of Ensemble of Self-Organizing Maps

Directory of Open Access Journals (Sweden)

Leandro Antonio Pasa

2015-01-01

Full Text Available This study presents a factorial experiment to investigate the ensemble of Kohonen Self-Organizing Maps. Clusters Validity Indexes and the Mean Square Quantization Error were used as a criterion for fusing Kohonen Maps, through three different equations and four approaches. Computational simulations were performed with traditional dataset, including those with high dimensionality, not linearly separable classes, Gaussian mixtures, almost touching clusters, and unbalanced classes, from the UCI Machine Learning Repository and from Fundamental Clustering Problems Suite, with variations in map size, number of ensemble components, and the percentage of dataset bagging. The proposed method achieves a better classification than a single Kohonen Map and we applied the Wilcoxon Signed Rank Test to evidence its effectiveness.

Theoretical and applied aspects of the self-organizing maps

OpenAIRE

Cottrell , Marie; Olteanu , Madalina; Rossi , Fabrice; Villa-Vialaneix , Nathalie

2016-01-01

International audience; The Self-Organizing Map (SOM) is widely used, easy to implement , has nice properties for data mining by providing both clustering and visual representation. It acts as an extension of the k-means algorithm that preserves as much as possible the topological structure of the data. However, since its conception, the mathematical study of the SOM remains difficult and has be done only in very special cases. In WSOM 2005, Jean-Claude Fort presented the state of the art, th...

Controlling Schottky energy barriers in organic electronic devices using self-assembled monolayers

Science.gov (United States)

Campbell, I. H.; Rubin, S.; Zawodzinski, T. A.; Kress, J. D.; Martin, R. L.; Smith, D. L.; Barashkov, N. N.; Ferraris, J. P.

1996-11-01

We demonstrate tuning of Schottky energy barriers in organic electronic devices by utilizing chemically tailored electrodes. The Schottky energy barrier of Ag on poly[2-methoxy, 5-(2'-ethyl-hexyloxy)- 1,4-phenylene was tuned over a range of more than 1 eV by using self-assembled monolayers (SAM's) to attach oriented dipole layers to the Ag prior to device fabrication. Kelvin probe measurements were used to determine the effect of the SAM's on the Ag surface potential. Ab initio Hartree-Fock calculations of the molecular dipole moments successfully describe the surface potential changes. The chemically tailored electrodes were then incorporated in organic diode structures and changes in the metal/organic Schottky energy barriers were measured using an electroabsorption technique. These results demonstrate the use of self-assembled monolayers to control metal/organic interfacial electronic properties. They establish a physical principle for manipulating the relative energy levels between two materials and demonstrate an approach to improve metal/organic contacts in organic electronic devices.

Asymmetric neighborhood functions accelerate ordering process of self-organizing maps

International Nuclear Information System (INIS)

Ota, Kaiichiro; Aoki, Takaaki; Kurata, Koji; Aoyagi, Toshio

2011-01-01

A self-organizing map (SOM) algorithm can generate a topographic map from a high-dimensional stimulus space to a low-dimensional array of units. Because a topographic map preserves neighborhood relationships between the stimuli, the SOM can be applied to certain types of information processing such as data visualization. During the learning process, however, topological defects frequently emerge in the map. The presence of defects tends to drastically slow down the formation of a globally ordered topographic map. To remove such topological defects, it has been reported that an asymmetric neighborhood function is effective, but only in the simple case of mapping one-dimensional stimuli to a chain of units. In this paper, we demonstrate that even when high-dimensional stimuli are used, the asymmetric neighborhood function is effective for both artificial and real-world data. Our results suggest that applying the asymmetric neighborhood function to the SOM algorithm improves the reliability of the algorithm. In addition, it enables processing of complicated, high-dimensional data by using this algorithm.

Self-Organizing Maps Neural Networks Applied to the Classification of Ethanol Samples According to the Region of Commercialization

Directory of Open Access Journals (Sweden)

Aline Regina Walkoff

2017-10-01

Full Text Available Physical-chemical analysis data were collected, from 998 ethanol samples of automotive ethanol commercialized in the northern, midwestern and eastern regions of the state of Paraná. The data presented self-organizing maps (SOM neural networks, which classified them according to those regions. The self-organizing maps best configuration had a 45 x 45 topology and 5000 training epochs, with a final learning rate of 6.7x10-4, a final neighborhood relationship of 3x10-2 and a mean quantization error of 2x10-2. This neural network provided a topological map depicting three separated groups, each one corresponding to samples of a same region of commercialization. Four maps of weights, one for each parameter, were presented. The network established the pH was the most important variable for classification and electrical conductivity the least one. The self-organizing maps application allowed the segmentation of alcohol samples, therefore identifying them according to the region of commercialization. DOI: http://dx.doi.org/10.17807/orbital.v9i4.982

Controlling Schottky energy barriers in organic electronic devices using self-assembled monolayers

Energy Technology Data Exchange (ETDEWEB)

Campbell, I.H.; Rubin, S.; Zawodzinski, T.A.; Kress, J.D.; Martin, R.L.; Smith, D.L. [Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Barashkov, N.N.; Ferraris, J.P. [The University of Texas at Dallas, Richardson, Texas 75083 (United States)

1996-11-01

We demonstrate tuning of Schottky energy barriers in organic electronic devices by utilizing chemically tailored electrodes. The Schottky energy barrier of Ag on poly[2-methoxy], 5-(2{prime}-ethyl-hexyloxy)- 1,4-phenylene was tuned over a range of more than 1 eV by using self-assembled monolayers (SAM{close_quote}s) to attach oriented dipole layers to the Ag prior to device fabrication. Kelvin probe measurements were used to determine the effect of the SAM{close_quote}s on the Ag surface potential. {ital Ab} {ital initio} Hartree-Fock calculations of the molecular dipole moments successfully describe the surface potential changes. The chemically tailored electrodes were then incorporated in organic diode structures and changes in the metal/organic Schottky energy barriers were measured using an electroabsorption technique. These results demonstrate the use of self-assembled monolayers to control metal/organic interfacial electronic properties. They establish a physical principle for manipulating the relative energy levels between two materials and demonstrate an approach to improve metal/organic contacts in organic electronic devices. {copyright} {ital 1996 The American Physical Society.}

Controlling Schottky energy barriers in organic electronic devices using self-assembled monolayers

International Nuclear Information System (INIS)

Campbell, I.H.; Rubin, S.; Zawodzinski, T.A.; Kress, J.D.; Martin, R.L.; Smith, D.L.; Barashkov, N.N.; Ferraris, J.P.

1996-01-01

We demonstrate tuning of Schottky energy barriers in organic electronic devices by utilizing chemically tailored electrodes. The Schottky energy barrier of Ag on poly[2-methoxy], 5-(2'-ethyl-hexyloxy)- 1,4-phenylene was tuned over a range of more than 1 eV by using self-assembled monolayers (SAM close-quote s) to attach oriented dipole layers to the Ag prior to device fabrication. Kelvin probe measurements were used to determine the effect of the SAM close-quote s on the Ag surface potential. Ab initio Hartree-Fock calculations of the molecular dipole moments successfully describe the surface potential changes. The chemically tailored electrodes were then incorporated in organic diode structures and changes in the metal/organic Schottky energy barriers were measured using an electroabsorption technique. These results demonstrate the use of self-assembled monolayers to control metal/organic interfacial electronic properties. They establish a physical principle for manipulating the relative energy levels between two materials and demonstrate an approach to improve metal/organic contacts in organic electronic devices. copyright 1996 The American Physical Society

Authoring Tool for Identifying Learning Styles, Using Self-Organizing Maps on Mobile Devices

Directory of Open Access Journals (Sweden)

Ramón Zatarain Cabada

2011-05-01

Full Text Available This work explores a methodological proposal whose main objective is the identification of learning styles using a method of self-organizing maps designed to work, for the most part, on mobile devices. These maps can work in real time and without direct student interaction, which implies the absence of prior information. The results generated are an authoring tool for adaptive courses in Web 2.0 environments.

The morphological classification of normal and abnormal red blood cell using Self Organizing Map

Science.gov (United States)

Rahmat, R. F.; Wulandari, F. S.; Faza, S.; Muchtar, M. A.; Siregar, I.

2018-02-01

Blood is an essential component of living creatures in the vascular space. For possible disease identification, it can be tested through a blood test, one of which can be seen from the form of red blood cells. The normal and abnormal morphology of the red blood cells of a patient is very helpful to doctors in detecting a disease. With the advancement of digital image processing technology can be used to identify normal and abnormal blood cells of a patient. This research used self-organizing map method to classify the normal and abnormal form of red blood cells in the digital image. The use of self-organizing map neural network method can be implemented to classify the normal and abnormal form of red blood cells in the input image with 93,78% accuracy testing.

QUALITATIVE ANALYSIS OF OFFICIAL MILK CONTROL IN VALENCIA COMMUNITY (SPAIN BY SELF ORGANIZING MAPS

Directory of Open Access Journals (Sweden)

Carlos Javier Fernandez

2009-06-01

Full Text Available Breeding programs in dairy goats are mainly based on milk production and composition. Murciano-Granadina goats are located principally in the central and southern regions of Spain. This study is focused in Valencia Community (Spain and the objective is to study the Murciano-Granadina livestock based on the database from Murciano-Granadina Goat Breeders Association of Valencia (AMURVAL.  The aim of this study is to analyze the relationship among different variables related with milk production; milk yield, fat, protein, lactose, SCC, the number of births, lactation number and season. This analysis is carried out by using the Self Organizing Map. This tool allows mapping high-dimensional input spaces into much lower-dimensional spaces, thus making much more straightforward to understand any representation of data. These representations enable to visually extract qualitative relationships among variables (Visual Data Mining. A total of 3221 Murciano-Granadina dairy goats from AMURVAL were chosen. Self Organizing Maps (SOM were used to analyze data with the system identification toolbox of MATLAB v7. Data were obtained from Official Milk Control during 2006 campaign. SOM considered in this study is formed by 21´14 neurons (294 neurons; the chosen architecture is given by the range of the input variables used. The map shown that more than 70% of the goats has milk yield greater than 300 kg per lactation and goat, indicating good performance of farms. Besides, the SOM obtained indicate a group of neurons that included goats with high SSC (2%. The use of Self Organizing Maps in the descriptive analysis of this kind of data sets has proven to be highly valuable in extracting qualitative conclusions and guiding in improving the performance of farms.

Self-organizing maps based on limit cycle attractors.

Science.gov (United States)

Huang, Di-Wei; Gentili, Rodolphe J; Reggia, James A

2015-03-01

Recent efforts to develop large-scale brain and neurocognitive architectures have paid relatively little attention to the use of self-organizing maps (SOMs). Part of the reason for this is that most conventional SOMs use a static encoding representation: each input pattern or sequence is effectively represented as a fixed point activation pattern in the map layer, something that is inconsistent with the rhythmic oscillatory activity observed in the brain. Here we develop and study an alternative encoding scheme that instead uses sparsely-coded limit cycles to represent external input patterns/sequences. We establish conditions under which learned limit cycle representations arise reliably and dominate the dynamics in a SOM. These limit cycles tend to be relatively unique for different inputs, robust to perturbations, and fairly insensitive to timing. In spite of the continually changing activity in the map layer when a limit cycle representation is used, map formation continues to occur reliably. In a two-SOM architecture where each SOM represents a different sensory modality, we also show that after learning, limit cycles in one SOM can correctly evoke corresponding limit cycles in the other, and thus there is the potential for multi-SOM systems using limit cycles to work effectively as hetero-associative memories. While the results presented here are only first steps, they establish the viability of SOM models based on limit cycle activity patterns, and suggest that such models merit further study. Copyright © 2014 Elsevier Ltd. All rights reserved.

Controlling charge injection in organic electronic devices using self-assembled monolayers

Science.gov (United States)

Campbell, I. H.; Kress, J. D.; Martin, R. L.; Smith, D. L.; Barashkov, N. N.; Ferraris, J. P.

1997-12-01

We demonstrate control and improvement of charge injection in organic electronic devices by utilizing self-assembled monolayers (SAMs) to manipulate the Schottky energy barrier between a metal electrode and the organic electronic material. Hole injection from Cu electrodes into the electroluminescent conjugated polymer poly[2-methoxy,5-(2'-ethyl-hexyloxy)-1,4-phenylene vinylene] was varied by using two conjugated-thiol based SAMs. The chemically modified electrodes were incorporated in organic diode structures and changes in the metal/polymer Schottky energy barriers and current-voltage characteristics were measured. Decreasing (increasing) the Schottky energy barrier improves (degrades) charge injection into the polymer.

Image Fusion Based on the Self-Organizing Feature Map Neural Networks

Institute of Scientific and Technical Information of China (English)

ZHANG Zhaoli; SUN Shenghe

2001-01-01

This paper presents a new image datafusion scheme based on the self-organizing featuremap (SOFM) neural networks.The scheme consists ofthree steps:(1) pre-processing of the images,whereweighted median filtering removes part of the noisecomponents corrupting the image,(2) pixel clusteringfor each image using two-dimensional self-organizingfeature map neural networks,and (3) fusion of the im-ages obtained in Step (2) utilizing fuzzy logic,whichsuppresses the residual noise components and thusfurther improves the image quality.It proves thatsuch a three-step combination offers an impressive ef-fectiveness and performance improvement,which isconfirmed by simulations involving three image sen-sors (each of which has a different noise structure).

Visualizing the topical structure of the medical sciences: a self-organizing map approach.

Directory of Open Access Journals (Sweden)

André Skupin

Full Text Available We implement a high-resolution visualization of the medical knowledge domain using the self-organizing map (SOM method, based on a corpus of over two million publications. While self-organizing maps have been used for document visualization for some time, (1 little is known about how to deal with truly large document collections in conjunction with a large number of SOM neurons, (2 post-training geometric and semiotic transformations of the SOM tend to be limited, and (3 no user studies have been conducted with domain experts to validate the utility and readability of the resulting visualizations. Our study makes key contributions to all of these issues.Documents extracted from Medline and Scopus are analyzed on the basis of indexer-assigned MeSH terms. Initial dimensionality is reduced to include only the top 10% most frequent terms and the resulting document vectors are then used to train a large SOM consisting of over 75,000 neurons. The resulting two-dimensional model of the high-dimensional input space is then transformed into a large-format map by using geographic information system (GIS techniques and cartographic design principles. This map is then annotated and evaluated by ten experts stemming from the biomedical and other domains.Study results demonstrate that it is possible to transform a very large document corpus into a map that is visually engaging and conceptually stimulating to subject experts from both inside and outside of the particular knowledge domain. The challenges of dealing with a truly large corpus come to the fore and require embracing parallelization and use of supercomputing resources to solve otherwise intractable computational tasks. Among the envisaged future efforts are the creation of a highly interactive interface and the elaboration of the notion of this map of medicine acting as a base map, onto which other knowledge artifacts could be overlaid.

Controlling charge injection in organic electronic devices using self-assembled monolayers

Energy Technology Data Exchange (ETDEWEB)

Campbell, I.H.; Kress, J.D.; Martin, R.L.; Smith, D.L. [Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Barashkov, N.N.; Ferraris, J.P. [The University of Texas at Dallas, Richardson, Texas 75083 (United States)

1997-12-01

We demonstrate control and improvement of charge injection in organic electronic devices by utilizing self-assembled monolayers (SAMs) to manipulate the Schottky energy barrier between a metal electrode and the organic electronic material. Hole injection from Cu electrodes into the electroluminescent conjugated polymer poly[2-methoxy,5-(2{sup {prime}}-ethyl-hexyloxy)-1,4-phenylene vinylene] was varied by using two conjugated-thiol based SAMs. The chemically modified electrodes were incorporated in organic diode structures and changes in the metal/polymer Schottky energy barriers and current{endash}voltage characteristics were measured. Decreasing (increasing) the Schottky energy barrier improves (degrades) charge injection into the polymer. {copyright} {ital 1997 American Institute of Physics.}

New Angle on the Parton Distribution Functions: Self-Organizing Maps

International Nuclear Information System (INIS)

Honkanen, H.; Liuti, S.

2009-01-01

Neural network (NN) algorithms have been recently applied to construct Parton Distribution Function (PDF) parametrizations, providing an alternative to standard global fitting procedures. Here we explore a novel technique using Self-Organizing Maps (SOMs). SOMs are a class of clustering algorithms based on competitive learning among spatially-ordered neurons. We train our SOMs with stochastically generated PDF samples. On every optimization iteration the PDFs are clustered on the SOM according to a user-defined feature and the most promising candidates are used as a seed for the subsequent iteration using the topology of the map to guide the PDF generating process. Our goal is a fitting procedure that, at variance with the standard neural network approaches, will allow for an increased control of the systematic bias by enabling user interaction in the various stages of the process.

Self-Organizing Maps for Fingerprint Image Quality Assessment

DEFF Research Database (Denmark)

Olsen, Martin Aastrup; Tabassi, Elham; Makarov, Anton

2013-01-01

Fingerprint quality assessment is a crucial task which needs to be conducted accurately in various phases in the biometric enrolment and recognition processes. Neglecting quality measurement will adversely impact accuracy and efficiency of biometric recognition systems (e.g. verification and iden......Fingerprint quality assessment is a crucial task which needs to be conducted accurately in various phases in the biometric enrolment and recognition processes. Neglecting quality measurement will adversely impact accuracy and efficiency of biometric recognition systems (e.g. verification...... machine learning techniques. We train a self-organizing map (SOM) to cluster blocks of fingerprint images based on their spatial information content. The output of the SOM is a high-level representation of the finger image, which forms the input to a Random Forest trained to learn the relationship between...

Electronic self-organization in layered transition metal dichalcogenides

Energy Technology Data Exchange (ETDEWEB)

Ritschel, Tobias

2015-10-30

The interplay between different self-organized electronically ordered states and their relation to unconventional electronic properties like superconductivity constitutes one of the most exciting challenges of modern condensed matter physics. In the present thesis this issue is thoroughly investigated for the prototypical layered material 1T-TaS{sub 2} both experimentally and theoretically. At first the static charge density wave order in 1T-TaS{sub 2} is investigated as a function of pressure and temperature by means of X-ray diffraction. These data indeed reveal that the superconductivity in this material coexists with an inhomogeneous charge density wave on a macroscopic scale in real space. This result is fundamentally different from a previously proposed separation of superconducting and insulating regions in real space. Furthermore, the X-ray diffraction data uncover the important role of interlayer correlations in 1T-TaS{sub 2}. Based on the detailed insights into the charge density wave structure obtained by the X-ray diffraction experiments, density functional theory models are deduced in order to describe the electronic structure of 1T-TaS{sub 2} in the second part of this thesis. As opposed to most previous studies, these calculations take the three-dimensional character of the charge density wave into account. Indeed the electronic structure calculations uncover complex orbital textures, which are interwoven with the charge density wave order and cause dramatic differences in the electronic structure depending on the alignment of the orbitals between neighboring layers. Furthermore, it is demonstrated that these orbital-mediated effects provide a route to drive semiconductor-to-metal transitions with technologically pertinent gaps and on ultrafast timescales. These results are particularly relevant for the ongoing development of novel, miniaturized and ultrafast devices based on layered transition metal dichalcogenides. The discovery of orbital textures

Self-organizing maps for measuring similarity of audiovisual speech percepts

DEFF Research Database (Denmark)

Bothe, Hans-Heinrich

The goal of this work is to find a way to measure similarity of audiovisual speech percepts. Phoneme-related self-organizing maps (SOM) with a rectangular basis are trained with data material from a (labeled) video film. For the training, a combination of auditory speech features and corresponding....... Dependent on the training data, these other units may also be contextually immediate neighboring units. The poster demonstrates the idea with text material spoken by one individual subject using a set of simple audio-visual features. The data material for the training process consists of 44 labeled...... sentences in German with a balanced phoneme repertoire. As a result it can be stated that (i) the SOM can be trained to map auditory and visual features in a topology-preserving way and (ii) they show strain due to the influence of other audio-visual units. The SOM can be used to measure similarity amongst...

Improving Charge Injection in Organic Electronic Devices Using Self-Assembled Monolayers

Science.gov (United States)

Campbell, I. H.; Kress, J. D.; Martin, R. L.; Smith, D. L.; Barashkov, N. N.; Ferraris, J. P.

1997-03-01

Organic electronic devices consist of one or more insulating organic layers contacted by metallic conductors. The Schottky energy barrier between the metal and the organic material is determined by the work function of the metal contact as described in the ideal Schottky model. The magnitude of the metal/organic Schottky energy barrier controls charge injection from the metal into the organic layer. Previously, polar alkane-thiol based self-assembled monolayers (SAMs) were used to change the Schottky energy barrier between the metal and an organic film by more than 1 eV. In these SAMs, the large energy gap of the alkane molecules blocks charge injection into the organic layer despite the decrease of the Schottky energy barrier. Here, we demonstrate improved charge injection into the organic material by using conjugated self-assembled monolayers. The conjugated SAMs have modest energy gaps which allow improved charge injection into the organic layer. We present measurements of current-voltage characteristics and metal/organic Schottky energy barriers for device structures both with and without conjugated SAMs.

Intelligent Machine Vision for Automated Fence Intruder Detection Using Self-organizing Map

OpenAIRE

Veldin A. Talorete Jr.; Sherwin A Guirnaldo

2017-01-01

This paper presents an intelligent machine vision for automated fence intruder detection. A series of still captured images that contain fence events using Internet Protocol cameras was used as input data to the system. Two classifiers were used; the first is to classify human posture and the second one will classify intruder location. The system classifiers were implemented using Self-Organizing Map after the implementation of several image segmentation processes. The human posture classifie...

Growing hierarchical probabilistic self-organizing graphs.

Science.gov (United States)

López-Rubio, Ezequiel; Palomo, Esteban José

2011-07-01

Since the introduction of the growing hierarchical self-organizing map, much work has been done on self-organizing neural models with a dynamic structure. These models allow adjusting the layers of the model to the features of the input dataset. Here we propose a new self-organizing model which is based on a probabilistic mixture of multivariate Gaussian components. The learning rule is derived from the stochastic approximation framework, and a probabilistic criterion is used to control the growth of the model. Moreover, the model is able to adapt to the topology of each layer, so that a hierarchy of dynamic graphs is built. This overcomes the limitations of the self-organizing maps with a fixed topology, and gives rise to a faithful visualization method for high-dimensional data.

Large-Scale Mapping of Carbon Stocks in Riparian Forests with Self-Organizing Maps and the k-Nearest-Neighbor Algorithm

Directory of Open Access Journals (Sweden)

Leonhard Suchenwirth

2014-07-01

Full Text Available Among the machine learning tools being used in recent years for environmental applications such as forestry, self-organizing maps (SOM and the k-nearest neighbor (kNN algorithm have been used successfully. We applied both methods for the mapping of organic carbon (Corg in riparian forests due to their considerably high carbon storage capacity. Despite the importance of floodplains for carbon sequestration, a sufficient scientific foundation for creating large-scale maps showing the spatial Corg distribution is still missing. We estimated organic carbon in a test site in the Danube Floodplain based on RapidEye remote sensing data and additional geodata. Accordingly, carbon distribution maps of vegetation, soil, and total Corg stocks were derived. Results were compared and statistically evaluated with terrestrial survey data for outcomes with pure remote sensing data and for the combination with additional geodata using bias and the Root Mean Square Error (RMSE. Results show that SOM and kNN approaches enable us to reproduce spatial patterns of riparian forest Corg stocks. While vegetation Corg has very high RMSEs, outcomes for soil and total Corg stocks are less biased with a lower RMSE, especially when remote sensing and additional geodata are conjointly applied. SOMs show similar percentages of RMSE to kNN estimations.

Autonomous Data Collection Using a Self-Organizing Map.

Science.gov (United States)

Faigl, Jan; Hollinger, Geoffrey A

2018-05-01

The self-organizing map (SOM) is an unsupervised learning technique providing a transformation of a high-dimensional input space into a lower dimensional output space. In this paper, we utilize the SOM for the traveling salesman problem (TSP) to develop a solution to autonomous data collection. Autonomous data collection requires gathering data from predeployed sensors by moving within a limited communication radius. We propose a new growing SOM that adapts the number of neurons during learning, which also allows our approach to apply in cases where some sensors can be ignored due to a lower priority. Based on a comparison with available combinatorial heuristic algorithms for relevant variants of the TSP, the proposed approach demonstrates improved results, while also being less computationally demanding. Moreover, the proposed learning procedure can be extended to cases where particular sensors have varying communication radii, and it can also be extended to multivehicle planning.

Comparison of brass alloys composition by laser-induced breakdown spectroscopy and self-organizing maps

Energy Technology Data Exchange (ETDEWEB)

Pagnotta, Stefano; Grifoni, Emanuela; Legnaioli, Stefano [Applied and Laser Spectroscopy Laboratory, ICCOM-CNR, Research Area of Pisa, Via G. Moruzzi 1, 56124 Pisa (Italy); Lezzerini, Marco [Department of Earth Sciences, University of Pisa, Via S. Maria 53, 56126 Pisa (Italy); Lorenzetti, Giulia [Applied and Laser Spectroscopy Laboratory, ICCOM-CNR, Research Area of Pisa, Via G. Moruzzi 1, 56124 Pisa (Italy); Palleschi, Vincenzo, E-mail: vincenzo.palleschi@cnr.it [Applied and Laser Spectroscopy Laboratory, ICCOM-CNR, Research Area of Pisa, Via G. Moruzzi 1, 56124 Pisa (Italy); Department of Civilizations and Forms of Knowledge, University of Pisa, Via L. Galvani 1, 56126 Pisa (Italy)

2015-01-01

In this paper we face the problem of assessing similarities in the composition of different metallic alloys, using the laser-induced breakdown spectroscopy technique. The possibility of determining the degree of similarity through the use of artificial neural networks and self-organizing maps is discussed. As an example, we present a case study involving the comparison of two historical brass samples, very similar in their composition. The results of the paper can be extended to many other situations, not necessarily associated with cultural heritage and archeological studies, where objects with similar composition have to be compared. - Highlights: • A method for assessing the similarity of materials analyzed by LIBS is proposed. • Two very similar fragments of historical brass were analyzed. • Using a simple artificial neural network the composition of the two alloys was determined. • The composition of the two brass alloys was the same within the experimental error. • Using self-organizing maps, the probability of the alloys to have the same composition was assessed.

Comparison of brass alloys composition by laser-induced breakdown spectroscopy and self-organizing maps

International Nuclear Information System (INIS)

Pagnotta, Stefano; Grifoni, Emanuela; Legnaioli, Stefano; Lezzerini, Marco; Lorenzetti, Giulia; Palleschi, Vincenzo

2015-01-01

In this paper we face the problem of assessing similarities in the composition of different metallic alloys, using the laser-induced breakdown spectroscopy technique. The possibility of determining the degree of similarity through the use of artificial neural networks and self-organizing maps is discussed. As an example, we present a case study involving the comparison of two historical brass samples, very similar in their composition. The results of the paper can be extended to many other situations, not necessarily associated with cultural heritage and archeological studies, where objects with similar composition have to be compared. - Highlights: • A method for assessing the similarity of materials analyzed by LIBS is proposed. • Two very similar fragments of historical brass were analyzed. • Using a simple artificial neural network the composition of the two alloys was determined. • The composition of the two brass alloys was the same within the experimental error. • Using self-organizing maps, the probability of the alloys to have the same composition was assessed

Manifold Learning with Self-Organizing Mapping for Feature Extraction of Nonlinear Faults in Rotating Machinery

Directory of Open Access Journals (Sweden)

Lin Liang

2015-01-01

Full Text Available A new method for extracting the low-dimensional feature automatically with self-organization mapping manifold is proposed for the detection of rotating mechanical nonlinear faults (such as rubbing, pedestal looseness. Under the phase space reconstructed by single vibration signal, the self-organization mapping (SOM with expectation maximization iteration algorithm is used to divide the local neighborhoods adaptively without manual intervention. After that, the local tangent space alignment algorithm is adopted to compress the high-dimensional phase space into low-dimensional feature space. The proposed method takes advantages of the manifold learning in low-dimensional feature extraction and adaptive neighborhood construction of SOM and can extract intrinsic fault features of interest in two dimensional projection space. To evaluate the performance of the proposed method, the Lorenz system was simulated and rotation machinery with nonlinear faults was obtained for test purposes. Compared with the holospectrum approaches, the results reveal that the proposed method is superior in identifying faults and effective for rotating machinery condition monitoring.

An Algorithm Based on the Self-Organized Maps for the Classification of Facial Features

Directory of Open Access Journals (Sweden)

Gheorghe Gîlcă

2015-12-01

Full Text Available This paper deals with an algorithm based on Self Organized Maps networks which classifies facial features. The proposed algorithm can categorize the facial features defined by the input variables: eyebrow, mouth, eyelids into a map of their grouping. The groups map is based on calculating the distance between each input vector and each output neuron layer , the neuron with the minimum distance being declared winner neuron. The network structure consists of two levels: the first level contains three input vectors, each having forty-one values, while the second level contains the SOM competitive network which consists of 100 neurons. The proposed system can classify facial features quickly and easily using the proposed algorithm based on SOMs.

Clustering analysis of malware behavior using Self Organizing Map

DEFF Research Database (Denmark)

Pirscoveanu, Radu-Stefan; Stevanovic, Matija; Pedersen, Jens Myrup

2016-01-01

For the time being, malware behavioral classification is performed by means of Anti-Virus (AV) generated labels. The paper investigates the inconsistencies associated with current practices by evaluating the identified differences between current vendors. In this paper we rely on Self Organizing...... Map, an unsupervised machine learning algorithm, for generating clusters that capture the similarities between malware behavior. A data set of approximately 270,000 samples was used to generate the behavioral profile of malicious types in order to compare the outcome of the proposed clustering...... approach with the labels collected from 57 Antivirus vendors using VirusTotal. Upon evaluating the results, the paper concludes on shortcomings of relying on AV vendors for labeling malware samples. In order to solve the problem, a cluster-based classification is proposed, which should provide more...

Energy resolved electrochemical impedance spectroscopy for electronic structure mapping in organic semiconductors

Energy Technology Data Exchange (ETDEWEB)

Nádaždy, V., E-mail: nadazdy@savba.sk; Gmucová, K. [Institute of Physics SAS, Dúbravská cesta 9, 845 11 Bratislava (Slovakia); Schauer, F. [Faculty of Education, Trnava University in Trnava, 918 43 Trnava (Slovakia); Faculty of Applied Informatics, Tomas Bata University in Zlin, 760 05 Zlin (Czech Republic)

2014-10-06

We introduce an energy resolved electrochemical impedance spectroscopy method to map the electronic density of states (DOS) in organic semiconductor materials. The method consists in measurement of the charge transfer resistance of a semiconductor/electrolyte interface at a frequency where the redox reactions determine the real component of the impedance. The charge transfer resistance value provides direct information about the electronic DOS at the energy given by the electrochemical potential of the electrolyte, which can be adjusted using an external voltage. A simple theory for experimental data evaluation is proposed, along with an explanation of the corresponding experimental conditions. The method allows mapping over unprecedentedly wide energy and DOS ranges. Also, important DOS parameters can be determined directly from the raw experimental data without the lengthy analysis required in other techniques. The potential of the proposed method is illustrated by tracing weak bond defect states induced by ultraviolet treatment above the highest occupied molecular orbital in a prototypical σ-conjugated polymer, poly[methyl(phenyl)silylene]. The results agree well with those of our previous DOS reconstruction by post-transient space-charge-limited-current spectroscopy, which was, however, limited to a narrow energy range. In addition, good agreement of the DOS values measured on two common π-conjugated organic polymer semiconductors, polyphenylene vinylene and poly(3-hexylthiophene), with the rather rare previously published data demonstrate the accuracy of the proposed method.

Characterization of Suicidal Behaviour with Self-Organizing Maps

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José M. Leiva-Murillo

2013-01-01

Full Text Available The study of the variables involved in suicidal behavior is important from a social, medical, and economical point of view. Given the high number of potential variables of interest, a large population of subjects must be analysed in order to get conclusive results. In this paper, we describe a method based on self-organizing maps (SOMs for finding the most relevant variables even when their relation to suicidal behavior is strongly nonlinear. We have applied the method to a cohort with more than 8,000 subjects and 600 variables and discovered four groups of variables involved in suicidal behavior. According to the results, there are four main groups of risk factors that characterize the population of suicide attempters: mental disorders, alcoholism, impulsivity, and childhood abuse. The identification of specific subpopulations of suicide attempters is consistent with current medical knowledge and may provide a new avenue of research to improve the management of suicidal cases.

Curbing domestic violence: Instantiating C-K theory with formal concept analysis and emergent self-organizing maps

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Poelmans, J.; Elzinga, P.; Viaene, S.; Dedene, G.

2010-01-01

We propose a human-centred process for knowledge discovery from unstructured text that makes use of formal concept analysis and emergent self-organizing maps. The knowledge discovery process is conceptualized and interpreted as successive iterations through the concept-knowledge (C-K) theory design

Identification of lithofacies using Kohonen self-organizing maps

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Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.

2002-01-01

Lithofacies identification is a primary task in reservoir characterization. Traditional techniques of lithofacies identification from core data are costly, and it is difficult to extrapolate to non-cored wells. We present a low-cost automated technique using Kohonen self-organizing maps (SOMs) to identify systematically and objectively lithofacies from well log data. SOMs are unsupervised artificial neural networks that map the input space into clusters in a topological form whose organization is related to trends in the input data. A case study used five wells located in Appleton Field, Escambia County, Alabama (Smackover Formation, limestone and dolomite, Oxfordian, Jurassic). A five-input, one-dimensional output approach is employed, assuming the lithofacies are in ascending/descending order with respect to paleoenvironmental energy levels. To consider the possible appearance of new logfacies not seen in training mode, which may potentially appear in test wells, the maximum number of outputs is set to 20 instead of four, the designated number of lithosfacies in the study area. This study found eleven major clusters. The clusters were compared to depositional lithofacies identified by manual core examination. The clusters were ordered by the SOM in a pattern consistent with environmental gradients inferred from core examination: bind/boundstone, grainstone, packstone, and wackestone. This new approach predicted lithofacies identity from well log data with 78.8% accuracy which is more accurate than using a backpropagation neural network (57.3%). The clusters produced by the SOM are ordered with respect to paleoenvironmental energy levels. This energy-related clustering provides geologists and petroleum engineers with valuable geologic information about the logfacies and their interrelationships. This advantage is not obtained in backpropagation neural networks and adaptive resonance theory neural networks. ?? 2002 Elsevier Science Ltd. All rights reserved.

Self-Organizing Map Models of Language Acquisition

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Ping eLi

2013-11-01

Full Text Available Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic PDP architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development.

Self-enhancement learning: target-creating learning and its application to self-organizing maps.

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Kamimura, Ryotaro

2011-05-01

In this article, we propose a new learning method called "self-enhancement learning." In this method, targets for learning are not given from the outside, but they can be spontaneously created within a neural network. To realize the method, we consider a neural network with two different states, namely, an enhanced and a relaxed state. The enhanced state is one in which the network responds very selectively to input patterns, while in the relaxed state, the network responds almost equally to input patterns. The gap between the two states can be reduced by minimizing the Kullback-Leibler divergence between the two states with free energy. To demonstrate the effectiveness of this method, we applied self-enhancement learning to the self-organizing maps, or SOM, in which lateral interactions were added to an enhanced state. We applied the method to the well-known Iris, wine, housing and cancer machine learning database problems. In addition, we applied the method to real-life data, a student survey. Experimental results showed that the U-matrices obtained were similar to those produced by the conventional SOM. Class boundaries were made clearer in the housing and cancer data. For all the data, except for the cancer data, better performance could be obtained in terms of quantitative and topological errors. In addition, we could see that the trustworthiness and continuity, referring to the quality of neighborhood preservation, could be improved by the self-enhancement learning. Finally, we used modern dimensionality reduction methods and compared their results with those obtained by the self-enhancement learning. The results obtained by the self-enhancement were not superior to but comparable with those obtained by the modern dimensionality reduction methods.

Identifying changes in dissolved organic matter content and characteristics by fluorescence spectroscopy coupled with self-organizing map and classification and regression tree analysis during wastewater treatment.

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Yu, Huibin; Song, Yonghui; Liu, Ruixia; Pan, Hongwei; Xiang, Liancheng; Qian, Feng

2014-10-01

The stabilization of latent tracers of dissolved organic matter (DOM) of wastewater was analyzed by three-dimensional excitation-emission matrix (EEM) fluorescence spectroscopy coupled with self-organizing map and classification and regression tree analysis (CART) in wastewater treatment performance. DOM of water samples collected from primary sedimentation, anaerobic, anoxic, oxic and secondary sedimentation tanks in a large-scale wastewater treatment plant contained four fluorescence components: tryptophan-like (C1), tyrosine-like (C2), microbial humic-like (C3) and fulvic-like (C4) materials extracted by self-organizing map. These components showed good positive linear correlations with dissolved organic carbon of DOM. C1 and C2 were representative components in the wastewater, and they were removed to a higher extent than those of C3 and C4 in the treatment process. C2 was a latent parameter determined by CART to differentiate water samples of oxic and secondary sedimentation tanks from the successive treatment units, indirectly proving that most of tyrosine-like material was degraded by anaerobic microorganisms. C1 was an accurate parameter to comprehensively separate the samples of the five treatment units from each other, indirectly indicating that tryptophan-like material was decomposed by anaerobic and aerobic bacteria. EEM fluorescence spectroscopy in combination with self-organizing map and CART analysis can be a nondestructive effective method for characterizing structural component of DOM fractions and monitoring organic matter removal in wastewater treatment process. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nanopatched Graphene with Molecular Self-Assembly Toward Graphene-Organic Hybrid Soft Electronics.

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Kang, Boseok; Lee, Seong Kyu; Jung, Jaehyuck; Joe, Minwoong; Lee, Seon Baek; Kim, Jinsung; Lee, Changgu; Cho, Kilwon

2018-04-30

Increasing the mechanical durability of large-area polycrystalline single-atom-thick materials is a necessary step toward the development of practical and reliable soft electronics based on these materials. Here, it is shown that the surface assembly of organosilane by weak epitaxy forms nanometer-thick organic patches on a monolayer graphene surface and dramatically increases the material's resistance to harsh postprocessing environments, thereby increasing the number of ways in which graphene can be processed. The nanopatched graphene with the improved mechanical durability enables stable operation when used as transparent electrodes of wearable strain sensors. Also, the nanopatched graphene applied as an electrode modulates the molecular orientation of deposited organic semiconductor layers, and yields favorable nominal charge injection for organic transistors. These results demonstrate the potential for use of self-assembled organic nanopatches in graphene-based soft electronics. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self Organizing Maps to efficiently cluster and functionally interpret protein conformational ensembles

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Fabio Stella

2013-09-01

Full Text Available An approach that combines Self-Organizing maps, hierarchical clustering and network components is presented, aimed at comparing protein conformational ensembles obtained from multiple Molecular Dynamic simulations. As a first result the original ensembles can be summarized by using only the representative conformations of the clusters obtained. In addition the network components analysis allows to discover and interpret the dynamic behavior of the conformations won by each neuron. The results showed the ability of this approach to efficiently derive a functional interpretation of the protein dynamics described by the original conformational ensemble, highlighting its potential as a support for protein engineering.

Automatic lithofacies segmentation from well-logs data. A comparative study between the Self-Organizing Map (SOM) and Walsh transform

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Aliouane, Leila; Ouadfeul, Sid-Ali; Rabhi, Abdessalem; Rouina, Fouzi; Benaissa, Zahia; Boudella, Amar

2013-04-01

The main goal of this work is to realize a comparison between two lithofacies segmentation techniques of reservoir interval. The first one is based on the Kohonen's Self-Organizing Map neural network machine. The second technique is based on the Walsh transform decomposition. Application to real well-logs data of two boreholes located in the Algerian Sahara shows that the Self-organizing map is able to provide more lithological details that the obtained lithofacies model given by the Walsh decomposition. Keywords: Comparison, Lithofacies, SOM, Walsh References: 1)Aliouane, L., Ouadfeul, S., Boudella, A., 2011, Fractal analysis based on the continuous wavelet transform and lithofacies classification from well-logs data using the self-organizing map neural network, Arabian Journal of geosciences, doi: 10.1007/s12517-011-0459-4 2) Aliouane, L., Ouadfeul, S., Djarfour, N., Boudella, A., 2012, Petrophysical Parameters Estimation from Well-Logs Data Using Multilayer Perceptron and Radial Basis Function Neural Networks, Lecture Notes in Computer Science Volume 7667, 2012, pp 730-736, doi : 10.1007/978-3-642-34500-5_86 3)Ouadfeul, S. and Aliouane., L., 2011, Multifractal analysis revisited by the continuous wavelet transform applied in lithofacies segmentation from well-logs data, International journal of applied physics and mathematics, Vol01 N01. 4) Ouadfeul, S., Aliouane, L., 2012, Lithofacies Classification Using the Multilayer Perceptron and the Self-organizing Neural Networks, Lecture Notes in Computer Science Volume 7667, 2012, pp 737-744, doi : 10.1007/978-3-642-34500-5_87 5) Weisstein, Eric W. "Fast Walsh Transform." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/FastWalshTransform.html

Detecting domestic violence: Showcasing a knowledge browser based on formal concept analysis and emergent self organizing maps

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Elzinga, P.; Poelmans, J.; Viaene, S.; Dedene, G.; Cordeiro, J.; Filipe, J.

2009-01-01

Over 90% of the case data from police inquiries is stored as unstructured text in police databases. We use the combination of Formal Concept Analysis and Emergent Self Organizing Maps for exploring a dataset of unstructured police reports out of the Amsterdam-Amstelland police region in the

Mobile Anomaly Detection Based on Improved Self-Organizing Maps

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Chunyong Yin

2017-01-01

Full Text Available Anomaly detection has always been the focus of researchers and especially, the developments of mobile devices raise new challenges of anomaly detection. For example, mobile devices can keep connection with Internet and they are rarely turned off even at night. This means mobile devices can attack nodes or be attacked at night without being perceived by users and they have different characteristics from Internet behaviors. The introduction of data mining has made leaps forward in this field. Self-organizing maps, one of famous clustering algorithms, are affected by initial weight vectors and the clustering result is unstable. The optimal method of selecting initial clustering centers is transplanted from K-means to SOM. To evaluate the performance of improved SOM, we utilize diverse datasets and KDD Cup99 dataset to compare it with traditional one. The experimental results show that improved SOM can get higher accuracy rate for universal datasets. As for KDD Cup99 dataset, it achieves higher recall rate and precision rate.

Spot profile analysis and lifetime mapping in ultrafast electron diffraction: Lattice excitation of self-organized Ge nanostructures on Si(001

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T. Frigge

2015-05-01

Full Text Available Ultrafast high energy electron diffraction in reflection geometry is employed to study the structural dynamics of self-organized Germanium hut-, dome-, and relaxed clusters on Si(001 upon femtosecond laser excitation. Utilizing the difference in size and strain state the response of hut- and dome clusters can be distinguished by a transient spot profile analysis. Surface diffraction from {105}-type facets provide exclusive information on hut clusters. A pixel-by-pixel analysis of the dynamics of the entire diffraction pattern gives time constants of 40, 160, and 390 ps, which are assigned to the cooling time constants for hut-, dome-, and relaxed clusters.

Interpretation of fingerprint image quality features extracted by self-organizing maps

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Danov, Ivan; Olsen, Martin A.; Busch, Christoph

2014-05-01

Accurate prediction of fingerprint quality is of significant importance to any fingerprint-based biometric system. Ensuring high quality samples for both probe and reference can substantially improve the system's performance by lowering false non-matches, thus allowing finer adjustment of the decision threshold of the biometric system. Furthermore, the increasing usage of biometrics in mobile contexts demands development of lightweight methods for operational environment. A novel two-tier computationally efficient approach was recently proposed based on modelling block-wise fingerprint image data using Self-Organizing Map (SOM) to extract specific ridge pattern features, which are then used as an input to a Random Forests (RF) classifier trained to predict the quality score of a propagated sample. This paper conducts an investigative comparative analysis on a publicly available dataset for the improvement of the two-tier approach by proposing additionally three feature interpretation methods, based respectively on SOM, Generative Topographic Mapping and RF. The analysis shows that two of the proposed methods produce promising results on the given dataset.

Self-organizing map models of language acquisition

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Li, Ping; Zhao, Xiaowei

2013-01-01

Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic parallel distributed processing architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper, we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development. We suggest future directions in which these models can be extended, to better connect with behavioral and neural data, and to make clear predictions in testing relevant psycholinguistic theories. PMID:24312061

Hierarchical Self Organizing Map for Novelty Detection using Mobile Robot with Robust Sensor

International Nuclear Information System (INIS)

Sha'abani, M N A H; Miskon, M F; Sakidin, H

2013-01-01

This paper presents a novelty detection method based on Self Organizing Map neural network using a mobile robot. Based on hierarchical neural network, the network is divided into three networks; position, orientation and sensor measurement network. A simulation was done to demonstrate and validate the proposed method using MobileSim. Three cases of abnormal events; new, missing and shifted objects are employed for performance evaluation. The result of detection was then filtered for false positive detection. The result shows that the inspection produced less than 2% false positive detection at high sensitivity settings

Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps

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Javier Blesa

2009-11-01

Full Text Available The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition (SCADA systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps, in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

Clustering Multiple Sclerosis Subgroups with Multifractal Methods and Self-Organizing Map Algorithm

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Karaca, Yeliz; Cattani, Carlo

Magnetic resonance imaging (MRI) is the most sensitive method to detect chronic nervous system diseases such as multiple sclerosis (MS). In this paper, Brownian motion Hölder regularity functions (polynomial, periodic (sine), exponential) for 2D image, such as multifractal methods were applied to MR brain images, aiming to easily identify distressed regions, in MS patients. With these regions, we have proposed an MS classification based on the multifractal method by using the Self-Organizing Map (SOM) algorithm. Thus, we obtained a cluster analysis by identifying pixels from distressed regions in MR images through multifractal methods and by diagnosing subgroups of MS patients through artificial neural networks.

Electronic structure of self-organized InAs/GaAs quantum dots bounded by {136} facets

International Nuclear Information System (INIS)

Yang, Weidong; Lee, Hao; Johnson, Thomas J.; Sercel, Peter C.; Norman, A. G.

2000-01-01

Recent experiments indicate that the shape of self-organized InAs quantum dots grown on GaAs [001] is an elongated pyramid with bounding facets corresponding to a family of four {136} planes. This structure, which possesses C 2v symmetry, is quite different from square-base pyramidal or lens geometries, which have been assumed in previous electronic structure calculations for this system. In this paper, we consider theoretically the influence of the {136} shape on the electronic structure and optical properties of the quantum dots. We present a valence force-field calculation of the inhomogeneous strain and incorporate the results into an eight band k(vector sign)·p(vector sign) electronic structure calculation. The size dependence of the electronic structure is calculated and compared to experimental photoluminescence spectra. The effects of perturbations on the {136} shape are also considered. Calculations based on the {136} shape give good agreement with the observed level structure and optical polarization properties of self-organized InAs/GaAs quantum dots. (c) 2000 The American Physical Society

Analysis of self-organized In(Ga)As quantum structures with the scanning transmission electron microscope

International Nuclear Information System (INIS)

Sauerwald, Andres

2008-01-01

Aim of this thesis was to apply the analytical methods of the scanning transmission electron microscopy to the study of self-organized In(Ga)As quantum structures. With the imaging methods Z contrast and bright field (position resolutions in the subnanometer range) and especially with the possibilities of the quantitative chemical EELS analysis of the scanning transmission electron microscope (STEM) fundamental questions concerning morphology and chemical properties of self-organized quantum structures should be answered. By the high position resolution of the STEM among others essentail morphological and structural parameters in the growth behaviour of ''dot in a well'' (DWell) structures and of vertically correlated quantum dots (QDs) could be analyzed. For the optimization of DWell structures samples were studied, the nominal InAs-QD growth position was directedly varied within the embedding InGaAs quantum wells. The STEM offers in connection with the EELS method a large potential for the chemical analysis of quantum structures. Studied was a sample series of self-organized InGaAs/GaAs structures on GaAs substrate, the stress of which was changed by varying the Ga content of the INGaAs material between 2.4 % and 4.3 % [de

Semi-automatic mapping of linear-trending bedforms using 'Self-Organizing Maps' algorithm

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Foroutan, M.; Zimbelman, J. R.

2017-09-01

Increased application of high resolution spatial data such as high resolution satellite or Unmanned Aerial Vehicle (UAV) images from Earth, as well as High Resolution Imaging Science Experiment (HiRISE) images from Mars, makes it necessary to increase automation techniques capable of extracting detailed geomorphologic elements from such large data sets. Model validation by repeated images in environmental management studies such as climate-related changes as well as increasing access to high-resolution satellite images underline the demand for detailed automatic image-processing techniques in remote sensing. This study presents a methodology based on an unsupervised Artificial Neural Network (ANN) algorithm, known as Self Organizing Maps (SOM), to achieve the semi-automatic extraction of linear features with small footprints on satellite images. SOM is based on competitive learning and is efficient for handling huge data sets. We applied the SOM algorithm to high resolution satellite images of Earth and Mars (Quickbird, Worldview and HiRISE) in order to facilitate and speed up image analysis along with the improvement of the accuracy of results. About 98% overall accuracy and 0.001 quantization error in the recognition of small linear-trending bedforms demonstrate a promising framework.

Business Client Segmentation in Banking Using Self-Organizing Maps

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Bach Mirjana Pejić

2014-11-01

Full Text Available Segmentation in banking for the business client market is traditionally based on size measured in terms of income and the number of employees, and on statistical clustering methods (e.g. hierarchical clustering, k-means. The goal of the paper is to demonstrate that self-organizing maps (SOM effectively extend the pool of possible criteria for segmentation of the business client market with more relevant criteria, including behavioral, demographic, personal, operational, situational, and cross-selling products. In order to attain the goal of the paper, the dataset on business clients of several banks in Croatia, which, besides size, incorporates a number of different criteria, is analyzed using the SOM-Ward clustering algorithm of Viscovery SOMine software. The SOM-Ward algorithm extracted three segments that differ with respect to the attributes of foreign trade operations (import/export, annual income, origin of capital, important bank selection criteria, views on the loan selection and the industry. The analyzed segments can be used by banks for deciding on the direction of further marketing activities.

Segmentation of color images by chromaticity features using self-organizing maps

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Farid García-Lamont

2016-05-01

Full Text Available Usually, the segmentation of color images is performed using cluster-based methods and the RGB space to represent the colors. The drawback with these methods is the a priori knowledge of the number of groups, or colors, in the image; besides, the RGB space issensitive to the intensity of the colors. Humans can identify different sections within a scene by the chromaticity of its colors of, as this is the feature humans employ to tell them apart. In this paper, we propose to emulate the human perception of color by training a self-organizing map (SOM with samples of chromaticity of different colors. The image to process is mapped to the HSV space because in this space the chromaticity is decoupled from the intensity, while in the RGB space this is not possible. Our proposal does not require knowing a priori the number of colors within a scene, and non-uniform illumination does not significantly affect the image segmentation. We present experimental results using some images from the Berkeley segmentation database by employing SOMs with different sizes, which are segmented successfully using only chromaticity features.

Distributed Fast Self-Organized Maps for Massive Spectrophotometric Data Analysis †.

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Dafonte, Carlos; Garabato, Daniel; Álvarez, Marco A; Manteiga, Minia

2018-05-03

Analyzing huge amounts of data becomes essential in the era of Big Data, where databases are populated with hundreds of Gigabytes that must be processed to extract knowledge. Hence, classical algorithms must be adapted towards distributed computing methodologies that leverage the underlying computational power of these platforms. Here, a parallel, scalable, and optimized design for self-organized maps (SOM) is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA) Gaia spacecraft, although it could be extrapolated to other domains. The performance comparison between the sequential implementation and the distributed ones based on Apache Hadoop and Apache Spark is an important part of the work, as well as the detailed analysis of the proposed optimizations. Finally, a domain-specific visualization tool to explore astronomical SOMs is presented.

Self-organizing representations

Energy Technology Data Exchange (ETDEWEB)

Kohonen, T.

1983-01-01

A property which is commonplace in the brain but which has always been ignored in learning machines is the spatial order of the processing units. This order is clearly highly significant and in nature it develops gradually during the lifetime of the organism. It then serves as the basis for perceptual and cognitive processes, and memory, too. The spatial order in biological organisms is often believed to be genetically determined. It is therefore intriguing to learn that a meaningful and optimal spatial order is formed in an extremely simple self-organizing process whereby certain feature maps are formed automatically. 8 references.

Invertebrate diversity classification using self-organizing map neural network: with some special topological functions

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WenJun Zhang

2014-06-01

Full Text Available In present study we used self-organizing map (SOM neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.

Functional grouping and establishment of distribution patterns of invasive plants in China using self-organizing maps and indicator species analysis

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Wang Zi-Bo

2009-01-01

Full Text Available In the present study, we introduce two techniques - self-organizing maps (SOM and indicator species analysis (INDVAL - for understanding the richness patterns of invasive species. We first employed SOM to identify functional groups and then used INDVAL to identify the representative areas characterizing these functional groups. Quantitative traits and distributional information on 127 invasive plants in 28 provinces of China were collected to form the matrices for our study. The results indicate Jiangsu to be the top province with the highest number of invasive species, while Ningxia was the lowest. Six functional groups were identified by the SOM method, and five of them were found to have significantly representative provinces by the INDVAL method. Our study represents the first attempt to combine self-organizing maps and indicator species analysis to assess the macro-scale distribution of exotic species.

Artificial neural network with self-organizing mapping for reactor stability monitoring

International Nuclear Information System (INIS)

Okumura, Motofumi; Tsuji, Masashi; Shimazu, Yoichiro; Narabayashi, Tadashi

2008-01-01

In BWR stability monitoring damping ratio has been used as a stability index. A method for estimating the damping ratio by applying Principal Component Analysis (PCA) to neutron detector signals measured with local power range monitors (LPRMs) had been developed; In this method, measured fluctuating signal is decomposed into some independent components and the signal component directly related to stability is extracted among them to determine the damping ratio. For online monitoring, it is necessary to select stability related signal component efficiently. The self-organizing map (SOM) is one of the artificial neural networks and has the characteristics such that online learning is possible without supervised learning within a relatively short time. In the present study, the SOM was applied to extract the relevant signal component more quickly and more accurately, and the availability was confirmed through the feasibility study. (author)

FPGA implementation of self organizing map with digital phase locked loops.

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Hikawa, Hiroomi

2005-01-01

The self-organizing map (SOM) has found applicability in a wide range of application areas. Recently new SOM hardware with phase modulated pulse signal and digital phase-locked loops (DPLLs) has been proposed (Hikawa, 2005). The system uses the DPLL as a computing element since the operation of the DPLL is very similar to that of SOM's computation. The system also uses square waveform phase to hold the value of the each input vector element. This paper discuss the hardware implementation of the DPLL SOM architecture. For effective hardware implementation, some components are redesigned to reduce the circuit size. The proposed SOM architecture is described in VHDL and implemented on field programmable gate array (FPGA). Its feasibility is verified by experiments. Results show that the proposed SOM implemented on the FPGA has a good quantization capability, and its circuit size very small.

Distributed Fast Self-Organized Maps for Massive Spectrophotometric Data Analysis †

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Carlos Dafonte

2018-05-01

Full Text Available Analyzing huge amounts of data becomes essential in the era of Big Data, where databases are populated with hundreds of Gigabytes that must be processed to extract knowledge. Hence, classical algorithms must be adapted towards distributed computing methodologies that leverage the underlying computational power of these platforms. Here, a parallel, scalable, and optimized design for self-organized maps (SOM is proposed in order to analyze massive data gathered by the spectrophotometric sensor of the European Space Agency (ESA Gaia spacecraft, although it could be extrapolated to other domains. The performance comparison between the sequential implementation and the distributed ones based on Apache Hadoop and Apache Spark is an important part of the work, as well as the detailed analysis of the proposed optimizations. Finally, a domain-specific visualization tool to explore astronomical SOMs is presented.

Expression cartography of human tissues using self organizing maps

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Löffler Markus

2011-07-01

Full Text Available Abstract Background Parallel high-throughput microarray and sequencing experiments produce vast quantities of multidimensional data which must be arranged and analyzed in a concerted way. One approach to addressing this challenge is the machine learning technique known as self organizing maps (SOMs. SOMs enable a parallel sample- and gene-centered view of genomic data combined with strong visualization and second-level analysis capabilities. The paper aims at bridging the gap between the potency of SOM-machine learning to reduce dimension of high-dimensional data on one hand and practical applications with special emphasis on gene expression analysis on the other hand. Results The method was applied to generate a SOM characterizing the whole genome expression profiles of 67 healthy human tissues selected from ten tissue categories (adipose, endocrine, homeostasis, digestion, exocrine, epithelium, sexual reproduction, muscle, immune system and nervous tissues. SOM mapping reduces the dimension of expression data from ten of thousands of genes to a few thousand metagenes, each representing a minicluster of co-regulated single genes. Tissue-specific and common properties shared between groups of tissues emerge as a handful of localized spots in the tissue maps collecting groups of co-regulated and co-expressed metagenes. The functional context of the spots was discovered using overrepresentation analysis with respect to pre-defined gene sets of known functional impact. We found that tissue related spots typically contain enriched populations of genes related to specific molecular processes in the respective tissue. Analysis techniques normally used at the gene-level such as two-way hierarchical clustering are better represented and provide better signal-to-noise ratios if applied to the metagenes. Metagene-based clustering analyses aggregate the tissues broadly into three clusters containing nervous, immune system and the remaining tissues

Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

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Piastra, Marco

2013-05-01

Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mapping the Indonesian territory, based on pollution, social demography and geographical data, using self organizing feature map

Science.gov (United States)

Hernawati, Kuswari; Insani, Nur; Bambang S. H., M.; Nur Hadi, W.; Sahid

2017-08-01

This research aims to mapping the 33 (thirty-three) provinces in Indonesia, based on the data on air, water and soil pollution, as well as social demography and geography data, into a clustered model. The method used in this study was unsupervised method that combines the basic concept of Kohonen or Self-Organizing Feature Maps (SOFM). The method is done by providing the design parameters for the model based on data related directly/ indirectly to pollution, which are the demographic and social data, pollution levels of air, water and soil, as well as the geographical situation of each province. The parameters used consists of 19 features/characteristics, including the human development index, the number of vehicles, the availability of the plant's water absorption and flood prevention, as well as geographic and demographic situation. The data used were secondary data from the Central Statistics Agency (BPS), Indonesia. The data are mapped into SOFM from a high-dimensional vector space into two-dimensional vector space according to the closeness of location in term of Euclidean distance. The resulting outputs are represented in clustered grouping. Thirty-three provinces are grouped into five clusters, where each cluster has different features/characteristics and level of pollution. The result can used to help the efforts on prevention and resolution of pollution problems on each cluster in an effective and efficient way.

Surface stress and large-scale self-organization at organic-metal interfaces

Energy Technology Data Exchange (ETDEWEB)

Pollinger, Florian

2009-01-22

The role of elastic interactions, particularly for the self-organized formation of periodically faceted interfaces, was investigated in this thesis for archetype organic-metal interfaces. The cantilever bending technique was applied to study the change of surface stress upon formation of the interface between 3,4,9,10-perylene-tetracarboxylic-dianhydride (PTCDA) and Ag(111). The main focus of this work was on the investigation of the formation of the long-range ordered, self-organized faceted PTCDA/Ag(10 8 7) interface. Reciprocal space maps of this interface were recorded both by spot profile analysis low energy electron diffraction (SPA-LEED) and low energy electron microscopy (LEEM) in selected area LEED mode. Complementary to the reciprocal data, also microscopic real-space LEEM data were used to characterize the morphology of this interface. Six different facet faces ((111), (532), (743), (954), (13 9 5), and (542)) were observed for the preparation path of molecular adsorption on the substrate kept at 550 K. Facet-sensitive dark-field LEEM localized these facets to grow in homogeneous areas of microscopic extensions. The temperature-dependence of the interface formation was studied in a range between 418 K and 612 K in order to learn more about the kinetics of the process. Additional steeper facets of 27 inclination with respect to the (111) surface were observed in the low temperature regime. Furthermore, using facet-sensitive dark-field LEEM, spatial and size distributions of specific facets were studied for the different temperatures. Moreover, the facet dimensions were statistically analyzed. The total island size of the facets follows an exponential distribution, indicating a random growth mode in absence of any mutual facet interactions. While the length distribution of the facets also follows an exponential distribution, the width distribution is peaked, reflecting the high degree of lateral order. This anisotropy is temperature-dependent and occurs

Personal sleep pattern visualization using sequence-based kernel self-organizing map on sound data.

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Wu, Hongle; Kato, Takafumi; Yamada, Tomomi; Numao, Masayuki; Fukui, Ken-Ichi

2017-07-01

We propose a method to discover sleep patterns via clustering of sound events recorded during sleep. The proposed method extends the conventional self-organizing map algorithm by kernelization and sequence-based technologies to obtain a fine-grained map that visualizes the distribution and changes of sleep-related events. We introduced features widely applied in sound processing and popular kernel functions to the proposed method to evaluate and compare performance. The proposed method provides a new aspect of sleep monitoring because the results demonstrate that sound events can be directly correlated to an individual's sleep patterns. In addition, by visualizing the transition of cluster dynamics, sleep-related sound events were found to relate to the various stages of sleep. Therefore, these results empirically warrant future study into the assessment of personal sleep quality using sound data. Copyright © 2017 Elsevier B.V. All rights reserved.

Use of the self-organizing feature map to diagnose abnormal engineering change

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Lu, Ruei-Shan; Wu, Zhi-Ting; Peng, Kuo-Wei; Yu, Tai-Yi

2015-07-01

This study established identification manners with self-organizing feature map (SOM) to achieve the goal of monitoring Engineering Change (EC) based on historical data of a company that specializes in computers and peripherals. The product life cycle of this company is 3-6 months. The historical data were divided into three parts, each covering four months. The first part, comprising 2,343 records from January to April (the training period), comprise the Control Group. The second and third parts comprise Experimental Groups (EG) 1 and 2, respectively. For EG 1 and 2, the successful rate of recognizing information on abnormal ECs was approximately 96% and 95%, respectively. This paper shows the importance and screening procedures of abnormal engineering change for a particular company specializing in computers and peripherals.

An new self-organizing maps strategy for solving the traveling salesman problem

International Nuclear Information System (INIS)

Bai Yanping; Zhang Wendong; Jin Zhen

2006-01-01

This paper presents an approach to the well-known traveling salesman problem (TSP) using self-organizing maps (SOM). There are many types of SOM algorithms to solve the TSP found in the literature, whereas the purpose of this paper is to look for the incorporation of an efficient initialization methods and the definition of a parameters adaptation law to achieve better results and a faster convergence. Aspects of parameters adaptation, selecting the number of nodes of neurons, index of winner neurons and effect of the initial ordering of the cities, as well as the initial synaptic weights of the modified SOM algorithm are discussed. The complexity of the modified SOM algorithm is analyzed. The simulated results show an average deviation of 2.32% from the optimal tour length for a set of 12 TSP instances

An new self-organizing maps strategy for solving the traveling salesman problem

Energy Technology Data Exchange (ETDEWEB)

Bai Yanping [Key Lab of Instrument Science and Dynamic Measurement of Ministry of Education, North University of China, No. 3, Xueyuan Road, TaiYuan, ShanXi 030051 (China)]. E-mail: baiyp@nuc.edu.cn; Zhang Wendong [Key Lab of Instrument Science and Dynamic Measurement of Ministry of Education, North University of China, No. 3, Xueyuan Road, TaiYuan, ShanXi 030051 (China)]. E-mail: wdzhang@nuc.edu.cn; Jin Zhen [Department of Applied Mathematics, North University of China, No. 3 Xueyuan Road, TaiYuan, ShanXi 030051 (China)

2006-05-15

This paper presents an approach to the well-known traveling salesman problem (TSP) using self-organizing maps (SOM). There are many types of SOM algorithms to solve the TSP found in the literature, whereas the purpose of this paper is to look for the incorporation of an efficient initialization methods and the definition of a parameters adaptation law to achieve better results and a faster convergence. Aspects of parameters adaptation, selecting the number of nodes of neurons, index of winner neurons and effect of the initial ordering of the cities, as well as the initial synaptic weights of the modified SOM algorithm are discussed. The complexity of the modified SOM algorithm is analyzed. The simulated results show an average deviation of 2.32% from the optimal tour length for a set of 12 TSP instances.

Analysis of Vehicle-Following Heterogeneity Using Self-Organizing Feature Maps

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Jie Yang

2014-01-01

Full Text Available A self-organizing feature map (SOM was used to represent vehicle-following and to analyze the heterogeneities in vehicle-following behavior. The SOM was constructed in such a way that the prototype vectors represented vehicle-following stimuli (the follower’s velocity, relative velocity, and gap while the output signals represented the response (the follower’s acceleration. Vehicle trajectories collected at a northbound segment of Interstate 80 Freeway at Emeryville, CA, were used to train the SOM. The trajectory information of two selected pairs of passenger cars was then fed into the trained SOM to identify similar stimuli experienced by the followers. The observed responses, when the stimuli were classified by the SOM into the same category, were compared to discover the interdriver heterogeneity. The acceleration profile of another passenger car was analyzed in the same fashion to observe the interdriver heterogeneity. The distribution of responses derived from data sets of car-following-car and car-following-truck, respectively, was compared to ascertain inter-vehicle-type heterogeneity.

A learning heuristic for space mapping and searching self-organizing systems using adaptive mesh refinement

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Phillips, Carolyn L.

2014-09-01

In a complex self-organizing system, small changes in the interactions between the system's components can result in different emergent macrostructures or macrobehavior. In chemical engineering and material science, such spontaneously self-assembling systems, using polymers, nanoscale or colloidal-scale particles, DNA, or other precursors, are an attractive way to create materials that are precisely engineered at a fine scale. Changes to the interactions can often be described by a set of parameters. Different contiguous regions in this parameter space correspond to different ordered states. Since these ordered states are emergent, often experiment, not analysis, is necessary to create a diagram of ordered states over the parameter space. By issuing queries to points in the parameter space (e.g., performing a computational or physical experiment), ordered states can be discovered and mapped. Queries can be costly in terms of resources or time, however. In general, one would like to learn the most information using the fewest queries. Here we introduce a learning heuristic for issuing queries to map and search a two-dimensional parameter space. Using a method inspired by adaptive mesh refinement, the heuristic iteratively issues batches of queries to be executed in parallel based on past information. By adjusting the search criteria, different types of searches (for example, a uniform search, exploring boundaries, sampling all regions equally) can be flexibly implemented. We show that this method will densely search the space, while preferentially targeting certain features. Using numerical examples, including a study simulating the self-assembly of complex crystals, we show how this heuristic can discover new regions and map boundaries more accurately than a uniformly distributed set of queries.

Interconnected growing self-organizing maps for auditory and semantic acquisition modeling

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Mengxue eCao

2014-03-01

Full Text Available Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic--semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners; a reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1 I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2 clear auditory and semantic boundaries can be found in the network representation; (3 cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4 reinforcing-by-link training leads to well-perceived auditory--semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.

Seismic facies analysis from pre-stack data using self-organizing maps

International Nuclear Information System (INIS)

Kourki, Meysam; Ali Riahi, Mohammad

2014-01-01

In facies analysis, seismic data are clustered in different groups. Each group represents subsurface points with similar physical properties. Different groups can be related to differences in lithology, physical properties of rocks and fluid changes in the rocks. The supervised and unsupervised data clustering are known as two types of clustering architecture. In supervised clustering, the number of clusters is predefined, while in unsupervised clustering, a collection of patterns partitions into groups without predefined clusters. In this study, the pre-stack data clustering is used for seismic facies analysis. In this way, a horizon was selected from pre-stack data, followed by sorting of data using offset. A trace associated with each CDP is constructed, for which the first and second samples are related to the first and second offsets, respectively. The created trace is called consolidated trace which is characteristic of subsurface points. These consolidated traces are clustered by using self-organizing maps (SOM). In proposed pre-stack seismic data clustering, points with similar physical properties are placed in one cluster. Seismic data associated with hydrocarbon reservoirs have very different characteristics that are easily recognized. The efficiency of the proposed method was tested on both synthetic and real seismic data. The results showed that the algorithm improves the data classification and the points of different properties are noticeable in final maps. (paper)

APPLYING PRINCIPAL COMPONENT ANALYSIS, MULTILAYER PERCEPTRON AND SELF-ORGANIZING MAPS FOR OPTICAL CHARACTER RECOGNITION

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Khuat Thanh Tung

2016-11-01

Full Text Available Optical Character Recognition plays an important role in data storage and data mining when the number of documents stored as images is increasing. It is expected to find the ways to convert images of typewritten or printed text into machine-encoded text effectively in order to support for the process of information handling effectively. In this paper, therefore, the techniques which are being used to convert image into editable text in the computer such as principal component analysis, multilayer perceptron network, self-organizing maps, and improved multilayer neural network using principal component analysis are experimented. The obtained results indicated the effectiveness and feasibility of the proposed methods.

Identifying regions of interest in medical images using self-organizing maps.

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Teng, Wei-Guang; Chang, Ping-Lin

2012-10-01

Advances in data acquisition, processing and visualization techniques have had a tremendous impact on medical imaging in recent years. However, the interpretation of medical images is still almost always performed by radiologists. Developments in artificial intelligence and image processing have shown the increasingly great potential of computer-aided diagnosis (CAD). Nevertheless, it has remained challenging to develop a general approach to process various commonly used types of medical images (e.g., X-ray, MRI, and ultrasound images). To facilitate diagnosis, we recommend the use of image segmentation to discover regions of interest (ROI) using self-organizing maps (SOM). We devise a two-stage SOM approach that can be used to precisely identify the dominant colors of a medical image and then segment it into several small regions. In addition, by appropriately conducting the recursive merging steps to merge smaller regions into larger ones, radiologists can usually identify one or more ROIs within a medical image.

High-resolution Self-Organizing Maps for advanced visualization and dimension reduction.

Science.gov (United States)

Saraswati, Ayu; Nguyen, Van Tuc; Hagenbuchner, Markus; Tsoi, Ah Chung

2018-05-04

Kohonen's Self Organizing feature Map (SOM) provides an effective way to project high dimensional input features onto a low dimensional display space while preserving the topological relationships among the input features. Recent advances in algorithms that take advantages of modern computing hardware introduced the concept of high resolution SOMs (HRSOMs). This paper investigates the capabilities and applicability of the HRSOM as a visualization tool for cluster analysis and its suitabilities to serve as a pre-processor in ensemble learning models. The evaluation is conducted on a number of established benchmarks and real-world learning problems, namely, the policeman benchmark, two web spam detection problems, a network intrusion detection problem, and a malware detection problem. It is found that the visualization resulted from an HRSOM provides new insights concerning these learning problems. It is furthermore shown empirically that broad benefits from the use of HRSOMs in both clustering and classification problems can be expected. Copyright © 2018 Elsevier Ltd. All rights reserved.

CUSTOMER SEGMENTATION DENGAN METODE SELF ORGANIZING MAP (STUDI KASUS: UD. FENNY

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A. A. Gde Bagus Ariana

2012-11-01

Full Text Available Saat ini persaingan bisnis pada perusahaan retail tidak hanya dengan menggunakan perangkat sistem informasi namun sudah dilengkapi dengan sistem pendukung keputusan. Salah satu metode sistem pendukung keputusan yang digunakan adalah data mining. Data mining digunakan untuk menemukan pola-pola yang tersembunyi pada database. UD. Fenny sebagai perusahaan retail ingin menemukan pola segmentasi pelanggan dengan menggunakan model RFM (Recency, Frequency, Monetary. Metode data mining untuk melakukan proses segmentasi adalah metode clustering. Clustering merupakan proses penggugusan data menjadi kelompok-kelompok yang memiliki kemiripan secara tidak terawasi (unsupervised. Sebelum melakukan proses clustering, dilakukan proses persiapan data dengan membuat datawarehouse menggunakan skema bintang (star scema. Selanjutnya dilakukan proses clustering dengan menggunakan metode Self Organizing Map (SOM/Kohonen. Metode ini merupakan salah satu model jaringan saraf tiruan yang menggunakan metode unsupervised. Dari hasil percobaan metode SOM melakukan proses clustering dan menggambarkan hasil clustering pada SOM plot. Dengan melakukan proses clustering, pihak pengambil keputusan dapat memahami segmentasi customer dan melakukan upaya peningkatan pelayanan customer.

Self-Organizing Maps on the Cell Broadband Engine Architecture

International Nuclear Information System (INIS)

McConnell, Sabine M

2010-01-01

We present and evaluate novel parallel implementations of Self-Organizing Maps for the Cell Broadband Engine Architecture. Motivated by the interactive nature of the data-mining process, we evaluate the scalability of the implementations on two clusters using different network characteristics and incarnations (PS3 TM console and PowerXCell 8i) of the architecture. Our implementations use varying combinations of the Power Processing Elements (PPEs) and Synergistic Processing Elements (SPEs) found in the Cell architecture. For a single processor, our implementation scaled well with the number of SPEs regardless of the incarnation. When combining multiple PS3 TM consoles, the synchronization over the slower network resulted in poor speedups and demonstrated that the use of such a low-cost cluster may be severely restricted, even without the use of SPEs. When using multiple SPEs for the PowerXCell 8i cluster, the speedup grew linearly with increasing number of SPEs for a given number of processors, and linear up to a maximum with the number of processors for a given number of SPEs. Our implementation achieved a worst-case efficiency of 67% for the maximum number of processing elements involved in the computation, but consistently higher values for smaller numbers of processing elements with speedups of up to 70.

Use of Self-Organizing Maps for Balanced Scorecard analysis to monitor the performance of dialysis clinic chains.

Science.gov (United States)

Cattinelli, Isabella; Bolzoni, Elena; Barbieri, Carlo; Mari, Flavio; Martin-Guerrero, José David; Soria-Olivas, Emilio; Martinez-Martinez, José Maria; Gomez-Sanchis, Juan; Amato, Claudia; Stopper, Andrea; Gatti, Emanuele

2012-03-01

The Balanced Scorecard (BSC) is a validated tool to monitor enterprise performances against specific objectives. Through the choice and the evaluation of strategic Key Performance Indicators (KPIs), it provides a measure of the past company's outcome and allows planning future managerial strategies. The Fresenius Medical Care (FME) BSC makes use of 30 KPIs for a continuous quality improvement strategy within its dialysis clinics. Each KPI is monthly associated to a score that summarizes the clinic efficiency for that month. Standard statistical methods are currently used to analyze the BSC data and to give a comprehensive view of the corporate improvements to the top management. We herein propose the Self-Organizing Maps (SOMs) as an innovative approach to extrapolate information from the FME BSC data and to present it in an easy-readable informative form. A SOM is a computational technique that allows projecting high-dimensional datasets to a two-dimensional space (map), thus providing a compressed representation. The SOM unsupervised (self-organizing) training procedure results in a map that preserves similarity relations existing in the original dataset; in this way, the information contained in the high-dimensional space can be more easily visualized and understood. The present work demonstrates the effectiveness of the SOM approach in extracting useful information from the 30-dimensional BSC dataset: indeed, SOMs enabled both to highlight expected relationships between the KPIs and to uncover results not predictable with traditional analyses. Hence we suggest SOMs as a reliable complementary approach to the standard methods for BSC interpretation.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

Science.gov (United States)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

An application of the Self Organizing Map Algorithm to computer aided classification of ASTER multispectral data

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Ferdinando Giacco

2008-01-01

Full Text Available In this paper we employ the Kohonen’s Self Organizing Map (SOM as a strategy for an unsupervised analysis of ASTER multispectral (MS images. In order to obtain an accurate clusterization we introduce as input for the network, in addition to spectral data, some texture measures extracted from IKONOS images, which gives a contribution to the classification of manmade structures. After clustering of SOM outcomes, we associated each cluster with a major land cover and compared them with prior knowledge of the scene analyzed.

Resting state cortico-cerebellar functional connectivity networks: A comparison of anatomical and self-organizing map approaches

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Jessica A Bernard

2012-08-01

Full Text Available The cerebellum plays a role in a wide variety of complex behaviors. In order to better understand the role of the cerebellum in human behavior, it is important to know how this structure interacts with cortical and other subcortical regions of the brain. To date, several studies have investigated the cerebellum using resting-state functional connectivity magnetic resonance imaging (fcMRI; Buckner et al., 2011; Krienen & Buckner, 2009; O’Reilly et al., 2009. However, none of this work has taken an anatomically-driven approach. Furthermore, though detailed maps of cerebral cortex and cerebellum networks have been proposed using different network solutions based on the cerebral cortex (Buckner et al., 2011, it remains unknown whether or not an anatomical lobular breakdown best encompasses the networks of the cerebellum. Here, we used fcMRI to create an anatomically-driven cerebellar connectivity atlas. Timecourses were extracted from the lobules of the right hemisphere and vermis. We found distinct networks for the individual lobules with a clear division into motor and non-motor regions. We also used a self-organizing map algorithm to parcellate the cerebellum. This allowed us to investigate redundancy and independence of the anatomically identified cerebellar networks. We found that while anatomical boundaries in the anterior cerebellum provide functional subdivisions of a larger motor grouping defined using our self-organizing map algorithm, in the posterior cerebellum, the lobules were made up of sub-regions associated with distinct functional networks. Together, our results indicate that the lobular boundaries of the human cerebellum are not indicative of functional boundaries, though anatomical divisions can be useful, as is the case of the anterior cerebellum. Additionally, driving the analyses from the cerebellum is key to determining the complete picture of functional connectivity within the structure.

An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps

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Jun Liu

2016-01-01

Full Text Available Virtual machines (VM on a Cloud platform can be influenced by a variety of factors which can lead to decreased performance and downtime, affecting the reliability of the Cloud platform. Traditional anomaly detection algorithms and strategies for Cloud platforms have some flaws in their accuracy of detection, detection speed, and adaptability. In this paper, a dynamic and adaptive anomaly detection algorithm based on Self-Organizing Maps (SOM for virtual machines is proposed. A unified modeling method based on SOM to detect the machine performance within the detection region is presented, which avoids the cost of modeling a single virtual machine and enhances the detection speed and reliability of large-scale virtual machines in Cloud platform. The important parameters that affect the modeling speed are optimized in the SOM process to significantly improve the accuracy of the SOM modeling and therefore the anomaly detection accuracy of the virtual machine.

The linkage between the lifestyle of knowledge-workers and their intra-metropolitan residential choice: A clustering approach based on self-organizing maps

DEFF Research Database (Denmark)

Frenkel, Amnon; Bendit, Edward; Kaplan, Sigal

2013-01-01

-Aviv metropolitan area and are analyzed with self-organizing maps for pattern recognition and classification. Five clusters are identified: nest-builders, bon-vivants, careerists, entrepreneurs and laid-back. Bon-vivants and entrepreneurs differ in their dwelling size and home-ownership, although both prefer...

Characterizing synoptic and cloud variability in the northern atlantic using self-organizing maps

Science.gov (United States)

Fish, Carly

Low-level clouds have a significant influence on the Earth's radiation budget and it is thus imperative to understand their behavior within the marine boundary layer (MBL). The cloud properties in the Northeast Atlantic region are highly variable in space and time and are a research focus for many atmospheric scientists. Characterizing the synoptic patterns in the region through the implementation of self-organizing maps (SOMs) enables a climatological grasp of cloud and atmospheric fields. ERA -- Interim and MODIS provide the platform to explore the variability in the Northeast Atlantic for over 30 years of data. Station data comes from CAP -- MBL on Graciosa Island in the Azores, which lies in a strong gradient of cloud and other atmospheric fields, offer an opportunity to incorporate an observational aspect for the years of 2009 and 2010.

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

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Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

Feature-based alert correlation in security systems using self organizing maps

Science.gov (United States)

Kumar, Munesh; Siddique, Shoaib; Noor, Humera

2009-04-01

The security of the networks has been an important concern for any organization. This is especially important for the defense sector as to get unauthorized access to the sensitive information of an organization has been the prime desire for cyber criminals. Many network security techniques like Firewall, VPN Concentrator etc. are deployed at the perimeter of network to deal with attack(s) that occur(s) from exterior of network. But any vulnerability that causes to penetrate the network's perimeter of defense, can exploit the entire network. To deal with such vulnerabilities a system has been evolved with the purpose of generating an alert for any malicious activity triggered against the network and its resources, termed as Intrusion Detection System (IDS). The traditional IDS have still some deficiencies like generating large number of alerts, containing both true and false one etc. By automatically classifying (correlating) various alerts, the high-level analysis of the security status of network can be identified and the job of network security administrator becomes much easier. In this paper we propose to utilize Self Organizing Maps (SOM); an Artificial Neural Network for correlating large amount of logged intrusion alerts based on generic features such as Source/Destination IP Addresses, Port No, Signature ID etc. The different ways in which alerts can be correlated by Artificial Intelligence techniques are also discussed. . We've shown that the strategy described in the paper improves the efficiency of IDS by better correlating the alerts, leading to reduced false positives and increased competence of network administrator.

Fault detection of sensors in nuclear reactors using self-organizing maps

Energy Technology Data Exchange (ETDEWEB)

Barbosa, Paulo Roberto; Tiago, Graziela Marchi [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Guarulhos, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

In this work a Fault Detection System was developed based on the self-organizing maps methodology. This method was applied to the IEA-R1 research reactor at IPEN using a database generated by a theoretical model of the reactor. The IEA-R1 research reactor is a pool type reactor of 5 MW, cooled and moderated by light water, and uses graphite and beryllium as reflector. The theoretical model was developed using the Matlab Guide toolbox. The equations are based in the IEA-R1 mass and energy inventory balance and physical as well as operational aspects are taken into consideration. In order to test the model ability for fault detection, faults were artificially produced. As the value of the maximum calibration error for special thermocouples is +- 0.5 deg C, it had been inserted faults in the sensor signals with the purpose to produce the database considered in this work. The results show a high percentage of correct classification, encouraging the use of the technique for this type of industrial application. (author)

Artificial neural network with self-organizing mapping for reactor stability monitoring

International Nuclear Information System (INIS)

Okumura, Motofumi; Tsuji, Masashi; Shimazu, Yoichiro

2009-01-01

In boiling water reactor (BWR) stability monitoring, damping ratio has been used as a stability index. A method for estimating the damping ratio by applying Principal Component Analysis (PCA) to neutron detector signals measured with local power range monitors (LPRMs) had been developed; in this method, measured fluctuating signal is decomposed into some independent components and the signal components directly related to stability are extracted among them to determine the damping ratio. For online monitoring, it is necessary to select stability related signal components efficiently. The self-organizing map (SOM) is one of the artificial neural networks (ANNs) and has the characteristics such that online learning is possible without supervised learning within a relatively short time. In the present study, the SOM was applied to extract the relevant signal components more quickly and more accurately, and the availability was confirmed through the feasibility study. For realizing online stability monitoring only with ANNs, another type of ANN that performs online processing of PCA was combined with SOM. And stability monitoring performance was investigated. (author)

Fault detection of sensors in nuclear reactors using self-organizing maps

International Nuclear Information System (INIS)

Barbosa, Paulo Roberto; Tiago, Graziela Marchi; Bueno, Elaine Inacio; Pereira, Iraci Martinez

2011-01-01

In this work a Fault Detection System was developed based on the self-organizing maps methodology. This method was applied to the IEA-R1 research reactor at IPEN using a database generated by a theoretical model of the reactor. The IEA-R1 research reactor is a pool type reactor of 5 MW, cooled and moderated by light water, and uses graphite and beryllium as reflector. The theoretical model was developed using the Matlab Guide toolbox. The equations are based in the IEA-R1 mass and energy inventory balance and physical as well as operational aspects are taken into consideration. In order to test the model ability for fault detection, faults were artificially produced. As the value of the maximum calibration error for special thermocouples is +- 0.5 deg C, it had been inserted faults in the sensor signals with the purpose to produce the database considered in this work. The results show a high percentage of correct classification, encouraging the use of the technique for this type of industrial application. (author)

Segmentation of head magnetic resonance image using self-mapping characteristic

International Nuclear Information System (INIS)

Madokoro, Hirokazu; Sato, Kazuhito; Ishii, Masaki; Kadowaki, Sakura

2004-01-01

In this paper, we proposed a segmentation method, for head magnetic resonance (MR) images. Our method used self mapping characteristic of a self-organization map (SOM), and it does not need the setting of the representative point by the operator. We considered the continuity and boundary in the brain tissues by the definition of the local block. In the evaluation experiment, we obtained the segmentation result of matching anatomical structure information. In addition, our method applied the clinical MR images, it was possible to obtain the effective and objective result for supporting the diagnosis of the brain atrophy by the doctor. (author)

Peptide π-Electron Conjugates: Organic Electronics for Biology?

Science.gov (United States)

Ardoña, Herdeline Ann M; Tovar, John D

2015-12-16

Highly ordered arrays of π-conjugated molecules are often viewed as a prerequisite for effective charge-transporting materials. Studies involving these materials have traditionally focused on organic electronic devices, with more recent emphasis on biological systems. In order to facilitate the transition to biological environments, biomolecules that can promote hierarchical ordering and water solubility are often covalently appended to the π-electron unit. This review highlights recent work on π-conjugated systems bound to peptide moieties that exhibit self-assembly and aims to provide an overview on the development and emerging applications of peptide-based supramolecular π-electron systems.

Achieving Optimal Self-Adaptivity for Dynamic Tuning of Organic Semiconductors through Resonance Engineering.

Science.gov (United States)

Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei

2016-08-03

Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic.

Cooperation-Controlled Learning for Explicit Class Structure in Self-Organizing Maps

Science.gov (United States)

Kamimura, Ryotaro

2014-01-01

We attempt to demonstrate the effectiveness of multiple points of view toward neural networks. By restricting ourselves to two points of view of a neuron, we propose a new type of information-theoretic method called “cooperation-controlled learning.” In this method, individual and collective neurons are distinguished from one another, and we suppose that the characteristics of individual and collective neurons are different. To implement individual and collective neurons, we prepare two networks, namely, cooperative and uncooperative networks. The roles of these networks and the roles of individual and collective neurons are controlled by the cooperation parameter. As the parameter is increased, the role of cooperative networks becomes more important in learning, and the characteristics of collective neurons become more dominant. On the other hand, when the parameter is small, individual neurons play a more important role. We applied the method to the automobile and housing data from the machine learning database and examined whether explicit class boundaries could be obtained. Experimental results showed that cooperation-controlled learning, in particular taking into account information on input units, could be used to produce clearer class structure than conventional self-organizing maps. PMID:25309950

Cooperation-Controlled Learning for Explicit Class Structure in Self-Organizing Maps

Directory of Open Access Journals (Sweden)

Ryotaro Kamimura

2014-01-01

Full Text Available We attempt to demonstrate the effectiveness of multiple points of view toward neural networks. By restricting ourselves to two points of view of a neuron, we propose a new type of information-theoretic method called “cooperation-controlled learning.” In this method, individual and collective neurons are distinguished from one another, and we suppose that the characteristics of individual and collective neurons are different. To implement individual and collective neurons, we prepare two networks, namely, cooperative and uncooperative networks. The roles of these networks and the roles of individual and collective neurons are controlled by the cooperation parameter. As the parameter is increased, the role of cooperative networks becomes more important in learning, and the characteristics of collective neurons become more dominant. On the other hand, when the parameter is small, individual neurons play a more important role. We applied the method to the automobile and housing data from the machine learning database and examined whether explicit class boundaries could be obtained. Experimental results showed that cooperation-controlled learning, in particular taking into account information on input units, could be used to produce clearer class structure than conventional self-organizing maps.

Electronic systems for the organization and planning of school

OpenAIRE

Vodová, Alena

2014-01-01

TITLE: Electronic systems for the organization and planning of school AUTHOR: Alena Vodová DEPARTMENT: The Center of School management SUPERVISOR: Ing. Petr Svoboda Ph.D. ABSTRACT: The bachelor thesis gives comprehensive overview electronic systems for organization and planning of school. Maps of species, describes their function, demonstrates the benefits, modes and applications to use in school. In the research part individuals system compares between them and validates their use in schools...

CLUSTER ANALYSIS UNTUK MEMPREDIKSI TALENTA PEMAIN BASKET MENGGUNAKAN JARINGAN SARAF TIRUAN SELF ORGANIZING MAPS (SOM

Directory of Open Access Journals (Sweden)

Gregorius Satia Budhi

2008-01-01

Full Text Available Basketball World has grown rapidly as the time goes on. This is signed by many competition and game all over the world. With the result there are many basketball players with their different playing characteristics. Demand for a coach or scout to look for or search great players to make a solid team as a coach requirement. With this application, a coach or scout will be helped in analyzing in decision making. This application uses Self Organizing Maps algorithm (SOM for Cluster Analysis. The real NBA player data is used for competitive learning or training process and real player data from Indonesian or Petra Christian University Basketball Players is used for testing process. The NBA Player data is prepared through cleaning process and then is transformed into a form that can be processed by SOM Algorithm. After that, the data is clustered with the SOM algorithm. The result of that clusters is displayed into a form that is easy to view and analyze. This result can be saved into a text file. By using the output / result of this application, that are the clusters of NBA player, the user can see the statistics of each cluster. With these cluster statistics coach or scout can predict the statistic and the position of a testing player who is in the same cluster. This information can give a support for the coach or scout to make a decision. Abstract in Bahasa Indonesia : Dunia bola basket telah berkembang dengan pesat seiring dengan berjalannya waktu. Hal ini ditandai dengan munculnya berbagai macam dan jenis kompetisi dan pertandingan baik dunia maupun dalam negeri. Sehingga makin banyak dilahirkannya pemain berbakat dengan berbagai karakteristik permainan yang berbeda. Tuntutan bagi seorang pelatih/pemandu bakat, untuk dapat melihat secara jeli dalam memenuhi kebutuhan tim untuk membentuk tim yang solid. Dengan dibuatnya aplikasi ini, maka akan membantu proses analisis dan pengambilan keputusan bagi pelatih maupun pemandu bakat Aplikasi ini

Intelligent Machine Vision for Automated Fence Intruder Detection Using Self-organizing Map

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Veldin A. Talorete Jr.

2017-03-01

Full Text Available This paper presents an intelligent machine vision for automated fence intruder detection. A series of still captured images that contain fence events using Internet Protocol cameras was used as input data to the system. Two classifiers were used; the first is to classify human posture and the second one will classify intruder location. The system classifiers were implemented using Self-Organizing Map after the implementation of several image segmentation processes. The human posture classifier is in charge of classifying the detected subject’s posture patterns from subject’s silhouette. Moreover, the Intruder Localization Classifier is in charge of classifying the detected pattern’s location classifier will estimate the location of the intruder with respect to the fence using geometric feature from images as inputs. The system is capable of activating the alarm, display the actual image and depict the location of the intruder when an intruder is detected. In detecting intruder posture, the system’s success rate of 88%. Overall system accuracy for day-time intruder localization is 83% and an accuracy of 88% for night-time intruder localization

Postprocessing of Accidental Scenarios by Semi-Supervised Self-Organizing Maps

Directory of Open Access Journals (Sweden)

Francesco Di Maio

2017-01-01

Full Text Available Integrated Deterministic and Probabilistic Safety Analysis (IDPSA of dynamic systems calls for the development of efficient methods for accidental scenarios generation. The necessary consideration of failure events timing and sequencing along the scenarios requires the number of scenarios to be generated to increase with respect to conventional PSA. Consequently, their postprocessing for retrieving safety relevant information regarding the system behavior is challenged because of the large amount of generated scenarios that makes the computational cost for scenario postprocessing enormous and the retrieved information difficult to interpret. In the context of IDPSA, the interpretation consists in the classification of the generated scenarios as safe, failed, Near Misses (NMs, and Prime Implicants (PIs. To address this issue, in this paper we propose the use of an ensemble of Semi-Supervised Self-Organizing Maps (SSSOMs whose outcomes are combined by a locally weighted aggregation according to two strategies: a locally weighted aggregation and a decision tree based aggregation. In the former, we resort to the Local Fusion (LF principle for accounting the classification reliability of the different SSSOM classifiers, whereas in the latter we build a classification scheme to select the appropriate classifier (or ensemble of classifiers, for the type of scenario to be classified. The two strategies are applied for the postprocessing of the accidental scenarios of a dynamic U-Tube Steam Generator (UTSG.

An Information-Theoretic-Cluster Visualization for Self-Organizing Maps.

Science.gov (United States)

Brito da Silva, Leonardo Enzo; Wunsch, Donald C

2018-06-01

Improved data visualization will be a significant tool to enhance cluster analysis. In this paper, an information-theoretic-based method for cluster visualization using self-organizing maps (SOMs) is presented. The information-theoretic visualization (IT-vis) has the same structure as the unified distance matrix, but instead of depicting Euclidean distances between adjacent neurons, it displays the similarity between the distributions associated with adjacent neurons. Each SOM neuron has an associated subset of the data set whose cardinality controls the granularity of the IT-vis and with which the first- and second-order statistics are computed and used to estimate their probability density functions. These are used to calculate the similarity measure, based on Renyi's quadratic cross entropy and cross information potential (CIP). The introduced visualizations combine the low computational cost and kernel estimation properties of the representative CIP and the data structure representation of a single-linkage-based grouping algorithm to generate an enhanced SOM-based visualization. The visual quality of the IT-vis is assessed by comparing it with other visualization methods for several real-world and synthetic benchmark data sets. Thus, this paper also contains a significant literature survey. The experiments demonstrate the IT-vis cluster revealing capabilities, in which cluster boundaries are sharply captured. Additionally, the information-theoretic visualizations are used to perform clustering of the SOM. Compared with other methods, IT-vis of large SOMs yielded the best results in this paper, for which the quality of the final partitions was evaluated using external validity indices.

Self Organization in Compensated Semiconductors

Science.gov (United States)

Berezin, Alexander A.

2004-03-01

In partially compensated semiconductor (PCS) Fermi level is pinned to donor sub-band. Due to positional randomness and almost isoenergetic hoppings, donor-spanned electronic subsystem in PCS forms fluid-like highly mobile collective state. This makes PCS playground for pattern formation, self-organization, complexity emergence, electronic neural networks, and perhaps even for origins of life, bioevolution and consciousness. Through effects of impact and/or Auger ionization of donor sites, whole PCS may collapse (spinodal decomposition) into microblocks potentially capable of replication and protobiological activity (DNA analogue). Electronic screening effects may act in RNA fashion by introducing additional length scale(s) to system. Spontaneous quantum computing on charged/neutral sites becomes potential generator of informationally loaded microstructures akin to "Carl Sagan Effect" (hidden messages in Pi in his "Contact") or informational self-organization of "Library of Babel" of J.L. Borges. Even general relativity effects at Planck scale (R.Penrose) may affect the dynamics through (e.g.) isotopic variations of atomic mass and local density (A.A.Berezin, 1992). Thus, PCS can serve as toy model (experimental and computational) at interface of physics and life sciences.

Self-organizing maps applied to two-phase flow on natural circulation loop studies

Energy Technology Data Exchange (ETDEWEB)

Castro, Leonardo F.; Cunha, Kelly de P.; Andrade, Delvonei A.; Sabundjian, Gaiane; Torres, Walmir M.; Macedo, Luiz A.; Rocha, Marcelo da S.; Masotti, Paulo H.F.; Mesquita, Roberto N. de, E-mail: rnavarro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2015-07-01

Two-phase flow of liquid and gas is found in many closed circuits using natural circulation for cooling purposes. Natural circulation phenomenon is important on recent nuclear power plant projects for heat removal on 'loss of pump power' or 'plant shutdown' accidents. The accuracy of heat transfer estimation has been improved based on models that require precise prediction of pattern transitions of flow. Self-Organizing Maps are trained to digital images acquired on natural circulation flow instabilities. This technique will allow the selection of the more important characteristics associated with each flow pattern, enabling a better comprehension of each observed instability. This periodic flow oscillation behavior can be observed thoroughly in this facility due its glass-made tubes transparency. The Natural Circulation Facility (Circuito de Circulacao Natural - CCN) installed at Instituto de Pesquisas Energeticas e Nucleares, IPEN/CNEN, is an experimental circuit designed to provide thermal hydraulic data related to one and two phase flow under natural circulation conditions. (author)

Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models.

Science.gov (United States)

Mahony, Shaun; McInerney, James O; Smith, Terry J; Golden, Aaron

2004-03-05

Many current gene prediction methods use only one model to represent protein-coding regions in a genome, and so are less likely to predict the location of genes that have an atypical sequence composition. It is likely that future improvements in gene finding will involve the development of methods that can adequately deal with intra-genomic compositional variation. This work explores a new approach to gene-prediction, based on the Self-Organizing Map, which has the ability to automatically identify multiple gene models within a genome. The current implementation, named RescueNet, uses relative synonymous codon usage as the indicator of protein-coding potential. While its raw accuracy rate can be less than other methods, RescueNet consistently identifies some genes that other methods do not, and should therefore be of interest to gene-prediction software developers and genome annotation teams alike. RescueNet is recommended for use in conjunction with, or as a complement to, other gene prediction methods.

Segmentation of Natural Gas Customers in Industrial Sector Using Self-Organizing Map (SOM) Method

Science.gov (United States)

Masbar Rus, A. M.; Pramudita, R.; Surjandari, I.

2018-03-01

The usage of the natural gas which is non-renewable energy, needs to be more efficient. Therefore, customer segmentation becomes necessary to set up a marketing strategy to be right on target or to determine an appropriate fee. This research was conducted at PT PGN using one of data mining method, i.e. Self-Organizing Map (SOM). The clustering process is based on the characteristic of its customers as a reference to create the customer segmentation of natural gas customers. The input variables of this research are variable of area, type of customer, the industrial sector, the average usage, standard deviation of the usage, and the total deviation. As a result, 37 cluster and 9 segment from 838 customer data are formed. These 9 segments then employed to illustrate the general characteristic of the natural gas customer of PT PGN.

Self-organizing neural networks for automatic detection and classification of contrast-enhancing lesions in dynamic MR-mammography

International Nuclear Information System (INIS)

Vomweg, T.W.; Teifke, A.; Kauczor, H.U.; Achenbach, T.; Rieker, O.; Schreiber, W.G.; Heitmann, K.R.; Beier, T.; Thelen, M.

2005-01-01

Purpose: Investigation and statistical evaluation of 'Self-Organizing Maps', a special type of neural networks in the field of artificial intelligence, classifying contrast enhancing lesions in dynamic MR-mammography. Material and Methods: 176 investigations with proven histology after core biopsy or operation were randomly divided into two groups. Several Self-Organizing Maps were trained by investigations of the first group to detect and classify contrast enhancing lesions in dynamic MR-mammography. Each single pixel's signal/time curve of all patients within the second group was analyzed by the Self-Organizing Maps. The likelihood of malignancy was visualized by color overlays on the MR-images. At last assessment of contrast-enhancing lesions by each different network was rated visually and evaluated statistically. Results: A well balanced neural network achieved a sensitivity of 90.5% and a specificity of 72.2% in predicting malignancy of 88 enhancing lesions. Detailed analysis of false-positive results revealed that every second fibroadenoma showed a 'typical malignant' signal/time curve without any chance to differentiate between fibroadenomas and malignant tissue regarding contrast enhancement alone; but this special group of lesions was represented by a well-defined area of the Self-Organizing Map. Discussion: Self-Organizing Maps are capable of classifying a dynamic signal/time curve as 'typical benign' or 'typical malignant'. Therefore, they can be used as second opinion. In view of the now known localization of fibroadenomas enhancing like malignant tumors at the Self-Organizing Map, these lesions could be passed to further analysis by additional post-processing elements (e.g., based on T2-weighted series or morphology analysis) in the future. (orig.)

A NEW RECOGNITION TECHNIQUE NAMED SOMP BASED ON PALMPRINT USING NEURAL NETWORK BASED SELF ORGANIZING MAPS

Directory of Open Access Journals (Sweden)

A. S. Raja

2012-08-01

Full Text Available The word biometrics refers to the use of physiological or biological characteristics of human to recognize and verify the identity of an individual. Palmprint has become a new class of human biometrics for passive identification with uniqueness and stability. This is considered to be reliable due to the lack of expressions and the lesser effect of aging. In this manuscript a new Palmprint based biometric system based on neural networks self organizing maps (SOM is presented. The method is named as SOMP. The paper shows that the proposed SOMP method improves the performance and robustness of recognition. The proposed method is applied to a variety of datasets and the results are shown.

The self-organizing map, a new approach to apprehend the Madden–Julian Oscillation influence on the intraseasonal variability of rainfall in the southern African region

CSIR Research Space (South Africa)

Oettli, P

2013-11-01

Full Text Available -linear classification method, the self-organizing map (SOM), a type of artificial neural network used to produce a low-dimensional representation of high-dimensional datasets, to capture more accurately the life cycle of the MJO and its global impacts...

Reaction-Map of Organic Chemistry

Science.gov (United States)

Murov, Steven

2007-01-01

The Reaction-Map of Organic Chemistry lists all the most commonly studied reactions in organic chemistry on one page. The discussed Reaction-Map will act as another learning aide for the students, making the study of organic chemistry much easier.

Self-organizing maps as a chemometric tool for aromatic pattern recognition of soluble coffee - doi: 10.4025/actascitechnol.v34i1.10892

Directory of Open Access Journals (Sweden)

Evandro Bona

2011-11-01

Full Text Available The electronic nose (EN is an instrument very used for food flavor analysis. However, it is also necessary to integrate the equipment with a multivariable pattern recognition system, and to this end the principal component analysis (PCA is the first choice. Alternatively, self-organizing maps (SOM had been also suggested, since they are a nonlinear and reliable technique. In this study SOM were used to distinguish soluble coffee according to EN data. The proposed methodology had identified all of the seven coffees evaluated; in addition, the groups and relationships detected were similar to those obtained through PCA. Also, the analysis of network weights allowed gathering the e-nose sensors into 4 groups according to the behavior regarding the samples. Results confirm SOM as an efficient tool to EN data pos-processing, and have showed the methodology as a promising choice for the development of new products and quality control of soluble coffee.

Transient classification for the IRIS reactor using self-organized maps built in free platform

International Nuclear Information System (INIS)

Doraskevicius Junior, Waldemar

2005-01-01

Kohonen's Self Organized Maps (SOM) were tested with data from several operational conditions of the nuclear reactor IRIS (International Reactor Innovative and Secure) to develop an effective tool in the classification and transient identification in nuclear reactors. The data were derived from 56 simulations of the operation of IRIS, from steady-state conditions to accidents. The digital system built for the tests was based on the JAVA platform for the portability and scalability, and for being one of the free development platforms. Satisfactory results of operation classification were obtained with reasonable processing time in personal computers; about two to five minutes were spent for ordination and convergence of the learning on the data base. The methodology of this work was extended to the supervision of logistics of natural gas for Brazilian pipelines, showing satisfactory results for the classification of deliveries for simultaneous measurement in several points. (author)

Self-Organizing Robots

CERN Document Server

Murata, Satoshi

2012-01-01

It is man’s ongoing hope that a machine could somehow adapt to its environment by reorganizing itself. This is what the notion of self-organizing robots is based on. The theme of this book is to examine the feasibility of creating such robots within the limitations of current mechanical engineering. The topics comprise the following aspects of such a pursuit: the philosophy of design of self-organizing mechanical systems; self-organization in biological systems; the history of self-organizing mechanical systems; a case study of a self-assembling/self-repairing system as an autonomous distributed system; a self-organizing robot that can create its own shape and robotic motion; implementation and instrumentation of self-organizing robots; and the future of self-organizing robots. All topics are illustrated with many up-to-date examples, including those from the authors’ own work. The book does not require advanced knowledge of mathematics to be understood, and will be of great benefit to students in the rob...

Using self-organizing maps to determine observation threshold limit predictions in highly variant data

Science.gov (United States)

Paganoni, C.A.; Chang, K.C.; Robblee, M.B.

2006-01-01

A significant data quality challenge for highly variant systems surrounds the limited ability to quantify operationally reasonable limits on the data elements being collected and provide reasonable threshold predictions. In many instances, the number of influences that drive a resulting value or operational range is too large to enable physical sampling for each influencer, or is too complicated to accurately model in an explicit simulation. An alternative method to determine reasonable observation thresholds is to employ an automation algorithm that would emulate a human analyst visually inspecting data for limits. Using the visualization technique of self-organizing maps (SOM) on data having poorly understood relationships, a methodology for determining threshold limits was developed. To illustrate this approach, analysis of environmental influences that drive the abundance of a target indicator species (the pink shrimp, Farfantepenaeus duorarum) provided a real example of applicability. The relationship between salinity and temperature and abundance of F. duorarum is well documented, but the effect of changes in water quality upstream on pink shrimp abundance is not well understood. The highly variant nature surrounding catch of a specific number of organisms in the wild, and the data available from up-stream hydrology measures for salinity and temperature, made this an ideal candidate for the approach to provide a determination about the influence of changes in hydrology on populations of organisms.

Hierarchical organization versus self-organization

OpenAIRE

Busseniers, Evo

2014-01-01

In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these two definitions are given. For the structure we will use some existing definitions in graph theory, for the function we will use existing theory on (self-)organization. In the t...

Assessment of self-organizing maps to analyze sole-carbon source utilization profiles.

Science.gov (United States)

Leflaive, Joséphine; Céréghino, Régis; Danger, Michaël; Lacroix, Gérard; Ten-Hage, Loïc

2005-07-01

The use of community-level physiological profiles obtained with Biolog microplates is widely employed to consider the functional diversity of bacterial communities. Biolog produces a great amount of data which analysis has been the subject of many studies. In most cases, after some transformations, these data were investigated with classical multivariate analyses. Here we provided an alternative to this method, that is the use of an artificial intelligence technique, the Self-Organizing Maps (SOM, unsupervised neural network). We used data from a microcosm study of algae-associated bacterial communities placed in various nutritive conditions. Analyses were carried out on the net absorbances at two incubation times for each substrates and on the chemical guild categorization of the total bacterial activity. Compared to Principal Components Analysis and cluster analysis, SOM appeared as a valuable tool for community classification, and to establish clear relationships between clusters of bacterial communities and sole-carbon sources utilization. Specifically, SOM offered a clear bidimensional projection of a relatively large volume of data and were easier to interpret than plots commonly obtained with multivariate analyses. They would be recommended to pattern the temporal evolution of communities' functional diversity.

Analysis of Flue Gas Emission Data from Fluidized Bed Combustion Using Self-Organizing Maps

Directory of Open Access Journals (Sweden)

Mika Liukkonen

2010-01-01

Full Text Available Efficient combustion of fuels with lower emissions levels has become a demanding task in modern power plants, and new tools are needed to diagnose their energy production. The goals of the study were to find dependencies between process variables and the concentrations of gaseous emission components and to create multivariate nonlinear models describing their formation in the process. First, a generic process model was created by using a self-organizing map, which was clustered with the k-means algorithm to create subsets representing the different states of the process. Characteristically, these process states may include high- and low- load situations and transition states where the load is increased or decreased. Then emission models were constructed for both the entire process and for the process state of high boiler load. The main conclusion is that the methodology used is able to reveal such phenomena that occur within the process states and that could otherwise be difficult to observe.

Multiscale visual quality assessment for cluster analysis with self-organizing maps

Science.gov (United States)

Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

2011-01-01

Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

Use of self-organizing maps for classification of defects in the tubes from the steam generator of nuclear power plants

International Nuclear Information System (INIS)

Mesquita, Roberto Navarro de

2002-01-01

This thesis obtains a new classification method for different steam generator tube defects in nuclear power plants using Eddy Current Test signals. The method uses self-organizing maps to compare different signal characteristics efficiency to identify and classify these defects. A multiple inference system is proposed which composes the different extracted characteristic trained maps classification to infer the final defect type. The feature extraction methods used are the Wavelet zero-crossings representation, the linear predictive coding (LPC), and other basic signal representations on time like module and phase. Many characteristic vectors are obtained with combinations of these extracted characteristics. These vectors are tested to classify the defects and the best ones are applied to the multiple inference system. A systematic study of pre-processing, calibration and analysis methods for the steam generator tube defect signals in nuclear power plants is done. The method efficiency is demonstrated and characteristic maps with the main prototypes are obtained for each steam generator tube defect type. (author)

Electric radiation mapping of silver/zinc oxide nanoantennas by using electron holography

Energy Technology Data Exchange (ETDEWEB)

Sanchez, J. E.; Mendoza-Santoyo, F.; Cantu-Valle, J.; Velazquez-Salazar, J.; José Yacaman, M.; Ponce, A. [Department of Physics and Astronomy, University of Texas at San Antonio, San Antonio 78249 (United States); González, F. J. [Coordinación para la Innovación y la Aplicación de la Ciencia y la Tecnología, Universidad Autónoma de San Luís Potosí, San Luis Potosí 78210 (Mexico); Diaz de Leon, R. [Instituto Tecnológico de San Luis Potosí, San Luis Potosi 78437 (Mexico)

2015-01-21

In this work, we report the fabrication of self-assembled zinc oxide nanorods grown on pentagonal faces of silver nanowires by using microwaves irradiation. The nanostructures resemble a hierarchal nanoantenna and were used to study the far and near field electrical metal-semiconductor behavior from the electrical radiation pattern resulting from the phase map reconstruction obtained using off-axis electron holography. As a comparison, we use electric numerical approximations methods for a finite number of ZnO nanorods on the Ag nanowires and show that the electric radiation intensities maps match closely the experimental results obtained with electron holography. The time evolution of the radiation pattern as generated from the nanostructure was recorded under in-situ radio frequency signal stimulation, in which the generated electrical source amplitude and frequency were varied from 0 to 5 V and from 1 to 10 MHz, respectively. The phase maps obtained from electron holography show the change in the distribution of the electric radiation pattern for individual nanoantennas. The mapping of this electrical behavior is of the utmost importance to gain a complete understanding for the metal-semiconductor (Ag/ZnO) heterojunction that will help to show the mechanism through which these receiving/transmitting structures behave at nanoscale level.

Analyzing the effectiveness of flare dispensing programs against pulse width modulation seekers using self-organizing maps

Science.gov (United States)

Şahingil, Mehmet C.; Aslan, Murat Š.

2013-10-01

Infrared guided missile seekers utilizing pulse width modulation in target tracking is one of the threats against air platforms. To be able to achieve a "soft-kill" protection of own platform against these type of threats, one needs to examine carefully the seeker operating principle with its special electronic counter-counter measure (ECCM) capability. One of the cost-effective ways of soft kill protection is to use flare decoys in accordance with an optimized dispensing program. Such an optimization requires a good understanding of the threat seeker, capabilities of the air platform and engagement scenario information between them. Modeling and simulation is very powerful tool to achieve a valuable insight and understand the underlying phenomenology. A careful interpretation of simulation results is crucial to infer valuable conclusions from the data. In such an interpretation there are lots of factors (features) which affect the results. Therefore, powerful statistical tools and pattern recognition algorithms are of special interest in the analysis. In this paper, we show how self-organizing maps (SOMs), which is one of those powerful tools, can be used in analyzing the effectiveness of various flare dispensing programs against a PWM seeker. We perform several Monte Carlo runs for a typical engagement scenario in a MATLAB-based simulation environment. In each run, we randomly change the flare dispending program and obtain corresponding class: "successful" or "unsuccessful", depending on whether the corresponding flare dispensing program deceives the seeker or not, respectively. Then, in the analysis phase, we use SOMs to interpret and visualize the results.

Exploring the spatio-temporal interrelation between groundwater and surface water by using the self-organizing maps

Science.gov (United States)

Chen, I.-Ting; Chang, Li-Chiu; Chang, Fi-John

2018-01-01

In this study, we propose a soft-computing methodology to visibly explore the spatio-temporal groundwater variations of the Kuoping River basin in southern Taiwan. The self-organizing map (SOM) is implemented to investigate the interactive mechanism between surface water and groundwater over the river basin based on large high-dimensional data sets coupled with their occurrence times. We find that extracting the occurrence time from each 30-day moving average data set in the clustered neurons of the SOM is a crucial step to learn the spatio-temporal interaction between surface water and groundwater. We design 2-D Topological Bubble Map to summarize all the groundwater values of four aquifers in a neuron, which can visibly explore the major features of the groundwater in the vertical direction. The constructed SOM topological maps nicely display that: (1) the groundwater movement, in general, extends from the eastern area to the western, where groundwater in the eastern area can be easily recharged from precipitation in wet seasons and discharged into streams during dry seasons due to the high permeability in this area; (2) the water movements in the four aquifers of the study area are quite different, and the seasonal variations of groundwater in the second and third aquifers are larger than those of the others; and (3) the spatial distribution and seasonal variations of groundwater and surface water are comprehensively linked together over the constructed maps to present groundwater characteristics and the interrelation between groundwater and surface water. The proposed modeling methodology not only can classify the large complex high-dimensional data sets into visible topological maps to effectively facilitate the quantitative status of regional groundwater resources but can also provide useful elaboration for future groundwater management.

Chemotaxonomy of three genera of the Annonaceae family using self-organizing maps and 13C NMR data of diterpenes

International Nuclear Information System (INIS)

Scotti, Luciana; Tavares, Josean Fechine; Silva, Marcelo Sobral da; Falcao, Emanuela Viana; Silva, Luana de Morais e; Soares, Gabriela Cristina da Silva; Scotti, Marcus Tullius

2012-01-01

The Annonaceae family is distributed throughout Neotropical regions of the world. In Brazil, it covers nearly all natural formations particularly Annona, Xylopia and Polyalthia and is characterized chemically by the production of sources of terpenoids (mainly diterpenes), alkaloids, steroids, polyphenols and, flavonoids. Studies from 13 C NMR data of diterpenes related with their botanical occurrence were used to generate self-organizing maps. Results corroborate those in the literature obtained from morphological and molecular data for three genera and the model can be used to project other diterpenes. Therefore, the model produced can predict which genera are likely to contain a compound. (author)

SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance.

Science.gov (United States)

Sacha, Dominik; Kraus, Matthias; Bernard, Jurgen; Behrisch, Michael; Schreck, Tobias; Asano, Yuki; Keim, Daniel A

2018-01-01

Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.

Classification of passive auditory event-related potentials using discriminant analysis and self-organizing feature maps.

Science.gov (United States)

Schönweiler, R; Wübbelt, P; Tolloczko, R; Rose, C; Ptok, M

2000-01-01

Discriminant analysis (DA) and self-organizing feature maps (SOFM) were used to classify passively evoked auditory event-related potentials (ERP) P(1), N(1), P(2) and N(2). Responses from 16 children with severe behavioral auditory perception deficits, 16 children with marked behavioral auditory perception deficits, and 14 controls were examined. Eighteen ERP amplitude parameters were selected for examination of statistical differences between the groups. Different DA methods and SOFM configurations were trained to the values. SOFM had better classification results than DA methods. Subsequently, measures on another 37 subjects that were unknown for the trained SOFM were used to test the reliability of the system. With 10-dimensional vectors, reliable classifications were obtained that matched behavioral auditory perception deficits in 96%, implying central auditory processing disorder (CAPD). The results also support the assumption that CAPD includes a 'non-peripheral' auditory processing deficit. Copyright 2000 S. Karger AG, Basel.

PREFACE: Self-organized nanostructures

Science.gov (United States)

Rousset, Sylvie; Ortega, Enrique

2006-04-01

the EUROCORES SONS Programme under the auspices of the European Science Foundation and the VI Framework Programme of the European Community. It was also funded by CNRS `formation permanente'. Major topics relevant to self-organization are covered in these papers. The first two papers deal with the physics of self-organized nucleation and growth. Both metal and semiconductor templates are investigated. The paper by Meyer zu Heringdorf focuses on the mesoscopic patterns formed by the Au-induced faceting of vicinal Si (001). Repain et al describe how uniform and long-range ordered nanostructures are built on a surface by using nucleation on a point-defect array. Electronic properties of such self-organized systems are reviewed by Mugarza and Ortega. The next three papers deal with molecules and self-organization. In the paper presented by Kröger, molecules are deposited on vicinal Au surfaces and are studied by STM. A very active field in self-organized nanostructures is the chemical route for nanoparticle synthesis. The paper by Piléni deals with self-organization of inorganic crystals produced by evaporation of a solution, also called colloids. Their physical properties are also treated. Gacoin et al illustrate chemical synthesis, including the template approach, using organized mesoporous silica films for the production of semiconductor or metal arrays of particles. An alternative method is developed in the paper by Allongue and Maroun which is the electrochemical method of building arrays of nanostructures. Ultimately, self-organization is a very interdisciplinary field. There is also an attempt in this issue to present some of the challenges using biology. The paper by Belamie et al deals with the self-assembly of biological macromolecules, such as chitin and collagen. Finally, Molodtsov and co-workers describe how a biological template can be used in order to achieve novel materials made of hybrid metallo-organic nanostructures.

High-resolution charge carrier mobility mapping of heterogeneous organic semiconductors

Science.gov (United States)

Button, Steven W.; Mativetsky, Jeffrey M.

2017-08-01

Organic electronic device performance is contingent on charge transport across a heterogeneous landscape of structural features. Methods are therefore needed to unravel the effects of local structure on overall electrical performance. Using conductive atomic force microscopy, we construct high-resolution out-of-plane hole mobility maps from arrays of 5000 to 16 000 current-voltage curves. To demonstrate the efficacy of this non-invasive approach for quantifying and mapping local differences in electrical performance due to structural heterogeneities, we investigate two thin film test systems, one bearing a heterogeneous crystal structure [solvent vapor annealed 5,11-Bis(triethylsilylethynyl)anthradithiophene (TES-ADT)—a small molecule organic semiconductor] and one bearing a heterogeneous chemical composition [p-DTS(FBTTh2)2:PC71BM—a high-performance organic photovoltaic active layer]. TES-ADT shows nearly an order of magnitude difference in hole mobility between semicrystalline and crystalline areas, along with a distinct boundary between the two regions, while p-DTS(FBTTh2)2:PC71BM exhibits subtle local variations in hole mobility and a nanoscale domain structure with features below 10 nm in size. We also demonstrate mapping of the built-in potential, which plays a significant role in organic light emitting diode and organic solar cell operation.

A Electronic Map Data Model Based on PDF

Science.gov (United States)

Zhou, Xiaodong; Yang, Chuncheng; Meng, Nina; Peng, Peng

2018-05-01

In this paper, we proposed the PDFEMAP (PDF electronic map) that is a kind of new electronic map products aiming at the current situation and demand of the use of electronic map products. Firstly gives the definition and characteristics of PDFEMAP, followed by a detailed description of the data model and method for generating PDFEMAP, and finally expounds application modes of the PDFEMAP which feasibility and effectiveness are verified.

Self-organization observed in either fusion or strongly coupled plasmas

International Nuclear Information System (INIS)

Himura, Haruhiko; Sanpei, Akio

2011-01-01

If self-organization happens in the fusion plasma, the plasma alters its shape by weakening the confining magnetic field. The self-organized plasma is stable and robust, so its configuration is conserved even during transport in asymmetric magnetic fields. The self-organization of the plasma is driven by an electrostatic potential. Examples of the plasma that has such strong potential are non-neutral plasmas of pure ions or electrons and dusty plasmas. In the present paper, characteristic phenomena of strongly coupled plasmas such as particle aggregation and formation of the ordered structure are discussed. (T.I.)

Content-based image retrieval using a signature graph and a self-organizing map

Directory of Open Access Journals (Sweden)

Van Thanh The

2016-06-01

Full Text Available In order to effectively retrieve a large database of images, a method of creating an image retrieval system CBIR (contentbased image retrieval is applied based on a binary index which aims to describe features of an image object of interest. This index is called the binary signature and builds input data for the problem of matching similar images. To extract the object of interest, we propose an image segmentation method on the basis of low-level visual features including the color and texture of the image. These features are extracted at each block of the image by the discrete wavelet frame transform and the appropriate color space. On the basis of a segmented image, we create a binary signature to describe the location, color and shape of the objects of interest. In order to match similar images, we provide a similarity measure between the images based on binary signatures. Then, we present a CBIR model which combines a signature graph and a self-organizing map to cluster and store similar images. To illustrate the proposed method, experiments on image databases are reported, including COREL,Wang and MSRDI.

Electron dose map inversion based on several algorithms

International Nuclear Information System (INIS)

Li Gui; Zheng Huaqing; Wu Yican; Fds Team

2010-01-01

The reconstruction to the electron dose map in radiation therapy was investigated by constructing the inversion model of electron dose map with different algorithms. The inversion model of electron dose map based on nonlinear programming was used, and this model was applied the penetration dose map to invert the total space one. The realization of this inversion model was by several inversion algorithms. The test results with seven samples show that except the NMinimize algorithm, which worked for just one sample, with great error,though,all the inversion algorithms could be realized to our inversion model rapidly and accurately. The Levenberg-Marquardt algorithm, having the greatest accuracy and speed, could be considered as the first choice in electron dose map inversion.Further tests show that more error would be created when the data close to the electron range was used (tail error). The tail error might be caused by the approximation of mean energy spectra, and this should be considered to improve the method. The time-saving and accurate algorithms could be used to achieve real-time dose map inversion. By selecting the best inversion algorithm, the clinical need in real-time dose verification can be satisfied. (authors)

Implementation of Self Organizing Map (SOM) as decision support: Indonesian telematics services MSMEs empowerment

Science.gov (United States)

Tosida, E. T.; Maryana, S.; Thaheer, H.; Hardiani

2017-01-01

Information technology and communication (telematics) is one of the most rapidly developing business sectors in Indonesia. It has strategic position in its contribution towards planning and implementation of developmental, economics, social, politics and defence strategies in business, communication and education. Aid absorption for the national telecommunication SMEs is relatively low; therefore, improvement is needed using analysis on business support cluster of which basis is types of business. In the study, the business support cluster analysis is specifically implemented for Indonesian telecommunication service. The data for the business are obtained from the National Census of Economic (Susenas 2006). The method used to develop cluster model is an Artificial Neural Network (ANN) system called Self-Organizing Maps (SOM) algorithm. Based on Index of Davies Bouldin (IDB), the accuracy level of the cluster model is 0.37 or can be categorized as good. The cluster model is developed to find out telecommunication business clusters that has influence towards the national economy so that it is easier for the government to supervise telecommunication business.

Elemental mapping in scanning transmission electron microscopy

International Nuclear Information System (INIS)

Allen, L J; D'Alfonso, A J; Lugg, N R; Findlay, S D; LeBeau, J M; Stemmer, S

2010-01-01

We discuss atomic resolution chemical mapping in scanning transmission electron microscopy (STEM) based on core-loss electron energy loss spectroscopy (EELS) and also on energy dispersive X-ray (EDX) imaging. Chemical mapping using EELS can yield counterintuitive results which, however, can be understood using first principles calculations. Experimental chemical maps based on EDX bear out the thesis that such maps are always likely to be directly interpretable. This can be explained in terms of the local nature of the effective optical potential for ionization under those imaging conditions. This is followed by an excursion into the complementary technique of elemental mapping using energy-filtered transmission electron microscopy (EFTEM) in a conventional transmission electron microscope. We will then consider the widely used technique of Z-contrast or high-angle annular dark field (HAADF) imaging, which is based on phonon excitation, where it has recently been shown that intensity variations can be placed on an absolute scale by normalizing the measured intensities to the incident beam. Results, showing excellent agreement between theory and experiment to within a few percent, are shown for Z-contrast imaging from a sample of PbWO 4 .

An effective self-assessment based on concept map extraction from test-sheet for personalized learning

Science.gov (United States)

Liew, Keng-Hou; Lin, Yu-Shih; Chang, Yi-Chun; Chu, Chih-Ping

2013-12-01

Examination is a traditional way to assess learners' learning status, progress and performance after a learning activity. Except the test grade, a test sheet hides some implicit information such as test concepts, their relationships, importance, and prerequisite. The implicit information can be extracted and constructed a concept map for considering (1) the test concepts covered in the same question means these test concepts have strong relationships, and (2) questions in the same test sheet means the test concepts are relative. Concept map has been successfully employed in many researches to help instructors and learners organize relationships among concepts. However, concept map construction depends on experts who need to take effort and time for the organization of the domain knowledge. In addition, the previous researches regarding to automatic concept map construction are limited to consider all learners of a class, which have not considered personalized learning. To cope with this problem, this paper proposes a new approach to automatically extract and construct concept map based on implicit information in a test sheet. Furthermore, the proposed approach also can help learner for self-assessment and self-diagnosis. Finally, an example is given to depict the effectiveness of proposed approach.

Chemotaxonomy of three genera of the Annonaceae family using self-organizing maps and {sup 13}C NMR data of diterpenes

Energy Technology Data Exchange (ETDEWEB)

Scotti, Luciana; Tavares, Josean Fechine; Silva, Marcelo Sobral da [Universidade Federal da Paraiba (UFPB), Joao Pessoa, PB (Brazil). Dept. de Ciencias Farmaceuticas; Falcao, Emanuela Viana; Silva, Luana de Morais e; Soares, Gabriela Cristina da Silva; Scotti, Marcus Tullius, E-mail: mtscotti@ccae.ufpb.br [Universidade Federal da Paraiba (UFPB), Rio Tinto, PB (Brazil). Dept. de Engenharia e Meio Ambiente

2012-07-01

The Annonaceae family is distributed throughout Neotropical regions of the world. In Brazil, it covers nearly all natural formations particularly Annona, Xylopia and Polyalthia and is characterized chemically by the production of sources of terpenoids (mainly diterpenes), alkaloids, steroids, polyphenols and, flavonoids. Studies from {sup 13}C NMR data of diterpenes related with their botanical occurrence were used to generate self-organizing maps. Results corroborate those in the literature obtained from morphological and molecular data for three genera and the model can be used to project other diterpenes. Therefore, the model produced can predict which genera are likely to contain a compound. (author)

Self-organizing plasmas

International Nuclear Information System (INIS)

Hayashi, T.; Sato, T.

1999-01-01

The primary purpose of this paper is to extract a grand view of self-organization through an extensive computer simulation of plasmas. The assertion is made that self-organization is governed by three key processes, i.e. the existence of an open complex system, the existence of information (energy) sources and the existence of entropy generation and expulsion processes. We find that self-organization takes place in an intermittent fashion when energy is supplied continuously from outside. In contrast, when the system state is suddenly changed into a non-equilibrium state externally, the system evolves stepwise and reaches a minimum energy state. We also find that the entropy production rate is maximized whenever a new ordered structure is created and that if the entropy generated during the self-organizing process is expelled from the system, then the self-organized structure becomes more prominent and clear. (author)

Patterns identification in supervisory systems of nuclear reactors installations and gas pipelines systems using self-organizing maps

International Nuclear Information System (INIS)

Doraskevicius Junior, Waldemar

2005-01-01

Self-Organizing Maps, SOM, of Kohonen were studied, implemented and tested with the aim of developing, for the energy branch, an effective tool especially for transient identification in nuclear reactors and for gas pipelines networks logistic supervision, by classifying operations and identifying transients or abnormalities. The digital system for the test was developed in Java platform, for the portability and scalability, and for belonging to free development platforms. The system, executed in personal computers, showed satisfactory results to aid in decision taking, by classifying IRIS (International Reactor Innovative and Secure) reactor operation conditions (data from simulator) and by classifying Southeast (owner: TRANSPETRO - Brazil) gas pipeline network. Various adaptations were needed for such business, as new topologies for the output layer of artificial neural network and particular preparation for the input data. (author)

Biomimetic self-assembly of a functional asymmetrical electronic device.

Science.gov (United States)

Boncheva, Mila; Gracias, David H; Jacobs, Heiko O; Whitesides, George M

2002-04-16

This paper introduces a biomimetic strategy for the fabrication of asymmetrical, three-dimensional electronic devices modeled on the folding of a chain of polypeptide structural motifs into a globular protein. Millimeter-size polyhedra-patterned with logic devices, wires, and solder dots-were connected in a linear string by using flexible wire. On self-assembly, the string folded spontaneously into two domains: one functioned as a ring oscillator, and the other one as a shift register. This example demonstrates that biomimetic principles of design and self-organization can be applied to generate multifunctional electronic systems of complex, three-dimensional architecture.

Real-space mapping of electronic orbitals

Energy Technology Data Exchange (ETDEWEB)

Löffler, Stefan, E-mail: stefan.loeffler@tuwien.ac.at [Department for Materials Science and Engineering, McMaster University, 1280 Main Street West, L8S 4M1 Hamilton, Ontario (Canada); University Service Centre for Transmission Electron Microscopy, TU Vienna, Wiedner Hauptstraße 8-10/E057B, 1040 Wien (Austria); Institute for Solid State Physics, TU Vienna, Wiedner Hauptstraße 8-10/E138, 1040 Wien (Austria); Bugnet, Matthieu; Gauquelin, Nicolas [Department for Materials Science and Engineering, McMaster University, 1280 Main Street West, L8S 4M1 Hamilton, Ontario (Canada); Lazar, Sorin [FEI Electron Optics, Achtseweg Noord 5, 5651 GG Eindhoven (Netherlands); Assmann, Elias; Held, Karsten [Institute for Solid State Physics, TU Vienna, Wiedner Hauptstraße 8-10/E138, 1040 Wien (Austria); Botton, Gianluigi A. [Department for Materials Science and Engineering, McMaster University, 1280 Main Street West, L8S 4M1 Hamilton, Ontario (Canada); Schattschneider, Peter [University Service Centre for Transmission Electron Microscopy, TU Vienna, Wiedner Hauptstraße 8-10/E057B, 1040 Wien (Austria); Institute for Solid State Physics, TU Vienna, Wiedner Hauptstraße 8-10/E138, 1040 Wien (Austria)

2017-06-15

Highlights: • Electronic orbitals in Rutile are mapped using STEM-EELS. • Inelastic scattering simulations are performed for the experimental conditions. • The experiments and the simulations are found to be in excellent agreement. - Abstract: Electronic states are responsible for most material properties, including chemical bonds, electrical and thermal conductivity, as well as optical and magnetic properties. Experimentally, however, they remain mostly elusive. Here, we report the real-space mapping of selected transitions between p and d states on the Ångström scale in bulk rutile (TiO{sub 2}) using electron energy-loss spectrometry (EELS), revealing information on individual bonds between atoms. On the one hand, this enables the experimental verification of theoretical predictions about electronic states. On the other hand, it paves the way for directly investigating electronic states under conditions that are at the limit of the current capabilities of numerical simulations such as, e.g., the electronic states at defects, interfaces, and quantum dots.

Self-organizing maps applied to two-phase flow on natural circulation loop study

International Nuclear Information System (INIS)

Castro, Leonardo Ferreira

2016-01-01

Two-phase flow of liquid and gas is found in many closed circuits using natural circulation for cooling purposes. Natural circulation phenomenon is important on recent nuclear power plant projects for decay heat removal. The Natural Circulation Facility (Circuito de Circulacao Natural CCN) installed at Instituto de Pesquisas Energeticas e Nucleares, IPEN/CNEN, is an experimental circuit designed to provide thermal hydraulic data related to single and two-phase flow under natural circulation conditions. This periodic flow oscillation behavior can be observed thoroughly in this facility due its glass-made tubes transparency. The heat transfer estimation has been improved based on models that require precise prediction of pattern transitions of flow. This work presents experiments realized at CCN to visualize natural circulation cycles in order to classify two-phase flow patterns associated with phase transients and static instabilities of flow. Images are compared and clustered using Kohonen Self-organizing Maps (SOM's) applied on different digital image features. The Full Frame Discret Cosine Transform (FFDCT) coefficients were used as input for the classification task, enabling good results. FFDCT prototypes obtained can be associated to each flow pattern, enabling a better comprehension of each observed instability. A systematic test methodology was used to verify classifier robustness.

Covariance and correlation estimation in electron-density maps.

Science.gov (United States)

Altomare, Angela; Cuocci, Corrado; Giacovazzo, Carmelo; Moliterni, Anna; Rizzi, Rosanna

2012-03-01

Quite recently two papers have been published [Giacovazzo & Mazzone (2011). Acta Cryst. A67, 210-218; Giacovazzo et al. (2011). Acta Cryst. A67, 368-382] which calculate the variance in any point of an electron-density map at any stage of the phasing process. The main aim of the papers was to associate a standard deviation to each pixel of the map, in order to obtain a better estimate of the map reliability. This paper deals with the covariance estimate between points of an electron-density map in any space group, centrosymmetric or non-centrosymmetric, no matter the correlation between the model and target structures. The aim is as follows: to verify if the electron density in one point of the map is amplified or depressed as an effect of the electron density in one or more other points of the map. High values of the covariances are usually connected with undesired features of the map. The phases are the primitive random variables of our probabilistic model; the covariance changes with the quality of the model and therefore with the quality of the phases. The conclusive formulas show that the covariance is also influenced by the Patterson map. Uncertainty on measurements may influence the covariance, particularly in the final stages of the structure refinement; a general formula is obtained taking into account both phase and measurement uncertainty, valid at any stage of the crystal structure solution.

Performance Comparison of Reputation Assessment Techniques Based on Self-Organizing Maps in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Sabrina Sicari

2017-01-01

Full Text Available Many solutions based on machine learning techniques have been proposed in literature aimed at detecting and promptly counteracting various kinds of malicious attack (data violation, clone, sybil, neglect, greed, and DoS attacks, which frequently affect Wireless Sensor Networks (WSNs. Besides recognizing the corrupted or violated information, also the attackers should be identified, in order to activate the proper countermeasures for preserving network’s resources and to mitigate their malicious effects. To this end, techniques adopting Self-Organizing Maps (SOM for intrusion detection in WSN were revealed to represent a valuable and effective solution to the problem. In this paper, the mechanism, namely, Good Network (GoNe, which is based on SOM and is able to assess the reliability of the sensor nodes, is compared with another relevant and similar work existing in literature. Extensive performance simulations, in terms of nodes’ classification, attacks’ identification, data accuracy, energy consumption, and signalling overhead, have been carried out in order to demonstrate the better feasibility and efficiency of the proposed solution in WSN field.

Self-organizing map analysis using multivariate data from theophylline powders predicted by a thin-plate spline interpolation.

Science.gov (United States)

Yasuda, Akihito; Onuki, Yoshinori; Kikuchi, Shingo; Takayama, Kozo

2010-11-01

The quality by design concept in pharmaceutical formulation development requires establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline powders were prepared based on the standard formulation. The angle of repose, compressibility, cohesion, and dispersibility were measured as the response variables. These responses were predicted quantitatively on the basis of a nonlinear TPS. A large amount of data on these powders was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the powders could be classified into several distinctive clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and powder characteristics. For instance, the quantities of microcrystalline cellulose (MCC) and magnesium stearate (Mg-St) were classified distinctly into each cluster, indicating that the quantities of MCC and Mg-St were crucial for determining the powder characteristics. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline powder formulations. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Self-Mapping in Treating Suicide Ideation: A Case Study

Science.gov (United States)

Robertson, Lloyd Hawkeye

2011-01-01

This case study traces the development and use of a self-mapping exercise in the treatment of a youth who had been at risk for re-attempting suicide. A life skills exercise was modified to identify units of culture called "memes" from which a map of the youth's self was prepared. A successful treatment plan followed the mapping exercise. The…

75 FR 63878 - Self-Regulatory Organizations; Self-Regulatory Organizations; Notice of Filing and Immediate...

Science.gov (United States)

2010-10-18

...-Regulatory Organizations; Self-Regulatory Organizations; Notice of Filing and Immediate Effectiveness of...(b)(1). \\2\\ 17 CFR 240.19b-4. I. Self-Regulatory Organization's Statement of the Terms of Substance... Public Reference Room. II. Self-Regulatory Organization's Statement of the Purpose of, and Statutory...

Application Self-organizing Map Type in a Study of the Profile of Gasoline C Commercialized in the Eastern and Northern Parana Regions

Directory of Open Access Journals (Sweden)

Lívia Ramazzoti Silva

2015-06-01

Full Text Available Artificial neural networks self-organizing map type (SOM was used to classify samples of automotive gasoline C marketed in the eastern and northern regions of the state of Paraná, Brazil. The input order of parameters in the network were the values of temperature of the first drop, the 10, 50 and 90% distilled bulk, the final boiling point, density, residue content and alcohol content. A network with a topology of 25x25 and 5000 training epochs was used. The weight maps of input parameters for the trained network identified that the most important parameters for classifying samples were the temperature of the first drop and the temperature of the 10% and 50% of the distilled fuel. DOI: http://dx.doi.org/10.17807/orbital.v7i2.732 

Adopting of Agile methods in Software Development Organizations: Systematic Mapping

Directory of Open Access Journals (Sweden)

Samia Abdalhamid

2017-11-01

Full Text Available Adoption of agile methods in the software development organization is considered as a powerful solution to deal with the quickly changing and regularly developing business environment and fully-educated customers with constantly rising expectation, such as shorter time periods and an extraordinary level of response and service. This study investigates the adoption of agile approaches in software development organizations by using systematic mapping. Six research questions are identified, and to answer these questions a number of research papers have been reviewed in electronic databases. Finally, 25 research papers are examined and answers to all research questions are provided.

Quantitative microstructure characterization of self-annealed copper films with electron backscatter diffraction

DEFF Research Database (Denmark)

Pantleon, Karen; Gholinia, A.; Somers, Marcel A. J.

2008-01-01

Electron backscatter diffraction (EBSD) was applied to analyze cross sections of self-annealed copper electrodeposits, for which earlier the kinetics of self-annealing had been investigated by in-situ X-ray diffraction (XRD). The EBSD investigations on the grain size, grain boundary character...... and crystallographic texture of copper films with different thicknesses essentially supplement results from in-situ XRD. Twin relations between neighboring grains were identified from the orientation maps and the observed twin chains confirm multiple twinning in copper electrodeposits as the mechanism...

Applications of Self-Organizing Maps for Ecomorphological Investigations through Early Ontogeny of Fish

Science.gov (United States)

Russo, Tommaso; Scardi, Michele; Cataudella, Stefano

2014-01-01

We propose a new graphical approach to the analysis of multi-temporal morphological and ecological data concerning the life history of fish, which can typically serves models in ecomorphological investigations because they often undergo significant ontogenetic changes. These changes can be very complex and difficult to describe, so that visualization, abstraction and interpretation of the underlying relationships are often impeded. Therefore, classic ecomorphological analyses of covariation between morphology and ecology, performed by means of multivariate techniques, may result in non-exhaustive models. The Self Organizing map (SOM) is a new, effective approach for pursuing this aim. In this paper, lateral outlines of larval stages of gilthead sea bream (Sparus aurata) and dusky grouper (Epinephelus marginatus) were recorded and broken down using by means of Elliptic Fourier Analysis (EFA). Gut contents of the same specimens were also collected and analyzed. Then, shape and trophic habits data were examined by SOM, which allows both a powerful visualization of shape changes and an easy comparison with trophic habit data, via their superimposition onto the trained SOM. Thus, the SOM provides a direct visual approach for matching morphological and ecological changes during fish ontogenesis. This method could be used as a tool to extract and investigate relationships between shape and other sinecological or environmental variables, which cannot be taken into account simultaneously using conventional statistical methods. PMID:24466185

Adaptive monitoring of emissions in energy boilers using self-organizing maps: An application to a biomass-fired CFB (circulating fluidized bed)

International Nuclear Information System (INIS)

Liukkonen, M.; Hiltunen, T.

2014-01-01

Improvement of energy efficiency, reduction of operating costs, and reduction of harmful emissions released into the atmosphere are issues of major concern in modern energy plants. While air emissions have to be restricted due to tightening environmental legislation, at the same time it is ever more important to be able to respond quickly to any changes in the load demand or fuel quality. As unpredictability increases with changing fuel quality and more complex operational strategies, undesired phenomena such as increased emission release rates may become more likely. Therefore, it is crucial that emission monitoring systems are able to adapt to varying conditions, and advanced methodologies are needed for monitoring and decision-support. In this paper a novel approach for advanced monitoring of emissions in CFB (circulating fluidized bed) boilers is described. In this approach a model based on SOM (self-organizing maps) is updated regularly to respond to the prevailing condition of the boiler. After creating each model a new set of measurements is input to the system, and the current state of the process is determined using vector distance calculation. Finally, the system evaluates the current condition and may alert if a preset limit defined for each emission component is exceeded. - Highlights: • An adaptive monitoring approach based on self-organizing maps is presented. • The system can monitor the current state of a combustion process and its emissions. • The system is designed to alert when the preset limits defined for emissions are exceeded. • Due to regular updating routine the system is able to adapt to changing conditions. • The application is demonstrated using data from a biomass-fired energy boiler

The Performance of the Smart Cities in China—A Comparative Study by Means of Self-Organizing Maps and Social Networks Analysis

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Dong Lu

2015-06-01

Full Text Available Smart cities link the city services, citizens, resource and infrastructures together and form the heart of the modern society. As a “smart” ecosystem, smart cities focus on sustainable growth, efficiency, productivity and environmentally friendly development. By comparing with the European Union, North America and other countries, smart cities in China are still in the preliminary stage. This study offers a comparative analysis of ten smart cities in China on the basis of an extensive database covering two time periods: 2005–2007 and 2008–2010. The unsupervised computational neural network self-organizing map (SOM analysis is adopted to map out the various cities based on their performance. The demonstration effect and mutual influences between these ten smart cities are also discussed by using social network analysis. Based on the smart city performance and cluster network, current problems for smart city development in China were pointed out. Future research directions for smart city research are discussed at the end this paper.

Self-organizing map analysis using multivariate data from theophylline tablets predicted by a thin-plate spline interpolation.

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Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Yamamoto, Rie; Takayama, Kozo

2013-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared based on a standard formulation. The tensile strength, disintegration time, and stability of these variables were measured as response variables. These responses were predicted quantitatively based on nonlinear TPS. A large amount of data on these tablets was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the tablets were classified into several distinct clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and tablet characteristics. The results of this study suggest that increasing the proportion of microcrystalline cellulose (MCC) improved the tensile strength and the stability of tensile strength of these theophylline tablets. In addition, the proportion of MCC has an optimum value for disintegration time and stability of disintegration. Increasing the proportion of magnesium stearate extended disintegration time. Increasing the compression force improved tensile strength, but degraded the stability of disintegration. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulations.

Ordination of self-organizing feature map neural networks and its application to the study of plant communities

Institute of Scientific and Technical Information of China (English)

Jintun ZHANG; Dongping MENG; Yuexiang XI

2009-01-01

A self-organizing feature map (SOFM) neural network is a powerful tool in analyzing and solving complex, non-linear problems. According to its features, a SOFM is entirely compatible with ordination studies of plant communities. In our present work, mathematical principles, and ordination techniques and procedures are introduced. A SOFM ordination was applied to the study of plant communities in the middle of the Taihang mountains. The ordination was carried out by using the NNTool box in MATLAB. The results of 68 quadrats of plant communities were distributed in SOFM space. The ordination axes showed the ecological gradients clearly and provided the relationships between communities with ecological meaning. The results are consistent with the reality of vegetation in the study area. This suggests that SOFM ordination is an effective technique in plant ecology. During ordination procedures, it is easy to carry out clustering of communities and so it is beneficial for combining classification and ordination in vegetation studies.

Temporal Comparison Between NIRS and EEG Signals During a Mental Arithmetic Task Evaluated with Self-Organizing Maps.

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Oyama, Katsunori; Sakatani, Kaoru

2016-01-01

Simultaneous monitoring of brain activity with near-infrared spectroscopy and electroencephalography allows spatiotemporal reconstruction of the hemodynamic response regarding the concentration changes in oxyhemoglobin and deoxyhemoglobin that are associated with recorded brain activity such as cognitive functions. However, the accuracy of state estimation during mental arithmetic tasks is often different depending on the length of the segment for sampling of NIRS and EEG signals. This study compared the results of a self-organizing map and ANOVA, which were both used to assess the accuracy of state estimation. We conducted an experiment with a mental arithmetic task performed by 10 participants. The lengths of the segment in each time frame for observation of NIRS and EEG signals were compared with the 30-s, 1-min, and 2-min segment lengths. The optimal segment lengths were different for NIRS and EEG signals in the case of classification of feature vectors into the states of performing a mental arithmetic task and being at rest.

Modeling Poroelastic Wave Propagation in a Real 2-D Complex Geological Structure Obtained via Self-Organizing Maps

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Itzá Balam, Reymundo; Iturrarán-Viveros, Ursula; Parra, Jorge O.

2018-03-01

Two main stages of seismic modeling are geological model building and numerical computation of seismic response for the model. The quality of the computed seismic response is partly related to the type of model that is built. Therefore, the model building approaches become as important as seismic forward numerical methods. For this purpose, three petrophysical facies (sands, shales and limestones) are extracted from reflection seismic data and some seismic attributes via the clustering method called Self-Organizing Maps (SOM), which, in this context, serves as a geological model building tool. This model with all its properties is the input to the Optimal Implicit Staggered Finite Difference (OISFD) algorithm to create synthetic seismograms for poroelastic, poroacoustic and elastic media. The results show a good agreement between observed and 2-D synthetic seismograms. This demonstrates that the SOM classification method enables us to extract facies from seismic data and allows us to integrate the lithology at the borehole scale with the 2-D seismic data.

Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015 Using Self-Organizing Maps

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Adeoluwa Akande

2017-01-01

Full Text Available The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

Self-interaction and charge transfer in organic semiconductors

Energy Technology Data Exchange (ETDEWEB)

Koerzdoerfer, Thomas

2009-12-18

This work concentrates on the problem of self-interaction, which is one of the most serious problems of commonly used approximative density functionals. As a major result of this work, it is demonstrated that self-interaction plays a decisive role for the performance of different approximative functionals in predicting accurate electronic properties of organic molecular semiconductors. In search for a solution to the self-interaction problem, a new concept for correcting commonly used density functionals for self-interaction is introduced and applied to a variety of systems, spanning small molecules, extended molecular chains, and organic molecular semiconductors. It is further shown that the performance of functionals that are not free from self-interaction can vary strongly for different systems and observables of interest, thus entailing the danger of misinterpretation of the results obtained from those functionals. The underlying reasons for the varying performance of commonly used density functionals are discussed thoroughly in this work. Finally, this thesis provides strategies that allow to analyze the reliability of commonly used approximations to the exchange-correlation functional for particular systems of interest. This cumulative dissertation is divided into three parts. Part I gives a short introduction into DFT and its time-dependent extension (TDDFT). Part II provides further insights into the self-interaction problem, presents a newly developed concept for the correction of self-interaction, gives an introduction into the publications, and discusses their basic results. Finally, the four publications on self-interaction and charge-transfer in extended molecular systems and organic molecular semiconductors are collected in Part III. (orig.)

Autonomous distributed self-organizing and self-healing hardware architecture - The eDNA concept

DEFF Research Database (Denmark)

Boesen, Michael Reibel; Madsen, Jan; Keymeulen, Didier

2011-01-01

This paper presents the current state of the autonomous distributed self-organizing and self-healing electronic DNA (eDNA) hardware architecture (patent pending). In its current prototype state, the eDNA architecture is capable of responding to multiple injected faults by autonomously reconfiguring...... itself to accommodate the fault and keep the application running. This paper will also disclose advanced features currently available in the simulation model only. These features are future work and will soon be implemented in hardware. Finally we will describe step-by-step how an application...

Visualization of amino acid composition differences between processed protein from different animal species by self-organizing feature maps

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Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN

2016-06-01

Full Text Available Amino acids are the dominant organic components of processed animal proteins, however there has been limited investigation of differences in their composition between various protein sources. Information on these differences will not only be helpful for their further utilization but also provide fundamental information for developing species-specific identification methods. In this study, self-organizing feature maps (SOFM were used to visualize amino acid composition of fish meal, and meat and bone meal (MBM produced from poultry, ruminants and swine. SOFM display the similarities and differences in amino acid composition between protein sources and effectively improve data transparency. Amino acid composition was shown to be useful for distinguishing fish meal from MBM due to their large concentration differences between glycine, lysine and proline. However, the amino acid composition of the three MBMs was quite similar. The SOFM results were consistent with those obtained by analysis of variance and principal component analysis but more straightforward. SOFM was shown to have a robust sample linkage capacity and to be able to act as a powerful means to link different sample for further data mining.

A simple electronic circuit realization of the tent map

Energy Technology Data Exchange (ETDEWEB)

Campos-Canton, I. [Fac. de Ciencias, Universidad Autonoma de San Luis Potosi, Alvaro Obregon 64, 78000 San Luis Potosi, SLP (Mexico)], E-mail: icampos@galia.fc.uaslp.mx; Campos-Canton, E. [Departamento de Fisico Matematicas, Universidad Autonoma de San Luis Potosi, Alvaro Obregon 64, 78000 San Luis Potosi, SLP (Mexico)], E-mail: ecamp@uaslp.mx; Murguia, J.S. [Departamento de Fisico Matematicas, Universidad Autonoma de San Luis Potosi, Alvaro Obregon 64, 78000 San Luis Potosi, SLP (Mexico)], E-mail: ondeleto@uaslp.mx; Rosu, H.C. [Division de Materiales Avanzados, Instituto Potosino de Investigacion Cientifica y Tecnologica, Camino a la presa San Jose 2055, 78216 San Luis Potosi, SLP (Mexico)], E-mail: hcr@ipicyt.edu.mx

2009-10-15

We present a very simple electronic implementation of the tent map, one of the best-known discrete dynamical systems. This is achieved by using integrated circuits and passive elements only. The experimental behavior of the tent map electronic circuit is compared with its numerical simulation counterpart. We find that the electronic circuit presents fixed points, periodicity, period doubling, chaos and intermittency that match with high accuracy the corresponding theoretical values.

Self-Organized Ni Nanocrystal Embedded in BaTiO3 Epitaxial Film

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Ge FF

2010-01-01

Full Text Available Abstract Ni nanocrystals (NCs were embedded in BaTiO3 epitaxial films using the laser molecular beam epitaxy. The processes involving the self-organization of Ni NCs and the epitaxial growth of BaTiO3 were discussed. With the in situ monitoring of reflection high-energy electron diffraction, the nanocomposite films were engineered controllably by the fine alternation of the self-organization of Ni NCs and the epitaxial growth of BaTiO3. The transmission electron microscopy and the X-ray diffraction characterization confirmed that the composite film consists of the Ni NCs layers alternating with the (001/(100-oriented epitaxial BaTiO3 separation layers.

Toward control of the metal-organic interfacial electronic structure in molecular electronics: a first-principles study on self-assembled monolayers of pi-conjugated molecules on noble metals.

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Heimel, Georg; Romaner, Lorenz; Zojer, Egbert; Brédas, Jean-Luc

2007-04-01

Self-assembled monolayers (SAMs) of organic molecules provide an important tool to tune the work function of electrodes in plastic electronics and significantly improve device performance. Also, the energetic alignment of the frontier molecular orbitals in the SAM with the Fermi energy of a metal electrode dominates charge transport in single-molecule devices. On the basis of first-principles calculations on SAMs of pi-conjugated molecules on noble metals, we provide a detailed description of the mechanisms that give rise to and intrinsically link these interfacial phenomena at the atomic level. The docking chemistry on the metal side of the SAM determines the level alignment, while chemical modifications on the far side provide an additional, independent handle to modify the substrate work function; both aspects can be tuned over several eV. The comprehensive picture established in this work provides valuable guidelines for controlling charge-carrier injection in organic electronics and current-voltage characteristics in single-molecule devices.

Discovery of possible gene relationships through the application of self-organizing maps to DNA microarray databases.

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Chavez-Alvarez, Rocio; Chavoya, Arturo; Mendez-Vazquez, Andres

2014-01-01

DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques--an unsupervised artificial neural network called a Self-Organizing Map (SOM)-which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms.

Thiazole-based organic semiconductors for organic electronics.

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Lin, Yuze; Fan, Haijun; Li, Yongfang; Zhan, Xiaowei

2012-06-19

Over the past two decades, organic semiconductors have been the subject of intensive academic and commercial interests. Thiazole is a common electron-accepting heterocycle due to electron-withdrawing nitrogen of imine (C=N), several moieties based on thiazole have been widely introduced into organic semiconductors, and yielded high performance in organic electronic devices. This article reviews recent developments in the area of thiazole-based organic semiconductors, particularly thiazole, bithiazole, thiazolothiazole and benzobisthiazole-based small molecules and polymers, for applications in organic field-effect transistors, solar cells and light-emitting diodes. The remaining problems and challenges, and the key research direction in near future are discussed. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Brain Basis of Self: Self-Organization and Lessons from Dreaming

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David eKahn

2013-07-01

Full Text Available Through dreaming a different facet of the self is created as a result of a self-organizing process in the brain. Self-organization in biological systems often happens as an answer to an environmental change for which the existing system cannot cope; self-organization creates a system that can cope in the newly changed environment. In dreaming, self-organization serves the function of organizing disparate memories into a dream since the dreamer herself is not able to control how individual memories become weaved into a dream. The self-organized dream provides, thereby, a wide repertoire of experiences; this expanded repertoire of experience results in an expansion of the self beyond that obtainable when awake. Since expression of the self is associated with activity in specific areas of the brain, the article also discusses the brain basis of the self by reviewing studies of brain injured patients, discussing brain imaging studies in normal brain functioning when focused, when daydreaming and when asleep and dreaming.

Clustering self-organizing maps (SOM) method for human papillomavirus (HPV) DNA as the main cause of cervical cancer disease

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Bustamam, A.; Aldila, D.; Fatimah, Arimbi, M. D.

2017-07-01

One of the most widely used clustering method, since it has advantage on its robustness, is Self-Organizing Maps (SOM) method. This paper discusses the application of SOM method on Human Papillomavirus (HPV) DNA which is the main cause of cervical cancer disease, the most dangerous cancer in developing countries. We use 18 types of HPV DNA-based on the newest complete genome. By using open-source-based program R, clustering process can separate 18 types of HPV into two different clusters. There are two types of HPV in the first cluster while 16 others in the second cluster. The analyzing result of 18 types HPV based on the malignancy of the virus (the difficultness to cure). Two of HPV types the first cluster can be classified as tame HPV, while 16 others in the second cluster are classified as vicious HPV.

Kinetic Monte Carlo Modeling of Charge Carriers in Organic Electronic Devices: Suppression of the Self-Interaction Error

KAUST Repository

Li, Haoyuan

2017-05-18

Kinetic Monte Carlo (KMC) simulations have emerged as an important tool to help improve the efficiency of organic electronic devices by providing a better understanding of their device physics. In the KMC simulation of an organic device, the reliability of the results depends critically on the accuracy of the chosen charge-transfer rates, which are themselves strongly influenced by the site-energy differences. These site-energy differences include components coming from the electrostatic forces present in the system, which are often evaluated through electric potentials described by the Poisson equation. Here we show that the charge-carrier self-interaction errors that appear when evaluating the site-energy differences can lead to unreliable simulation results. To eliminate these errors, we propose two approaches that are also found to reduce the impact of finite-size effects. As a consequence, reliable results can be obtained at reduced computational costs. The proposed methodologies can be extended to other device simulation techniques as well.

Spiking neurons in a hierarchical self-organizing map model can learn to develop spatial and temporal properties of entorhinal grid cells and hippocampal place cells.

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Praveen K Pilly

Full Text Available Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous

Contractive type non-self mappings on metric spaces of hyperbolic type

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Ciric, Ljubomir B.

2006-05-01

Let (X,d) be a metric space of hyperbolic type and K a nonempty closed subset of X. In this paper we study a class of mappings from K into X (not necessarily self-mappings on K), which are defined by the contractive condition (2.1) below, and a class of pairs of mappings from K into X which satisfy the condition (2.28) below. We present fixed point and common fixed point theorems which are generalizations of the corresponding fixed point theorems of Ciric [L.B. Ciric, Quasi-contraction non-self mappings on Banach spaces, Bull. Acad. Serbe Sci. Arts 23 (1998) 25-31; L.B. Ciric, J.S. Ume, M.S. Khan, H.K.T. Pathak, On some non-self mappings, Math. Nachr. 251 (2003) 28-33], Rhoades [B.E. Rhoades, A fixed point theorem for some non-self mappings, Math. Japon. 23 (1978) 457-459] and many other authors. Some examples are presented to show that our results are genuine generalizations of known results from this area.

Atmospheric Convective Organization: Self-Organized Criticality or Homeostasis?

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Yano, Jun-Ichi

2015-04-01

Atmospheric convection has a tendency organized on a hierarchy of scales ranging from the mesoscale to the planetary scales, with the latter especially manifested by the Madden-Julian oscillation. The present talk examines two major possible mechanisms of self-organization identified in wider literature from a phenomenological thermodynamic point of view by analysing a planetary-scale cloud-resolving model simulation. The first mechanism is self-organized criticality. A saturation tendency of precipitation rate with the increasing column-integrated water, reminiscence of critical phenomena, indicates self-organized criticality. The second is a self-regulation mechanism that is known as homeostasis in biology. A thermodynamic argument suggests that such self-regulation maintains the column-integrated water below a threshold by increasing the precipitation rate. Previous analyses of both observational data as well as cloud-resolving model (CRM) experiments give mixed results. A satellite data analysis suggests self-organized criticality. Some observational data as well as CRM experiments support homeostasis. Other analyses point to a combination of these two interpretations. In this study, a CRM experiment over a planetary-scale domain with a constant sea-surface temperature is analyzed. This analysis shows that the relation between the column-integrated total water and precipitation suggests self-organized criticality, whereas the one between the column-integrated water vapor and precipitation suggests homeostasis. The concurrent presence of these two mechanisms are further elaborated by detailed statistical and budget analyses. These statistics are scale invariant, reflecting a spatial scaling of precipitation processes. These self-organization mechanisms are most likely be best theoretically understood by the energy cycle of the convective systems consisting of the kinetic energy and the cloud-work function. The author has already investigated the behavior of this

A Self-Organizing Map-Based Approach to Generating Reduced-Size, Statistically Similar Climate Datasets

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Cabell, R.; Delle Monache, L.; Alessandrini, S.; Rodriguez, L.

2015-12-01

Climate-based studies require large amounts of data in order to produce accurate and reliable results. Many of these studies have used 30-plus year data sets in order to produce stable and high-quality results, and as a result, many such data sets are available, generally in the form of global reanalyses. While the analysis of these data lead to high-fidelity results, its processing can be very computationally expensive. This computational burden prevents the utilization of these data sets for certain applications, e.g., when rapid response is needed in crisis management and disaster planning scenarios resulting from release of toxic material in the atmosphere. We have developed a methodology to reduce large climate datasets to more manageable sizes while retaining statistically similar results when used to produce ensembles of possible outcomes. We do this by employing a Self-Organizing Map (SOM) algorithm to analyze general patterns of meteorological fields over a regional domain of interest to produce a small set of "typical days" with which to generate the model ensemble. The SOM algorithm takes as input a set of vectors and generates a 2D map of representative vectors deemed most similar to the input set and to each other. Input predictors are selected that are correlated with the model output, which in our case is an Atmospheric Transport and Dispersion (T&D) model that is highly dependent on surface winds and boundary layer depth. To choose a subset of "typical days," each input day is assigned to its closest SOM map node vector and then ranked by distance. Each node vector is treated as a distribution and days are sampled from them by percentile. Using a 30-node SOM, with sampling every 20th percentile, we have been able to reduce 30 years of the Climate Forecast System Reanalysis (CFSR) data for the month of October to 150 "typical days." To estimate the skill of this approach, the "Measure of Effectiveness" (MOE) metric is used to compare area and overlap

Assessment of habitat conditions using Self-Organizing Feature Maps for reintroduction/introduction of Aldrovanda vesiculosa L. in Poland

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Piotr Kosiba

2011-07-01

Full Text Available The study objects were Aldrovanda vesiculosa L., an endangered species and fifty five water sites in Poland. The aim of the present work was to test the Self-Organizing Feature Map in order to examine and predict water properties and type of trophicity for restoration of the rare plant. Descriptive statistical parameters have been calculated, analysis of variance and cluster analysis were carried out and SOFM model has been constructed for analysed sites. The results of SOFM model and cluster analysis were compared. The study revealed that the ordination of individuals and groups of neurons in topological map of sites are similar in relation to dendrogram of cluster analysis, but not identical. The constructed SOFM model is related with significantly different contents of chemical water properties and type of trophicity. It appeared that sites with A. vesiculosa are predominantly distrophic and eutrophic waters shifted to distrophicity. The elevated model showed the sites with chemical properties favourable for restoration the species. Determined was the range of ecological tolerance of the species in relation to habitat conditions as stenotopic or relatively stenotopic in respect of the earlier accepted eutrophic status. The SOFM appeared to be a useful technique for ordination of ecological data and provides a novel framework for the discovery and forecasting of ecosystem properties constituting a validation of the SOFM method in this type of studies.

Organic molecules deposited on graphene: A computational investigation of self-assembly and electronic structure

International Nuclear Information System (INIS)

Oliveira, I. S. S. de; Miwa, R. H.

2015-01-01

We use ab initio simulations to investigate the adsorption and the self-assembly processes of tetracyanoquinodimethane (TCNQ), tetrafluoro-tetracyanoquinodimethane (F4-TCNQ), and tetrasodium 1,3,6,8-pyrenetetrasulfonic acid (TPA) on the graphene surface. We find that there are no chemical bonds at the molecule–graphene interface, even at the presence of grain boundaries on the graphene surface. The molecules bond to graphene through van der Waals interactions. In addition to the molecule–graphene interaction, we performed a detailed study of the role played by the (lateral) molecule–molecule interaction in the formation of the, experimentally verified, self-assembled layers of TCNQ and TPA on graphene. Regarding the electronic properties, we calculate the electronic charge transfer from the graphene sheet to the TCNQ and F4-TCNQ molecules, leading to a p-doping of graphene. Meanwhile, such charge transfer is reduced by an order of magnitude for TPA molecules on graphene. In this case, it is not expected a significant doping process upon the formation of self-assembled layer of TPA molecules on the graphene sheet

Classification of sediments by means of Self-Organizing Maps and sediment quality guidelines in sites of the southern Spanish coastline

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O. VESES

2013-08-01

Full Text Available This study was carried out to classify 112 marine and estuarine sites of the southern Spanish coastline (about 918 km long according to similar sediment characteristics by means of artificial neural networks (ANNs such as Self-Organizing Maps (SOM and sediment quality guidelines from a dataset consisted of 16 physical and chemical parameters including sediment granulometry, trace and major elements, total N and P and organic carbon content. The use of ANNs such as SOM made possible the classification of the sampling sites according to their similar chemical characteristics. Visual correlations between geochemical parameters were extracted due to the powerful visual characteristics (component planes of the SOM revealing that ANNs are an excellent tool to be incorporated in sediment quality assessments. Besides, almost 20% of the sites were classified as medium-high or high priority sites in order to take future remediation actions due to their high mean Effects Range-Median Quotient (m-ERMQ value. Priority sites included the estuaries of the major rivers (Tinto, Odiel, Palmones, etc. and several locations along the eastern coastline.

From self-organization to self-assembly: a new materialism?

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Vincent, Bernadette Bensaude

2016-09-01

While self-organization has been an integral part of academic discussions about the distinctive features of living organisms, at least since Immanuel Kant's Critique of Judgement, the term 'self-assembly' has only been used for a few decades as it became a hot research topic with the emergence of nanotechnology. Could it be considered as an attempt at reducing vital organization to a sort of assembly line of molecules? Considering the context of research on self-assembly I argue that the shift of attention from self-organization to self-assembly does not really challenge the boundary between chemistry and biology. Self-assembly was first and foremost investigated in an engineering context as a strategy for manufacturing without human intervention and did not raise new perspectives on the emergence of vital organization itself. However self-assembly implies metaphysical assumptions that this paper tries to disentangle. It first describes the emergence of self-assembly as a research field in the context of materials science and nanotechnology. The second section outlines the metaphysical implications and will emphasize a sharp contrast between the ontology underlying two practices of self-assembly developed under the umbrella of synthetic biology. And unexpectedly, we shall see that chemists are less on the reductionist side than most synthetic biologists. Finally, the third section ventures some reflections on the kind of design involved in self-assembly practices.

Navigating 3D electron microscopy maps with EM-SURFER.

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Esquivel-Rodríguez, Juan; Xiong, Yi; Han, Xusi; Guang, Shuomeng; Christoffer, Charles; Kihara, Daisuke

2015-05-30

The Electron Microscopy DataBank (EMDB) is growing rapidly, accumulating biological structural data obtained mainly by electron microscopy and tomography, which are emerging techniques for determining large biomolecular complex and subcellular structures. Together with the Protein Data Bank (PDB), EMDB is becoming a fundamental resource of the tertiary structures of biological macromolecules. To take full advantage of this indispensable resource, the ability to search the database by structural similarity is essential. However, unlike high-resolution structures stored in PDB, methods for comparing low-resolution electron microscopy (EM) density maps in EMDB are not well established. We developed a computational method for efficiently searching low-resolution EM maps. The method uses a compact fingerprint representation of EM maps based on the 3D Zernike descriptor, which is derived from a mathematical series expansion for EM maps that are considered as 3D functions. The method is implemented in a web server named EM-SURFER, which allows users to search against the entire EMDB in real-time. EM-SURFER compares the global shapes of EM maps. Examples of search results from different types of query structures are discussed. We developed EM-SURFER, which retrieves structurally relevant matches for query EM maps from EMDB within seconds. The unique capability of EM-SURFER to detect 3D shape similarity of low-resolution EM maps should prove invaluable in structural biology.

Using a Metro Map Metaphor for organizing Web-based learning resources

DEFF Research Database (Denmark)

Grønbæk, Kaj; Bang, Tove; Hansen, Per Steen

2002-01-01

This paper briefly describes the WebNize system and how it applies a Metro Map metaphor for organizing guided tours in Web based resources. Then, experiences in using the Metro Map based tours in a Knowledge Sharing project at the library at Aarhus School of Business (ASB) in Denmark, are discussed...... is to create models for Intelligent Knowledge Solutions that can contribute to form the learning environments of the School in the 21st century. The WebNize system is used for sharing of knowledge through metro maps for specific subject areas made available in the Learning Resource Centre at ASB. The metro....... The Library has been involved in establishing a Learning Resource Center (LRC). The LRC serves as an exploratorium for the development and the testing of new forms of communication and learning, at the same time as it integrates the information resources of the electronic research library. The objective...

Innovative Mechanism of Rural Organization Based on Self-Organization

OpenAIRE

Wang, Xing jin; Gao, Bing

2011-01-01

The paper analyzes the basic situation for the formation of innovative rural organizations with the form of self-organization; revels the features of self-organization, including the four aspects of openness of rural organization, innovation of rural organization is far away from equilibrium, the non-linear response mechanism of rural organization innovation and the random rise and fall of rural organization innovation. The evolution mechanism of rural organization innovation is reveled accor...

Self: an adaptive pressure arising from self-organization, chaotic dynamics, and neural Darwinism.

Science.gov (United States)

Bruzzo, Angela Alessia; Vimal, Ram Lakhan Pandey

2007-12-01

In this article, we establish a model to delineate the emergence of "self" in the brain making recourse to the theory of chaos. Self is considered as the subjective experience of a subject. As essential ingredients of subjective experiences, our model includes wakefulness, re-entry, attention, memory, and proto-experiences. The stability as stated by chaos theory can potentially describe the non-linear function of "self" as sensitive to initial conditions and can characterize it as underlying order from apparently random signals. Self-similarity is discussed as a latent menace of a pathological confusion between "self" and "others". Our test hypothesis is that (1) consciousness might have emerged and evolved from a primordial potential or proto-experience in matter, such as the physical attractions and repulsions experienced by electrons, and (2) "self" arises from chaotic dynamics, self-organization and selective mechanisms during ontogenesis, while emerging post-ontogenically as an adaptive pressure driven by both volume and synaptic-neural transmission and influencing the functional connectivity of neural nets (structure).

Walkable self-overlapping virtual reality maze and map visualization demo

DEFF Research Database (Denmark)

Serubugo, Sule; Skantarova, Denisa; Evers, Nicolaj

2017-01-01

This paper describes our demonstration of a walkable self-overlapping maze and its corresponding map to facilitate asymmetric collaboration for room-scale virtual reality setups in public places.......This paper describes our demonstration of a walkable self-overlapping maze and its corresponding map to facilitate asymmetric collaboration for room-scale virtual reality setups in public places....

Organizing the Electronic Century

OpenAIRE

Richard N. Langlois

2007-01-01

This paper's title is an echo of Alfred Chandler's (2001) chronicle of the electronics industry, Inventing the Electronic Century. The paper attempts (A) a general reinterpretation of the pattern of technological advance in (American) electronics over the twentieth century and (B) a somewhat revisionist account of the role of organization and institution in that advance. The paper stresses the complex effects of product architecture and intellectual property regime on industrial organization ...

Self-powered vision electronic-skin basing on piezo-photodetecting Ppy/PVDF pixel-patterned matrix for mimicking vision

Science.gov (United States)

Han, Wuxiao; Zhang, Linlin; He, Haoxuan; Liu, Hongmin; Xing, Lili; Xue, Xinyu

2018-06-01

The development of multifunctional electronic-skin that establishes human-machine interfaces, enhances perception abilities or has other distinct biomedical applications is the key to the realization of artificial intelligence. In this paper, a new self-powered (battery-free) flexible vision electronic-skin has been realized from pixel-patterned matrix of piezo-photodetecting PVDF/Ppy film. The electronic-skin under applied deformation can actively output piezoelectric voltage, and the outputting signal can be significantly influenced by UV illumination. The piezoelectric output can act as both the photodetecting signal and electricity power. The reliability is demonstrated over 200 light on–off cycles. The sensing unit matrix of 6 × 6 pixels on the electronic-skin can realize image recognition through mapping multi-point UV stimuli. This self-powered vision electronic-skin that simply mimics human retina may have potential application in vision substitution.

Self-powered vision electronic-skin basing on piezo-photodetecting Ppy/PVDF pixel-patterned matrix for mimicking vision.

Science.gov (United States)

Han, Wuxiao; Zhang, Linlin; He, Haoxuan; Liu, Hongmin; Xing, Lili; Xue, Xinyu

2018-06-22

The development of multifunctional electronic-skin that establishes human-machine interfaces, enhances perception abilities or has other distinct biomedical applications is the key to the realization of artificial intelligence. In this paper, a new self-powered (battery-free) flexible vision electronic-skin has been realized from pixel-patterned matrix of piezo-photodetecting PVDF/Ppy film. The electronic-skin under applied deformation can actively output piezoelectric voltage, and the outputting signal can be significantly influenced by UV illumination. The piezoelectric output can act as both the photodetecting signal and electricity power. The reliability is demonstrated over 200 light on-off cycles. The sensing unit matrix of 6 × 6 pixels on the electronic-skin can realize image recognition through mapping multi-point UV stimuli. This self-powered vision electronic-skin that simply mimics human retina may have potential application in vision substitution.

Innovative Mechanism of Rural Organization Based on Self-Organization

Institute of Scientific and Technical Information of China (English)

2011-01-01

The paper analyzes the basic situation of the formation of innovative rural organizations with the form of self-organization;reveals the features of self-organization,including the four aspects of openness of rural organization,innovation of rural organization far away from equilibrium,the non-linear response mechanism of rural organization innovation and the random rise and fall of rural organization innovation.The evolution mechanism of rural organization innovation is revealed according to the growth stage,the ideal stage,the decline and the fall stage.The paper probes into the basic restriction mechanism of the self-organization evaluation of rural organization from three aspects,including target recognition,path dependence and knowledge sharing.The basic measures on cultivating the innovative mechanism of rural organization are put forward.Firstly,constructing the dissipative structure of rural organization innovation;secondly,cultivating the dynamic study capability of rural organization innovation system;thirdly,selecting the step-by-step evolution strategy of rural organization innovation system.

The self-organizing fractal theory as a universal discovery method: the phenomenon of life

Directory of Open Access Journals (Sweden)

Kurakin Alexei

2011-03-01

Full Text Available Abstract A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy. An application of the new discovery method to life sciences reveals that moving electrons represent a keystone physical force (flux that powers, animates, informs, and binds all living structures-processes into a planetary-wide, multiscale system of electron flow/circulation, and that all living organisms and their larger-scale organizations emerge to function as electron transport networks that are supported by and, at the same time, support the flow of electrons down the Earth's redox gradient maintained along the core-mantle-crust-ocean-atmosphere axis of the planet. The presented findings lead to a radically new perspective on the nature and origin of life, suggesting that living matter

The self-organizing fractal theory as a universal discovery method: the phenomenon of life.

Science.gov (United States)

Kurakin, Alexei

2011-03-29

A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy.An application of the new discovery method to life sciences reveals that moving electrons represent a keystone physical force (flux) that powers, animates, informs, and binds all living structures-processes into a planetary-wide, multiscale system of electron flow/circulation, and that all living organisms and their larger-scale organizations emerge to function as electron transport networks that are supported by and, at the same time, support the flow of electrons down the Earth's redox gradient maintained along the core-mantle-crust-ocean-atmosphere axis of the planet. The presented findings lead to a radically new perspective on the nature and origin of life, suggesting that living matter is an organizational state

Self-Organization and the Self-Assembling Process in Tissue Engineering

Science.gov (United States)

Eswaramoorthy, Rajalakshmanan; Hadidi, Pasha; Hu, Jerry C.

2015-01-01

In recent years, the tissue engineering paradigm has shifted to include a new and growing subfield of scaffoldless techniques which generate self-organizing and self-assembling tissues. This review aims to provide a cogent description of this relatively new research area, with special emphasis on applications toward clinical use and research models. Particular emphasis is placed on providing clear definitions of self-organization and the self-assembling process, as delineated from other scaffoldless techniques in tissue engineering and regenerative medicine. Significantly, during formation, self-organizing and self-assembling tissues display biological processes similar to those that occur in vivo. These help lead to the recapitulation of native tissue morphological structure and organization. Notably, functional properties of these tissues also approach native tissue values; some of these engineered tissues are already in clinical trials. This review aims to provide a cohesive summary of work in this field, and to highlight the potential of self-organization and the self-assembling process to provide cogent solutions to current intractable problems in tissue engineering. PMID:23701238

Orientation and phase mapping in the transmission electron microscope using precession-assisted diffraction spot recognition: state-of-the-art results.

Science.gov (United States)

Viladot, D; Véron, M; Gemmi, M; Peiró, F; Portillo, J; Estradé, S; Mendoza, J; Llorca-Isern, N; Nicolopoulos, S

2013-10-01

A recently developed technique based on the transmission electron microscope, which makes use of electron beam precession together with spot diffraction pattern recognition now offers the possibility to acquire reliable orientation/phase maps with a spatial resolution down to 2 nm on a field emission gun transmission electron microscope. The technique may be described as precession-assisted crystal orientation mapping in the transmission electron microscope, precession-assisted crystal orientation mapping technique-transmission electron microscope, also known by its product name, ASTAR, and consists in scanning the precessed electron beam in nanoprobe mode over the specimen area, thus producing a collection of precession electron diffraction spot patterns, to be thereafter indexed automatically through template matching. We present a review on several application examples relative to the characterization of microstructure/microtexture of nanocrystalline metals, ceramics, nanoparticles, minerals and organics. The strengths and limitations of the technique are also discussed using several application examples. ©2013 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

Your space or mine? Mapping self in time.

Directory of Open Access Journals (Sweden)

Brittany M Christian

Full Text Available While humans are capable of mentally transcending the here and now, this faculty for mental time travel (MTT is dependent upon an underlying cognitive representation of time. To this end, linguistic, cognitive and behavioral evidence has revealed that people understand abstract temporal constructs by mapping them to concrete spatial domains (e.g. past=backward, future=forward. However, very little research has investigated factors that may determine the topographical characteristics of these spatiotemporal maps. Guided by the imperative role of episodic content for retrospective and prospective thought (i.e., MTT, here we explored the possibility that the spatialization of time is influenced by the amount of episodic detail a temporal unit contains. In two experiments, participants mapped temporal events along mediolateral (Experiment 1 and anterioposterior (Experiment 2 spatial planes. Importantly, the temporal units varied in self-relevance as they pertained to temporally proximal or distal events in the participant's own life, the life of a best friend or the life of an unfamiliar other. Converging evidence from both experiments revealed that the amount of space used to represent time varied as a function of target (self, best friend or unfamiliar other and temporal distance. Specifically, self-time was represented as occupying more space than time pertaining to other targets, but only for temporally proximal events. These results demonstrate the malleability of space-time mapping and suggest that there is a self-specific conceptualization of time that may influence MTT as well as other temporally relevant cognitive phenomena.

Electronic processes in organic electronics bridging nanostructure, electronic states and device properties

CERN Document Server

Kudo, Kazuhiro; Nakayama, Takashi; Ueno, Nobuo

2015-01-01

The book covers a variety of studies of organic semiconductors, from fundamental electronic states to device applications, including theoretical studies. Furthermore, innovative experimental techniques, e.g., ultrahigh sensitivity photoelectron spectroscopy, photoelectron yield spectroscopy, spin-resolved scanning tunneling microscopy (STM), and a material processing method with optical-vortex and polarization-vortex lasers, are introduced. As this book is intended to serve as a textbook for a graduate level course or as reference material for researchers in organic electronics and nanoscience from electronic states, fundamental science that is necessary to understand the research is described. It does not duplicate the books already written on organic electronics, but focuses mainly on electronic properties that arise from the nature of organic semiconductors (molecular solids). The new experimental methods introduced in this book are applicable to various materials (e.g., metals, inorganic and organic mater...

Self-organized Learning Environments

DEFF Research Database (Denmark)

Dalsgaard, Christian; Mathiasen, Helle

2007-01-01

system actively. The two groups used the system in their own way to support their specific activities and ways of working. The paper concludes that self-organized learning environments can strengthen the development of students’ academic as well as social qualifications. Further, the paper identifies......The purpose of the paper is to discuss the potentials of using a conference system in support of a project based university course. We use the concept of a self-organized learning environment to describe the shape of the course. In the paper we argue that educational technology, such as conference...... systems, has a potential to support students’ development of self-organized learning environments and facilitate self-governed activities in higher education. The paper is based on an empirical study of two project groups’ use of a conference system. The study showed that the students used the conference...

Autonomous Dynamically Self-Organizing and Self-Healing Distributed Hardware Architecture - the eDNA Concept

Science.gov (United States)

Boesen, Michael Reibel; Madsen, Jan; Keymeulen, Didier

2011-01-01

This paper presents the current state of the autonomous dynamically self-organizing and self-healing electronic DNA (eDNA) hardware architecture (patent pending). In its current prototype state, the eDNA architecture is capable of responding to multiple injected faults by autonomously reconfiguring itself to accommodate the fault and keep the application running. This paper will also disclose advanced features currently available in the simulation model only. These features are future work and will soon be implemented in hardware. Finally we will describe step-by-step how an application is implemented on the eDNA architecture.

Self-Organization in Embedded Real-Time Systems

CERN Document Server

Brinkschulte, Uwe; Rettberg, Achim

2013-01-01

This book describes the emerging field of self-organizing, multicore, distributed and real-time embedded systems.  Self-organization of both hardware and software can be a key technique to handle the growing complexity of modern computing systems. Distributed systems running hundreds of tasks on dozens of processors, each equipped with multiple cores, requires self-organization principles to ensure efficient and reliable operation. This book addresses various, so-called Self-X features such as self-configuration, self-optimization, self-adaptation, self-healing and self-protection. Presents open components for embedded real-time adaptive and self-organizing applications; Describes innovative techniques in: scheduling, memory management, quality of service, communications supporting organic real-time applications; Covers multi-/many-core embedded systems supporting real-time adaptive systems and power-aware, adaptive hardware and software systems; Includes case studies of open embedded real-time self-organizi...

NOAA Office of Exploration and Research > About OER > Organization > Map of

Science.gov (United States)

About OER Overview Organization Guiding Documents Organizational Structure Map of Staff and Affiliate of Staff and Affiliate Locations About OER Organization Map of Staff and Affiliate Locations Home About OER Overview Organization Guiding Documents Organizational Structure Map of Staff and Affiliate

Constructing Ozone Profile Climatologies with Self-Organizing Maps: Illustrations with CONUS Ozonesonde Data

Science.gov (United States)

Thompson, A. M.; Stauffer, R. M.; Young, G. S.

2015-12-01

Ozone (O3) trends analysis is typically performed with monthly or seasonal averages. Although this approach works well for stratospheric or total O3, uncertainties in tropospheric O3 amounts may be large due to rapid meteorological changes near the tropopause and in the lower free troposphere (LFT) where pollution has a days-weeks lifetime. We use self-organizing maps (SOM), a clustering technique, as an alternative for creating tropospheric climatologies from O3 soundings. In a previous study of 900 tropical ozonesondes, clusters representing >40% of profiles deviated > 1-sigma from mean O­3. Here SOM are based on 15 years of data from four sites in the contiguous US (CONUS; Boulder, CO; Huntsville, AL; Trinidad Head, CA; Wallops Island, VA). Ozone profiles from 2 - 12 km are used to evaluate the impact of tropopause variability on climatology; 2 - 6 km O3 profile segments are used for the LFT. Near-tropopause O­3 is twice the mean O­3 mixing ratio in three clusters of 2 - 12 km O3, representing > 15% of profiles at each site. Large mid and lower-tropospheric O3 deviations from monthly means are found in clusters of both 2 - 12 and 2 - 6 km O3. Positive offsets result from pollution and stratosphere-to-troposphere exchange. In the LFT the lowest tropospheric O3 is associated with subtropical air. Some clusters include profiles with common seasonality but other factors, e.g., tropopause height or LFT column amount, characterize other SOM nodes. Thus, as for tropical profiles, CONUS O­3 averages can be a poor choice for a climatology.

Estimation Algorithm of Machine Operational Intention by Bayes Filtering with Self-Organizing Map

Directory of Open Access Journals (Sweden)

Satoshi Suzuki

2012-01-01

Full Text Available We present an intention estimator algorithm that can deal with dynamic change of the environment in a man-machine system and will be able to be utilized for an autarkical human-assisting system. In the algorithm, state transition relation of intentions is formed using a self-organizing map (SOM from the measured data of the operation and environmental variables with the reference intention sequence. The operational intention modes are identified by stochastic computation using a Bayesian particle filter with the trained SOM. This method enables to omit the troublesome process to specify types of information which should be used to build the estimator. Applying the proposed method to the remote operation task, the estimator's behavior was analyzed, the pros and cons of the method were investigated, and ways for the improvement were discussed. As a result, it was confirmed that the estimator can identify the intention modes at 44–94 percent concordance ratios against normal intention modes whose periods can be found by about 70 percent of members of human analysts. On the other hand, it was found that human analysts' discrimination which was used as canonical data for validation differed depending on difference of intention modes. Specifically, an investigation of intentions pattern discriminated by eight analysts showed that the estimator could not identify the same modes that human analysts could not discriminate. And, in the analysis of the multiple different intentions, it was found that the estimator could identify the same type of intention modes to human-discriminated ones as well as 62–73 percent when the first and second dominant intention modes were considered.

Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

Directory of Open Access Journals (Sweden)

Sheng-Jun Wang

2011-06-01

Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

Flexible and Cellulose-based Organic Electronics

OpenAIRE

Edberg, Jesper

2017-01-01

Organic electronics is the study of organic materials with electronic functionality and the applications of such materials. In the 1970s, the discovery that polymers can be made electrically conductive led to an explosion within this field which has continued to grow year by year. One of the attractive features of organic electronic materials is their inherent mechanical flexibility, which has led to the development of numerous flexible electronics technologies such as organic light emitting ...

Screen media usage, sleep time and academic performance in adolescents: clustering a self-organizing maps analysis.

Science.gov (United States)

Peiró-Velert, Carmen; Valencia-Peris, Alexandra; González, Luis M; García-Massó, Xavier; Serra-Añó, Pilar; Devís-Devís, José

2014-01-01

Screen media usage, sleep time and socio-demographic features are related to adolescents' academic performance, but interrelations are little explored. This paper describes these interrelations and behavioral profiles clustered in low and high academic performance. A nationally representative sample of 3,095 Spanish adolescents, aged 12 to 18, was surveyed on 15 variables linked to the purpose of the study. A Self-Organizing Maps analysis established non-linear interrelationships among these variables and identified behavior patterns in subsequent cluster analyses. Topological interrelationships established from the 15 emerging maps indicated that boys used more passive videogames and computers for playing than girls, who tended to use mobile phones to communicate with others. Adolescents with the highest academic performance were the youngest. They slept more and spent less time using sedentary screen media when compared to those with the lowest performance, and they also showed topological relationships with higher socioeconomic status adolescents. Cluster 1 grouped boys who spent more than 5.5 hours daily using sedentary screen media. Their academic performance was low and they slept an average of 8 hours daily. Cluster 2 gathered girls with an excellent academic performance, who slept nearly 9 hours per day, and devoted less time daily to sedentary screen media. Academic performance was directly related to sleep time and socioeconomic status, but inversely related to overall sedentary screen media usage. Profiles from the two clusters were strongly differentiated by gender, age, sedentary screen media usage, sleep time and academic achievement. Girls with the highest academic results had a medium socioeconomic status in Cluster 2. Findings may contribute to establishing recommendations about the timing and duration of screen media usage in adolescents and appropriate sleep time needed to successfully meet the demands of school academics and to improve

Screen media usage, sleep time and academic performance in adolescents: clustering a self-organizing maps analysis.

Directory of Open Access Journals (Sweden)

Carmen Peiró-Velert

Full Text Available Screen media usage, sleep time and socio-demographic features are related to adolescents' academic performance, but interrelations are little explored. This paper describes these interrelations and behavioral profiles clustered in low and high academic performance. A nationally representative sample of 3,095 Spanish adolescents, aged 12 to 18, was surveyed on 15 variables linked to the purpose of the study. A Self-Organizing Maps analysis established non-linear interrelationships among these variables and identified behavior patterns in subsequent cluster analyses. Topological interrelationships established from the 15 emerging maps indicated that boys used more passive videogames and computers for playing than girls, who tended to use mobile phones to communicate with others. Adolescents with the highest academic performance were the youngest. They slept more and spent less time using sedentary screen media when compared to those with the lowest performance, and they also showed topological relationships with higher socioeconomic status adolescents. Cluster 1 grouped boys who spent more than 5.5 hours daily using sedentary screen media. Their academic performance was low and they slept an average of 8 hours daily. Cluster 2 gathered girls with an excellent academic performance, who slept nearly 9 hours per day, and devoted less time daily to sedentary screen media. Academic performance was directly related to sleep time and socioeconomic status, but inversely related to overall sedentary screen media usage. Profiles from the two clusters were strongly differentiated by gender, age, sedentary screen media usage, sleep time and academic achievement. Girls with the highest academic results had a medium socioeconomic status in Cluster 2. Findings may contribute to establishing recommendations about the timing and duration of screen media usage in adolescents and appropriate sleep time needed to successfully meet the demands of school academics and

Structural characterization of self-assembled semiconductor islands by three-dimensional X-ray diffraction mapping in reciprocal space

International Nuclear Information System (INIS)

Holy, V.; Mundboth, K.; Mokuta, C.; Metzger, T.H.; Stangl, J.; Bauer, G.; Boeck, T.; Schmidbauer, M.

2008-01-01

For the first time self-organized epitaxially grown semiconductor islands were investigated by a full three-dimensional mapping of the scattered X-ray intensity in reciprocal space. Intensity distributions were measured in a coplanar diffraction geometry around symmetric and asymmetric Bragg reflections. The 3D intensity maps were compared with theoretical simulations based on continuum-elasticity simulations of internal strains in the islands and on kinematical scattering theory whereby local chemical composition and strain profiles of the islands were retrieved

Self-organizing sensing and actuation for automatic control

Science.gov (United States)

Cheng, George Shu-Xing

2017-07-04

A Self-Organizing Process Control Architecture is introduced with a Sensing Layer, Control Layer, Actuation Layer, Process Layer, as well as Self-Organizing Sensors (SOS) and Self-Organizing Actuators (SOA). A Self-Organizing Sensor for a process variable with one or multiple input variables is disclosed. An artificial neural network (ANN) based dynamic modeling mechanism as part of the Self-Organizing Sensor is described. As a case example, a Self-Organizing Soft-Sensor for CFB Boiler Bed Height is presented. Also provided is a method to develop a Self-Organizing Sensor.

Using parallel factor analysis modeling (PARAFAC) and self-organizing maps to track senescence-induced patterns in leaf litter leachate

Science.gov (United States)

Wheeler, K. I.; Levia, D. F., Jr.; Hudson, J. E.

2017-12-01

As trees undergo autumnal processes such as resorption, senescence, and leaf abscission, the dissolved organic matter (DOM) contribution of leaf litter leachate to streams changes. However, little research has investigated how the fluorescent DOM (FDOM) changes throughout the autumn and how this differs inter- and intraspecifically. Two of the major impacts of global climate change on forested ecosystems include altering phenology and causing forest community species and subspecies composition restructuring. We examined changes in FDOM in leachate from American beech (Fagus grandifolia Ehrh.) leaves in Maryland, Rhode Island, Vermont, and North Carolina and yellow poplar (Liriodendron tulipifera L.) leaves from Maryland throughout three different phenophases: green, senescing, and freshly abscissed. Beech leaves from Maryland and Rhode Island have previously been identified as belonging to the same distinct genetic cluster and beech trees from Vermont and the study site in North Carolina from the other. FDOM in samples was characterized using excitation-emission matrices (EEMs) and a six-component parallel factor analysis (PARAFAC) model was created to identify components. Self-organizing maps (SOMs) were used to visualize variation and patterns in the PARAFAC component proportions of the leachate samples. Phenophase and species had the greatest influence on determining where a sample mapped on the SOM when compared to genetic clusters and geographic origin. Throughout senescence, FDOM from all the trees transitioned from more protein-like components to more humic-like ones. Percent greenness of the sampled leaves and the proportion of the tyrosine-like component 1 were found to significantly differ between the two genetic beech clusters. This suggests possible differences in photosynthesis and resorption between the two genetic clusters of beech. The use of SOMs to visualize differences in patterns of senescence between the different species and genetic

Application of self-organizing feature maps to analyze the relationships between ignitable liquids and selected mass spectral ions.

Science.gov (United States)

Frisch-Daiello, Jessica L; Williams, Mary R; Waddell, Erin E; Sigman, Michael E

2014-03-01

The unsupervised artificial neural networks method of self-organizing feature maps (SOFMs) is applied to spectral data of ignitable liquids to visualize the grouping of similar ignitable liquids with respect to their American Society for Testing and Materials (ASTM) class designations and to determine the ions associated with each group. The spectral data consists of extracted ion spectra (EIS), defined as the time-averaged mass spectrum across the chromatographic profile for select ions, where the selected ions are a subset of ions from Table 2 of the ASTM standard E1618-11. Utilization of the EIS allows for inter-laboratory comparisons without the concern of retention time shifts. The trained SOFM demonstrates clustering of the ignitable liquid samples according to designated ASTM classes. The EIS of select samples designated as miscellaneous or oxygenated as well as ignitable liquid residues from fire debris samples are projected onto the SOFM. The results indicate the similarities and differences between the variables of the newly projected data compared to those of the data used to train the SOFM. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Self-standing chitosan films as dielectrics in organic thin-film transistors

Directory of Open Access Journals (Sweden)

J. Morgado

2013-12-01

Full Text Available Organic thin film transistors, using self-standing 50 µm thick chitosan films as dielectric, are fabricated using sublimed pentacene or two conjugated polymers deposited by spin coating as semiconductors. Field-effect mobilities are found to be similar to values obtained with other dielectrics and, in the case of pentacene, a value (0.13 cm2/(V•s comparable to high performing transistors was determined. In spite of the low On/Off ratios (a maximum value of 600 was obtained for the pentacene-based transistors, these are promising results for the area of sustainable organic electronics in general and for biocompatible electronics in particular.

Self-organized complex space charge configurations at the origin of flicker noise

International Nuclear Information System (INIS)

Popescu, S.; Lozneanu, E.; Sanduloviciu, M.

2003-01-01

Based on experimental results obtained from a plasma diode we explain the fluctuations of the voltage supported by a non-linear gaseous conductor by the dynamical behavior of spatiotemporal patterns, in the form of moving double layers, formed after self-organization. Such phenomena appear when the system is subjected to an external constraint that creates and maintains a local gradient of electron kinetic energy. The described phenomenology suggests a plausible explanation for the appearance of flicker noise also in other physical systems, as for example semiconductors and, implicitly, offers a new model for the so-called self-organized criticality concept

17 CFR 249.819 - Form 19b-4, for electronic filing with respect to proposed rule changes by all self-regulatory...

Science.gov (United States)

2010-04-01

... filing with respect to proposed rule changes by all self-regulatory organizations. 249.819 Section 249..., SECURITIES EXCHANGE ACT OF 1934 Forms for Self-Regulatory Organization Rule Changes and Forms for....819 Form 19b-4, for electronic filing with respect to proposed rule changes by all self-regulatory...

System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

Science.gov (United States)

Lu, Bin; Harley, Ronald G.; Du, Liang; Yang, Yi; Sharma, Santosh K.; Zambare, Prachi; Madane, Mayura A.

2014-06-17

A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.

Submolecular Gates Self-Assemble for Hot-Electron Transfer in Proteins.

Science.gov (United States)

Filip-Granit, Neta; Goldberg, Eran; Samish, Ilan; Ashur, Idan; van der Boom, Milko E; Cohen, Hagai; Scherz, Avigdor

2017-07-27

Redox reactions play key roles in fundamental biological processes. The related spatial organization of donors and acceptors is assumed to undergo evolutionary optimization facilitating charge mobilization within the relevant biological context. Experimental information from submolecular functional sites is needed to understand the organization strategies and driving forces involved in the self-development of structure-function relationships. Here we exploit chemically resolved electrical measurements (CREM) to probe the atom-specific electrostatic potentials (ESPs) in artificial arrays of bacteriochlorophyll (BChl) derivatives that provide model systems for photoexcited (hot) electron donation and withdrawal. On the basis of computations we show that native BChl's in the photosynthetic reaction center (RC) self-assemble at their ground-state as aligned gates for functional charge transfer. The combined computational and experimental results further reveal how site-specific polarizability perpendicular to the molecular plane enhances the hot-electron transport. Maximal transport efficiency is predicted for a specific, ∼5 Å, distance above the center of the metalized BChl, which is in remarkably close agreement with the distance and mutual orientation of corresponding native cofactors. These findings provide new metrics and guidelines for analysis of biological redox centers and for designing charge mobilizing machines such as artificial photosynthesis.

Calculation of Self-consistent Radial Electric Field in Presence of Convective Electron Transport in a Stellarator

International Nuclear Information System (INIS)

Kernbichler, W.; Heyn, M.F.; Kasilov, S.V.

2003-01-01

Convective transport of supra-thermal electrons can play a significant role in the energy balance of stellarators in case of high power electron cyclotron heating. Here, together with neoclassical thermal particle fluxes also the supra-thermal electron flux should be taken into account in the flux ambipolarity condition, which defines the self-consistent radial electric field. Since neoclassical particle fluxes are non-linear functions of the radial electric field, one needs an iterative procedure to solve the ambipolarity condition, where the supra-thermal electron flux has to be calculated for each iteration. A conventional Monte-Carlo method used earlier for evaluation of supra-thermal electron fluxes is rather slow for performing the iterations in reasonable computer time. In the present report, the Stochastic Mapping Technique (SMT), which is more effective than the conventional Monte Carlo method, is used instead. Here, the problem with a local monoenergetic supra-thermal particle source is considered and the effect of supra-thermal electron fluxes on both, the self-consistent radial electric field and the formation of different roots of the ambipolarity condition are studied

Self-Organizing Maps: A Data Mining Tool for the Analysis of Airborne Geophysical Data Collected over the Brazilian Amazon

Science.gov (United States)

Carneiro, C.; Fraser, S. J.; Crosta, A. P.; Silva, A.; Barros, C.

2011-12-01

Regional airborne geophysical data sets are being collected worldwide to promote mineral exploration and resource development. These data sets often are collected over highly prospective terranes, where access is limited or there are environmental concerns. Such regional surveys typically consist of two or more sensor packages being flown in an aircraft over the survey area and vast amounts of near-continuous data can be acquired in a relatively short time. Increasingly, there is also a need to process such data in a timely fashion to demonstrate the data's value and indicate the potential return or value of the survey to the funding agency. To assist in the timely analysis of such regional data sets, we have used an exploratory data mining approach: the Self Organizing Map (SOM). Because SOM is based on vector quantization and measures of vector similarity, it is an ideal tool to analyze a data set consisting of disparate geophysical input parameters to look for relationships and trends. We report on our use of SOM to analyze part of a regional airborne geophysical survey collected over the prospective Anapu-Tuere region of the Brazilian Amazon. Magnetic and spectrometric gamma ray data were used as input to our SOM analysis, and the results used to discriminate and identify various rock types and produce a "pseudo" geological map over the study area. The ability of SOM to define discrete domains of rock-types with similar properties allowed us to expand upon existing geological knowledge of the area for mapping purposes; and, often it was the combination of the magnetic and radiometric responses that identified a lithology's unique response. One particular unit was identified that had an association with known gold mineralization, which consequently highlighted the prospectivity of that unit elsewhere in the survey area. Our results indicate that SOM can be used for the semi-automatic analysis of regional airborne geophysical data to assist in geological mapping

Electronic, structural and chemical effects of charge-transfer at organic/inorganic interfaces

Science.gov (United States)

Otero, R.; Vázquez de Parga, A. L.; Gallego, J. M.

2017-07-01

During the last decade, interest on the growth and self-assembly of organic molecular species on solid surfaces spread over the scientific community, largely motivated by the promise of cheap, flexible and tunable organic electronic and optoelectronic devices. These efforts lead to important advances in our understanding of the nature and strength of the non-bonding intermolecular interactions that control the assembly of the organic building blocks on solid surfaces, which have been recently reviewed in a number of excellent papers. To a large extent, such studies were possible because of a smart choice of model substrate-adsorbate systems where the molecule-substrate interactions were purposefully kept low, so that most of the observed supramolecular structures could be understood simply by considering intermolecular interactions, keeping the role of the surface always relatively small (although not completely negligible). On the other hand, the systems which are more relevant for the development of organic electronic devices include molecular species which are electron donors, acceptors or blends of donors and acceptors. Adsorption of such organic species on solid surfaces is bound to be accompanied by charge-transfer processes between the substrate and the adsorbates, and the physical and chemical properties of the molecules cannot be expected any longer to be the same as in solution phase. In recent years, a number of groups around the world have started tackling the problem of the adsorption, self- assembly and electronic and chemical properties of organic species which interact rather strongly with the surface, and for which charge-transfer must be considered. The picture that is emerging shows that charge transfer can lead to a plethora of new phenomena, from the development of delocalized band-like electron states at molecular overlayers, to the existence of new substrate-mediated intermolecular interactions or the strong modification of the chemical

Spatial Mapping of Organic Carbon in Returned Samples from Mars

Science.gov (United States)

Siljeström, S.; Fornaro, T.; Greenwalt, D.; Steele, A.

2018-04-01

To map organic material spatially to minerals present in the sample will be essential for the understanding of the origin of any organics in returned samples from Mars. It will be shown how ToF-SIMS may be used to map organics in samples from Mars.

Localization of electrons by electron-electron interaction in an Anderson model

International Nuclear Information System (INIS)

Ritala, R.K.; Kurkijaervi, J.

1981-01-01

We study the effect of attractive Hubbard interaction on disordered electron system. We map the interacting system back to noninteracting one and determine self-consistently the disorder change due to interaction in the system. (author)

Synthesis Road Map Problems in Organic Chemistry

Science.gov (United States)

Schaller, Chris P.; Graham, Kate J.; Jones, T. Nicholas

2014-01-01

Road map problems ask students to integrate their knowledge of organic reactions with pattern recognition skills to "fill in the blanks" in the synthesis of an organic compound. Students are asked to identify familiar organic reactions in unfamiliar contexts. A practical context, such as a medicinally useful target compound, helps…

Chaoticity of interval self-maps with positive entropy

International Nuclear Information System (INIS)

Xiong Jincheng.

1988-12-01

Li and Yorke originally introduced the notion of chaos for continuous self-map of the interval I = (0,1). In the present paper we show that an interval self-map with positive topological entropy has a chaoticity more complicated than the chaoticity in the sense of Li and Yorke. The main result is that if f:I → I is continuous and has a periodic point with odd period > 1 then there exists a closed subset K of I invariant with respect to f such that the periodic points are dense in K, the periods of periodic points in K form an infinite set and f|K is topologically mixing. (author). 9 refs

Topology assisted self-organization of colloidal nanoparticles: application to 2D large-scale nanomastering

Directory of Open Access Journals (Sweden)

Hind Kadiri

2014-08-01

Full Text Available Our aim was to elaborate a novel method for fully controllable large-scale nanopatterning. We investigated the influence of the surface topology, i.e., a pre-pattern of hydrogen silsesquioxane (HSQ posts, on the self-organization of polystyrene beads (PS dispersed over a large surface. Depending on the post size and spacing, long-range ordering of self-organized polystyrene beads is observed wherein guide posts were used leading to single crystal structure. Topology assisted self-organization has proved to be one of the solutions to obtain large-scale ordering. Besides post size and spacing, the colloidal concentration and the nature of solvent were found to have a significant effect on the self-organization of the PS beads. Scanning electron microscope and associated Fourier transform analysis were used to characterize the morphology of the ordered surfaces. Finally, the production of silicon molds is demonstrated by using the beads as a template for dry etching.

The Self-Organized Archive: SPASE, PDS and Archive Cooperatives

Science.gov (United States)

King, T. A.; Hughes, J. S.; Roberts, D. A.; Walker, R. J.; Joy, S. P.

2005-05-01

Information systems with high quality metadata enable uses and services which often go beyond the original purpose. There are two types of metadata: annotations which are items that comment on or describe the content of a resource and identification attributes which describe the external properties of the resource itself. For example, annotations may indicate which columns are present in a table of data, whereas an identification attribute would indicate source of the table, such as the observatory, instrument, organization, and data type. When the identification attributes are collected and used as the basis of a search engine, a user can constrain on an attribute, the archive can then self-organize around the constraint, presenting the user with a particular view of the archive. In an archive cooperative where each participating data system or archive may have its own metadata standards, providing a multi-system search engine requires that individual archive metadata be mapped to a broad based standard. To explore how cooperative archives can form a larger self-organized archive we will show how the Space Physics Archive Search and Extract (SPASE) data model will allow different systems to create a cooperative and will use Planetary Data System (PDS) plus existing space physics activities as a demonstration.

Organic High Electron Mobility Transistors Realized by 2D Electron Gas.

Science.gov (United States)

Zhang, Panlong; Wang, Haibo; Yan, Donghang

2017-09-01

A key breakthrough in inorganic modern electronics is the energy-band engineering that plays important role to improve device performance or develop novel functional devices. A typical application is high electron mobility transistors (HEMTs), which utilizes 2D electron gas (2DEG) as transport channel and exhibits very high electron mobility over traditional field-effect transistors (FETs). Recently, organic electronics have made very rapid progress and the band transport model is demonstrated to be more suitable for explaining carrier behavior in high-mobility crystalline organic materials. Therefore, there emerges a chance for applying energy-band engineering in organic semiconductors to tailor their optoelectronic properties. Here, the idea of energy-band engineering is introduced and a novel device configuration is constructed, i.e., using quantum well structures as active layers in organic FETs, to realize organic 2DEG. Under the control of gate voltage, electron carriers are accumulated and confined at quantized energy levels, and show efficient 2D transport. The electron mobility is up to 10 cm 2 V -1 s -1 , and the operation mechanisms of organic HEMTs are also argued. Our results demonstrate the validity of tailoring optoelectronic properties of organic semiconductors by energy-band engineering, offering a promising way for the step forward of organic electronics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electron self-injection in the donut bubble wakefield

Science.gov (United States)

Firouzjaei, Ali Shekari; Shokri, Babak

2018-05-01

We investigate electron self-injection in a donut bubble wakefield driven by a Laguerre-Gauss laser pulse. The present work discusses the electron capture by modeling the analytical donut bubble field. We discuss the self-injection of the electrons from plasma for various initial conditions and then compare the results. We show that the donut bubble can trap plasma electrons forming a hollow beam. We present the phase spaces and longitudinal momentum evolution for the trapped electrons in the bubble and discuss their characteristic behaviors and stability. It will be shown that the electrons self-injected in the front are ideal for applications in which a good stability and low energy spread are essential.

Self-organization phenomena in plasma physics

International Nuclear Information System (INIS)

Sanduloviciu, M.; Popescu, S.

2001-01-01

The self-assembling in nature and laboratory of structures in systems away from thermodynamic equilibrium is one of the problems that mostly fascinates the scientists working in all branches of science. In this context a substantial progress has been obtained by investigating the appearance of spatial and spatiotemporal patterns in plasma. These experiments revealed the presence of a scenario of self-organization able to suggest an answer to the central problem of the 'Science of Complexity', why matter transits spontaneously from a disordered into an ordered state? Based on this scenario of self-organization we present arguments proving the possibility to explain the challenging problems of nonequilibrium physics in general. These problems refer to: (i) genuine origin of phase transitions observed in gaseous conductors and semiconductors; (ii) the elucidation of the role played by self-organization in the simulation of oscillations; (iii) the physical basis of anomalous transport of matter and energy with special reference to the possibilities of improving the economical performance of fusion devices; (iv) the possibility to use self-confined gaseous space charged configurations as an alternative to the magnetically confined plasma used at present in fusion devices. In other branches of sciences, as for instance in Biology, the self-organization scenario reveals a new insight into a mechanism able to explain the appearance of the simplest possible space charge configuration able to evolve, under suitable conditions, into prebiotic structures. Referring to phenomena observed in nature, the same self-organization scenario suggests plausible answers to the appearance of ball lightening but also to the origin of the flickering phenomena observed in the light emission of the Sun and stars. For theory the described self-organization scenario offers a new physical basis for many problems of nonlinear science not solved yet and also a new model for the so-called 'self

Modeling hydrologic and geomorphic hazards across post-fire landscapes using a self-organizing map approach

Science.gov (United States)

Friedel, Michael J.

2011-01-01

Few studies attempt to model the range of possible post-fire hydrologic and geomorphic hazards because of the sparseness of data and the coupled, nonlinear, spatial, and temporal relationships among landscape variables. In this study, a type of unsupervised artificial neural network, called a self-organized map (SOM), is trained using data from 540 burned basins in the western United States. The sparsely populated data set includes variables from independent numerical landscape categories (climate, land surface form, geologic texture, and post-fire condition), independent landscape classes (bedrock geology and state), and dependent initiation processes (runoff, landslide, and runoff and landslide combination) and responses (debris flows, floods, and no events). Pattern analysis of the SOM-based component planes is used to identify and interpret relations among the variables. Application of the Davies-Bouldin criteria following k-means clustering of the SOM neurons identified eight conceptual regional models for focusing future research and empirical model development. A split-sample validation on 60 independent basins (not included in the training) indicates that simultaneous predictions of initiation process and response types are at least 78% accurate. As climate shifts from wet to dry conditions, forecasts across the burned landscape reveal a decreasing trend in the total number of debris flow, flood, and runoff events with considerable variability among individual basins. These findings suggest the SOM may be useful in forecasting real-time post-fire hazards, and long-term post-recovery processes and effects of climate change scenarios.

Self-organizing map network-based precipitation regionalization for the Tibetan Plateau and regional precipitation variability

Science.gov (United States)

Wang, Nini; Yin, Jianchuan

2017-12-01

A precipitation-based regionalization for the Tibetan Plateau (TP) was investigated for regional precipitation trend analysis and frequency analysis using data from 1113 grid points covering the period 1900-2014. The results utilizing self-organizing map (SOM) network suggest that four clusters of precipitation coherent zones can be identified, including the southwestern edge, the southern edge, the southeastern region, and the north central region. Regionalization results of the SOM network satisfactorily represent the influences of the atmospheric circulation systems such as the East Asian summer monsoon, the south Asian summer monsoon, and the mid-latitude westerlies. Regionalization results also well display the direct impacts of physical geographical features of the TP such as orography, topography, and land-sea distribution. Regional-scale annual precipitation trend as well as regional differences of annual and seasonal total precipitation were investigated by precipitation index such as precipitation concentration index (PCI) and Standardized Anomaly Index (SAI). Results demonstrate significant negative long-term linear trends in southeastern TP and the north central part of the TP, indicating arid and semi-arid regions in the TP are getting drier. The empirical mode decomposition (EMD) method shows an evolution of the main cycle with 4 and 12 months for all the representative grids of four sub-regions. The cross-wavelet analysis suggests that predominant and effective period of Indian Ocean Dipole (IOD) on monthly precipitation is around ˜12 months, except for the representative grid of the northwestern region.

Self-organizing feature map (neural networks) as a tool to select the best indicator of road traffic pollution (soil, leaves or bark of Robinia pseudoacacia L.).

Science.gov (United States)

Samecka-Cymerman, A; Stankiewicz, A; Kolon, K; Kempers, A J

2009-07-01

Concentrations of the elements Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were measured in the leaves and bark of Robinia pseudoacacia and the soil in which it grew, in the town of Oleśnica (SW Poland) and at a control site. We selected this town because emission from motor vehicles is practically the only source of air pollution, and it seemed interesting to evaluate its influence on soil and plants. The self-organizing feature map (SOFM) yielded distinct groups of soils and R. pseudoacacia leaves and bark, depending on traffic intensity. Only the map classifying bark samples identified an additional group of highly polluted sites along the main highway from Wrocław to Warszawa. The bark of R. pseudoacacia seems to be a better bioindicator of long-term cumulative traffic pollution in the investigated area, while leaves are good indicators of short-term seasonal accumulation trends.

Usage of self-organizing neural networks in evaluation of consumer behaviour

Directory of Open Access Journals (Sweden)

Jana Weinlichová

2010-01-01

Full Text Available This article deals with evaluation of consumer data by Artificial Intelligence methods. In methodical part there are described learning algorithms for Kohonen maps on the principle of supervised learning, unsupervised learning and semi-supervised learning. The principles of supervised learning and unsupervised learning are compared. On base of binding conditions of these principles there is pointed out an advantage of semi-supervised learning. Three algorithms are described for the semi-supervised learning: label propagation, self-training and co-training. Especially usage of co-training in Kohonen map learning seems to be promising point of other research. In concrete application of Kohonen neural network on consumer’s expense the unsupervised learning method has been chosen – the self-organization. So the features of data are evaluated by clustering method called Kohonen maps. These input data represents consumer expenses of households in countries of European union and are characterised by 12-dimension vector according to commodity classification. The data are evaluated in several years, so we can see their distribution, similarity or dissimilarity and also their evolution. In the article we discus other usage of this method for this type of data and also comparison of our results with results reached by hierarchical cluster analysis.

Calculation of the electron trajectory for 200 kV self-shielded electron accelerator

International Nuclear Information System (INIS)

Wang Shuiqing

2000-01-01

In order to calculate the electron trajectory of 200 kV self-shielded electron accelerator, the electric field is calculated with a TRAJ program. In this program, following electron track mash points one by one, the electron beam trajectories are calculated. Knowing the effect of grid voltage on electron optics and gaining grid voltage focusing effect in the various energy grades, the authors have gained scientific basis for adjusting grid voltage, and also accumulated a wealth of experience for designing self-shielded electron accelerator or electron curtain in future

Non-Taylor magnetohydrodynamic self-organization

International Nuclear Information System (INIS)

Zhu, Shao-ping; Horiuchi, Ritoku; Sato, Tetsuya.

1994-10-01

A self-organization process in a plasma with a finite pressure is investigated by means of a three-dimensional magnetohydrodynamic simulation. It is demonstrated that a non-Taylor finite β self-organized state is realized in which a perpendicular component of the electric current is generated and the force-free(parallel) current decreases until they reach to almost the same level. The self-organized state is described by an MHD force-balance relation, namely, j perpendicular = B x ∇p/B·B and j parallel = μB where μ is not a constant, and the pressure structure resembles the structure of the toroidal magnetic field intensity. Unless an anomalous perpendicular thermal conduction arises, the plasma cannot relax to a Taylor state but to a non-Taylor (non-force-free) self-organized state. This state becomes more prominent for a weaker resistivity condition. The non-Taylor state has a rather universal property, for example, independence of the initial β value. Another remarkable finding is that the Taylor's conjecture of helicity conservation is, in a strict sense, not valid. The helicity dissipation occurs and its rate slows down critically in accordance with the stepwise relaxation of the magnetic energy. It is confirmed that the driven magnetic reconnection caused by the nonlinearly excited plasma kink flows plays the leading role in all of these key features of the non-Taylor self-organization. (author)

Self-focusing relativistic electron streams in plasmas

International Nuclear Information System (INIS)

Cox, J.L. Jr.

1975-01-01

A relativistic electron stream propagating through a dense plasma induces current and charge densities which determine how the stream can self-focus. Magnetic self-focusing is possible because stream-current neutralization, although extensive, is not complete. Electric self-focusing can occur because the stream charge becomes overneutralized when the net current is smaller than a critical value. Under some circumstances, the latter process can cause the stream to focus into a series of electron bunches

Self-organized neural network for the quality control of 12-lead ECG signals

International Nuclear Information System (INIS)

Chen, Yun; Yang, Hui

2012-01-01

Telemedicine is very important for the timely delivery of health care to cardiovascular patients, especially those who live in the rural areas of developing countries. However, there are a number of uncertainty factors inherent to the mobile-phone-based recording of electrocardiogram (ECG) signals such as personnel with minimal training and other extraneous noises. PhysioNet organized a challenge in 2011 to develop efficient algorithms that can assess the ECG signal quality in telemedicine settings. This paper presents our efforts in this challenge to integrate multiscale recurrence analysis with a self-organizing map for controlling the ECG signal quality. As opposed to directly evaluating the 12-lead ECG, we utilize an information-preserving transform, i.e. Dower transform, to derive the 3-lead vectorcardiogram (VCG) from the 12-lead ECG in the first place. Secondly, we delineate the nonlinear and nonstationary characteristics underlying the 3-lead VCG signals into multiple time-frequency scales. Furthermore, a self-organizing map is trained, in both supervised and unsupervised ways, to identify the correlations between signal quality and multiscale recurrence features. The efficacy and robustness of this approach are validated using real-world ECG recordings available from PhysioNet. The average performance was demonstrated to be 95.25% for the training dataset and 90.0% for the independent test dataset with unknown labels. (paper)

CrowdMapping: A Crowdsourcing-Based Terminology Mapping Method for Medical Data Standardization.

Science.gov (United States)

Mao, Huajian; Chi, Chenyang; Huang, Boyu; Meng, Haibin; Yu, Jinghui; Zhao, Dongsheng

2017-01-01

Standardized terminology is the prerequisite of data exchange in analysis of clinical processes. However, data from different electronic health record systems are based on idiosyncratic terminology systems, especially when the data is from different hospitals and healthcare organizations. Terminology standardization is necessary for the medical data analysis. We propose a crowdsourcing-based terminology mapping method, CrowdMapping, to standardize the terminology in medical data. CrowdMapping uses a confidential model to determine how terminologies are mapped to a standard system, like ICD-10. The model uses mappings from different health care organizations and evaluates the diversity of the mapping to determine a more sophisticated mapping rule. Further, the CrowdMapping model enables users to rate the mapping result and interact with the model evaluation. CrowdMapping is a work-in-progress system, we present initial results mapping terminologies.

Complete electronics self-teaching guide with projects

CERN Document Server

Boysen, Earl

2012-01-01

An all-in-one resource on everything electronics-related! For almost 30 years, this book has been a classic text for electronics enthusiasts. Now completely updated for today's technology, this latest version combines concepts, self-tests, and hands-on projects to offer you a completely repackaged and revised resource. This unique self-teaching guide features easy-to-understand explanations that are presented in a user-friendly format to help you learn the essentials you need to work with electronic circuits. All you need is a general understanding of electronics concepts such as Oh

The concept of self-organizing systems. Why bother?

Science.gov (United States)

Elverfeldt, Kirsten v.; Embleton-Hamann, Christine; Slaymaker, Olav

2016-04-01

Complexity theory and the concept of self-organizing systems provide a rather challenging conceptual framework for explaining earth systems change. Self-organization - understood as the aggregate processes internal to an environmental system that lead to a distinctive spatial or temporal organization - reduces the possibility of implicating a specific process as being causal, and it poses some restrictions on the idea that external drivers cause a system to change. The concept of self-organizing systems suggests that many phenomena result from an orchestration of different mechanisms, so that no causal role can be assigned to an individual factor or process. The idea that system change can be due to system-internal processes of self-organization thus proves a huge challenge to earth system research, especially in the context of global environmental change. In order to understand the concept's implications for the Earth Sciences, we need to know the characteristics of self-organizing systems and how to discern self-organizing systems. Within the talk, we aim firstly at characterizing self-organizing systems, and secondly at highlighting the advantages and difficulties of the concept within earth system sciences. The presentation concludes that: - The concept of self-organizing systems proves especially fruitful for small-scale earth surface systems. Beach cusps and patterned ground are only two of several other prime examples of self-organizing earth surface systems. They display characteristics of self-organization like (i) system-wide order from local interactions, (ii) symmetry breaking, (iii) distributed control, (iv) robustness and resilience, (v) nonlinearity and feedbacks, (vi) organizational closure, (vii) adaptation, and (viii) variation and selection. - It is comparatively easy to discern self-organization in small-scale systems, but to adapt the concept to larger scale systems relevant to global environmental change research is more difficult: Self-organizing

Self-organized voids revisited: Experimental verification of the formation mechanism

International Nuclear Information System (INIS)

Song Juan; Jiang Yan; Ye Jun-Yi; Qian Meng-Di; Lin Xian; Bian Hua-Dong; Dai Ye; Ma Guo-Hong; Luo Fang-Fang; Chen Qing-Xi; Zhao Quan-Zhong; Qiu Jian-Rong

2014-01-01

We conduct several experiments to further clarify the formation mechanism of a self-organized void array induced by a single laser beam, including energy-related experiments, refractive-index-contrast-related experiments, depth-related experiments, and effective-numerical-aperture experiment. These experiments indicate that the interface spherical aberration is indeed responsible for the formation of void arrays. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory.

Science.gov (United States)

Chen, Qiuwen; Rui, Han; Li, Weifeng; Zhang, Yanhui

2014-06-01

Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004-2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial-temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial-temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. Copyright © 2014 Elsevier B.V. All rights reserved.

Electron spin from self interaction

International Nuclear Information System (INIS)

Spavieri, G.

1992-01-01

The author explores the possibility that the electron self-interaction is the origin of the spin and of the radiative effects of QED. The electron is conceived as a charged, massless, point particle with a quantum or stochastic, internal motion about its center of mass and bound by a self-interaction potential. The hydrodynamic equations of motion describing the electron in its center of mass frame are related to non-Markovian stochastic equations recently used to derive the Schroedinger equation. By averaging over this stochastic internal motion and identifying the energy with the rest mass energy, the angular momentum exhibits properties characteristic of spin. The electromagnetic self-interactions added to the Hamiltonian of the particle correct the g factor to yield the anomalous value (g-2)/2 ∼ 1159.7(2.3) X 10 -6 in agreement with experiment. Calculations of other open-quotes radiativeclose quotes effects including the Lamb shift are presented. The results obtained are finite and suggest that the QED corrections attributed to radiative effects could be obtained classically, i.e., without second quantization and renormalization, by complementing the Dirac theory with this self-interaction mechanism. The g factor dependence on the external magnetic field of this and other spin models is compared with that of QED, showing that these theories can be tested by the present precision measurements of the g factor. 33 refs., 2 tabs

Self-organizing neural networks for automatic detection and classification of contrast-enhancing lesions in dynamic MR-mammography; Selbstorganisierende neuronale Netze zur automatischen Detektion und Klassifikation von Kontrast(mittel)-verstaerkten Laesionen in der dynamischen MR-Mammographie

Energy Technology Data Exchange (ETDEWEB)

Vomweg, T.W.; Teifke, A.; Kauczor, H.U.; Achenbach, T.; Rieker, O.; Schreiber, W.G.; Heitmann, K.R.; Beier, T.; Thelen, M. [Klinik und Poliklinik fuer Radiologie, Klinikum der Univ. Mainz (Germany)

2005-05-01

Purpose: Investigation and statistical evaluation of 'Self-Organizing Maps', a special type of neural networks in the field of artificial intelligence, classifying contrast enhancing lesions in dynamic MR-mammography. Material and Methods: 176 investigations with proven histology after core biopsy or operation were randomly divided into two groups. Several Self-Organizing Maps were trained by investigations of the first group to detect and classify contrast enhancing lesions in dynamic MR-mammography. Each single pixel's signal/time curve of all patients within the second group was analyzed by the Self-Organizing Maps. The likelihood of malignancy was visualized by color overlays on the MR-images. At last assessment of contrast-enhancing lesions by each different network was rated visually and evaluated statistically. Results: A well balanced neural network achieved a sensitivity of 90.5% and a specificity of 72.2% in predicting malignancy of 88 enhancing lesions. Detailed analysis of false-positive results revealed that every second fibroadenoma showed a 'typical malignant' signal/time curve without any chance to differentiate between fibroadenomas and malignant tissue regarding contrast enhancement alone; but this special group of lesions was represented by a well-defined area of the Self-Organizing Map. Discussion: Self-Organizing Maps are capable of classifying a dynamic signal/time curve as 'typical benign' or 'typical malignant'. Therefore, they can be used as second opinion. In view of the now known localization of fibroadenomas enhancing like malignant tumors at the Self-Organizing Map, these lesions could be passed to further analysis by additional post-processing elements (e.g., based on T2-weighted series or morphology analysis) in the future. (orig.)

Spiers memorial lecture. Organic electronics: an organic materials perspective.

Science.gov (United States)

Wudl, Fred

2014-01-01

This Introductory Lecture is intended to provide a background to Faraday Discussion 174: "Organic Photonics and Electronics" and will consist of a chronological, subjective review of organic electronics. Starting with "ancient history" (1888) and history (1950-present), the article will take us to the present. The principal developments involved the processes of charge carrier generation and charge transport in molecular solids, starting with insulators (photoconductors) and moving to metals, to semiconductors and ending with the most popular semiconductor devices, such as organic light-emitting diodes (OLEDs), organic field effect transistors (OFETs) and organic photovoltaics (OPVs). The presentation will be from an organic chemistry/materials point of view.

Characterization of multilayer nitride coatings by electron microscopy and modulus mapping

International Nuclear Information System (INIS)

Pemmasani, Sai Pramod; Rajulapati, Koteswararao V.; Ramakrishna, M.; Valleti, Krishna; Gundakaram, Ravi C.; Joshi, Shrikant V.

2013-01-01

This paper discusses multi-scale characterization of physical vapour deposited multilayer nitride coatings using a combination of electron microscopy and modulus mapping. Multilayer coatings with a triple layer structure based on TiAlN and nanocomposite nitrides with a nano-multilayered architecture were deposited by Cathodic arc deposition and detailed microstructural studies were carried out employing Energy Dispersive Spectroscopy, Electron Backscattered Diffraction, Focused Ion Beam and Cross sectional Transmission Electron Microscopy in order to identify the different phases and to study microstructural features of the various layers formed as a result of the deposition process. Modulus mapping was also performed to study the effect of varying composition on the moduli of the nano-multilayers within the triple layer coating by using a Scanning Probe Microscopy based technique. To the best of our knowledge, this is the first attempt on modulus mapping of cathodic arc deposited nitride multilayer coatings. This work demonstrates the application of Scanning Probe Microscopy based modulus mapping and electron microscopy for the study of coating properties and their relation to composition and microstructure. - Highlights: • Microstructure of a triple layer nitride coating studied at multiple length scales. • Phases identified by EDS, EBSD and SAED (TEM). • Nanolayered, nanocomposite structure of the coating studied using FIB and TEM. • Modulus mapping identified moduli variation even in a nani-multilayer architecture

Self-organizing feature map (neural networks) as a tool to select the best indicator of road traffic pollution (soil, leaves or bark of Robinia pseudoacacia L.)

Energy Technology Data Exchange (ETDEWEB)

Samecka-Cymerman, A., E-mail: sameckaa@biol.uni.wroc.p [Department of Ecology, Biogeochemistry and Environmental Protection, Wroclaw University, ul. Kanonia 6/8, 50-328 Wroclaw (Poland); Stankiewicz, A.; Kolon, K. [Department of Ecology, Biogeochemistry and Environmental Protection, Wroclaw University, ul. Kanonia 6/8, 50-328 Wroclaw (Poland); Kempers, A.J. [Department of Environmental Sciences, Radboud University of Nijmegen, Toernooiveld, 6525 ED Nijmegen (Netherlands)

2009-07-15

Concentrations of the elements Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were measured in the leaves and bark of Robinia pseudoacacia and the soil in which it grew, in the town of Olesnica (SW Poland) and at a control site. We selected this town because emission from motor vehicles is practically the only source of air pollution, and it seemed interesting to evaluate its influence on soil and plants. The self-organizing feature map (SOFM) yielded distinct groups of soils and R. pseudoacacia leaves and bark, depending on traffic intensity. Only the map classifying bark samples identified an additional group of highly polluted sites along the main highway from Wroclaw to Warszawa. The bark of R. pseudoacacia seems to be a better bioindicator of long-term cumulative traffic pollution in the investigated area, while leaves are good indicators of short-term seasonal accumulation trends. - Once trained, SOFM could be used in the future to recognize types of pollution.

Mapping Soil Organic Matter with Hyperspectral Imaging

Science.gov (United States)

Moni, Christophe; Burud, Ingunn; Flø, Andreas; Rasse, Daniel

2014-05-01

Soil organic matter (SOM) plays a central role for both food security and the global environment. Soil organic matter is the 'glue' that binds soil particles together, leading to positive effects on soil water and nutrient availability for plant growth and helping to counteract the effects of erosion, runoff, compaction and crusting. Hyperspectral measurements of samples of soil profiles have been conducted with the aim of mapping soil organic matter on a macroscopic scale (millimeters and centimeters). Two soil profiles have been selected from the same experimental site, one from a plot amended with biochar and another one from a control plot, with the specific objective to quantify and map the distribution of biochar in the amended profile. The soil profiles were of size (30 x 10 x 10) cm3 and were scanned with two pushbroomtype hyperspectral cameras, one which is sensitive in the visible wavelength region (400 - 1000 nm) and one in the near infrared region (1000 - 2500 nm). The images from the two detectors were merged together into one full dataset covering the whole wavelength region. Layers of 15 mm were removed from the 10 cm high sample such that a total of 7 hyperspectral images were obtained from the samples. Each layer was analyzed with multivariate statistical techniques in order to map the different components in the soil profile. Moreover, a 3-dimensional visalization of the components through the depth of the sample was also obtained by combining the hyperspectral images from all the layers. Mid-infrared spectroscopy of selected samples of the measured soil profiles was conducted in order to correlate the chemical constituents with the hyperspectral results. The results show that hyperspectral imaging is a fast, non-destructive technique, well suited to characterize soil profiles on a macroscopic scale and hence to map elements and different organic matter quality present in a complete pedon. As such, we were able to map and quantify biochar in our

Self-organization in irregular landscapes: Detecting autogenic interactions from field data using descriptive statistics and dynamical systems theory

Science.gov (United States)

Larsen, L.; Watts, D.; Khurana, A.; Anderson, J. L.; Xu, C.; Merritts, D. J.

2015-12-01

The classic signal of self-organization in nature is pattern formation. However, the interactions and feedbacks that organize depositional landscapes do not always result in regular or fractal patterns. How might we detect their existence and effects in these "irregular" landscapes? Emergent landscapes such as newly forming deltaic marshes or some restoration sites provide opportunities to study the autogenic processes that organize landscapes and their physical signatures. Here we describe a quest to understand autogenic vs. allogenic controls on landscape evolution in Big Spring Run, PA, a landscape undergoing restoration from bare-soil conditions to a target wet meadow landscape. The contemporary motivation for asking questions about autogenic vs. allogenic controls is to evaluate how important initial conditions or environmental controls may be for the attainment of management objectives. However, these questions can also inform interpretation of the sedimentary record by enabling researchers to separate signals that may have arisen through self-organization processes from those resulting from environmental perturbations. Over three years at Big Spring Run, we mapped the dynamic evolution of floodplain vegetation communities and distributions of abiotic variables and topography. We used principal component analysis and transition probability analysis to detect associative interactions between vegetation and geomorphic variables and convergent cross-mapping on lidar data to detect causal interactions between biomass and topography. Exploratory statistics revealed that plant communities with distinct morphologies exerted control on landscape evolution through stress divergence (i.e., channel initiation) and promoting the accumulation of fine sediment in channels. Together, these communities participated in a negative feedback that maintains low energy and multiple channels. Because of the spatially explicit nature of this feedback, causal interactions could not

The dynamics of ant mosaics in tropical rainforests characterized using the Self-Organizing Map algorithm.

Science.gov (United States)

Dejean, Alain; Azémar, Frédéric; Céréghino, Régis; Leponce, Maurice; Corbara, Bruno; Orivel, Jérôme; Compin, Arthur

2016-08-01

Ants, the most abundant taxa among canopy-dwelling animals in tropical rainforests, are mostly represented by territorially dominant arboreal ants (TDAs) whose territories are distributed in a mosaic pattern (arboreal ant mosaics). Large TDA colonies regulate insect herbivores, with implications for forestry and agronomy. What generates these mosaics in vegetal formations, which are dynamic, still needs to be better understood. So, from empirical research based on 3 Cameroonian tree species (Lophira alata, Ochnaceae; Anthocleista vogelii, Gentianaceae; and Barteria fistulosa, Passifloraceae), we used the Self-Organizing Map (SOM, neural network) to illustrate the succession of TDAs as their host trees grow and age. The SOM separated the trees by species and by size for L. alata, which can reach 60 m in height and live several centuries. An ontogenic succession of TDAs from sapling to mature trees is shown, and some ecological traits are highlighted for certain TDAs. Also, because the SOM permits the analysis of data with many zeroes with no effect of outliers on the overall scatterplot distributions, we obtained ecological information on rare species. Finally, the SOM permitted us to show that functional groups cannot be selected at the genus level as congeneric species can have very different ecological niches, something particularly true for Crematogaster spp., which include a species specifically associated with B. fistulosa, nondominant species and TDAs. Therefore, the SOM permitted the complex relationships between TDAs and their growing host trees to be analyzed, while also providing new information on the ecological traits of the ant species involved. © 2015 Institute of Zoology, Chinese Academy of Sciences.

Tracking senescence-induced patterns in leaf litter leachate using parallel factor analysis (PARAFAC) modeling and self-organizing maps

Science.gov (United States)

Wheeler, K. I.; Levia, D. F.; Hudson, J. E.

2017-09-01

In autumn, the dissolved organic matter (DOM) contribution of leaf litter leachate to streams in forested watersheds changes as trees undergo resorption, senescence, and leaf abscission. Despite its biogeochemical importance, little work has investigated how leaf litter leachate DOM changes throughout autumn and how any changes might differ interspecifically and intraspecifically. Since climate change is expected to cause vegetation migration, it is necessary to learn how changes in forest composition could affect DOM inputs via leaf litter leachate. We examined changes in leaf litter leachate fluorescent DOM (FDOM) from American beech (Fagus grandifolia Ehrh.) leaves in Maryland, Rhode Island, Vermont, and North Carolina and from yellow poplar (Liriodendron tulipifera L.) leaves from Maryland. FDOM in leachate samples was characterized by excitation-emission matrices (EEMs). A six-component parallel factor analysis (PARAFAC) model was created to identify components that accounted for the majority of the variation in the data set. Self-organizing maps (SOM) compared the PARAFAC component proportions of leachate samples. Phenophase and species exerted much stronger influence on the determination of a sample's SOM placement than geographic origin. As expected, FDOM from all trees transitioned from more protein-like components to more humic-like components with senescence. Percent greenness of sampled leaves and the proportion of tyrosine-like component 1 were found to be significantly different between the two genetic beech clusters, suggesting differences in photosynthesis and resorption. Our results highlight the need to account for interspecific and intraspecific variations in leaf litter leachate FDOM throughout autumn when examining the influence of allochthonous inputs to streams.

The Relationship between Self-Assembly and Conformal Mappings

Science.gov (United States)

Duque, Carlos; Santangelo, Christian

The isotropic growth of a thin sheet has been used as a way to generate programmed shapes through controlled buckling. We discuss how conformal mappings, which are transformations that locally preserve angles, provide a way to quantify the area growth needed to produce a particular shape. A discrete version of the conformal map can be constructed from circle packings, which are maps between packings of circles whose contact network is preserved. This provides a link to the self-assembly of particles on curved surfaces. We performed simulations of attractive particles on a curved surface using molecular dynamics. The resulting particle configurations were used to generate the corresponding discrete conformal map, allowing us to quantify the degree of area distortion required to produce a particular shape by finding particle configurations that minimize the area distortion.

Simulation study of one-dimensional self-organized pattern in an atmospheric-pressure dielectric barrier discharge

Energy Technology Data Exchange (ETDEWEB)

Zhang, Jiao; Wang, Yanhui, E-mail: wangyh@dlut.edu.cn; Wang, Dezhen, E-mail: wangdez@dlut.edu.cn [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China)

2015-04-15

A two-dimensional fluid model is developed to simulate the one-dimensional self-organized patterns in an atmospheric-pressure dielectric barrier discharge (DBD) driven by sinusoidal voltage in argon. Under certain conditions, by changing applied voltage amplitude, the transversely uniform discharge can evolve into the patterned discharge and the varied self-organized patterned discharges with different numbers and arrangements of discharge channels can be observed. Similar to the uniform atmospheric-pressure DBD, the patterned discharge mode is found to undergo a transition from Townsend regime, sub-glow regime to glow regime with increasing applied voltage amplitude. In the different regimes, charged particles and electric field display different dynamical behaviors. If the voltage amplitude is increased over a certain value, the discharge enters an asymmetric patterned discharge mode, and then transforms into the spatially chaotic state with out-of-order discharge channels. The reason for forming the one-dimensional self-organized pattern is mainly due to the so-called activation-inhibition effect resulting from the local high electron density region appearing in discharge space. Electrode arrangement is the reason that induces local high electron density.

Complexity of a kind of interval continuous self-map of finite type

International Nuclear Information System (INIS)

Wang Lidong; Chu Zhenyan; Liao Gongfu

2011-01-01

Highlights: → We find the Hausdorff dimension for an interval continuous self-map f of finite type is s element of (0,1) on a non-wandering set. → f| Ω(f) has positive topological entropy. → f| Ω(f) is chaotic such as Devaney chaos, Kato chaos, two point distributional chaos and so on. - Abstract: An interval map is called finitely typal, if the restriction of the map to non-wandering set is topologically conjugate with a subshift of finite type. In this paper, we prove that there exists an interval continuous self-map of finite type such that the Hausdorff dimension is an arbitrary number in the interval (0, 1), discuss various chaotic properties of the map and the relations between chaotic set and the set of recurrent points.

Complexity of a kind of interval continuous self-map of finite type

Energy Technology Data Exchange (ETDEWEB)

Wang Lidong, E-mail: wld@dlnu.edu.cn [Institute of Mathematics, Dalian Nationalities University, Dalian 116600 (China); Institute of Mathematics, Jilin Normal University, Siping 136000 (China); Chu Zhenyan, E-mail: chuzhenyan8@163.com [Institute of Mathematics, Dalian Nationalities University, Dalian 116600 (China) and Institute of Mathematics, Jilin University, Changchun 130023 (China); Liao Gongfu, E-mail: liaogf@email.jlu.edu.cn [Institute of Mathematics, Jilin University, Changchun 130023 (China)

2011-10-15

Highlights: > We find the Hausdorff dimension for an interval continuous self-map f of finite type is s element of (0,1) on a non-wandering set. > f|{sub {Omega}(f)} has positive topological entropy. > f|{sub {Omega}(f)} is chaotic such as Devaney chaos, Kato chaos, two point distributional chaos and so on. - Abstract: An interval map is called finitely typal, if the restriction of the map to non-wandering set is topologically conjugate with a subshift of finite type. In this paper, we prove that there exists an interval continuous self-map of finite type such that the Hausdorff dimension is an arbitrary number in the interval (0, 1), discuss various chaotic properties of the map and the relations between chaotic set and the set of recurrent points.

Cell shape characterization and classification with discrete Fourier transforms and self-organizing maps.

Science.gov (United States)

Kriegel, Fabian L; Köhler, Ralf; Bayat-Sarmadi, Jannike; Bayerl, Simon; Hauser, Anja E; Niesner, Raluca; Luch, Andreas; Cseresnyes, Zoltan

2018-03-01

Cells in their natural environment often exhibit complex kinetic behavior and radical adjustments of their shapes. This enables them to accommodate to short- and long-term changes in their surroundings under physiological and pathological conditions. Intravital multi-photon microscopy is a powerful tool to record this complex behavior. Traditionally, cell behavior is characterized by tracking the cells' movements, which yields numerous parameters describing the spatiotemporal characteristics of cells. Cells can be classified according to their tracking behavior using all or a subset of these kinetic parameters. This categorization can be supported by the a priori knowledge of experts. While such an approach provides an excellent starting point for analyzing complex intravital imaging data, faster methods are required for automated and unbiased characterization. In addition to their kinetic behavior, the 3D shape of these cells also provide essential clues about the cells' status and functionality. New approaches that include the study of cell shapes as well may also allow the discovery of correlations amongst the track- and shape-describing parameters. In the current study, we examine the applicability of a set of Fourier components produced by Discrete Fourier Transform (DFT) as a tool for more efficient and less biased classification of complex cell shapes. By carrying out a number of 3D-to-2D projections of surface-rendered cells, the applied method reduces the more complex 3D shape characterization to a series of 2D DFTs. The resulting shape factors are used to train a Self-Organizing Map (SOM), which provides an unbiased estimate for the best clustering of the data, thereby characterizing groups of cells according to their shape. We propose and demonstrate that such shape characterization is a powerful addition to, or a replacement for kinetic analysis. This would make it especially useful in situations where live kinetic imaging is less practical or not

Threshold-Voltage Shifts in Organic Transistors Due to Self-Assembled Monolayers at the Dielectric: Evidence for Electronic Coupling and Dipolar Effects.

Science.gov (United States)

Aghamohammadi, Mahdieh; Rödel, Reinhold; Zschieschang, Ute; Ocal, Carmen; Boschker, Hans; Weitz, R Thomas; Barrena, Esther; Klauk, Hagen

2015-10-21

The mechanisms behind the threshold-voltage shift in organic transistors due to functionalizing of the gate dielectric with self-assembled monolayers (SAMs) are still under debate. We address the mechanisms by which SAMs determine the threshold voltage, by analyzing whether the threshold voltage depends on the gate-dielectric capacitance. We have investigated transistors based on five oxide thicknesses and two SAMs with rather diverse chemical properties, using the benchmark organic semiconductor dinaphtho[2,3-b:2',3'-f]thieno[3,2-b]thiophene. Unlike several previous studies, we have found that the dependence of the threshold voltage on the gate-dielectric capacitance is completely different for the two SAMs. In transistors with an alkyl SAM, the threshold voltage does not depend on the gate-dielectric capacitance and is determined mainly by the dipolar character of the SAM, whereas in transistors with a fluoroalkyl SAM the threshold voltages exhibit a linear dependence on the inverse of the gate-dielectric capacitance. Kelvin probe force microscopy measurements indicate this behavior is attributed to an electronic coupling between the fluoroalkyl SAM and the organic semiconductor.

Note: Electron energy spectroscopy mapping of surface with scanning tunneling microscope.

Science.gov (United States)

Li, Meng; Xu, Chunkai; Zhang, Panke; Li, Zhean; Chen, Xiangjun

2016-08-01

We report a novel scanning probe electron energy spectrometer (SPEES) which combines a double toroidal analyzer with a scanning tunneling microscope to achieve both topography imaging and electron energy spectroscopy mapping of surface in situ. The spatial resolution of spectroscopy mapping is determined to be better than 0.7 ± 0.2 μm at a tip sample distance of 7 μm. Meanwhile, the size of the field emission electron beam spot on the surface is also measured, and is about 3.6 ± 0.8 μm in diameter. This unambiguously demonstrates that the spatial resolution of SPEES technique can be much better than the size of the incident electron beam.

Note: Electron energy spectroscopy mapping of surface with scanning tunneling microscope

Energy Technology Data Exchange (ETDEWEB)

Li, Meng; Xu, Chunkai, E-mail: xuck@ustc.edu.cn, E-mail: xjun@ustc.edu.cn; Zhang, Panke; Li, Zhean; Chen, Xiangjun, E-mail: xuck@ustc.edu.cn, E-mail: xjun@ustc.edu.cn [Hefei National Laboratory for Physical Science at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China and Synergetic Innovation Center of Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei 230026 (China)

2016-08-15

We report a novel scanning probe electron energy spectrometer (SPEES) which combines a double toroidal analyzer with a scanning tunneling microscope to achieve both topography imaging and electron energy spectroscopy mapping of surface in situ. The spatial resolution of spectroscopy mapping is determined to be better than 0.7 ± 0.2 μm at a tip sample distance of 7 μm. Meanwhile, the size of the field emission electron beam spot on the surface is also measured, and is about 3.6 ± 0.8 μm in diameter. This unambiguously demonstrates that the spatial resolution of SPEES technique can be much better than the size of the incident electron beam.

Note: Electron energy spectroscopy mapping of surface with scanning tunneling microscope

International Nuclear Information System (INIS)

Li, Meng; Xu, Chunkai; Zhang, Panke; Li, Zhean; Chen, Xiangjun

2016-01-01

We report a novel scanning probe electron energy spectrometer (SPEES) which combines a double toroidal analyzer with a scanning tunneling microscope to achieve both topography imaging and electron energy spectroscopy mapping of surface in situ. The spatial resolution of spectroscopy mapping is determined to be better than 0.7 ± 0.2 μm at a tip sample distance of 7 μm. Meanwhile, the size of the field emission electron beam spot on the surface is also measured, and is about 3.6 ± 0.8 μm in diameter. This unambiguously demonstrates that the spatial resolution of SPEES technique can be much better than the size of the incident electron beam.

A buffer material optimal design in the radioactive wastes geological disposal using the satisficing trade-off method and the self-organizing map

International Nuclear Information System (INIS)

Okamoto, Takashi; Hanaoka, Yuya; Aiyoshi, Eitaro; Kobayashi, Yoko

2012-01-01

In this paper, we consider a multi-objective optimization method in order to obtain a preferred solution for the buffer material optimal design problem in the high-level radioactive wastes geological disposal. The buffer material optimal design problem is formulated as a constrained multi-objective optimization problem. Its Pareto optimal solutions are distributed evenly on whole bounds of the feasible region. Hence, we develop a search method to find a preferred solution easily for a decision maker from the Pareto optimal solutions which are distributed evenly and vastly. In the preferred solution search method, the visualization technique of a Pareto optimal solution set using the self-organizing map is introduced into the satisficing trade-off method which is the interactive method to obtain a Pareto optimal solution that satisfies a decision maker. We confirm the effectiveness of the preferred solution search method in the buffer material optimal design problem. (author)

Differentiating the Spatiotemporal Distribution of Natural and Anthropogenic Processes on River Water-Quality Variation Using a Self-Organizing Map With Factor Analysis.

Science.gov (United States)

Wang, Yeuh-Bin; Liu, Chen-Wuing; Lee, Jin-Jing

2015-08-01

To elucidate the historical improvement and advanced measure of river water quality in the Taipei metropolitan area, this study applied the self-organizing map (SOM) technique with factor analysis (FA) to differentiate the spatiotemporal distribution of natural and anthropogenic processes on river water-quality variation spanning two decades. The SOM clustered river water quality into five groups: very low pollution, low pollution, moderate pollution, high pollution, and very high pollution. FA was then used to extract four latent factors that dominated water quality from 1991 to 2011 including three anthropogenic process factors (organic, industrial, and copper pollution) and one natural process factor [suspended solids (SS) pollution]. The SOM revealed that the water quality improved substantially over time. However, the downstream river water quality was still classified as high pollution because of an increase in anthropogenic activity. FA showed the spatiotemporal pattern of each factor score decreasing over time, but the organic pollution factor downstream of the Tamsui River, as well as the SS factor scores in the upstream major tributary (the Dahan Stream), remained within the high pollution level. Therefore, we suggest that public sewage-treatment plants should be upgraded from their current secondary biological processing to advanced treatment processing. The conservation of water and soil must also be reinforced to decrease the SS loading of the Dahan Stream from natural erosion processes in the future.

Real-space Mapping of Surface Trap States in CIGSe Nanocrystals using 4D Electron Microscopy

KAUST Repository

Bose, Riya

2016-05-26

Surface trap states in semiconductor copper indium gallium selenide nanocrystals (NCs) which serve as undesirable channels for non-radiative carrier recombination, remain a great challenge impeding the development of solar and optoelectronics devices based on these NCs. In order to design efficient passivation techniques to minimize these trap states, a precise knowledge about the charge carrier dynamics on the NCs surface is essential. However, selective mapping of surface traps requires capabilities beyond the reach of conventional laser spectroscopy and static electron microscopy; it can only be accessed by using a one-of-a-kind, second-generation four-dimensional scanning ultrafast electron microscope (4D S-UEM) with sub-picosecond temporal and nanometer spatial resolutions. Here, we precisely map the surface charge carrier dynamics of copper indium gallium selenide NCs before and after surface passivation in real space and time using S-UEM. The time-resolved snapshots clearly demonstrate that the density of the trap states is significantly reduced after zinc sulfide (ZnS) shelling. Furthermore, removal of trap states and elongation of carrier lifetime are confirmed by the increased photocurrent of the self-biased photodetector fabricated using the shelled NCs.

Real-space Mapping of Surface Trap States in CIGSe Nanocrystals using 4D Electron Microscopy

KAUST Repository

Bose, Riya; Bera, Ashok; Parida, Manas R.; Adhikari, Aniruddha; Shaheen, Basamat; Alarousu, Erkki; Sun, Jingya; Wu, Tao; Bakr, Osman; Mohammed, Omar F.

2016-01-01

Surface trap states in semiconductor copper indium gallium selenide nanocrystals (NCs) which serve as undesirable channels for non-radiative carrier recombination, remain a great challenge impeding the development of solar and optoelectronics devices based on these NCs. In order to design efficient passivation techniques to minimize these trap states, a precise knowledge about the charge carrier dynamics on the NCs surface is essential. However, selective mapping of surface traps requires capabilities beyond the reach of conventional laser spectroscopy and static electron microscopy; it can only be accessed by using a one-of-a-kind, second-generation four-dimensional scanning ultrafast electron microscope (4D S-UEM) with sub-picosecond temporal and nanometer spatial resolutions. Here, we precisely map the surface charge carrier dynamics of copper indium gallium selenide NCs before and after surface passivation in real space and time using S-UEM. The time-resolved snapshots clearly demonstrate that the density of the trap states is significantly reduced after zinc sulfide (ZnS) shelling. Furthermore, removal of trap states and elongation of carrier lifetime are confirmed by the increased photocurrent of the self-biased photodetector fabricated using the shelled NCs.

The genotype-phenotype map of an evolving digital organism

OpenAIRE

Fortuna, Miguel A.; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms fr...

Quantification of Hepatorenal Index for Computer-Aided Fatty Liver Classification with Self-Organizing Map and Fuzzy Stretching from Ultrasonography

Directory of Open Access Journals (Sweden)

Kwang Baek Kim

2015-01-01

Full Text Available Accurate measures of liver fat content are essential for investigating hepatic steatosis. For a noninvasive inexpensive ultrasonographic analysis, it is necessary to validate the quantitative assessment of liver fat content so that fully automated reliable computer-aided software can assist medical practitioners without any operator subjectivity. In this study, we attempt to quantify the hepatorenal index difference between the liver and the kidney with respect to the multiple severity status of hepatic steatosis. In order to do this, a series of carefully designed image processing techniques, including fuzzy stretching and edge tracking, are applied to extract regions of interest. Then, an unsupervised neural learning algorithm, the self-organizing map, is designed to establish characteristic clusters from the image, and the distribution of the hepatorenal index values with respect to the different levels of the fatty liver status is experimentally verified to estimate the differences in the distribution of the hepatorenal index. Such findings will be useful in building reliable computer-aided diagnostic software if combined with a good set of other characteristic feature sets and powerful machine learning classifiers in the future.

75 FR 39299 - Self-Regulatory Organizations; NASDAQ OMX BX, Inc.; Notice of Filing and Immediate Effectiveness...

Science.gov (United States)

2010-07-08

... French as the Bourse de Montr[eacute]al Inc. II. Self-Regulatory Organization's Statement of the Purpose... submitted by any of the following methods: Electronic Comments Use the Commission's Internet comment form...

Molecular surface mesh generation by filtering electron density map.

Science.gov (United States)

Giard, Joachim; Macq, Benoît

2010-01-01

Bioinformatics applied to macromolecules are now widely spread and in continuous expansion. In this context, representing external molecular surface such as the Van der Waals Surface or the Solvent Excluded Surface can be useful for several applications. We propose a fast and parameterizable algorithm giving good visual quality meshes representing molecular surfaces. It is obtained by isosurfacing a filtered electron density map. The density map is the result of the maximum of Gaussian functions placed around atom centers. This map is filtered by an ideal low-pass filter applied on the Fourier Transform of the density map. Applying the marching cubes algorithm on the inverse transform provides a mesh representation of the molecular surface.

Molecular Surface Mesh Generation by Filtering Electron Density Map

Directory of Open Access Journals (Sweden)

Joachim Giard

2010-01-01

Full Text Available Bioinformatics applied to macromolecules are now widely spread and in continuous expansion. In this context, representing external molecular surface such as the Van der Waals Surface or the Solvent Excluded Surface can be useful for several applications. We propose a fast and parameterizable algorithm giving good visual quality meshes representing molecular surfaces. It is obtained by isosurfacing a filtered electron density map. The density map is the result of the maximum of Gaussian functions placed around atom centers. This map is filtered by an ideal low-pass filter applied on the Fourier Transform of the density map. Applying the marching cubes algorithm on the inverse transform provides a mesh representation of the molecular surface.

Gaia eclipsing binary and multiple systems. Supervised classification and self-organizing maps

Science.gov (United States)

Süveges, M.; Barblan, F.; Lecoeur-Taïbi, I.; Prša, A.; Holl, B.; Eyer, L.; Kochoska, A.; Mowlavi, N.; Rimoldini, L.

2017-07-01

Context. Large surveys producing tera- and petabyte-scale databases require machine-learning and knowledge discovery methods to deal with the overwhelming quantity of data and the difficulties of extracting concise, meaningful information with reliable assessment of its uncertainty. This study investigates the potential of a few machine-learning methods for the automated analysis of eclipsing binaries in the data of such surveys. Aims: We aim to aid the extraction of samples of eclipsing binaries from such databases and to provide basic information about the objects. We intend to estimate class labels according to two different, well-known classification systems, one based on the light curve morphology (EA/EB/EW classes) and the other based on the physical characteristics of the binary system (system morphology classes; detached through overcontact systems). Furthermore, we explore low-dimensional surfaces along which the light curves of eclipsing binaries are concentrated, and consider their use in the characterization of the binary systems and in the exploration of biases of the full unknown Gaia data with respect to the training sets. Methods: We have explored the performance of principal component analysis (PCA), linear discriminant analysis (LDA), Random Forest classification and self-organizing maps (SOM) for the above aims. We pre-processed the photometric time series by combining a double Gaussian profile fit and a constrained smoothing spline, in order to de-noise and interpolate the observed light curves. We achieved further denoising, and selected the most important variability elements from the light curves using PCA. Supervised classification was performed using Random Forest and LDA based on the PC decomposition, while SOM gives a continuous 2-dimensional manifold of the light curves arranged by a few important features. We estimated the uncertainty of the supervised methods due to the specific finite training set using ensembles of models constructed

Microstructural control over soluble pentacene deposited by capillary pen printing for organic electronics.

Science.gov (United States)

Lee, Wi Hyoung; Min, Honggi; Park, Namwoo; Lee, Junghwi; Seo, Eunsuk; Kang, Boseok; Cho, Kilwon; Lee, Hwa Sung

2013-08-28

Research into printing techniques has received special attention for the commercialization of cost-efficient organic electronics. Here, we have developed a capillary pen printing technique to realize a large-area pattern array of organic transistors and systematically investigated self-organization behavior of printed soluble organic semiconductor ink. The capillary pen-printed deposits of organic semiconductor, 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS_PEN), was well-optimized in terms of morphological and microstructural properties by using ink with mixed solvents of chlorobenzene (CB) and 1,2-dichlorobenzene (DCB). Especially, a 1:1 solvent ratio results in the best transistor performances. This result is attributed to the unique evaporation characteristics of the TIPS_PEN deposits where fast evaporation of CB induces a morphological evolution at the initial printed position, and the remaining DCB with slow evaporation rate offers a favorable crystal evolution at the pinned position. Finally, a large-area transistor array was facilely fabricated by drawing organic electrodes and active layers with a versatile capillary pen. Our approach provides an efficient printing technique for fabricating large-area arrays of organic electronics and further suggests a methodology to enhance their performances by microstructural control of the printed organic semiconducting deposits.

‘’Mapping Self- and Co-regulation Approaches in the EU Context’’ : Explorative Study for the European Commission, DG Connect

NARCIS (Netherlands)

Senden, L.A.J.; Kica, E.; Klinger, Kilian; Hiemstra, M.I.

2015-01-01

This report presents a first mapping or inventory of the different approaches to self- and co- regulation (SCR) that can be found within the EU context, in a number of Member States (MS) and international organizations. The report consists of four sections. Whereas the first section provides an

Social-Ecological Patterns of Soil Heavy Metals Based on a Self-Organizing Map (SOM: A Case Study in Beijing, China

Directory of Open Access Journals (Sweden)

Binwu Wang

2014-03-01

Full Text Available The regional management of trace elements in soils requires understanding the interaction between the natural system and human socio-economic activities. In this study, a social-ecological patterns of heavy metals (SEPHM approach was proposed to identify the heavy metal concentration patterns and processes in different ecoregions of Beijing (China based on a self-organizing map (SOM. Potential ecological risk index (RI values of Cr, Ni, Zn, Hg, Cu, As, Cd and Pb were calculated for 1,018 surface soil samples. These data were averaged in accordance with 253 communities and/or towns, and compared with demographic, agriculture structure, geomorphology, climate, land use/cover, and soil-forming parent material to discover the SEPHM. Multivariate statistical techniques were further applied to interpret the control factors of each SEPHM. SOM application clustered the 253 towns into nine groups on the map size of 12 × 7 plane (quantization error 1.809; topographic error, 0.0079. The distribution characteristics and Spearman rank correlation coefficients of RIs were strongly associated with the population density, vegetation index, industrial and mining land percent and road density. The RIs were relatively high in which towns in a highly urbanized area with large human population density exist, while low RIs occurred in mountainous and high vegetation cover areas. The resulting dataset identifies the SEPHM of Beijing and links the apparent results of RIs to driving factors, thus serving as an excellent data source to inform policy makers for legislative and land management actions.

Development, application and evaluation of a computational tool for management high voltage break disconnector based on self-organizing maps and image processing

International Nuclear Information System (INIS)

Freitas Colaco, Daniel; Alexandria, Auzuir R. de; Cortez, Paulo Cesar; Frota, Joao Batista B.; Nunes de Lima, Jose Nunes de; Albuquerque, Victor Hugo C. de

2010-01-01

This work has the objective of developing, analysing and applying a new tool for management the status of break disconnectors in high voltage substations from digital images. This tool uses a non-supervised kind of artificial neural network using the Kohonen learning algorithm, known as a self-organizing maps. In order to develop the proposed tool, C/C++ programming language, provided with easily used interfaces, is used. In order to obtain the results, three environments are considered: one for laboratory simulation and two pilot projects installed in the Fortaleza II/CHESF substation. These pilots are used for 230 kV EV-2000 type and 500 kV semi-pantographic type break disconnector management tests. The results prove the developed system's efficiency, because it is able to detect 100% of open and closed identification situations. However, the neural network utilised for management break disconnectors has become suitable for installation in high voltage substations in order to support the maintenance team in safely handling these disconnectors.

Development, application and evaluation of a computational tool for management high voltage break disconnector based on self-organizing maps and image processing

Energy Technology Data Exchange (ETDEWEB)

Freitas Colaco, Daniel, E-mail: colaco@deti.ufc.b [Universidade Federal do Ceara (UFC), Centro de Tecnologia (CT), Departamento de Engenharia de Teleinformatica - DETI, Campus do PICI S/N, Bloco 723, 60455-970 Fortaleza, Ceara (Brazil); Alexandria, Auzuir R. de, E-mail: auzuir@ifce.edu.b [Instituto Federal de Educacao, Ciencia e Tecnologia do Ceara (IFCE), Area da industria, Nucleo de Simulacao Computacional-N5IMCO, Campus Fortaleza, Av. Treze de Maio, 2081, 60040-531 Fortaleza, Ceara (Brazil); Cortez, Paulo Cesar, E-mail: cortez@deti.ufc.b [Universidade Federal do Ceara (UFC), Centro de Tecnologia (CT), Departamento de Engenharia de Teleinformatica - DETI, Campus do PICI S/N, Bloco 723, 60455-970 Fortaleza, Ceara (Brazil); Frota, Joao Batista B., E-mail: jb@ifce.edu.b [Instituto Federal de Educacao, Ciencia e Tecnologia do Ceara (IFCE), Area da industria, Nucleo de Simulacao Computacional-N5IMCO, Campus Fortaleza, Av. Treze de Maio, 2081, 60040-531 Fortaleza, Ceara (Brazil); Nunes de Lima, Jose Nunes de, E-mail: josenl@chesf.gov.b [Companhia Hidro Eletrica do Sao Francisco (CHESF), Rua Delmiro Gouveia, 333, 50761-901 Recife, Pernambuco (Brazil); Albuquerque, Victor Hugo C. de, E-mail: victor.albuquerque@fe.up.p [Universidade de Fortaleza (UNIFOR), Centro de Ciencias Tecnologicas (CCT), Nucleo de Pesquisas Tecnologicas - NPT, Av. Washington Soares, 1321, Sala NPT/CCT, CEP 60.811-905, Edson Queiroz (Brazil); Universidade Federal da Paraiba (UFPB), Departamento de Engenharia Mecanica (DEM), Cidade Universitaria, S/N, 58059-900 Joao Pessoa, Paraiba (Brazil)

2010-11-15

This work has the objective of developing, analysing and applying a new tool for management the status of break disconnectors in high voltage substations from digital images. This tool uses a non-supervised kind of artificial neural network using the Kohonen learning algorithm, known as a self-organizing maps. In order to develop the proposed tool, C/C++ programming language, provided with easily used interfaces, is used. In order to obtain the results, three environments are considered: one for laboratory simulation and two pilot projects installed in the Fortaleza II/CHESF substation. These pilots are used for 230 kV EV-2000 type and 500 kV semi-pantographic type break disconnector management tests. The results prove the developed system's efficiency, because it is able to detect 100% of open and closed identification situations. However, the neural network utilised for management break disconnectors has become suitable for installation in high voltage substations in order to support the maintenance team in safely handling these disconnectors.

Electron self-exchange in hemoglobins revealed by deutero-hemin substitution.

Science.gov (United States)

Athwal, Navjot Singh; Alagurajan, Jagannathan; Sturms, Ryan; Fulton, D Bruce; Andreotti, Amy H; Hargrove, Mark S

2015-09-01

Hemoglobins (phytoglobins) from rice plants (nsHb1) and from the cyanobacterium Synechocystis (PCC 6803) (SynHb) can reduce hydroxylamine with two electrons to form ammonium. The reaction requires intermolecular electron transfer between protein molecules, and rapid electron self-exchange might play a role in distinguishing these hemoglobins from others with slower reaction rates, such as myoglobin. A relatively rapid electron self-exchange rate constant has been measured for SynHb by NMR, but the rate constant for myoglobin is equivocal and a value for nsHb1 has not yet been measured. Here we report electron self-exchange rate constants for nsHb1 and Mb as a test of their role in hydroxylamine reduction. These proteins are not suitable for analysis by NMR ZZ exchange, so a method was developed that uses cross-reactions between each hemoglobin and its deutero-hemin substituted counterpart. The resulting electron transfer is between identical proteins with low driving forces and thus closely approximates true electron self-exchange. The reactions can be monitored spectrally due to the distinct spectra of the prosthetic groups, and from this electron self-exchange rate constants of 880 (SynHb), 2900 (nsHb1), and 0.05M(-1) s(-1) (Mb) have been measured for each hemoglobin. Calculations of cross-reactions using these values accurately predict hydroxylamine reduction rates for each protein, suggesting that electron self-exchange plays an important role in the reaction. Copyright © 2015 Elsevier Inc. All rights reserved.

Self-consistent electron transport in collisional plasmas

International Nuclear Information System (INIS)

Mason, R.J.

1982-01-01

A self-consistent scheme has been developed to model electron transport in evolving plasmas of arbitrary classical collisionality. The electrons and ions are treated as either multiple donor-cell fluids, or collisional particles-in-cell. Particle suprathermal electrons scatter off ions, and drag against fluid background thermal electrons. The background electrons undergo ion friction, thermal coupling, and bremsstrahlung. The components move in self-consistent advanced E-fields, obtained by the Implicit Moment Method, which permits Δt >> ω/sub p/ -1 and Δx >> lambda/sub D/ - offering a 10 2 - 10 3 -fold speed-up over older explicit techniques. The fluid description for the background plasma components permits the modeling of transport in systems spanning more than a 10 7 -fold change in density, and encompassing contiguous collisional and collisionless regions. Results are presented from application of the scheme to the modeling of CO 2 laser-generated suprathermal electron transport in expanding thin foils, and in multi-foil target configurations

Portraits of self-organization in fish schools interacting with robots

Science.gov (United States)

Aureli, M.; Fiorilli, F.; Porfiri, M.

2012-05-01

In this paper, we propose an enabling computational and theoretical framework for the analysis of experimental instances of collective behavior in response to external stimuli. In particular, this work addresses the characterization of aggregation and interaction phenomena in robot-animal groups through the exemplary analysis of fish schooling in the vicinity of a biomimetic robot. We adapt global observables from statistical mechanics to capture the main features of the shoal collective motion and its response to the robot from experimental observations. We investigate the shoal behavior by using a diffusion mapping analysis performed on these global observables that also informs the definition of relevant portraits of self-organization.

Quantifying Postural Control during Exergaming Using Multivariate Whole-Body Movement Data: A Self-Organizing Maps Approach.

Directory of Open Access Journals (Sweden)

Mike van Diest

Full Text Available Exergames are becoming an increasingly popular tool for training balance ability, thereby preventing falls in older adults. Automatic, real time, assessment of the user's balance control offers opportunities in terms of providing targeted feedback and dynamically adjusting the gameplay to the individual user, yet algorithms for quantification of balance control remain to be developed. The aim of the present study was to identify movement patterns, and variability therein, of young and older adults playing a custom-made weight-shifting (ice-skating exergame.Twenty older adults and twenty young adults played a weight-shifting exergame under five conditions of varying complexity, while multi-segmental whole-body movement data were captured using Kinect. Movement coordination patterns expressed during gameplay were identified using Self Organizing Maps (SOM, an artificial neural network, and variability in these patterns was quantified by computing Total Trajectory Variability (TTvar. Additionally a k Nearest Neighbor (kNN classifier was trained to discriminate between young and older adults based on the SOM features.Results showed that TTvar was significantly higher in older adults than in young adults, when playing the exergame under complex task conditions. The kNN classifier showed a classification accuracy of 65.8%.Older adults display more variable sway behavior than young adults, when playing the exergame under complex task conditions. The SOM features characterizing movement patterns expressed during exergaming allow for discriminating between young and older adults with limited accuracy. Our findings contribute to the development of algorithms for quantification of balance ability during home-based exergaming for balance training.

Variable magnification dual lens electron holography for semiconductor junction profiling and strain mapping

International Nuclear Information System (INIS)

Wang, Y.Y.; Li, J.; Domenicucci, A.; Bruley, J.

2013-01-01

Dual lens operation for electron holography, which was developed previously (Wang et al., Ultramicroscopy 101 (2004) 63–72; US patent: 7,015,469 B2 (2006)), is re-investigated for bright field (junction profiling) and dark field (strain mapping) electron holography using FEI instrumentation (i.e. F20 and Titan). It is found that dual lens operation provides a wide operational range for electron holography. In addition, the dark field image tilt increases at high objective lens current to include Si 〈0 0 4〉 diffraction spot. Under the condition of high spatial resolution (1 nm fringe spacing), a large field of view (450 nm), and high fringe contrast (26%) with dual lens operation, a junction map is obtained and strain maps of Si device on 〈2 2 0〉 and 〈0 0 4〉 diffraction are acquired. In this paper, a fringe quality number, N′, which is number of fringe times fringe contrast, is proposed to estimate the quality of an electron hologram and mathematical reasoning for the N′ number is provided. -- Highlights: ► Dual lens electron holography is implemented on FEI instruments (Titan and F20). ► Wide range of field of view (0.1–0.9 μm) and fringe spacing (0.5–6 nm) is achieved. ► Fringe quality number is proposed to quantify the quality of an electron hologram. ► Junction map at high spatial resolution is provided. ► Strain maps along 〈2 2 0〉 and 〈0 0 4〉 direction of Si by dark field electron holography are reported.

On the relation between orbital-localization and self-interaction errors in the density functional theory treatment of organic semiconductors.

Science.gov (United States)

Körzdörfer, T

2011-03-07

It is commonly argued that the self-interaction error (SIE) inherent in semilocal density functionals is related to the degree of the electronic localization. Yet at the same time there exists a latent ambiguity in the definitions of the terms "localization" and "self-interaction," which ultimately prevents a clear and readily accessible quantification of this relationship. This problem is particularly pressing for organic semiconductor molecules, in which delocalized molecular orbitals typically alternate with localized ones, thus leading to major distortions in the eigenvalue spectra. This paper discusses the relation between localization and SIEs in organic semiconductors in detail. Its findings provide further insights into the SIE in the orbital energies and yield a new perspective on the failure of self-interaction corrections that identify delocalized orbital densities with electrons. © 2011 American Institute of Physics.

Organic electronics emerging concepts and technologies

CERN Document Server

Santato, Clara

2013-01-01

An overview of the tremendous potential of organic electronics, concentrating on those emerging topics and technologies that will form the focus of research over the next five to ten years. The young and energetic team of editors with an excellent research track record has brought together internationally renowned authors to review up-and-coming topics, some for the first time, such as organic spintronics, iontronics, light emitting transistors, organic sensors and advanced structural analysis. As a result, this book serves the needs of experienced researchers in organic electronics, graduate

Recent Progress of Self-Powered Sensing Systems for Wearable Electronics.

Science.gov (United States)

Lou, Zheng; Li, La; Wang, Lili; Shen, Guozhen

2017-12-01

Wearable/flexible electronic sensing systems are considered to be one of the key technologies in the next generation of smart personal electronics. To realize personal portable devices with mobile electronics application, i.e., wearable electronic sensors that can work sustainably and continuously without an external power supply are highly desired. The recent progress and advantages of wearable self-powered electronic sensing systems for mobile or personal attachable health monitoring applications are presented. An overview of various types of wearable electronic sensors, including flexible tactile sensors, wearable image sensor array, biological and chemical sensor, temperature sensors, and multifunctional integrated sensing systems is provided. Self-powered sensing systems with integrated energy units are then discussed, separated as energy harvesting self-powered sensing systems, energy storage integrated sensing systems, and all-in-on integrated sensing systems. Finally, the future perspectives of self-powered sensing systems for wearable electronics are discussed. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MAP SERVICES FOR MANAGEMENT OF HUNTING ORGANIZATIONS (THE CASE OF HUNTING ORGANIZATION “MEDVEDICA”

Directory of Open Access Journals (Sweden)

S. A. Zaichenko

2013-01-01

Full Text Available The current state map support of the system of hunting management requires updating an information database and the creation of new schemes of hunting organization. In this case the beneficial is using of satellite imagery data for the mapping and also for important environmental research. Presentation of the results in the form of Internet web services provides broad benefits to the paper version of the maps.

Organic-based molecular switches for molecular electronics.

Science.gov (United States)

Fuentes, Noelia; Martín-Lasanta, Ana; Alvarez de Cienfuegos, Luis; Ribagorda, Maria; Parra, Andres; Cuerva, Juan M

2011-10-05

In a general sense, molecular electronics (ME) is the branch of nanotechnology which studies the application of molecular building blocks for the fabrication of electronic components. Among the different types of molecules, organic compounds have been revealed as promising candidates for ME, due to the easy access, great structural diversity and suitable electronic and mechanical properties. Thanks to these useful capabilities, organic molecules have been used to emulate electronic devices at the nanoscopic scale. In this feature article, we present the diverse strategies used to develop organic switches towards ME with special attention to non-volatile systems.

Organ specific mapping of in vivo redox state in control and cigarette smoke-exposed mice using EPR/NMR co-imaging

Science.gov (United States)

Caia, George L.; Efimova, Olga V.; Velayutham, Murugesan; El-Mahdy, Mohamed A.; Abdelghany, Tamer M.; Kesselring, Eric; Petryakov, Sergey; Sun, Ziqi; Samouilov, Alexandre; Zweier, Jay L.

2014-01-01

In vivo mapping of alterations in redox status is important for understanding organ specific pathology and disease. While electron paramagnetic resonance imaging (EPRI) enables spatial mapping of free radicals, it does not provide anatomic visualization of the body. Proton MRI is well suited to provide anatomical visualization. We applied EPR/NMR co-imaging instrumentation to map and monitor the redox state of living mice under normal or oxidative stress conditions induced by secondhand cigarette smoke (SHS) exposure. A hybrid co-imaging instrument, EPRI (1.2 GHz) / proton MRI (16.18 MHz), suitable for whole-body co-imaging of mice was utilized with common magnet and gradients along with dual EPR/NMR resonators that enable co-imaging without sample movement. The metabolism of the nitroxide probe, 3–carbamoyl–proxyl (3-CP), was used to map the redox state of control and SHS-exposed mice. Co-imaging allowed precise 3D mapping of radical distribution and reduction in major organs such as the heart, lungs, liver, bladder and kidneys. Reductive metabolism was markedly decreased in SHS-exposed mice and EPR/NMR co-imaging allowed quantitative assessment of this throughout the body. Thus, in vivo EPR/NMR co-imaging enables in vivo organ specific mapping of free radical metabolism and redox stress and the alterations that occur in the pathogenesis of disease. PMID:22296801

Subcellular localisation of radionuclides by transmission electronic microscopy in aquatic and terrestrial organisms

Energy Technology Data Exchange (ETDEWEB)

Floriani, M.; Grasset, G.; Simon, O.; Morlon, H.; Laroche, L. [CEA Cadarache (DEI/SECRE/LRE), Laboratory of Radioecology and Ecotoxicology, Institute for Radioprotection and Nuclear Safety, 13 - Saint-Paul-lez-Durance (France)

2004-07-01

The global framework of this study is to go further in the understanding of the involved mechanisms of uranium and selenium internalisation at the subcellular level and of their toxicity towards several aquatic and terrestrial organisms. In this context, the applications and performances of a Scanning Transmission Electron Microscope (TEM/STEM) equipped with CCD camera and Energy-Dispersive- X-Ray (EDAX) analysis are reported. The principal merit of this equipment is the clear expression of element distribution with nanometer resolution. The sample for TEM analysis were prepared in ultrathin sections of 70-140 nm (thickness) and those for EDAX in sections of 200-500 nm. This method offers the possibility of a direct correlation between histological image and distribution map of trace elements. For each sample, following TEM analysis, EDAX spectra or EDAX mapping were also recorded to confirm the identity of the electron dense material in the scanned sections. Demonstration of the usefulness of this method to understand the bioaccumulation mechanisms and to study the effect of the pollutant uptake at the subcellular level was performed for target organs of a metal (U) and a metalloid (Se) in various biological models: a higher rooted plant (Phaseolus vulgaris)) and a freshwater invertebrate (Orconectes Limosus) and a unicellular green alga (Chlamydomonas reinhardtii)). TEM-EDAX analysis revealed the presence of U-deposits in gills and digestive gland in crayfish, and in vacuoles or in the cytoplasm of different rooted cells bean. In the alga, the accumulation of Se was found in electron-dense granules within cytoplasm associated with ultrastructural changes and starch accumulation. (author)

Subcellular localisation of radionuclides by transmission electronic microscopy in aquatic and terrestrial organisms

International Nuclear Information System (INIS)

Floriani, M.; Grasset, G.; Simon, O.; Morlon, H.; Laroche, L.

2004-01-01

The global framework of this study is to go further in the understanding of the involved mechanisms of uranium and selenium internalisation at the subcellular level and of their toxicity towards several aquatic and terrestrial organisms. In this context, the applications and performances of a Scanning Transmission Electron Microscope (TEM/STEM) equipped with CCD camera and Energy-Dispersive- X-Ray (EDAX) analysis are reported. The principal merit of this equipment is the clear expression of element distribution with nanometer resolution. The sample for TEM analysis were prepared in ultrathin sections of 70-140 nm (thickness) and those for EDAX in sections of 200-500 nm. This method offers the possibility of a direct correlation between histological image and distribution map of trace elements. For each sample, following TEM analysis, EDAX spectra or EDAX mapping were also recorded to confirm the identity of the electron dense material in the scanned sections. Demonstration of the usefulness of this method to understand the bioaccumulation mechanisms and to study the effect of the pollutant uptake at the subcellular level was performed for target organs of a metal (U) and a metalloid (Se) in various biological models: a higher rooted plant (Phaseolus vulgaris)) and a freshwater invertebrate (Orconectes Limosus) and a unicellular green alga (Chlamydomonas reinhardtii)). TEM-EDAX analysis revealed the presence of U-deposits in gills and digestive gland in crayfish, and in vacuoles or in the cytoplasm of different rooted cells bean. In the alga, the accumulation of Se was found in electron-dense granules within cytoplasm associated with ultrastructural changes and starch accumulation. (author)

Interfacial self-organization of bolaamphiphiles bearing mesogenic groups: relationships between the molecular structures and their self-organized morphologies.

Science.gov (United States)

Song, Bo; Liu, Guanqing; Xu, Rui; Yin, Shouchun; Wang, Zhiqiang; Zhang, Xi

2008-04-15

This article discusses the relationship between the molecular structure of bolaamphiphiles bearing mesogenic groups and their interfacial self-organized morphology. On the basis of the molecular structures of bolaamphiphiles, we designed and synthesized a series of molecules with different hydrophobic alkyl chain lengths, hydrophilic headgroups, mesogenic groups, and connectors between the alkyl chains and the mesogenic group. Through investigating their interfacial self-organization behavior, some experiential rules are summarized: (1) An appropriate alkyl chain length is necessary to form stable surface micelles; (2) different categories of headgroups have a great effect on the interfacial self-organized morphology; (3) different types of mesogenic groups have little effect on the structure of the interfacial assembly when it is changed from biphenyl to azobenzene or stilbene; (4) the orientation of the ester linker between the mesogenic group and alkyl chain can greatly influence the interfacial self-organization behavior. It is anticipated that this line of research may be helpful for the molecular engineering of bolaamphiphiles to form tailor-made morphologies.

Segmentation and profiling consumers in a multi-channel environment using a combination of self-organizing maps (SOM method, and logistic regression

Directory of Open Access Journals (Sweden)

Seyed Ali Akbar Afjeh

2014-05-01

Full Text Available Market segmentation plays essential role on understanding the behavior of people’s interests in purchasing various products and services through various channels. This paper presents an empirical investigation to shed light on consumer’s purchasing attitude as well as gathering information in multi-channel environment. The proposed study of this paper designed a questionnaire and distributed it among 800 people who were at least 18 years of age and had some experiences on purchasing goods and services on internet, catalog or regular shopping centers. Self-organizing map, SOM, clustering technique was performed based on consumer’s interest in gathering information as well as purchasing products through internet, catalog and shopping centers and determined four segments. There were two types of questions for the proposed study of this paper. The first group considered participants’ personal characteristics such as age, gender, income, etc. The second group of questions was associated with participants’ psychographic characteristics including price consciousness, quality consciousness, time pressure, etc. Using multinominal logistic regression technique, the study determines consumers’ behaviors in each four segments.

Non-fullerene electron acceptors for organic photovoltaic devices

Energy Technology Data Exchange (ETDEWEB)

Jenekhe, Samson A.; Li, Haiyan; Earmme, Taeshik; Ren, Guoqiang

2017-11-07

Non-fullerene electron acceptors for highly efficient organic photovoltaic devices are described. The non-fullerene electron acceptors have an extended, rigid, .pi.-conjugated electron-deficient framework that can facilitate exciton and charge derealization. The non-fullerene electron acceptors can physically mix with a donor polymer and facilitate improved electron transport. The non-fullerene electron acceptors can be incorporated into organic electronic devices, such as photovoltaic cells.

Self organized criticality

International Nuclear Information System (INIS)

Creutz, M.

1993-03-01

Self organized criticality refers to the tendency of highly dissipative systems to drive themselves to a critical state. This has been proposed to explain why observed physics often displays a wide disparity of length and time scales. The phenomenon can be studied in simple cellular automaton models

Explaining the “how” of self-esteem development : The self-organizing self-esteem model

NARCIS (Netherlands)

de Ruiter, Naomi M.P.; van Geert, Paul L.C.; Kunnen, E. Saskia

2017-01-01

The current article proposes a theoretical model of self-esteem called the Self-Organizing Self-Esteem (SOSE) model. The model provides an integrative framework for conceptualizing and understanding the intrinsic dynamics of self-esteem and the role of the context across 3 levels of development: The

Unravelling surface and interfacial structures of a metal-organic framework by transmission electron microscopy.

Science.gov (United States)

Zhu, Yihan; Ciston, Jim; Zheng, Bin; Miao, Xiaohe; Czarnik, Cory; Pan, Yichang; Sougrat, Rachid; Lai, Zhiping; Hsiung, Chia-En; Yao, Kexin; Pinnau, Ingo; Pan, Ming; Han, Yu

2017-05-01

Metal-organic frameworks (MOFs) are crystalline porous materials with designable topology, porosity and functionality, having promising applications in gas storage and separation, ion conduction and catalysis. It is challenging to observe MOFs with transmission electron microscopy (TEM) due to the extreme instability of MOFs upon electron beam irradiation. Here, we use a direct-detection electron-counting camera to acquire TEM images of the MOF ZIF-8 with an ultralow dose of 4.1 electrons per square ångström to retain the structural integrity. The obtained image involves structural information transferred up to 2.1 Å, allowing the resolution of individual atomic columns of Zn and organic linkers in the framework. Furthermore, TEM reveals important local structural features of ZIF-8 crystals that cannot be identified by diffraction techniques, including armchair-type surface terminations and coherent interfaces between assembled crystals. These observations allow us to understand how ZIF-8 crystals self-assemble and the subsequent influence of interfacial cavities on mass transport of guest molecules.

Redox potential distribution of an organic-rich contaminated site obtained by the inversion of self-potential data

Science.gov (United States)

Abbas, M.; Jardani, A.; Soueid Ahmed, A.; Revil, A.; Brigaud, L.; Bégassat, Ph.; Dupont, J. P.

2017-11-01

Mapping the redox potential of shallow aquifers impacted by hydrocarbon contaminant plumes is important for the characterization and remediation of such contaminated sites. The redox potential of groundwater is indicative of the biodegradation of hydrocarbons and is important in delineating the shapes of contaminant plumes. The self-potential method was used to reconstruct the redox potential of groundwater associated with an organic-rich contaminant plume in northern France. The self-potential technique is a passive technique consisting in recording the electrical potential distribution at the surface of the Earth. A self-potential map is essentially the sum of two contributions, one associated with groundwater flow referred to as the electrokinetic component, and one associated with redox potential anomalies referred to as the electroredox component (thermoelectric and diffusion potentials are generally negligible). A groundwater flow model was first used to remove the electrokinetic component from the observed self-potential data. Then, a residual self-potential map was obtained. The source current density generating the residual self-potential signals is assumed to be associated with the position of the water table, an interface characterized by a change in both the electrical conductivity and the redox potential. The source current density was obtained through an inverse problem by minimizing a cost function including a data misfit contribution and a regularizer. This inversion algorithm allows the determination of the vertical and horizontal components of the source current density taking into account the electrical conductivity distribution of the saturated and non-saturated zones obtained independently by electrical resistivity tomography. The redox potential distribution was finally determined from the inverted residual source current density. A redox map was successfully built and the estimated redox potential values correlated well with in

Molecular characterization of organic electronic films.

Science.gov (United States)

DeLongchamp, Dean M; Kline, R Joseph; Fischer, Daniel A; Richter, Lee J; Toney, Michael F

2011-01-18

Organic electronics have emerged as a viable competitor to amorphous silicon for the active layer in low-cost electronics. The critical performance of organic electronic materials is closely related to their morphology and molecular packing. Unlike their inorganic counterparts, polymers combine complex repeat unit structure and crystalline disorder. This combination prevents any single technique from being able to uniquely solve the packing arrangement of the molecules. Here, a general methodology for combining multiple, complementary techniques that provide accurate unit cell dimensions and molecular orientation is described. The combination of measurements results in a nearly complete picture of the organic film morphology. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-organization in metal complexes

International Nuclear Information System (INIS)

Radecka-Paryzek, W.

1999-01-01

Inorganic self-organization involves the spontaneous generation of well-defined supramolecular architectures from metal ions and organic ligands. The basic concept of supramolecular chemistry is a molecular recognition. When the substrate are metal ions, recognition is expressed in the stability and selectivity of metal ion complexation by organic ligands and depends on the geometry of the ligand and on their binding sites that it contains. The combination of the geometric features of the ligand units and the coordination geometries of the metal ions provides very efficient tool for the synthesis of novel, intriguing and highly sophisticated species such as catenanes, box structures, double and triple helicates with a variety of interesting properties. The article will focus on the examples of inorganic self-organization involving the templating as a first step for the assembly of supramolecular structures of high complexity. (author)

Highlighting material structure with transmission electron diffraction correlation coefficient maps.

Science.gov (United States)

Kiss, Ákos K; Rauch, Edgar F; Lábár, János L

2016-04-01

Correlation coefficient maps are constructed by computing the differences between neighboring diffraction patterns collected in a transmission electron microscope in scanning mode. The maps are shown to highlight material structural features like grain boundaries, second phase particles or dislocations. The inclination of the inner crystal interfaces are directly deduced from the resulting contrast. Copyright © 2016 Elsevier B.V. All rights reserved.

Self-organizing networks

DEFF Research Database (Denmark)

Marchetti, Nicola; Prasad, Neeli R.; Johansson, Johan

2010-01-01

In this paper, a general overview of Self-Organizing Networks (SON), and the rationale and state-of-the-art of wireless SON are first presented. The technical and business requirements are then briefly treated, and the research challenges within the field of SON are highlighted. Thereafter, the r...

Variable magnification dual lens electron holography for semiconductor junction profiling and strain mapping

Energy Technology Data Exchange (ETDEWEB)

Wang, Y.Y., E-mail: wangyy@us.ibm.com [IBM Micro-electronics Division, Zip 40E, Hudson Valley Research Park, 2070 Route 52, Hopewell Junction, NY 12533 (United States); Li, J.; Domenicucci, A. [IBM Micro-electronics Division, Zip 40E, Hudson Valley Research Park, 2070 Route 52, Hopewell Junction, NY 12533 (United States); Bruley, J. [IBM TJ Watson Research Center, 1101 Kitchawan Road, Route 134 Yorktown Heights, NY 10598 (United States)

2013-01-15

Dual lens operation for electron holography, which was developed previously (Wang et al., Ultramicroscopy 101 (2004) 63-72; US patent: 7,015,469 B2 (2006)), is re-investigated for bright field (junction profiling) and dark field (strain mapping) electron holography using FEI instrumentation (i.e. F20 and Titan). It is found that dual lens operation provides a wide operational range for electron holography. In addition, the dark field image tilt increases at high objective lens current to include Si Left-Pointing-Angle-Bracket 0 0 4 Right-Pointing-Angle-Bracket diffraction spot. Under the condition of high spatial resolution (1 nm fringe spacing), a large field of view (450 nm), and high fringe contrast (26%) with dual lens operation, a junction map is obtained and strain maps of Si device on Left-Pointing-Angle-Bracket 2 2 0 Right-Pointing-Angle-Bracket and Left-Pointing-Angle-Bracket 0 0 4 Right-Pointing-Angle-Bracket diffraction are acquired. In this paper, a fringe quality number, N Prime , which is number of fringe times fringe contrast, is proposed to estimate the quality of an electron hologram and mathematical reasoning for the N Prime number is provided. -- Highlights: Black-Right-Pointing-Pointer Dual lens electron holography is implemented on FEI instruments (Titan and F20). Black-Right-Pointing-Pointer Wide range of field of view (0.1-0.9 {mu}m) and fringe spacing (0.5-6 nm) is achieved. Black-Right-Pointing-Pointer Fringe quality number is proposed to quantify the quality of an electron hologram. Black-Right-Pointing-Pointer Junction map at high spatial resolution is provided. Black-Right-Pointing-Pointer Strain maps along Left-Pointing-Angle-Bracket 2 2 0 Right-Pointing-Angle-Bracket and Left-Pointing-Angle-Bracket 0 0 4 Right-Pointing-Angle-Bracket direction of Si by dark field electron holography are reported.

Assessment of the Eutrophication-Related Environmental Parameters in Two Mediterranean Lakes by Integrating Statistical Techniques and Self-Organizing Maps.

Science.gov (United States)

Hadjisolomou, Ekaterini; Stefanidis, Konstantinos; Papatheodorou, George; Papastergiadou, Evanthia

2018-03-19

During the last decades, Mediterranean freshwater ecosystems, especially lakes, have been under severe pressure due to increasing eutrophication and water quality deterioration. In this article, we compared the effectiveness of different data analysis methods by assessing the contribution of environmental parameters to eutrophication processes. For this purpose, principal components analysis (PCA), cluster analysis, and a self-organizing map (SOM) were applied, using water quality data from two transboundary lakes of North Greece. SOM is considered as an advanced and powerful data analysis tool because of its ability to represent complex and nonlinear relationships among multivariate data sets. The results of PCA and cluster analysis agreed with the SOM results, although the latter provided more information because of the visualization abilities regarding the parameters' relationships. Besides nutrients that were found to be a key factor for controlling chlorophyll-a (Chl - a), water temperature was related positively with algal production, while the Secchi disk depth parameter was found to be highly important and negatively related toeutrophic conditions. In general, the SOM results were more specific and allowed direct associations between the water quality variables. Our work showed that SOMs can be used effectively in limnological studies to produce robust and interpretable results, aiding scientists and managers to cope with environmental problems such as eutrophication.

Assessment of the Eutrophication-Related Environmental Parameters in Two Mediterranean Lakes by Integrating Statistical Techniques and Self-Organizing Maps

Directory of Open Access Journals (Sweden)

Ekaterini Hadjisolomou

2018-03-01

Full Text Available During the last decades, Mediterranean freshwater ecosystems, especially lakes, have been under severe pressure due to increasing eutrophication and water quality deterioration. In this article, we compared the effectiveness of different data analysis methods by assessing the contribution of environmental parameters to eutrophication processes. For this purpose, principal components analysis (PCA, cluster analysis, and a self-organizing map (SOM were applied, using water quality data from two transboundary lakes of North Greece. SOM is considered as an advanced and powerful data analysis tool because of its ability to represent complex and nonlinear relationships among multivariate data sets. The results of PCA and cluster analysis agreed with the SOM results, although the latter provided more information because of the visualization abilities regarding the parameters’ relationships. Besides nutrients that were found to be a key factor for controlling chlorophyll-a (Chl-a, water temperature was related positively with algal production, while the Secchi disk depth parameter was found to be highly important and negatively related toeutrophic conditions. In general, the SOM results were more specific and allowed direct associations between the water quality variables. Our work showed that SOMs can be used effectively in limnological studies to produce robust and interpretable results, aiding scientists and managers to cope with environmental problems such as eutrophication.

Self-organizing periodicity in development: organ positioning in plants.

Science.gov (United States)

Bhatia, Neha; Heisler, Marcus G

2018-02-08

Periodic patterns during development often occur spontaneously through a process of self-organization. While reaction-diffusion mechanisms are often invoked, other types of mechanisms that involve cell-cell interactions and mechanical buckling have also been identified. Phyllotaxis, or the positioning of plant organs, has emerged as an excellent model system to study the self-organization of periodic patterns. At the macro scale, the regular spacing of organs on the growing plant shoot gives rise to the typical spiral and whorled arrangements of plant organs found in nature. In turn, this spacing relies on complex patterns of cell polarity that involve feedback between a signaling molecule - the plant hormone auxin - and its polar, cell-to-cell transport. Here, we review recent progress in understanding phyllotaxis and plant cell polarity and highlight the development of new tools that can help address the remaining gaps in our understanding. © 2018. Published by The Company of Biologists Ltd.

USING STROKE-BASED OR CHARACTER-BASED SELF-ORGANIZING MAPS IN THE RECOGNITION OF ONLINE, CONNECTED CURSIVE SCRIPT

NARCIS (Netherlands)

SCHOMAKER, L

Comparisons are made between a number of stroke-based and character-based recognizers of connected cursive script. In both approaches a Kohonen self-organizing neural network is used as a feature-vector quantizer. It is found that a ''best match only'' character-based recognizer performs better than

Studies on Manfred Eigen's model for the self-organization of information processing.

Science.gov (United States)

Ebeling, W; Feistel, R

2018-05-01

In 1971, Manfred Eigen extended the principles of Darwinian evolution to chemical processes, from catalytic networks to the emergence of information processing at the molecular level, leading to the emergence of life. In this paper, we investigate some very general characteristics of this scenario, such as the valuation process of phenotypic traits in a high-dimensional fitness landscape, the effect of spatial compartmentation on the valuation, and the self-organized transition from structural to symbolic genetic information of replicating chain molecules. In the first part, we perform an analysis of typical dynamical properties of continuous dynamical models of evolutionary processes. In particular, we study the mapping of genotype to continuous phenotype spaces following the ideas of Wright and Conrad. We investigate typical features of a Schrödinger-like dynamics, the consequences of the high dimensionality, the leading role of saddle points, and Conrad's extra-dimensional bypass. In the last part, we discuss in brief the valuation of compartment models and the self-organized emergence of molecular symbols at the beginning of life.

Modeling Directional Selectivity Using Self-Organizing Delay-Aadaptation Maps

OpenAIRE

Tversky, Mr. Tal; Miikkulainen, Dr. Risto

2002-01-01

Using a delay adaptation learning rule, we model the activity-dependent development of directionally selective cells in the primary visual cortex. Based on input stimuli, a learning rule shifts delays to create synchronous arrival of spikes at cortical cells. As a result, delays become tuned creating a smooth cortical map of direction selectivity. This result demonstrates how delay adaption can serve as a powerful abstraction for modeling temporal learning in the brain.

Domination, self-determination and circular organizing

NARCIS (Netherlands)

Romme, A.G.L.

2002-01-01

The emergence of self-organizing forms of control, based on the idea of self-determination, have challenged traditional forms of control based on the concept of domination. As such, self-determination has been put forward as an alternative rather than as a complement to domination. This paper

Highlighting material structure with transmission electron diffraction correlation coefficient maps

International Nuclear Information System (INIS)

Kiss, Ákos K.; Rauch, Edgar F.; Lábár, János L.

2016-01-01

Correlation coefficient maps are constructed by computing the differences between neighboring diffraction patterns collected in a transmission electron microscope in scanning mode. The maps are shown to highlight material structural features like grain boundaries, second phase particles or dislocations. The inclination of the inner crystal interfaces are directly deduced from the resulting contrast. - Highlights: • We propose a novel technique to image the structure of polycrystalline TEM-samples. • Correlation coefficients maps highlights the evolution of the diffracting signal. • 3D views of grain boundaries are provided for nano-particles or polycrystals.

Noncovalent Interactions in Organic Electronic Materials

KAUST Repository

Ravva, Mahesh Kumar

2017-06-29

In this chapter, we provide an overview of how noncovalent interactions, determined by the chemical structure of π-conjugated molecules and polymers, govern essential aspects of the electronic, optical, and mechanical characteristics of organic semiconductors. We begin by describing general aspects of materials design, including the wide variety of chemistries exploited to control the electronic and optical properties of these materials. We then discuss explicit examples of how the study of noncovalent interactions can provide deeper chemical insights that can improve the design of new generations of organic electronic materials.

Profile of the biodiesel B100 commercialized in the region of Londrina: application of artificial neural networks of the type self organizing maps

Directory of Open Access Journals (Sweden)

Vilson Machado de Campos Filho

2015-10-01

Full Text Available The 97 samples were grouped according to the year of analysis. For each year, letters from A to D were attributed, between 2010 and 2013; A (33 B (25 C (24 and D (15. The parameters of compliance previously analyzed are those established by the National Agency of Petroleum, Natural Gas and Biofuels (ANP, through resolution ANP 07/2008. The parameters analyzed were density, flash point, peroxide and acid value. The observed values were presented to Artificial Neural Network (ANN Self Organizing MAP (SOM in order to classify, by physical-chemical properties, each sample from year of production. The ANN was trained on different days and randomly divided samples into two groups, training and test set. It was found that SOM network differentiated samples by the year and the compliance parameters, allowing to identify that the density and the flash point were the most significant compliance parameters, so good for the distinction and classification of these samples.

Spontaneously self-organized structures in electron plasma

International Nuclear Information System (INIS)

Noga, M.

1983-01-01

Properties of phase transitions between disordered and ordered states in a system of interacting electrons are derived from first principles. It is shown that the formation of a static spin density wave state is due to a phase transition of the third kind. (orig.)

Self-Organization Activities of College Students: Challenges and Opportunities

Science.gov (United States)

Shmurygina, Natalia; Bazhenova, Natalia; Bazhenov, Ruslan; Nikolaeva, Natalia; Tcytcarev, Andrey

2016-01-01

The article provides the analysis of self-organization activities of college students related to their participation in youth associations activities. The purpose of research is to disclose a degree of students' activities demonstration based on self-organization processes, assessment of existing self-organization practices of the youth,…

Identification of Outlier Loci Responding to Anthropogenic and Natural Selection Pressure in Stream Insects Based on a Self-Organizing Map

Directory of Open Access Journals (Sweden)

Bin Li

2016-05-01

Full Text Available Water quality maintenance should be considered from an ecological perspective since water is a substrate ingredient in the biogeochemical cycle and is closely linked with ecosystem functioning and services. Addressing the status of live organisms in aquatic ecosystems is a critical issue for appropriate prediction and water quality management. Recently, genetic changes in biological organisms have garnered more attention due to their in-depth expression of environmental stress on aquatic ecosystems in an integrative manner. We demonstrate that genetic diversity would adaptively respond to environmental constraints in this study. We applied a self-organizing map (SOM to characterize complex Amplified Fragment Length Polymorphisms (AFLP of aquatic insects in six streams in Japan with natural and anthropogenic variability. After SOM training, the loci compositions of aquatic insects effectively responded to environmental selection pressure. To measure how important the role of loci compositions was in the population division, we altered the AFLP data by flipping the existence of given loci individual by individual. Subsequently we recognized the cluster change of the individuals with altered data using the trained SOM. Based on SOM recognition of these altered data, we determined the outlier loci (over 90th percentile that showed drastic changes in their belonging clusters (D. Subsequently environmental responsiveness (Ek’ was also calculated to address relationships with outliers in different species. Outlier loci were sensitive to slightly polluted conditions including Chl-a, NH4-N, NOX-N, PO4-P, and SS, and the food material, epilithon. Natural environmental factors such as altitude and sediment additionally showed relationships with outliers in somewhat lower levels. Poly-loci like responsiveness was detected in adapting to environmental constraints. SOM training followed by recognition shed light on developing algorithms de novo to

Organic electronic devices using phthalimide compounds

Science.gov (United States)

Hassan, Azad M.; Thompson, Mark E.

2010-09-07

Organic electronic devices comprising a phthalimide compound. The phthalimide compounds disclosed herein are electron transporters with large HOMO-LUMO gaps, high triplet energies, large reduction potentials, and/or thermal and chemical stability. As such, these phthalimide compounds are suitable for use in any of various organic electronic devices, such as OLEDs and solar cells. In an OLED, the phthalimide compounds may serve various functions, such as a host in the emissive layer, as a hole blocking material, or as an electron transport material. In a solar cell, the phthalimide compounds may serve various functions, such as an exciton blocking material. Various examples of phthalimide compounds which may be suitable for use in the present invention are disclosed.

Self-organizing of critical state in granulated superconductors

International Nuclear Information System (INIS)

Ginzburg, S.L.; Savitskaya, N.E.

2000-01-01

Critical state in granulated superconductors was studied on the basis of two mathematical models - the system of differential equations for calibration and invariant difference of phases and a simplified model describing the system of associated images and equivalent to the standard models to study self-organizing criticality. The critical state of granulated superconductors in all studied cases was shown to be self-organized. Besides, it is shown that the applied models are practically equivalent ones, that is they both show similar critical behavior and lead to coincidence of noncritical phenomena. For the first time one showed that the occurrence of self-organized critically within the system of nonlinear differential equations and its equivalence to self-organized critically in the standard models [ru

Amorphous electron-accepting materials for organic optoelectronics

NARCIS (Netherlands)

Ganesan, P.

2007-01-01

The importance of organic materials for use in electronic devices such as OLEDs, OFETs and photovoltaic cells has increased significantly over the past decade. Organic materials have been attractive candidates for such electronic devices because of their compatibility with high-throughput,

Analog Organic Electronics Building Blocks for Organic Smart Sensor Systems on Foil

CERN Document Server

Marien, Hagen; Heremans, Paul

2013-01-01

 This book provides insight into organic electronics technology and in analog circuit techniques that can be used to increase the performance of both analog and digital organic circuits. It explores the domain of organic electronics technology for analog circuit applications, specifically smart sensor systems.  It focuses on all the building blocks in the data path of an organic sensor system between the sensor and the digital processing block. Sensors, amplifiers, analog-to-digital converters and DC-DC converters are discussed in detail. Coverage includes circuit techniques, circuit implementation, design decisions and measurement results of the building blocks described. Offers readers the first book to focus on analog organic circuit design; Discusses organic electronics technology for analog circuit applications in the context of smart sensor systems; Describes all building blocks necessary for an organic sensor system between the sensor and the digital processing block; Includes circuit techniques, cir...

Complex Systems and Self-organization Modelling

CERN Document Server

Bertelle, Cyrille; Kadri-Dahmani, Hakima

2009-01-01

The concern of this book is the use of emergent computing and self-organization modelling within various applications of complex systems. The authors focus their attention both on the innovative concepts and implementations in order to model self-organizations, but also on the relevant applicative domains in which they can be used efficiently. This book is the outcome of a workshop meeting within ESM 2006 (Eurosis), held in Toulouse, France in October 2006.

Self-Organized Construction with Continuous Building Material

DEFF Research Database (Denmark)

Heinrich, Mary Katherine; Wahby, Mostafa; Divband Soorati, Mohammad

2016-01-01

Self-organized construction with continuous, structured building material, as opposed to modular units, offers new challenges to the robot-based construction process and lends the opportunity for increased flexibility in constructed artifact properties, such as shape and deformation. As an example...... investigation, we look at continuous filaments organized into braided structures, within the context of bio-hybrids constructing architectural artifacts. We report the result of an early swarm robot experiment. The robots successfully constructed a braid in a self-organized process. The construction process can...... be extended by using different materials and by embedding sensors during the self-organized construction directly into the braided structure. In future work, we plan to apply dedicated braiding robot hardware and to construct sophisticated 3-d structures with local variability in patterns of filament...

Self organising maps for visualising and modelling.

Science.gov (United States)

Brereton, Richard G

2012-05-02

The paper describes the motivation of SOMs (Self Organising Maps) and how they are generally more accessible due to the wider available modern, more powerful, cost-effective computers. Their advantages compared to Principal Components Analysis and Partial Least Squares are discussed. These allow application to non-linear data, are not so dependent on least squares solutions, normality of errors and less influenced by outliers. In addition there are a wide variety of intuitive methods for visualisation that allow full use of the map space. Modern problems in analytical chemistry include applications to cultural heritage studies, environmental, metabolomic and biological problems result in complex datasets. Methods for visualising maps are described including best matching units, hit histograms, unified distance matrices and component planes. Supervised SOMs for classification including multifactor data and variable selection are discussed as is their use in Quality Control. The paper is illustrated using four case studies, namely the Near Infrared of food, the thermal analysis of polymers, metabolomic analysis of saliva using NMR, and on-line HPLC for pharmaceutical process monitoring.

Self organising maps for visualising and modelling

Science.gov (United States)

2012-01-01

The paper describes the motivation of SOMs (Self Organising Maps) and how they are generally more accessible due to the wider available modern, more powerful, cost-effective computers. Their advantages compared to Principal Components Analysis and Partial Least Squares are discussed. These allow application to non-linear data, are not so dependent on least squares solutions, normality of errors and less influenced by outliers. In addition there are a wide variety of intuitive methods for visualisation that allow full use of the map space. Modern problems in analytical chemistry include applications to cultural heritage studies, environmental, metabolomic and biological problems result in complex datasets. Methods for visualising maps are described including best matching units, hit histograms, unified distance matrices and component planes. Supervised SOMs for classification including multifactor data and variable selection are discussed as is their use in Quality Control. The paper is illustrated using four case studies, namely the Near Infrared of food, the thermal analysis of polymers, metabolomic analysis of saliva using NMR, and on-line HPLC for pharmaceutical process monitoring. PMID:22594434

Modeling self-organization of novel organic materials

Science.gov (United States)

Sayar, Mehmet

In this thesis, the structural organization of oligomeric multi-block molecules is analyzed by computational analysis of coarse-grained models. These molecules form nanostructures with different dimensionalities, and the nanostructured nature of these materials leads to novel structural properties at different length scales. Previously, a number of oligomeric triblock rodcoil molecules have been shown to self-organize into mushroom shaped noncentrosymmetric nanostructures. Interestingly, thin films of these molecules contain polar domains and a finite macroscopic polarization. However, the fully polarized state is not the equilibrium state. In the first chapter, by solving a model with dipolar and Ising-like short range interactions, we show that polar domains are stable in films composed of aggregates as opposed to isolated molecules. Unlike classical molecular systems, these nanoaggregates have large intralayer spacings (a ≈ 6 nm), leading to a reduction in the repulsive dipolar interactions that oppose polar order within layers. This enables the formation of a striped pattern with polar domains of alternating directions. The energies of the possible structures at zero temperature are computed exactly and results of Monte Carlo simulations are provided at non-zero temperatures. In the second chapter, the macroscopic polarization of such nanostructured films is analyzed in the presence of a short range surface interaction. The surface interaction leads to a periodic domain structure where the balance between the up and down domains is broken, and therefore films of finite thickness have a net macroscopic polarization. The polarization per unit volume is a function of film thickness and strength of the surface interaction. Finally, in chapter three, self-organization of organic molecules into a network of one dimensional objects is analyzed. Multi-block organic dendron rodcoil molecules were found to self-organize into supramolecular nanoribbons (threads) and

Strong Electron Self-Cooling in the Cold-Electron Bolometers Designed for CMB Measurements

Science.gov (United States)

Kuzmin, L. S.; Pankratov, A. L.; Gordeeva, A. V.; Zbrozhek, V. O.; Revin, L. S.; Shamporov, V. A.; Masi, S.; de Bernardis, P.

2018-03-01

We have realized cold-electron bolometers (CEB) with direct electron self-cooling of the nanoabsorber by SIN (Superconductor-Insulator-Normal metal) tunnel junctions. This electron self-cooling acts as a strong negative electrothermal feedback, improving noise and dynamic properties. Due to this cooling the photon-noise-limited operation of CEBs was realized in array of bolometers developed for the 345 GHz channel of the OLIMPO Balloon Telescope in the power range from 10 pW to 20 pW at phonon temperature Tph =310 mK. The negative electrothermal feedback in CEB is analogous to TES but instead of artificial heating we use cooling of the absorber. The high efficiency of the electron self-cooling to Te =100 mK without power load and to Te=160 mK under power load is achieved by: - a very small volume of the nanoabsorber (0.02 μm3) and a large area of the SIN tunnel junctions, - effective removal of hot quasiparticles by arranging double stock at both sides of the junctions and close position of the normal metal traps, - self-protection of the 2D array of CEBs against interferences by dividing them between N series CEBs (for voltage interferences) and M parallel CEBs (for current interferences), - suppression of Andreev reflection by a thin layer of Fe in the AlFe absorber. As a result even under high power load the CEBs are working at electron temperature Te less than Tph . To our knowledge, there is no analogue in the bolometers technology in the world for bolometers working at electron temperature colder than phonon temperature.

Topological mappings of video and audio data.

Science.gov (United States)

Fyfe, Colin; Barbakh, Wesam; Ooi, Wei Chuan; Ko, Hanseok

2008-12-01

We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM).(1) But whereas the GTM is an extension of a mixture of experts, this model is an extension of a product of experts.(2) We show visualisation and clustering results on a data set composed of video data of lips uttering 5 Korean vowels. Finally we note that we may dispense with the probabilistic underpinnings of the product of experts and derive the same algorithm as a minimisation of mean squared error between the prototypes and the data. This leads us to suggest a new algorithm which incorporates local and global information in the clustering. Both ot the new algorithms achieve better results than the standard Self-Organizing Map.

Dispersion self-energy of the electron

International Nuclear Information System (INIS)

Hawton, M.

1991-01-01

Electron mass renormalization and the Lamb shift have been investigated using the dispersion self-energy formalism. If shifts of both the electromagnetic field and quantum-mechanical transitions frequencies are considered, absorption from the electromagnetic field is canceled by emission due to atomic fluctuations. The frequencies of all modes are obtained from the self-consistency condition that the field seen by the electron is the same as the field produced by the expectation value of current. The radiation present can thus be viewed as arising from emission and subsequent reabsorption by matter. As developed here, the numerical predictions of dispersion theory are identical to those of quantum electrodynamics. The physical picture implied by dispersion theory is discussed in the context of semiclassical theories and quantum electrodynamics

Three-Dimensional Orientation Mapping in the Transmission Electron Microscope

DEFF Research Database (Denmark)

Liu, Haihua; Schmidt, Søren; Poulsen, Henning Friis

2011-01-01

resolution of 200 nanometers (nm). We describe here a nondestructive technique that enables 3D orientation mapping in the transmission electron microscope of mono- and multiphase nanocrystalline materials with a spatial resolution reaching 1 nm. We demonstrate the technique by an experimental study...

A Forecasting Approach Combining Self-Organizing Map with Support Vector Regression for Reservoir Inflow during Typhoon Periods

Directory of Open Access Journals (Sweden)

Gwo-Fong Lin

2016-01-01

Full Text Available This study describes the development of a reservoir inflow forecasting model for typhoon events to improve short lead-time flood forecasting performance. To strengthen the forecasting ability of the original support vector machines (SVMs model, the self-organizing map (SOM is adopted to group inputs into different clusters in advance of the proposed SOM-SVM model. Two different input methods are proposed for the SVM-based forecasting method, namely, SOM-SVM1 and SOM-SVM2. The methods are applied to an actual reservoir watershed to determine the 1 to 3 h ahead inflow forecasts. For 1, 2, and 3 h ahead forecasts, improvements in mean coefficient of efficiency (MCE due to the clusters obtained from SOM-SVM1 are 21.5%, 18.5%, and 23.0%, respectively. Furthermore, improvement in MCE for SOM-SVM2 is 20.9%, 21.2%, and 35.4%, respectively. Another SOM-SVM2 model increases the SOM-SVM1 model for 1, 2, and 3 h ahead forecasts obtained improvement increases of 0.33%, 2.25%, and 10.08%, respectively. These results show that the performance of the proposed model can provide improved forecasts of hourly inflow, especially in the proposed SOM-SVM2 model. In conclusion, the proposed model, which considers limit and higher related inputs instead of all inputs, can generate better forecasts in different clusters than are generated from the SOM process. The SOM-SVM2 model is recommended as an alternative to the original SVR (Support Vector Regression model because of its accuracy and robustness.

Evaluating Spatial Variability in Sediment and Phosphorus Concentration-Discharge Relationships Using Bayesian Inference and Self-Organizing Maps

Science.gov (United States)

Underwood, Kristen L.; Rizzo, Donna M.; Schroth, Andrew W.; Dewoolkar, Mandar M.

2017-12-01

Given the variable biogeochemical, physical, and hydrological processes driving fluvial sediment and nutrient export, the water science and management communities need data-driven methods to identify regions prone to production and transport under variable hydrometeorological conditions. We use Bayesian analysis to segment concentration-discharge linear regression models for total suspended solids (TSS) and particulate and dissolved phosphorus (PP, DP) using 22 years of monitoring data from 18 Lake Champlain watersheds. Bayesian inference was leveraged to estimate segmented regression model parameters and identify threshold position. The identified threshold positions demonstrated a considerable range below and above the median discharge—which has been used previously as the default breakpoint in segmented regression models to discern differences between pre and post-threshold export regimes. We then applied a Self-Organizing Map (SOM), which partitioned the watersheds into clusters of TSS, PP, and DP export regimes using watershed characteristics, as well as Bayesian regression intercepts and slopes. A SOM defined two clusters of high-flux basins, one where PP flux was predominantly episodic and hydrologically driven; and another in which the sediment and nutrient sourcing and mobilization were more bimodal, resulting from both hydrologic processes at post-threshold discharges and reactive processes (e.g., nutrient cycling or lateral/vertical exchanges of fine sediment) at prethreshold discharges. A separate DP SOM defined two high-flux clusters exhibiting a bimodal concentration-discharge response, but driven by differing land use. Our novel framework shows promise as a tool with broad management application that provides insights into landscape drivers of riverine solute and sediment export.

Electronic self-monitoring seal

International Nuclear Information System (INIS)

Campbell, J.W.

1978-01-01

The Electronic Self-Monitoring Seal is a new type of security seal which allows continuous verification of the seal's identity and status. The identity information is a function of the individual seal, time, and seal integrity. A description of this seal and its characteristics are presented. Also described are the use cycle for the seal and the support equipment for programming and verifying the seal

The Impact of Electronic Mind Maps on Students' Reading Comprehension

Science.gov (United States)

Mohaidat, Mohammad Mahmoud Talal

2018-01-01

This study aimed to investigate the impact of the electronic mind map (IMindMap) on the development of reading comprehension among the ninth grade students in Jordan. The sample of the study consisted of two ninth grade sections from two public schools in Irbid First Directorate during the academic 2016-2017. Each section consisted of (30)…

Quantum self-organization and nuclear collectivities

Science.gov (United States)

Otsuka, T.; Tsunoda, Y.; Togashi, T.; Shimizu, N.; Abe, T.

2018-02-01

The quantum self-organization is introduced as one of the major underlying mechanisms of the quantum many-body systems. In the case of atomic nuclei as an example, two types of the motion of nucleons, single-particle states and collective modes, dominate the structure of the nucleus. The outcome of the collective mode is determined basically by the balance between the effect of the mode-driving force (e.g., quadrupole force for the ellipsoidal deformation) and the resistance power against it. The single-particle energies are one of the sources to produce such resistance power: a coherent collective motion is more hindered by larger gaps between relevant single particle states. Thus, the single-particle state and the collective mode are “enemies” each other. However, the nuclear forces are demonstrated to be rich enough so as to enhance relevant collective mode by reducing the resistance power by changing singleparticle energies for each eigenstate through monopole interactions. This will be verified with the concrete example taken from Zr isotopes. Thus, when the quantum self-organization occurs, single-particle energies can be self-organized, being enhanced by (i) two quantum liquids, e.g., protons and neutrons, (ii) two major force components, e.g., quadrupole interaction (to drive collective mode) and monopole interaction (to control resistance). In other words, atomic nuclei are not necessarily like simple rigid vases containing almost free nucleons, in contrast to the naïve Fermi liquid picture. Type II shell evolution is considered to be a simple visible case involving excitations across a (sub)magic gap. The quantum self-organization becomes more important in heavier nuclei where the number of active orbits and the number of active nucleons are larger. The quantum self-organization is a general phenomenon, and is expected to be found in other quantum systems.

Analysis of self-organized In(Ga)As quantum structures with the scanning transmission electron microscope; Analyse selbstorganisierter In(Ga)As-Quantenstrukturen mit dem Raster-Transmissionselektronenmikroskop

Energy Technology Data Exchange (ETDEWEB)

Sauerwald, Andres

2008-05-27

Aim of this thesis was to apply the analytical methods of the scanning transmission electron microscopy to the study of self-organized In(Ga)As quantum structures. With the imaging methods Z contrast and bright field (position resolutions in the subnanometer range) and especially with the possibilities of the quantitative chemical EELS analysis of the scanning transmission electron microscope (STEM) fundamental questions concerning morphology and chemical properties of self-organized quantum structures should be answered. By the high position resolution of the STEM among others essentail morphological and structural parameters in the growth behaviour of 'dot in a well' (DWell) structures and of vertically correlated quantum dots (QDs) could be analyzed. For the optimization of DWell structures samples were studied, the nominal InAs-QD growth position was directedly varied within the embedding InGaAs quantum wells. The STEM offers in connection with the EELS method a large potential for the chemical analysis of quantum structures. Studied was a sample series of self-organized InGaAs/GaAs structures on GaAs substrate, the stress of which was changed by varying the Ga content of the INGaAs material between 2.4 % and 4.3 %. [German] Ziel dieser Arbeit war es, die analytischen Methoden der Raster-Transmissionselektronenmikroskopie zur Untersuchung selbstorganisierter In(Ga)As-Quantenstrukturen anzuwenden. Mit den abbildenden Methoden Z-Kontrast und Hellfeld (Ortsaufloesungen im Subnanometerbereich) und insbesondere mit den Moeglichkeiten der quantitativen chemischen EELS-Analyse des Raster-Transmissionselektronenmikroskops (RTEMs) sollten grundsaetzliche Fragestellungen hinsichtlich der Morphologie und der chemischen Eigenschaften selbstorganisierter Quantenstrukturen beantwortet werden. Durch die hohe Ortsaufloesung des RTEMs konnten u.a. essentielle morphologische und strukturelle Parameter im Wachstumsverhalten von 'Dot in a Well

Estimating temporal and spatial variation of ocean surface pCO2 in the North Pacific using a self-organizing map neural network technique

Directory of Open Access Journals (Sweden)

S. Nakaoka

2013-09-01

Full Text Available This study uses a neural network technique to produce maps of the partial pressure of oceanic carbon dioxide (pCO2sea in the North Pacific on a 0.25° latitude × 0.25° longitude grid from 2002 to 2008. The pCO2sea distribution was computed using a self-organizing map (SOM originally utilized to map the pCO2sea in the North Atlantic. Four proxy parameters – sea surface temperature (SST, mixed layer depth, chlorophyll a concentration, and sea surface salinity (SSS – are used during the training phase to enable the network to resolve the nonlinear relationships between the pCO2sea distribution and biogeochemistry of the basin. The observed pCO2sea data were obtained from an extensive dataset generated by the volunteer observation ship program operated by the National Institute for Environmental Studies (NIES. The reconstructed pCO2sea values agreed well with the pCO2sea measurements, with the root-mean-square error ranging from 17.6 μatm (for the NIES dataset used in the SOM to 20.2 μatm (for independent dataset. We confirmed that the pCO2sea estimates could be improved by including SSS as one of the training parameters and by taking into account secular increases of pCO2sea that have tracked increases in atmospheric CO2. Estimated pCO2sea values accurately reproduced pCO2sea data at several time series locations in the North Pacific. The distributions of pCO2sea revealed by 7 yr averaged monthly pCO2sea maps were similar to Lamont-Doherty Earth Observatory pCO2sea climatology, allowing, however, for a more detailed analysis of biogeochemical conditions. The distributions of pCO2sea anomalies over the North Pacific during the winter clearly showed regional contrasts between El Niño and La Niña years related to changes of SST and vertical mixing.

Relativistic fluid theories - Self organization

International Nuclear Information System (INIS)

Mahajan, S.M.; Hazeltine, R.D.; Yoshida, Z.

2003-01-01

Developments in two distinct but related subjects are reviewed: 1) Formulation and investigation of closed fluid theories which transcend the limitations of standard magnetohydrodynamics (MHD), in particular, theories which are valid in the long mean free path limit and in which pressure anisotropy, heat flow, and arbitrarily strong sheared flows are treated consistently, and 2) Exploitation of the two-fluid theories to derive new plasma configurations in which the flow-field is a co-determinant of the overall dynamics; some of these states belong to the category of self-organized relaxed states. Physical processes which may provide a route to self-organization and complexity are also explored. (author)

Effect of Structure and Disorder on the Charge Transport in Defined Self-Assembled Monolayers of Organic Semiconductors.

Science.gov (United States)

Schmaltz, Thomas; Gothe, Bastian; Krause, Andreas; Leitherer, Susanne; Steinrück, Hans-Georg; Thoss, Michael; Clark, Timothy; Halik, Marcus

2017-09-26

Self-assembled monolayer field-effect transistors (SAMFETs) are not only a promising type of organic electronic device but also allow detailed analyses of structure-property correlations. The influence of the morphology on the charge transport is particularly pronounced, due to the confined monolayer of 2D-π-stacked organic semiconductor molecules. The morphology, in turn, is governed by relatively weak van-der-Waals interactions and is thus prone to dynamic structural fluctuations. Accordingly, combining electronic and physical characterization and time-averaged X-ray analyses with the dynamic information available at atomic resolution from simulations allows us to characterize self-assembled monolayer (SAM) based devices in great detail. For this purpose, we have constructed transistors based on SAMs of two molecules that consist of the organic p-type semiconductor benzothieno[3,2-b][1]benzothiophene (BTBT), linked to a C 11 or C 12 alkylphosphonic acid. Both molecules form ordered SAMs; however, our experiments show that the size of the crystalline domains and the charge-transport properties vary considerably in the two systems. These findings were confirmed by molecular dynamics (MD) simulations and semiempirical molecular-orbital electronic-structure calculations, performed on snapshots from the MD simulations at different times, revealing, in atomistic detail, how the charge transport in organic semiconductors is influenced and limited by dynamic disorder.

Electronic charge rearrangement at metal/organic interfaces induced by weak van der Waals interactions

Science.gov (United States)

Ferri, Nicola; Ambrosetti, Alberto; Tkatchenko, Alexandre

2017-07-01

Electronic charge rearrangements at interfaces between organic molecules and solid surfaces play a key role in a wide range of applications in catalysis, light-emitting diodes, single-molecule junctions, molecular sensors and switches, and photovoltaics. It is common to utilize electrostatics and Pauli pushback to control the interface electronic properties, while the ubiquitous van der Waals (vdW) interactions are often considered to have a negligible direct contribution (beyond the obvious structural relaxation). Here, we apply a fully self-consistent Tkatchenko-Scheffler vdW density functional to demonstrate that the weak vdW interactions can induce sizable charge rearrangements at hybrid metal/organic systems (HMOS). The complex vdW correlation potential smears out the interfacial electronic density, thereby reducing the charge transfer in HMOS, changes the interface work functions by up to 0.2 eV, and increases the interface dipole moment by up to 0.3 Debye. Our results suggest that vdW interactions should be considered as an additional control parameter in the design of hybrid interfaces with the desired electronic properties.

Unravelling surface and interfacial structures of a metal–organic framework by transmission electron microscopy

KAUST Repository

Zhu, Yihan

2017-02-21

Metal–organic frameworks (MOFs) are crystalline porous materials with designable topology, porosity and functionality, having promising applications in gas storage and separation, ion conduction and catalysis1, 2, 3. It is challenging to observe MOFs with transmission electron microscopy (TEM) due to the extreme instability of MOFs upon electron beam irradiation4, 5, 6, 7. Here, we use a direct-detection electron-counting camera to acquire TEM images of the MOF ZIF-8 with an ultralow dose of 4.1 electrons per square ångström to retain the structural integrity. The obtained image involves structural information transferred up to 2.1 Å, allowing the resolution of individual atomic columns of Zn and organic linkers in the framework. Furthermore, TEM reveals important local structural features of ZIF-8 crystals that cannot be identified by diffraction techniques, including armchair-type surface terminations and coherent interfaces between assembled crystals. These observations allow us to understand how ZIF-8 crystals self-assemble and the subsequent influence of interfacial cavities on mass transport of guest molecules.

Organic/metal interfaces. Electronic and structural properties

Energy Technology Data Exchange (ETDEWEB)

Duhm, Steffen

2008-07-17

This work addresses several important topics of the field of organic electronics. The focus lies on organic/metal interfaces, which exist in all organic electronic devices. Physical properties of such interfaces are crucial for device performance. Four main topics have been covered: (i) the impact of molecular orientation on the energy levels, (ii) energy level tuning with strong electron acceptors, (iii) the role of thermodynamic equilibrium at organic/ organic homo-interfaces and (iv) the correlation of interfacial electronic structure and bonding distance. To address these issues a broad experimental approach was necessary: mainly ultraviolet photoelectron spectroscopy was used, supported by X-ray photoelectron spectroscopy, metastable atom electron spectroscopy, X-ray diffraction and X-ray standing waves, to examine vacuum sublimed thin films of conjugated organic molecules (COMs) in ultrahigh vacuum. (i) A novel approach is presented to explain the phenomenon that the ionization energy in molecular assemblies is orientation dependent. It is demonstrated that this is due to a macroscopic impact of intramolecular dipoles on the ionization energy in molecular assemblies. Furthermore, the correlation of molecular orientation and conformation has been studied in detail for COMs on various substrates. (ii) A new approach was developed to tune hole injection barriers ({delta}{sub h}) at organic/metal interfaces by adsorbing a (sub-) monolayer of an organic electron acceptor on the metal electrode. Charge transfer from the metal to the acceptor leads to a chemisorbed layer, which reduces {delta}{sub h} to the COM overlayer. This concept was tested with three acceptors and a lowering of {delta}{sub h} of up to 1.2 eV could be observed. (iii) A transition from vacuum-level alignment to molecular level pinning at the homo-interface between a lying monolayer and standing multilayers of a COM was observed, which depended on the amount of a pre-deposited acceptor. The

Self-Organized Transport System

Science.gov (United States)

2009-09-28

This report presents the findings of the simulation model for a self-organized transport system where traffic lights communicate with neighboring traffic lights and make decisions locally to adapt to traffic conditions in real time. The model is insp...

Self-organizing networks for extracting jet features

International Nuclear Information System (INIS)

Loennblad, L.; Peterson, C.; Pi, H.; Roegnvaldsson, T.

1991-01-01

Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent manner. This is successfully demonstrated with two applications from hadronic jet physics; hadronization model discrimination and separation of b.c. and light quarks. (orig.)

Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory

Energy Technology Data Exchange (ETDEWEB)

Chen, Qiuwen, E-mail: qchen@rcees.ac.cn [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China); China Three Gorges University, Daxuelu 8, Yichang 443002 (China); CEER, Nanjing Hydraulics Research Institute, Guangzhoulu 223, Nanjing 210029 (China); Rui, Han; Li, Weifeng; Zhang, Yanhui [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China)

2014-06-01

Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004–2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial–temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial–temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. - Highlights: • An innovative method is developed to analyze algal bloom risks with uncertainties. • The algal blooms in Taihu Lake showed obvious spatial and temporal patterns. • The lake is mainly characterized as moderate bloom but with high uncertainty. • Severe bloom with low uncertainty appeared occasionally in the northwest part. • The results provide important information to bloom monitoring and management.

Electron injection by evolution of self-modulated laser wakefields

International Nuclear Information System (INIS)

Kim, Changbum; Kim, Guang-Hoon; Kim, Jong-Uk; Lee, Hae June; Suk, Hyyong; Ko, In Soo

2003-01-01

Self-injection mechanisms in the self-modulated laser wakefield acceleration (SM-LWFA) are investigated. Two-dimensional (2D) particle-in-cell (PIC) simulations show that a significant amount of plasma electrons can be self-injected into the acceleration phase of a laser wakefield by a dynamic increase in the wake wavelength in the longitudinal direction. In this process, it is found that the wake wavelength increases due to the relativistic effect and this leads to a large amount of electron injection into the wakefields. In this paper, the injection phenomena are studied with 2D simulations and a brief explanation of the new self-injection mechanism is presented. (author)

Complexity in plasma: From self-organization to geodynamo

International Nuclear Information System (INIS)

Sato, T.

1996-01-01

A central theme of open-quote open-quote Complexity close-quote close-quote is the question of the creation of ordered structure in nature (self-organization). The assertion is made that self-organization is governed by three key processes, i.e., energy pumping, entropy expulsion and nonlinearity. Extensive efforts have been done to confirm this assertion through computer simulations of plasmas. A system exhibits markedly different features in self-organization, depending on whether the energy pumping is instantaneous or continuous, or whether the produced entropy is expulsed or reserved. The nonlinearity acts to bring a nonequilibrium state into a bifurcation, thus resulting in a new structure along with an anomalous entropy production. As a practical application of our grand view of self-organization a preferential generation of a dipole magnetic field is successfully demonstrated. copyright 1996 American Institute of Physics

Evaluation of Changes in Effluent Quality from Industrial Complexes on the Korean Nationwide Scale Using a Self-Organizing Map

Directory of Open Access Journals (Sweden)

Mi-Jung Bae

2012-04-01

Full Text Available One of the major issues related to the environment in the 21st century is sustainable development. The innovative economic growth policy has supported relatively successful economic development, but poor environmental conservation efforts, have consequently resulted in serious water quality pollution issues. Hence, assessments of water quality and health are fundamental processes towards conserving and restoring aquatic ecosystems. In this study, we characterized spatial and temporal changes in water quality (specifically physico-chemical variables plus priority and non-priority pollutants of discharges from industrial complexes on a national scale in Korea. The data were provided by the Water Quality Monitoring Program operated by the Ministry of Environment, Korea and were measured from 1989 to 2008 on a monthly basis at 61 effluent monitoring sites located at industrial complexes. Analysis of monthly and annual changes in water quality, using the seasonal Mann-Kendall test, indicated an improvement in water quality, which was inferred from a continuous increase in dissolved oxygen and decrease in other water quality factors. A Self-Organizing Map, which is an unsupervised artificial neural network, also indicated an improvement of effluent water quality, by showing spatial and temporal differences in the effluent water quality as well as in the occurrence of priority pollutants. Finally, our results suggested that continued long-term monitoring is necessary to establish plans and policies for wastewater management and health assessment.

Evaluation of Changes in Effluent Quality from Industrial Complexes on the Korean Nationwide Scale Using a Self-Organizing Map

Science.gov (United States)

Bae, Mi-Jung; Kim, Jun-Su; Park, Young-Seuk

2012-01-01

One of the major issues related to the environment in the 21st century is sustainable development. The innovative economic growth policy has supported relatively successful economic development, but poor environmental conservation efforts, have consequently resulted in serious water quality pollution issues. Hence, assessments of water quality and health are fundamental processes towards conserving and restoring aquatic ecosystems. In this study, we characterized spatial and temporal changes in water quality (specifically physico-chemical variables plus priority and non-priority pollutants) of discharges from industrial complexes on a national scale in Korea. The data were provided by the Water Quality Monitoring Program operated by the Ministry of Environment, Korea and were measured from 1989 to 2008 on a monthly basis at 61 effluent monitoring sites located at industrial complexes. Analysis of monthly and annual changes in water quality, using the seasonal Mann-Kendall test, indicated an improvement in water quality, which was inferred from a continuous increase in dissolved oxygen and decrease in other water quality factors. A Self-Organizing Map, which is an unsupervised artificial neural network, also indicated an improvement of effluent water quality, by showing spatial and temporal differences in the effluent water quality as well as in the occurrence of priority pollutants. Finally, our results suggested that continued long-term monitoring is necessary to establish plans and policies for wastewater management and health assessment. PMID:22690190

In situ intercalation strategies for device-quality hybrid inorganic-organic self-assembled quantum wells

Science.gov (United States)

Pradeesh, K.; Baumberg, J. J.; Prakash, G. Vijaya

2009-07-01

Thin films of self-organized quantum wells of inorganic-organic hybrid perovskites of (C6H9C2H4NH3)2PbI4 are formed from a simple intercalation strategy to yield well-ordered uniform films over centimeter-size scales. These films compare favorably with traditional solution-chemistry-synthesized thin films. The hybrid films show strong room-temperature exciton-related absorption and photoluminescence, which shift with fabrication protocol. We demonstrate the potential of this method for electronic and photonic device applications.

Variable magnification dual lens electron holography for semiconductor junction profiling and strain mapping.

Science.gov (United States)

Wang, Y Y; Li, J; Domenicucci, A; Bruley, J

2013-01-01

Dual lens operation for electron holography, which was developed previously (Wang et al., Ultramicroscopy 101 (2004) 63-72; US patent: 7,015,469 B2 (2006)), is re-investigated for bright field (junction profiling) and dark field (strain mapping) electron holography using FEI instrumentation (i.e. F20 and Titan). It is found that dual lens operation provides a wide operational range for electron holography. In addition, the dark field image tilt increases at high objective lens current to include Si diffraction spot. Under the condition of high spatial resolution (1 nm fringe spacing), a large field of view (450 nm), and high fringe contrast (26%) with dual lens operation, a junction map is obtained and strain maps of Si device on and diffraction are acquired. In this paper, a fringe quality number, N', which is number of fringe times fringe contrast, is proposed to estimate the quality of an electron hologram and mathematical reasoning for the N' number is provided. Copyright © 2012 Elsevier B.V. All rights reserved.

The role of hierarchy in self-organizing systems

NARCIS (Netherlands)

Ollfen, van W.; Romme, A.G.L.

1995-01-01

This paper discusses the role of hierarchy in human systems. Two kinds of self-organizing processes are distinguished: conservative and dissipative self-organization. The former leads to rather stable, specialistic systems, whereas the latter leads to continuously changing generalistic systems. When

Paramagnetic resonance and electronic conduction in organic semiconductors

International Nuclear Information System (INIS)

Nechtschein, M.

1963-01-01

As some organic bodies simultaneously display semi-conducting properties and a paramagnetism, this report addresses the study of conduction in organic bodies. The author first briefly recalls how relationships between conductibility and Electron Paramagnetic Resonance (EPR) can be noticed in a specific case (mineral and metallic semiconductors). He discusses published results related to paramagnetism and conductibility in organic bodies. He reviews various categories of organic bodies in which both properties are simultaneously present. He notably addresses radical molecular crystals, non-radical molecular crystals, charge transfer complexes, pyrolyzed coals, and pseudo-ferromagnetic organic structures. He discusses the issue of relationships between conduction (charge transfer by electrons) and ERP (which reveals the existence of non-paired electrons which provide free spins)

Integrative mapping analysis of chicken microchromosome 16 organization

Directory of Open Access Journals (Sweden)

Bed'hom Bertrand

2010-11-01

Full Text Available Abstract Background The chicken karyotype is composed of 39 chromosome pairs, of which 9 still remain totally absent from the current genome sequence assembly, despite international efforts towards complete coverage. Some others are only very partially sequenced, amongst which microchromosome 16 (GGA16, particularly under-represented, with only 433 kb assembled for a full estimated size of 9 to 11 Mb. Besides the obvious need of full genome coverage with genetic markers for QTL (Quantitative Trait Loci mapping and major genes identification studies, there is a major interest in the detailed study of this chromosome because it carries the two genetically independent MHC complexes B and Y. In addition, GGA16 carries the ribosomal RNA (rRNA genes cluster, also known as the NOR (nucleolus organizer region. The purpose of the present study is to construct and present high resolution integrated maps of GGA16 to refine its organization and improve its coverage with genetic markers. Results We developed 79 STS (Sequence Tagged Site markers to build a physical RH (radiation hybrid map and 34 genetic markers to extend the genetic map of GGA16. We screened a BAC (Bacterial Artificial Chromosome library with markers for the MHC-B, MHC-Y and rRNA complexes. Selected clones were used to perform high resolution FISH (Fluorescent In Situ Hybridization mapping on giant meiotic lampbrush chromosomes, allowing meiotic mapping in addition to the confirmation of the order of the three clusters along the chromosome. A region with high recombination rates and containing PO41 repeated elements separates the two MHC complexes. Conclusions The three complementary mapping strategies used refine greatly our knowledge of chicken microchromosome 16 organisation. The characterisation of the recombination hotspots separating the two MHC complexes demonstrates the presence of PO41 repetitive sequences both in tandem and inverted orientation. However, this region still needs to

In-situ observation of atomic self-organization processes in Xe nanocrystals embedded in Al

International Nuclear Information System (INIS)

Mitsuishi, K.; Song, M.; Furuya, K.; Birtcher, R. C.; Allen, C. W.; Donnelly, S. E.

1998-01-01

Self-organization processes in Xe nanocrystals embedded in Al are observed with in-situ high-resolution electron microscopy. Under electron irradiation, stacking fault type defects are produced in Xe nanocrystals. The defects recover in a layer by layer manner. Detailed analysis of the video reveals that the displacement of Xe atoms in the stacking fault was rather small for the Xe atoms at boundary between Xe and Al, suggesting the possibility of the stacking fault in Xe precipitate originating inside of precipitate, not at the Al/Xe interface

Estimation of austral summer net community production in the Amundsen Sea: Self-organizing map analysis approach

Science.gov (United States)

Park, K.; Hahm, D.; Lee, D. G.; Rhee, T. S.; Kim, H. C.

2014-12-01

The Amundsen Sea, Antarctica, has been known for one of the most susceptible region to the current climate change such as sea ice melting and sea surface temperature change. In the Southern Ocean, a predominant amount of primary production is occurring in the continental shelf region. Phytoplankton blooms take place during the austral summer due to the limited sunlit and sea ice cover. Thus, quantifying the variation of summer season net community production (NCP) in the Amundsen Sea is essential to analyze the influence of climate change to the variation of biogeochemical cycle in the Southern Ocean. During the past three years of 2011, 2012 and 2014 in austral summer, we have conducted underway observations of ΔO2/Ar and derived NCP of the Amundsen Sea. Despite the importance of NCP for understanding biological carbon cycle of the ocean, the observations are rather limited to see the spatio-temporal variation in the Amundsen Sea. Therefore, we applied self-organizing map (SOM) analysis to expand our observed data sets and estimate the NCP during the summer season. SOM analysis, a type of artificial neural network, has been proved to be a useful method for extracting and classifying features in geoscience. In oceanography, SOM has applied for the analysis of various properties of the seawater such as sea surface temperature, chlorophyll concentration, pCO2, and NCP. Especially it is useful to expand a spatial coverage of direct measurements or to estimate properties whose satellite observations are technically or spatially limited. In this study, we estimate summer season NCP and find a variables set which optimally delineates the NCP variation in the Amundsen Sea as well. Moreover, we attempt to analyze the interannual variation of the Amundsen Sea NCP by taking climatological factors into account for the SOM analysis.

Nanoparticle mediated electron transfer across organic layers: from current understanding to applications

Energy Technology Data Exchange (ETDEWEB)

Gooding, J. Justin; Alam, Muhammad Tanzirul; Barfidokht, Abbas; Carter, Lachlan, E-mail: justin.gooding@unsw.edu.au [School of Chemistry and Australian Centre for NanoMedicine, The University of New South Wales, Sydney (Australia)

2014-03-15

In the last few years electrode-organic layer-nanoparticle constructs have attracted considerable research interest for systems where in the absence of the nanoparticles the electrode is passivated. This is because it has been observed that if the organic layer is a good self-assembled monolayer that passivates the electrode, the presence of the nanoparticles 'switches on' faradaic electrochemistry and because electron transfer between the electrode and the nanoparticles is apparently independent of the thickness of the organic layer. This review 1) outlines the full extent of the experimental observations regarding this phenomenon, 2) discusses a recent theoretical description to explain the observations that have just been supported with experimental evidences and 3) provides an overview of the application of these systems in sensing and photovoltaic. (author)

Electrochemical impedance spectroscopy for study of electronic structure in disordered organic semiconductors—Possibilities and limitations

Science.gov (United States)

Schauer, F.; Nádaždy, V.; Gmucová, K.

2018-04-01

There is potential in applying conjugated polymers in novel organic optoelectronic devices, where a comprehensive understanding of the fundamental processes and energetics involved during transport and recombination is still lacking, limiting further device optimization. The electronic transport modeling and its optimization need the energy distribution of transport and defect states, expressed by the energy distribution of the Density of States (DOS) function, as input/comparative parameters. We present the Energy Resolved-Electrochemical Impedance Spectroscopy (ER-EIS) method for the study of transport and defect electronic states in organic materials. The method allows mapping over unprecedentedly wide energy and DOS ranges. The ER-EIS spectroscopic method is based on the small signal interaction between the surface of the organic film and the liquid electrolyte containing reduction-oxidation (redox) species, which is similar to the extraction of an electron by an acceptor and capture of an electron by a donor at a semiconductor surface. The desired DOS of electronic transport and defect states can be derived directly from the measured redox response signal to the small voltage perturbation at the instantaneous position of the Fermi energy, given by the externally applied voltage. The theory of the ER-EIS method and conditions for its validity for solid polymers are presented in detail. We choose four case studies on poly(3-hexylthiophene-2,5-diyl) and poly[methyl(phenyl)silane] to show the possibilities of the method to investigate the electronic structure expressed by DOS of polymers with a high resolution of about 6 orders of magnitude and in a wide energy range of 6 eV.

Flexible Organic Electronics in Biology: Materials and Devices.

Science.gov (United States)

Liao, Caizhi; Zhang, Meng; Yao, Mei Yu; Hua, Tao; Li, Li; Yan, Feng

2015-12-09

At the convergence of organic electronics and biology, organic bioelectronics attracts great scientific interest. The potential applications of organic semiconductors to reversibly transmit biological signals or stimulate biological tissues inspires many research groups to explore the use of organic electronics in biological systems. Considering the surfaces of movable living tissues being arbitrarily curved at physiological environments, the flexibility of organic bioelectronic devices is of paramount importance in enabling stable and reliable performances by improving the contact and interaction of the devices with biological systems. Significant advances in flexible organic bio-electronics have been achieved in the areas of flexible organic thin film transistors (OTFTs), polymer electrodes, smart textiles, organic electrochemical ion pumps (OEIPs), ion bipolar junction transistors (IBJTs) and chemiresistors. This review will firstly discuss the materials used in flexible organic bioelectronics, which is followed by an overview on various types of flexible organic bioelectronic devices. The versatility of flexible organic bioelectronics promises a bright future for this emerging area. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Self-organized computation with unreliable, memristive nanodevices

International Nuclear Information System (INIS)

Snider, G S

2007-01-01

Nanodevices have terrible properties for building Boolean logic systems: high defect rates, high variability, high death rates, drift, and (for the most part) only two terminals. Economical assembly requires that they be dynamical. We argue that strategies aimed at mitigating these limitations, such as defect avoidance/reconfiguration, or applying coding theory to circuit design, present severe scalability and reliability challenges. We instead propose to mitigate device shortcomings and exploit their dynamical character by building self-organizing, self-healing networks that implement massively parallel computations. The key idea is to exploit memristive nanodevice behavior to cheaply implement adaptive, recurrent networks, useful for complex pattern recognition problems. Pulse-based communication allows the designer to make trade-offs between power consumption and processing speed. Self-organization sidesteps the scalability issues of characterization, compilation and configuration. Network dynamics supplies a graceful response to device death. We present simulation results of such a network-a self-organized spatial filter array-that demonstrate its performance as a function of defects and device variation

Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

Directory of Open Access Journals (Sweden)

Jorge L. Zapotecatl

2017-01-01

Full Text Available Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave and a similar performance (close to optimal compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.

Association mapping of main tomato fruit sugars and organic acids

Directory of Open Access Journals (Sweden)

Jiantao Zhao

2016-08-01

Full Text Available Association mapping has been widely used to map the significant associated loci responsible for natural variation in complex traits and are valuable for crop improvement. Sugars and organic acids are the most important metabolites in tomato fruits. We used a collection of 174 tomato accessions composed of S. lycopersicum (123 accessions and S. lycopersicum var cerasiforme (51 accessions to detect significantly associated loci controlling the variation of main sugars and organic acids. The accessions were genotyped with 182 SSRs spreading over the tomato genome. Association mapping was conducted on the main sugars and organic acids detected by gas chromatography-mass spectrometer (GC-MS over two years using the mixed linear model (MLM. We detected a total of 58 significantly associated loci (P<0.001 for the 17 sugars and organic acids, including fructose, glucose, sucrose, citric acid, malic acid. These results not only co-localized with several reported QTLs, including fru9.1/PV, suc9.1/PV, ca2.1/HS, ca3.1/PV, ca4.1/PV and ca8.1/PV, but also provided a list of candidate significantly associated loci to be functionally validated. These significantly associated loci could be used for deciphering the genetic architecture of tomato fruit sugars and organic acids and for tomato quality breeding.

New insights into the structural organization of eukaryotic and prokaryotic cytoskeletons using cryo-electron tomography

International Nuclear Information System (INIS)

Kuerner, Julia; Medalia, Ohad; Linaroudis, Alexandros A.; Baumeister, Wolfgang

2004-01-01

Cryo-electron tomography (cryo-ET) is an emerging imaging technology that combines the potential of three-dimensional (3-D) imaging at molecular resolution (<5 nm) with a close-to-life preservation of the specimen. In conjunction with pattern recognition techniques, it enables us to map the molecular landscape inside cells. The application of cryo-ET to intact cells provides novel insights into the structure and the spatial organization of the cytoskeleton in prokaryotic and eukaryotic cells

Formation of self-organized anode patterns in arc discharge simulations

International Nuclear Information System (INIS)

Trelles, Juan Pablo

2013-01-01

Pattern formation and self-organization are phenomena commonly observed experimentally in diverse types of plasma systems, including atmospheric-pressure electric arc discharges. However, numerical simulations reproducing anode pattern formation in arc discharges have proven exceedingly elusive. Time-dependent three-dimensional thermodynamic non-equilibrium simulations reveal the spontaneous formation of self-organized patterns of anode attachment spots in the free-burning arc, a canonical thermal plasma flow established by a constant dc current between an axi-symmetric electrode configuration in the absence of external forcing. The number of spots, their size and distribution within the pattern depend on the applied total current and on the resolution of the spatial discretization, whereas the main properties of the plasma flow, such as maximum temperatures, velocity and voltage drop, depend only on the former. The sensibility of the solution to the spatial discretization stresses the computational requirements for comprehensive arc discharge simulations. The obtained anode patterns qualitatively agree with experimental observations and confirm that the spots originate at the fringes of the arc–anode attachment. The results imply that heavy-species–electron energy equilibration, in addition to thermal instability, has a dominant role in the formation of anode spots in arc discharges. (paper)

Self-organized titanium oxide nano-channels for resistive memory application

Energy Technology Data Exchange (ETDEWEB)

Barman, A.; Saini, C. P.; Dhar, S.; Kanjilal, A., E-mail: aloke.kanjilal@snu.edu.in [Department of Physics, School of Natural Sciences, Shiv Nadar University, NH-91, Tehsil Dadri, Gautam Buddha Nagar, Uttar Pradesh 201 314 (India); Sarkar, P. [Department of Physics, National Institute of Technology, Silchar, Assam 788 010 (India); Satpati, B.; Bhattacharyya, S. R. [Surface Physics and Material Science Division, Saha Institute of Nuclear Physics, 1/AF Bidhannagar, Kolkata 700 064 (India); Kabiraj, D.; Kanjilal, D. [Inter-University Accelerator Centre, Aruna Asaf Ali Marg, New Delhi 110 067 (India)

2015-12-14

Towards developing next generation scalable TiO{sub 2}-based resistive switching (RS) memory devices, the efficacy of 50 keV Ar{sup +}-ion irradiation to achieve self-organized nano-channel based structures at a threshold fluence of 5 × 10{sup 16} ions/cm{sup 2} at ambient temperature is presented. Although x-ray diffraction results suggest the amorphization of as-grown TiO{sub 2} layers, detailed transmission electron microscopy study reveals fluence-dependent evolution of voids and eventual formation of self-organized nano-channels between them. Moreover, gradual increase of TiO/Ti{sub 2}O{sub 3} in the near surface region, as monitored by x-ray photoelectron spectroscopy, establishes the upsurge in oxygen deficient centers. The impact of structural and chemical modification on local RS behavior has also been investigated by current-voltage measurements in conductive atomic force microscopy, while memory application is manifested by fabricating Pt/TiO{sub 2}/Pt/Ti/SiO{sub 2}/Si devices. Finally, the underlying mechanism of our experimental results has been analyzed and discussed in the light of oxygen vacancy migration through nano-channels.

Adaptive multiresolution method for MAP reconstruction in electron tomography

Energy Technology Data Exchange (ETDEWEB)

Acar, Erman, E-mail: erman.acar@tut.fi [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland); Peltonen, Sari; Ruotsalainen, Ulla [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland)

2016-11-15

3D image reconstruction with electron tomography holds problems due to the severely limited range of projection angles and low signal to noise ratio of the acquired projection images. The maximum a posteriori (MAP) reconstruction methods have been successful in compensating for the missing information and suppressing noise with their intrinsic regularization techniques. There are two major problems in MAP reconstruction methods: (1) selection of the regularization parameter that controls the balance between the data fidelity and the prior information, and (2) long computation time. One aim of this study is to provide an adaptive solution to the regularization parameter selection problem without having additional knowledge about the imaging environment and the sample. The other aim is to realize the reconstruction using sequences of resolution levels to shorten the computation time. The reconstructions were analyzed in terms of accuracy and computational efficiency using a simulated biological phantom and publically available experimental datasets of electron tomography. The numerical and visual evaluations of the experiments show that the adaptive multiresolution method can provide more accurate results than the weighted back projection (WBP), simultaneous iterative reconstruction technique (SIRT), and sequential MAP expectation maximization (sMAPEM) method. The method is superior to sMAPEM also in terms of computation time and usability since it can reconstruct 3D images significantly faster without requiring any parameter to be set by the user. - Highlights: • An adaptive multiresolution reconstruction method is introduced for electron tomography. • The method provides more accurate results than the conventional reconstruction methods. • The missing wedge and noise problems can be compensated by the method efficiently.

Assessment of oscillator strengths with multiconfigurational short-range density functional theory for electronic excitations in organic molecules

DEFF Research Database (Denmark)

Hedegård, Erik Donovan

2017-01-01

considered the large collection of organic molecules whose excited states were investigated with a range of electronic structure methods by Thiel et al. As a by-product of our calculations of oscillator strengths, we also obtain electronic excitation energies, which enable us to compare the performance......We have in a series of recent papers investigated electronic excited states with a hybrid between a complete active space self-consistent field (CASSCF) wave function and density functional theory (DFT). This method has been dubbed the CAS short-range DFT method (CAS–srDFT). The previous papers...

Singularity spectrum of self-organized criticality

International Nuclear Information System (INIS)

Canessa, E.

1992-10-01

I introduce a simple continuous probability theory based on the Ginzburg-Landau equation that provides for the first time a common analytical basis to relate and describe the main features of two seemingly different phenomena of condensed-matter physics, namely self-organized criticality and multifractality. Numerical support is given by a comparison with reported simulation data. Within the theory the origin of self-organized critical phenomena is analysed in terms of a nonlinear singularity spectrum different form the typical convex shape due to multifractal measures. (author). 29 refs, 5 figs

A data-mining framework for exploring the multi-relation between fish species and water quality through self-organizing map.

Science.gov (United States)

Tsai, Wen-Ping; Huang, Shih-Pin; Cheng, Su-Ting; Shao, Kwang-Tsao; Chang, Fi-John

2017-02-01

The steep slopes of rivers can easily lead to large variations in river water quality during typhoon seasons in Taiwan, which may poses significant impacts on riverine eco-hydrological environments. This study aims to investigate the relationship between fish communities and water quality by using artificial neural networks (ANNs) for comprehending the upstream eco-hydrological system in northern Taiwan. We collected a total of 276 heterogeneous datasets with 8 water quality parameters and 25 fish species from 10 sampling sites. The self-organizing feature map (SOM) was used to cluster, analyze and visualize the heterogeneous datasets. Furthermore, the structuring index (SI) was adopted to determine the relative importance of each input variable of the SOM and identify the indicator factors. The clustering results showed that the SOM could suitably reflect the spatial characteristics of fishery sampling sites. Besides, the patterns of water quality parameters and fish species could be distinguishably (visually) classified into three eco-water quality groups: 1) typical upstream freshwater fishes that depended the most on dissolved oxygen (DO); 2) typical middle-lower reach riverine freshwater fishes that depended the most on total phosphorus (TP) and ammonia nitrogen; and 3) low lands or pond (reservoirs) freshwater fishes that depended the most on water temperature, suspended solids and chemical oxygen demand. According to the results of the SI, the representative indicators of water quality parameters and fish species consisted of DO, TP and Onychostoma barbatulum. This grouping result suggested that the methodology can be used as a guiding reference to comprehensively relate ecology to water quality. Our methods offer a cost-effective alternative to more traditional methods for identifying key water quality factors relating to fish species. In addition, visualizing the constructed topological maps of the SOM could produce detailed inter-relation between water

Micro- and macro-scale self-organization in a dissipative plasma

International Nuclear Information System (INIS)

Skoric, M.M.; Sato, T.; Maluckov, A.; Jovanovic, M.S.

1998-10-01

We study a nonlinear three-wave interaction in an open dissipative model of stimulated Raman backscattering in a plasma. A hybrid kinetic-fluid scheme is proposed to include anomalous kinetic dissipation due to electron trapping and plasma wave breaking. We simulate a finite plasma with open boundaries and vary a transport parameter to examine a route to spatio-temporal complexity. An interplay between self-organization at micro (kinetic) and macro (wave/fluid) scales is revealed through quasi-periodic and intermittent evolution of dynamical variables, dissipative structures and related entropy rates. An evidence that entropy rate extrema correspond to structural transitions is found. (author)

Progresses in organic field-effect transistors and molecular electronics

Institute of Scientific and Technical Information of China (English)

Wu Weiping; Xu Wei; Hu Wenping; Liu Yunqi; Zhu Daoben

2006-01-01

In the past years,organic semiconductors have been extensively investigated as electronic materials for organic field-effect transistors (OFETs).In this review,we briefly summarize the current status of organic field-effect transistors including materials design,device physics,molecular electronics and the applications of carbon nanotubes in molecular electronics.Future prospects and investigations required to improve the OFET performance are also involved.

Information Driven Ecohydrologic Self-Organization

Directory of Open Access Journals (Sweden)

Benjamin L. Ruddell

2010-09-01

Full Text Available Variability plays an important role in the self-organized interaction between vegetation and its environment, yet the principles that characterize the role of the variability in these interactions remain elusive. To address this problem, we study the dependence between a number of variables measured at flux towers by quantifying the information flow between the different variables along with the associated time lag. By examining this network of feedback loops for seven ecosystems in different climate regions, we find that: (1 the feedback tends to maximize information production in the entire system, and the latter increases with increasing variability within the whole system; and (2 variables that participate in feedback exhibit moderated variability. Self-organization arises as a tradeoff where the ability of the total system to maximize information production through feedback is limited by moderate variability of the participating variables. This relationship between variability and information production leads to the emergence of ordered organization.

Tensor SOM and tensor GTM: Nonlinear tensor analysis by topographic mappings.

Science.gov (United States)

Iwasaki, Tohru; Furukawa, Tetsuo

2016-05-01

In this paper, we propose nonlinear tensor analysis methods: the tensor self-organizing map (TSOM) and the tensor generative topographic mapping (TGTM). TSOM is a straightforward extension of the self-organizing map from high-dimensional data to tensorial data, and TGTM is an extension of the generative topographic map, which provides a theoretical background for TSOM using a probabilistic generative model. These methods are useful tools for analyzing and visualizing tensorial data, especially multimodal relational data. For given n-mode relational data, TSOM and TGTM can simultaneously organize a set of n-topographic maps. Furthermore, they can be used to explore the tensorial data space by interactively visualizing the relationships between modes. We present the TSOM algorithm and a theoretical description from the viewpoint of TGTM. Various TSOM variations and visualization techniques are also described, along with some applications to real relational datasets. Additionally, we attempt to build a comprehensive description of the TSOM family by adapting various data structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relativistic electron beam - plasma interaction with intense self-fields

International Nuclear Information System (INIS)

Davidson, R.C.

1984-01-01

The major interest in the equilibrium, stability and radiation properties of relativistic electron beams and in beam-plasma interactions originates from several diverse research areas. It is well known that a many-body collection of charged particles in which there is not overall charge neutrality and/or current neutrality can be characterized by intense self-electric fields and/or self-magnetic fields. Moreover, the intense equilibrium self-fields associated with the lack of charge neutrality and/or current neutrality can have a large effect on particle trajectories and on detailed equilibrium and stability behavior. The main emphasis in Sections 9.1.2-9.1.5 of this chapter is placed on investigations of the important influence of self-fields on the equilibrium and stability properties of magnetically confined electron beam-plasma systems. Atomic processes and discrete particle interactions (binary collisions) are omitted from the analysis, and collective processes are assumed to dominate on the time and length scales of interest. Moreover, both macroscopic (Section 9.1.2) and kinetic (Sections 9.1.3-9.1.5) theoretical models are developed and used to investigate equilibrium and stability properties in straight cylindrical geometry. Several of the classical waves and instabilities characteristic of nonneutral plasmas and beam-plasma systems are analyzed in Sections 9.1.2-9.1.5, including stable surface oscillation on a nonneutral electron beam, the ion resonance instability, the diocotron instability, two-stream instabilities between beam electrons and plasma electrons and between beam electrons and plasma ions, the filamentation instability, the modified two-stream instability, etc

Self-bunching electron guns

Science.gov (United States)

Mako, Frederick M.; Len, L. K.

1999-05-01

We report on three electron gun projects that are aimed at power tube and injector applications. The purpose of the work is to develop robust electron guns which produce self-bunched, high-current-density beams. We have demonstrated, in a microwave cavity, self-bunching, cold electron emission, long life, and tolerance to contamination. The cold process is based on secondary electron emission. FMT has studied using simulation codes the resonant bunching process which gives rise to high current densities (0.01-5 kA/cm2), high charge bunches (up to 500 nC/bunch), and short pulses (1-100 ps) for frequencies from 1 to 12 GHz. The beam pulse width is nominally ˜5% of the rf period. The first project is the L-Band Micro-Pulse Gun (MPG). Measurements show ˜40 ps long micro-bunches at ˜20 A/cm2 without contamination due to air exposure. Lifetime testing has been carried out for about 18 months operating at 1.25 GHz for almost 24 hours per day at a repetition rate of 300 Hz and 5 μs-long macro-pulses. Approximately 5.8×1013 micro-bunches or 62,000 coulombs have passed through this gun and it is still working fine. The second project, the S-Band MPG, is now operational. It is functioning at a frequency of 2.85 GHz, a repetition rate of 30 Hz, with a 2 μs-long macro-pulse. It produces about 45 A in the macro-pulse. The third project is a 34.2 GHz frequency-multiplied source driven by an X-Band MPG. A point design was performed at an rf output power of 150 MW at 34.2 GHz. The resulting system efficiency is 53% and the gain is 60 dB. The system efficiency includes the input cavity efficiency, input driver efficiency (a 50 MW klystron at 11.4 GHz), output cavity efficiency, and the post-acceleration efficiency.

Self-Organization during Friction of Slide Bearing Antifriction Materials

Directory of Open Access Journals (Sweden)

Iosif S. Gershman

2015-12-01

Full Text Available This article discusses the peculiarities of self-organization behavior and formation of dissipative structures during friction of antifriction alloys for slide bearings against a steel counterbody. It shows that during self-organization, the moment of friction in a tribosystem may be decreasing with the load growth and in the bifurcations of the coefficient of friction with respect to load. Self-organization and the formation of dissipative structures lead to an increase in the seizure load.

Concept and Feasibility Study of Self-Organized Electrochemical Devices

National Research Council Canada - National Science Library

Moorehead, William

2002-01-01

.... In this work, using attractive and repulsive London-van der Waals forces, a self-organized, interpenetrating, separator-free rechargeable lithium ion battery called a self-organized battery system (SBS) is proposed...

Self-organization of spatial patterning in human embryonic stem cells

Science.gov (United States)

Deglincerti, Alessia; Etoc, Fred; Ozair, M. Zeeshan; Brivanlou, Ali H.

2017-01-01

The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatio-temporal choreography. Recently, human embryonic stem cells (ESCs) have been used to recapitulate in vitro the self-organization programs that are executed in the embryo in vivo. This represents a unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this essay, we review the recent literature on self-organization of human ESCs, with a particular focus on two examples: formation of embryonic germ layers and neural rosettes. Intriguingly, both activation and elimination of TGFβ signaling can initiate self-organization, albeit with different molecular underpinnings. We discuss the mechanisms underlying the formation of these structures in vitro and explore future challenges in the field. PMID:26970615

Emergence or self-organization?: Look to the soil population.

Science.gov (United States)

Addiscott, Tom

2011-07-01

EMERGENCE IS NOT WELL DEFINED, BUT ALL EMERGENT SYSTEMS HAVE THE FOLLOWING CHARACTERISTICS: the whole is more than the sum of the parts, they show bottom-up rather top-down organization and, if biological, they involve chemical signaling. Self-organization can be understood in terms of the second and third stages of thermodynamics enabling these stages used as analogs of ecosystem functioning. The second stage system was suggested earlier to provide a useful analog of the behavior of natural and agricultural ecosystems subjected to perturbations, but for this it needs the capacity for self-organization. Considering the hierarchy of the ecosystem suggests that this self-organization is provided by the third stage, whose entropy maximization acts as an analog of that of the soil population when it releases small molecules from much larger molecules in dead plant matter. This it does as vigorously as conditions allow. Through this activity, the soil population confers self-organization at both the ecosystem and the global level. The soil population has been seen as both emergent and self-organizing, supporting the suggestion that the two concepts are are so closely linked as to be virtually interchangeable. If this idea is correct one of the characteristics of a biological emergent system seems to be the ability to confer self-organization on an ecosystem or other entity which may be larger than itself. The beehive and the termite colony are emergent systems which share this ability.

Deterministic self-organization: Ordered positioning of InAs quantum dots by self-organized anisotropic strain engineering on patterned GaAs(311)B

International Nuclear Information System (INIS)

Selcuk, E.; Hamhuis, G.J.; Noetzel, R.

2009-01-01

Laterally ordered InGaAs quantum dot (QD) arrays, InAs QD molecules, and single InAs QDs in a spot-like periodic arrangement are created by self-organized anisotropic strain engineering of InGaAs/GaAs superlattice (SL) templates on planar GaAs (311)B substrates in molecular beam epitaxy. On shallow- and deep-patterned substrates the respectively generated steps and facets guide the self-organization process during SL template formation to create more complex ordering such as periodic stripes, depending on pattern design. Here we demonstrate for patterns such as shallow- and deepetched round holes and deep-etched zigzag mesas that the self-organized periodic arrangement of QD molecules and single QDs is spatially locked to the pattern sidewalls and corners. This extends the concept of guided self-organization to deterministic self-organization. Absolute position control of the QDs is achieved without one-to-one pattern definition. This guarantees the excellent arrangement control of the ordered QD molecules and single QDs with strong photoluminescence emission up to room temperature, which is required for future quantum functional devices. (copyright 2009 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Electronic properties of metal-organic and organic-organic interfaces studied by photoemission and photoabsorption spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Molodtsova, Olga

2006-07-01

In this work systematic studies of the organic semiconductor CuPc have been presented. In general the investigation can be devided in three parts. In the first one we have studied the electronic structure of clean CuPc thin film. The next two parts are devoted to organic-organic and metal-organic interface formation, where one of the interface components is CuPc thin film. The main results of this thesis are: - The electronic structure of the pristine organic semiconductor CuPc has been obtained by a combination of conventional and resonant photoemission, near-edge X-ray absorption, as well as by theoretical ab initio quantum-chemical calculations. The contributions of different atomic species as well as sites of the CuPc molecule to the electronic DOS has been established. A combined experimental and theoretical study of the unoccupied electronic density of states of CuPc was presented. - The electronic properties of the organic heterointerfaces between fullerite and pristine copper phthalocyanine were studied. Both interfaces, CuPc/C{sub 60} and C{sub 60}/CuPc, were found to be non-reactive with pronounced shifts of the vacuum level pointing to the formation of an interfacial dipole mainly at the CuPc side of the heterojunctions. The dipole values are close to the difference of the work functions of the two materials. Important interface parameters and hole-injection barriers were obtained. The sequence of deposition does not influence the electronic properties of the interfaces. - CuPc doped with potassium was studied by means of photoemission and photoabsorption spectroscopy. A detailed analysis of the core-level PE spectra allows one to propose possible lattice sites, which harbor the potassium ions. The films prepared in this thesis showed no finite electronic density of states at the Fermi level. - Two stages of the In/CuPc interface formation have been distinguished. The low-coverage stage is characterized by a strong diffusion of the In atoms into the

Differential phase-contrast dark-field electron holography for strain mapping

Energy Technology Data Exchange (ETDEWEB)

Denneulin, Thibaud, E-mail: thibaud.denneulin@cemes.fr; Houdellier, Florent, E-mail: florent.houdellier@cemes.fr; Hÿtch, Martin, E-mail: martin.hytch@cemes.fr

2016-01-15

Strain mapping is an active area of research in transmission electron microscopy. Here we introduce a dark-field electron holographic technique that shares several aspects in common with both off-axis and in-line holography. Two incident and convergent plane waves are produced in front of the specimen thanks to an electrostatic biprism in the condenser system of a transmission electron microscope. The interference of electron beams diffracted by the illuminated crystal is then recorded in a defocused plane. The differential phase recovered from the hologram is directly proportional to the strain in the sample. The strain can be quantified if the separation of the images due to the defocus is precisely determined. The present technique has the advantage that the derivative of the phase is measured directly which allows us to avoid numerical differentiation. The distribution of the noise in the reconstructed strain maps is isotropic and more homogeneous. This technique was used to investigate different samples: a Si/SiGe superlattice, transistors with SiGe source/drain and epitaxial PZT thin films. - Highlights: • DPC dark-field electron holography is set up with a condenser biprism. • The DPC phase is directly proportional to the lattice deformation. • The technique is illustrated with epitaxial SiGe and Pb(Zr,Ti)O{sub 3} samples. • The defocus allows us to control the strain sensitivity and the spatial resolution. • A solution is proposed to setup this technique with a post-specimen biprism.

Structural complexities in the active layers of organic electronics.

Science.gov (United States)

Lee, Stephanie S; Loo, Yueh-Lin

2010-01-01

The field of organic electronics has progressed rapidly in recent years. However, understanding the direct structure-function relationships between the morphology in electrically active layers and the performance of devices composed of these materials has proven difficult. The morphology of active layers in organic electronics is inherently complex, with heterogeneities existing across multiple length scales, from subnanometer to micron and millimeter range. A major challenge still facing the organic electronics community is understanding how the morphology across all of the length scales in active layers collectively determines the device performance of organic electronics. In this review we highlight experiments that have contributed to the elucidation of structure-function relationships in organic electronics and also point to areas in which knowledge of such relationships is still lacking. Such knowledge will lead to the ability to select active materials on the basis of their inherent properties for the fabrication of devices with prespecified characteristics.

Stranski–Krastanov transition and self-organized structures in low-strained AlInN/GaN multilayer structures

International Nuclear Information System (INIS)

Krost, A; Berger, C; Moser, P; Bläsing, J; Dadgar, A; Hums, C; Hempel, T; Bastek, B; Veit, P; Christen, J

2011-01-01

Low-strained AlInN/GaN multilayers aimed as Bragg mirrors were grown by metal organic vapour phase epitaxy on GaN/Si(1 1 1). In such structures the upper AlInN/GaN interfaces show a considerable roughening on a nanometre scale whereas the lower ones appear flat as evaluated by cross-sectional electron and transmission electron microscopy. The roughening is attributed to a Stranski–Krastanov transition from two-dimensional layer-by-layer to three-dimensional island growth. In addition, a self-organized wavy-like surface morphology on a micrometre scale is observed in such structures which we discuss in terms of Grinfeld instability

Self-Organization of Spatial Patterning in Human Embryonic Stem Cells.

Science.gov (United States)

Deglincerti, Alessia; Etoc, Fred; Ozair, M Zeeshan; Brivanlou, Ali H

2016-01-01

The developing embryo is a remarkable example of self-organization, where functional units are created in a complex spatiotemporal choreography. Recently, human embryonic stem cells (ESCs) have been used to recapitulate in vitro the self-organization programs that are executed in the embryo in vivo. This represents an unique opportunity to address self-organization in humans that is otherwise not addressable with current technologies. In this chapter, we review the recent literature on self-organization of human ESCs, with a particular focus on two examples: formation of embryonic germ layers and neural rosettes. Intriguingly, both activation and elimination of TGFβ signaling can initiate self-organization, albeit with different molecular underpinnings. We discuss the mechanisms underlying the formation of these structures in vitro and explore future challenges in the field. © 2016 Elsevier Inc. All rights reserved.

Automated grain mapping using wide angle convergent beam electron diffraction in transmission electron microscope for nanomaterials.

Science.gov (United States)

Kumar, Vineet

2011-12-01

The grain size statistics, commonly derived from the grain map of a material sample, are important microstructure characteristics that greatly influence its properties. The grain map for nanomaterials is usually obtained manually by visual inspection of the transmission electron microscope (TEM) micrographs because automated methods do not perform satisfactorily. While the visual inspection method provides reliable results, it is a labor intensive process and is often prone to human errors. In this article, an automated grain mapping method is developed using TEM diffraction patterns. The presented method uses wide angle convergent beam diffraction in the TEM. The automated technique was applied on a platinum thin film sample to obtain the grain map and subsequently derive grain size statistics from it. The grain size statistics obtained with the automated method were found in good agreement with the visual inspection method.

Self-organizing maps of Kohonen (SOM) applied to multidimensional monitoring data of the IEA-R1 nuclear research reactor

International Nuclear Information System (INIS)

Affonso, Gustavo S.; Pereira, Iraci M.; Mesquita, Roberto N. de; Bueno, Elaine I.

2011-01-01

Multivariate statistics comprise a set of statistical methods used in situations where many variables are database space subsets. Initially applied to human, social and biological sciences, these methods are being applied to many other areas such as education, geology, chemistry, physics, engineering, and many others. This spectra expansion was possible due to recent technological development of computation hardware and software that allows high and complex databases to be treated iteratively enabling further analysis. Following this trend, the neural networks called Self-Organizing Maps are turning into a powerful tool on visualization of implicit and unknown correlations in big sized database sets. Originally created by Kohonen in 1981, it was applied to speech recognition tasks. The SOM is being used as a comparative parameter to evaluate the performance of new multidimensional analysis methodologies. Most of methods require good variable input selection criteria and SOM has contributed to clustering, classification and prediction of multidimensional engineering process variables. This work proposes a method of applying SOM to a set of 58 IEA-R1 operational variables at IPEN research reactor which are monitored by a Data Acquisition System (DAS). This data set includes variables as temperature, flow mass rate, coolant level, nuclear radiation, nuclear power and control bars position. DAS enables the creation and storage of historical data which are used to contribute to Failure Detection and Monitoring System development. Results show good agreement with previous studies using other methods as GMDH and other predictive methods. (author)

Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

Science.gov (United States)

Hoomod, Haider K.; Kareem Jebur, Tuka

2018-05-01

Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

Self-organizing maps of Kohonen (SOM) applied to multidimensional monitoring data of the IEA-R1 nuclear research reactor

Energy Technology Data Exchange (ETDEWEB)

Affonso, Gustavo S.; Pereira, Iraci M.; Mesquita, Roberto N. de, E-mail: rnavarro@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Bueno, Elaine I., E-mail: ebueno@ifsp.gov.b [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), SP (Brazil)

2011-07-01

Multivariate statistics comprise a set of statistical methods used in situations where many variables are database space subsets. Initially applied to human, social and biological sciences, these methods are being applied to many other areas such as education, geology, chemistry, physics, engineering, and many others. This spectra expansion was possible due to recent technological development of computation hardware and software that allows high and complex databases to be treated iteratively enabling further analysis. Following this trend, the neural networks called Self-Organizing Maps are turning into a powerful tool on visualization of implicit and unknown correlations in big sized database sets. Originally created by Kohonen in 1981, it was applied to speech recognition tasks. The SOM is being used as a comparative parameter to evaluate the performance of new multidimensional analysis methodologies. Most of methods require good variable input selection criteria and SOM has contributed to clustering, classification and prediction of multidimensional engineering process variables. This work proposes a method of applying SOM to a set of 58 IEA-R1 operational variables at IPEN research reactor which are monitored by a Data Acquisition System (DAS). This data set includes variables as temperature, flow mass rate, coolant level, nuclear radiation, nuclear power and control bars position. DAS enables the creation and storage of historical data which are used to contribute to Failure Detection and Monitoring System development. Results show good agreement with previous studies using other methods as GMDH and other predictive methods. (author)

Electron self-mass in the semiclassical limit

International Nuclear Information System (INIS)

Pradham, T.; Khare, A.

1978-01-01

The semiclassical limit of the electron self-mass, which is the first order term in an expansion of the exact Dyson self-mass in powers of h/2π, is calculated. The result is quadratically divergent in the limit of the cut-off radius tending to zero. It is noted that the present result is quantum mechanical in the same sense as any WKB result and is exact to all orders in e 2 , in contrast to the logarithmically divergent self-mass given by other resuls. (U.K.)

Methodical Aspects of Applying Strategy Map in an Organization

Directory of Open Access Journals (Sweden)

Piotr Markiewicz

2013-06-01

Full Text Available One of important aspects of strategic management is the instrumental aspect included in a rich set of methods and techniques used at particular stages of strategic management process. The object of interest in this study is the development of views and the implementation of strategy as an element of strategic management and instruments in the form of methods and techniques. The commonly used method in strategy implementation and measuring progress is Balanced Scorecard (BSC. The method was created as a result of implementing the project “Measuring performance in the Organization of the future” of 1990, completed by a team under the supervision of David Norton (Kaplan, Norton 2002. The developed method was used first of all to evaluate performance by decomposition of a strategy into four perspectives and identification of measures of achievement. In the middle of 1990s the method was improved by enriching it, first of all, with a strategy map, in which the process of transition of intangible assets into tangible financial effects is reflected (Kaplan, Norton 2001. Strategy map enables illustration of cause and effect relationship between processes in all four perspectives and performance indicators at the level of organization. The purpose of the study being prepared is to present methodical conditions of using strategy maps in the strategy implementation process in organizations of different nature.

Use of self-organizing maps for classification of defects in the tubes from the steam generator of nuclear power plants; Classificacao de defeitos em tubos de gerador de vapor de plantas nucleares utilizando mapas auto-organizaveis

Energy Technology Data Exchange (ETDEWEB)

Mesquita, Roberto Navarro de

2002-07-01

This thesis obtains a new classification method for different steam generator tube defects in nuclear power plants using Eddy Current Test signals. The method uses self-organizing maps to compare different signal characteristics efficiency to identify and classify these defects. A multiple inference system is proposed which composes the different extracted characteristic trained maps classification to infer the final defect type. The feature extraction methods used are the Wavelet zero-crossings representation, the linear predictive coding (LPC), and other basic signal representations on time like module and phase. Many characteristic vectors are obtained with combinations of these extracted characteristics. These vectors are tested to classify the defects and the best ones are applied to the multiple inference system. A systematic study of pre-processing, calibration and analysis methods for the steam generator tube defect signals in nuclear power plants is done. The method efficiency is demonstrated and characteristic maps with the main prototypes are obtained for each steam generator tube defect type. (author)

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

Science.gov (United States)

Hortos, William S.

2006-05-01

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

Detecting tactical patterns in basketball: comparison of merge self-organising maps and dynamic controlled neural networks.

Science.gov (United States)

Kempe, Matthias; Grunz, Andreas; Memmert, Daniel

2015-01-01

The soaring amount of data, especially spatial-temporal data, recorded in recent years demands for advanced analysis methods. Neural networks derived from self-organizing maps established themselves as a useful tool to analyse static and temporal data. In this study, we applied the merge self-organising map (MSOM) to spatio-temporal data. To do so, we investigated the ability of MSOM's to analyse spatio-temporal data and compared its performance to the common dynamical controlled network (DyCoN) approach to analyse team sport position data. The position data of 10 players were recorded via the Ubisense tracking system during a basketball game. Furthermore, three different pre-selected plays were recorded for classification. Following data preparation, the different nets were trained with the data of the first half. The training success of both networks was evaluated by achieved entropy. The second half of the basketball game was presented to both nets for automatic classification. Both approaches were able to present the trained data extremely well and to detect the pre-selected plays correctly. In conclusion, MSOMs are a useful tool to analyse spatial-temporal data, especially in team sports. By their direct inclusion of different time length of tactical patterns, they open up new opportunities within team sports.

Applications of Organic and Printed Electronics A Technology-Enabled Revolution

CERN Document Server

2013-01-01

Organic and printed electronics can enable a revolution in the applications of electronics and this book offers readers an overview of the state-of-the-art in this rapidly evolving domain.  The potentially low cost, compatibility with flexible substrates and the wealth of devices that characterize organic and printed electronics will make possible applications that go far beyond the well-known displays made with large-area silicon electronics. Since organic electronics are still in their early stage, undergoing transition from lab-scale and prototype activities to production, this book serves as a valuable snapshot of the current landscape of the different devices enabled by this technology, reviewing all applications that are developing and those can be foreseen.   Provides a complete roadmap for organic and printed electronics research and development for the next several years; Includes an overview of the printing processes for organic electronics, along with state of the art applications, such as solar ...

Self-organization at the frictional interface for green tribology.

Science.gov (United States)

Nosonovsky, Michael

2010-10-28

Despite the fact that self-organization during friction has received relatively little attention from tribologists so far, it has the potential for the creation of self-healing and self-lubricating materials, which are important for green or environment-friendly tribology. The principles of the thermodynamics of irreversible processes and of the nonlinear theory of dynamical systems are used to investigate the formation of spatial and temporal structures during friction. The transition to the self-organized state with low friction and wear occurs through destabilization of steady-state (stationary) sliding. The criterion for destabilization is formulated and several examples are discussed: the formation of a protective film, microtopography evolution and slip waves. The pattern formation may involve self-organized criticality and reaction-diffusion systems. A special self-healing mechanism may be embedded into the material by coupling the corresponding required forces. The analysis provides the structure-property relationship, which can be applied for the design optimization of composite self-lubricating and self-healing materials for various ecologically friendly applications and green tribology.

Electronic Processes at Organic−Organic Interfaces: Insight from Modeling and Implications for Opto-electronic Devices †

KAUST Repository

Beljonne, David

2011-02-08

We report on the recent progress achieved in modeling the electronic processes that take place at interfaces between π-conjugated materials in organic opto-electronic devices. First, we provide a critical overview of the current computational techniques used to assess the morphology of organic: organic heterojunctions; we highlight the compromises that are necessary to handle large systems and multiple time scales while preserving the atomistic details required for subsequent computations of the electronic and optical properties. We then review some recent theoretical advances in describing the ground-state electronic structure at heterojunctions between donor and acceptor materials and highlight the role played by charge-transfer and long-range polarization effects. Finally, we discuss the modeling of the excited-state electronic structure at organic:organic interfaces, which is a key aspect in the understanding of the dynamics of photoinduced electron-transfer processes. © 2010 American Chemical Society.

ESR spectroscopy and electron distribution

International Nuclear Information System (INIS)

Davies, A.G.

1997-01-01

EPR spectroscopy can map out the electron distribution in a molecule, in much the same way as proton NMR spectroscopy can map out the proton distribution, and it provides some of the most direct evidence for the principal concepts underlying the electronic theory of organic structure and mechanism. This is illustrated for phenomena of conjugation, hyper-conjugation, substituent effects in annulenes, Hueckel theory, ring strain, the Mills-Nixon effect, and ion pairing. (author)

Crystal step edges can trap electrons on the surfaces of n-type organic semiconductors.

Science.gov (United States)

He, Tao; Wu, Yanfei; D'Avino, Gabriele; Schmidt, Elliot; Stolte, Matthias; Cornil, Jérôme; Beljonne, David; Ruden, P Paul; Würthner, Frank; Frisbie, C Daniel

2018-05-30

Understanding relationships between microstructure and electrical transport is an important goal for the materials science of organic semiconductors. Combining high-resolution surface potential mapping by scanning Kelvin probe microscopy (SKPM) with systematic field effect transport measurements, we show that step edges can trap electrons on the surfaces of single crystal organic semiconductors. n-type organic semiconductor crystals exhibiting positive step edge surface potentials display threshold voltages that increase and carrier mobilities that decrease with increasing step density, characteristic of trapping, whereas crystals that do not have positive step edge surface potentials do not have strongly step density dependent transport. A device model and microelectrostatics calculations suggest that trapping can be intrinsic to step edges for crystals of molecules with polar substituents. The results provide a unique example of a specific microstructure-charge trapping relationship and highlight the utility of surface potential imaging in combination with transport measurements as a productive strategy for uncovering microscopic structure-property relationships in organic semiconductors.

A concept mapping study on organic food consumers in Shanghai, China.

Science.gov (United States)

Hasimu, Huliyeti; Marchesini, Sergio; Canavari, Maurizio

2017-01-01

Despite some similarities with developed countries, the growth of organic market in China seems to follow a different path. Thus, important questions are how Chinese urban consumers perceive organic food, and what are the main concepts associated to the organic attribute. We aimed at representing in graphic form the network of mental associations with the organic concept. We used an adapted version of the "Brand concept mapping" method to acquire, process, and draw individual concept networks perceived by 50 organic food consumers in Shanghai. We then analyzed the data using network and cluster analysis to create aggregated maps for two distinct groups of consumers. Similarly to their peers in developed countries, Chinese consumers perceive organic food as healthy, safe and expensive. However, organic is not necessarily synonymous with natural produce in China, also due to a translation of the term that conveys the idea of a "technology advanced" product. Organic overlaps with the green food label in terms of image and positioning in the market, since they are easily associated and often confused. The two groups we identified show clear differences in the way the organic concept is associated to other concepts and features. The study provides useful information for practitioners: marketers of organic products in China should invest in communication to emphasize the differences with Green Food products and they should consider the possibility of segmenting organic consumers; Chinese policy makers should consider implementing information campaigns aimed at achieving a better understanding of the features of these quality labels among consumers. For researchers, the study confirms that the BCM method is effective and its integration with network and cluster analysis improves the interpretation of individual and aggregated maps. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular Electronics of Self-Assembled Monolayers

DEFF Research Database (Denmark)

Wang, Xintai

This thesis deals withmolecular electronic investigations on self-assembledmonolayers. The thesis is divided into seven chapters, as outlined below.Chapter 1 is a general introduction of the history of molecular electronics and its current state.Chapter 2 is separated into three parts. Part I...... providesa brief introduction toself-assembledmonolayers(SAMs), includingits structure, formation, and its role in molecular electronic investigations. Part II is an introduction of different molecular functions, which are interesting for designing real devices. Part III is an introduction of a novel carbon...... material: graphene, and how such material can be incorporated intothe field of molecular electronics.Chapter 3 is a brief introduction of important instruments used in this thesis.Chapter 4, 5 and 6 describe the major experimental work in this thesis. Chapter 4 introduces two novel anchoring...

Self-organization of physical fields and spin

International Nuclear Information System (INIS)

Pestov, I.B.

2008-01-01

The subject of the present investigation is the laws of intrinsic self-organization of fundamental physical fields. In the framework of the Theory of Self-Organization the geometrical and physical nature of spin phenomena is uncovered. The key points are spin symmetry (the fundamental realization of the concept of geometrical internal symmetry) and the spinning field (space of defining representation of spin symmetry). It is shown that the essence of spin is the bipolar structure of spin symmetry induced by the gravitational potentials. The bipolar structure provides natural violation of spin symmetry and leads to spinstatics (theory of spinning field outside the time) and spindynamics. The equations of spinstatics and spindynamics are derived. It is shown that Sommerfeld's formula can be derived from the equations of spindynamics and hence the correspondence principle is valid. This means that the Theory of Self-Organization provides the new understanding of spin phenomena

Achromatic elemental mapping beyond the nanoscale in the transmission electron microscope.

Science.gov (United States)

Urban, K W; Mayer, J; Jinschek, J R; Neish, M J; Lugg, N R; Allen, L J

2013-05-03

Newly developed achromatic electron optics allows the use of wide energy windows and makes feasible energy-filtered transmission electron microscopy (EFTEM) at atomic resolution. In this Letter we present EFTEM images formed using electrons that have undergone a silicon L(2,3) core-shell energy loss, exhibiting a resolution in EFTEM of 1.35 Å. This permits elemental mapping beyond the nanoscale provided that quantum mechanical calculations from first principles are done in tandem with the experiment to understand the physical information encoded in the images.

A self-organized internal models architecture for coding sensory-motor schemes

Directory of Open Access Journals (Sweden)

Esaú eEscobar Juárez

2016-04-01

Full Text Available Cognitive robotics research draws inspiration from theories and models on cognition, as conceived by neuroscience or cognitive psychology, to investigate biologically plausible computational models in artificial agents. In this field, the theoretical framework of Grounded Cognition provides epistemological and methodological grounds for the computational modeling of cognition. It has been stressed in the literature that textit{simulation}, textit{prediction}, and textit{multi-modal integration} are key aspects of cognition and that computational architectures capable of putting them into play in a biologically plausible way are a necessity.Research in this direction has brought extensive empirical evidencesuggesting that textit{Internal Models} are suitable mechanisms forsensory-motor integration. However, current Internal Models architectures show several drawbacks, mainly due to the lack of a unified substrate allowing for a true sensory-motor integration space, enabling flexible and scalable ways to model cognition under the embodiment hypothesis constraints.We propose the Self-Organized Internal ModelsArchitecture (SOIMA, a computational cognitive architecture coded by means of a network of self-organized maps, implementing coupled internal models that allow modeling multi-modal sensory-motor schemes. Our approach addresses integrally the issues of current implementations of Internal Models.We discuss the design and features of the architecture, and provide empirical results on a humanoid robot that demonstrate the benefits and potentialities of the SOIMA concept for studying cognition in artificial agents.

Radiation field mapping using a mechanical-electronic detector

Energy Technology Data Exchange (ETDEWEB)

Czayka, M., E-mail: mczayka@kent.ed [College of Technology, Kent State University-Ashtabula 3300 Lake Road West, Ashtabula, OH 44004 (United States); Program on Electron Beam Technology, Kent State University, P.O. Box 1028, Middlefield, OH 44062 (United States); Fisch, M. [Program on Electron Beam Technology, Kent State University, P.O. Box 1028, Middlefield, OH 44062 (United States); College of Technology, Kent State University, P.O. Box 5190, Kent, OH 44242-0001 (United States)

2010-04-15

A method of radiation field mapping of a scanned electron beam using a Faraday-type detector and an electromechanical linear translator is presented. Utilizing this arrangement, fluence and fluence rate measurements can be made at different locations within the radiation field. The Faraday-type detector used in these experiments differs from most as it consists of a hollow stainless steel sphere. Results are presented in two- and three-dimensional views of the radiation field.

Centimetre-scale electron diffusion in photoactive organic heterostructures

Science.gov (United States)

Burlingame, Quinn; Coburn, Caleb; Che, Xiaozhou; Panda, Anurag; Qu, Yue; Forrest, Stephen R.

2018-02-01

The unique properties of organic semiconductors, such as flexibility and lightness, are increasingly important for information displays, lighting and energy generation. But organics suffer from both static and dynamic disorder, and this can lead to variable-range carrier hopping, which results in notoriously poor electrical properties, with low electron and hole mobilities and correspondingly short charge-diffusion lengths of less than a micrometre. Here we demonstrate a photoactive (light-responsive) organic heterostructure comprising a thin fullerene channel sandwiched between an electron-blocking layer and a blended donor:C70 fullerene heterojunction that generates charges by dissociating excitons. Centimetre-scale diffusion of electrons is observed in the fullerene channel, and this can be fitted with a simple electron diffusion model. Our experiments enable the direct measurement of charge diffusivity in organic semiconductors, which is as high as 0.83 ± 0.07 square centimetres per second in a C60 channel at room temperature. The high diffusivity of the fullerene combined with the extraordinarily long charge-recombination time yields diffusion lengths of more than 3.5 centimetres, orders of magnitude larger than expected for an organic system.

Toward Environmentally Robust Organic Electronics: Approaches and Applications.

Science.gov (United States)

Lee, Eun Kwang; Lee, Moo Yeol; Park, Cheol Hee; Lee, Hae Rang; Oh, Joon Hak

2017-11-01

Recent interest in flexible electronics has led to a paradigm shift in consumer electronics, and the emergent development of stretchable and wearable electronics is opening a new spectrum of ubiquitous applications for electronics. Organic electronic materials, such as π-conjugated small molecules and polymers, are highly suitable for use in low-cost wearable electronic devices, and their charge-carrier mobilities have now exceeded that of amorphous silicon. However, their commercialization is minimal, mainly because of weaknesses in terms of operational stability, long-term stability under ambient conditions, and chemical stability related to fabrication processes. Recently, however, many attempts have been made to overcome such instabilities of organic electronic materials. Here, an overview is provided of the strategies developed for environmentally robust organic electronics to overcome the detrimental effects of various critical factors such as oxygen, water, chemicals, heat, and light. Additionally, molecular design approaches to π-conjugated small molecules and polymers that are highly stable under ambient and harsh conditions are explored; such materials will circumvent the need for encapsulation and provide a greater degree of freedom using simple solution-based device-fabrication techniques. Applications that are made possible through these strategies are highlighted. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electronic Structure Approach to Tunable Electronic Properties of Hybrid Organic-Inorganic Perovskites

Science.gov (United States)

Liu, Garnett; Huhn, William; Mitzi, David B.; Kanai, Yosuke; Blum, Volker

We present a study of the electronic structure of layered hybrid organic-inorganic perovskite (HOIP) materials using all-electron density-functional theory. Varying the nature of the organic and inorganic layers should enable systematically fine-tuning the carrier properties of each component. Using the HSE06 hybrid density functional including spin-orbit coupling (SOC), we validate the principle of tuning subsystem-specific parts of the electron band structures and densities of states in CH3NH3PbX3 (X=Cl, Br, I) compared to a modified organic component in layered (C6H5C2H4NH3) 2PbX4 (X=Cl, Br, I) and C20H22S4N2PbX4 (X=Cl, Br, I). We show that tunable shifts of electronic levels indeed arise by varying Cl, Br, I as the inorganic components, and CH3NH3+ , C6H5C2H4NH3+ , C20H22S4N22 + as the organic components. SOC is found to play an important role in splitting the conduction bands of the HOIP compounds investigated here. The frontier orbitals of the halide shift, increasing the gap, when Cl is substituted for Br and I.

Polarization-driven self-organization of silver nanoparticles in 1D and 2D subwavelength gratings for plasmonic photocatalysis

Science.gov (United States)

Baraldi, G.; Bakhti, S.; Liu, Z.; Reynaud, S.; Lefkir, Y.; Vocanson, F.; Destouches, N.

2017-01-01

One of the main challenges in plasmonics is to conceive large-scale, low-cost techniques suitable for the fabrication of metal nanoparticle patterns showing precise spatial organization. Here, we introduce a simple method based on continuous-wave laser illumination to induce the self-organization of silver nanoparticles within high-index thin films. We show that highly regular and homogeneous nanoparticle gratings can be produced on large areas using laser-controlled self-organization processes. This very versatile technique can provide 1D and 2D patterns at a subwavelength scale with tunable features. It does not need any stabilization or expensive devices, such as those required by optical or electron lithography, and is rapid to implement. Accurate in-plane and in-depth characterizations provide valuable information to explain the mechanisms that lead to pattern formation and especially how 2D self-organization can fall into place with successive laser scans. The regular and homogeneous 2D self-organization of metallic NPs with a single laser scan is also reported for the first time in this article. As the reported nanostructures are embedded in porous TiO2, we also theoretically explore the interesting potential of organization on the photocatalytic activity of Ag-NP-containing TiO2 porous films, which is one of the most promising materials for self-cleaning or remediation applications. Realistic electromagnetic simulations demonstrate that the periodic organization of silver nanoparticles can increase the light intensity within the film more than ten times that produced with randomly distributed nanoparticles, leading as expected to enhanced photocatalytic efficiency.

17 CFR 201.420 - Appeal of determinations by self-regulatory organizations.

Science.gov (United States)

2010-04-01

... self-regulatory organizations. 201.420 Section 201.420 Commodity and Securities Exchanges SECURITIES... Review § 201.420 Appeal of determinations by self-regulatory organizations. (a) Application for review... by a self-regulatory organization determination as to which a notice is required to be filed with the...

Organic Chemistry Self Instructional Package 2: Methane.

Science.gov (United States)

Zdravkovich, V.

This booklet, one of a series of 17 developed at Prince George's Community College, Largo, Maryland, provides an individualized, self-paced undergraduate organic chemistry instruction module designed to augment any course in organic chemistry but particularly those taught using the text "Organic Chemistry" by Morrison and Boyd. The…

Organic Chemistry Self Instructional Package 12: Alkynes.

Science.gov (United States)

Zdravkovich, V.

This booklet, one of a series of 17 developed at Prince George's Community College, Largo, Maryland, provides an individualized, self-paced undergraduate organic chemistry instruction module designed to augment any course in organic chemistry but particularly those taught using the text "Organic Chemistry" by Morrison and Boyd. The…

Application of Topic Map on Knowledge Organization

Directory of Open Access Journals (Sweden)

Sou-shan Wu

2003-06-01

Full Text Available Knowledge management (KM has received much attention from both academics and practitioners in the past few years. Following the KM trend, many organizations have built their own knowledge repositories or data warehouses. However, information or knowledge is still scattered everywhere without being properly managed. The rapid growth of the Internet accelerates the creation of unstructured and unclassified information and causes the explosion of information overload. The effort of browsing information through general-purpose search engines turns out to be tedious and painstaking. Hence, an effective technology to solve this information retrieval problem is much needed. The purpose of this research is to explore the application of text mining technique in organizing knowledge stored in unstructured natural language text documents. Major components of text mining techniques required for topic map in particular will be presented in detail.Two sets of unstructured documents are utilized to demonstrate the usage of SOM for topic categorization. The first set of documents is a collection of speeches given by Y.C. Wang, Chairman of the Taiwan Plastics Group, and the other is the collection of all laws and regulations related to securities and future markets in Taiwan. We also try to apply text mining to these two sets of documents to generate their respective topic maps, thus revealing the differences between organizing explicit and tacit knowledge as well as the difficulties associated with tacit knowledge.[Article content in Chinese

Measuring the Complexity of Self-Organizing Traffic Lights

Directory of Open Access Journals (Sweden)

Darío Zubillaga

2014-04-01

Full Text Available We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.

Self-focusing of laser beams in magnetized relativistic electron beams

International Nuclear Information System (INIS)

Whang, M.H.; Ho, A.Y.; Kuo, S.P.

1989-01-01

Recently, there is considerable interest in radiation focusing and optical guiding using the resonant interaction between the radiation field and electron beam. The result of radiation focusing has been shown to play a central role in the practical utilization of the FEL. This result allows the device to use longer interaction length for achieving higher output power. Likewise, the possibility of self-focusing of the laser beam in cyclotron resonance with a relativistic electron beam is also an important issue in the laser acceleration concepts for achieving high-gradient electron acceleration. The effectiveness of the acceleration process relies strongly on whether the laser intensity can be maintained at the desired level throughout the interaction. In this work, the authors study the problem concerning the self-focusing of laser beam in the relativistic electron beams under the cyclotron auto-resonance interaction. They assume that there is no electron density perturbation prohibited from the background magnetic field for the time scale of interest. The nonlinearity responsible for self-focusing process is introduced by the energy dependence of the relativistic mass of electrons. The plasma frequency varies with the electron energy which is proportional to the radiation amplitude. They then examine such a relativistic nonlinear effect on the propagation of a Gaussian beam in the electron beam. A parametric study of the dependence of the laser beam width on the axial position for various electron beam density has been performed

Printed Dielectric Mirrors and their Application in Organic Electronics

OpenAIRE

Bronnbauer, Carina

2017-01-01

Organic electronics are one of the future technologies of these days. It offers many advantages in comparison to heavy metal based inorganic electronics. For example, organic electronics are available in various colors, are often semitransparent, they can be fully solution processed and thus allow printing on top of rigid as well as on flexible substrates. All these characteristics enable a complete new area of applications for electronics. For example, the integration of semitransparent phot...

Self-bunching electron guns

CERN Document Server

Mako, F; Weilhammer, Peter

1999-01-01

We report on three electron gun projects that are aimed at power tube and injector applications. The purpose of the work is to develop robust electron guns which produce self-bunched, high-current-density beams. We have demonstrated cold emission, long life, and tolerance to contamination. The cold emission process is based on secondary electron emission. FMT has studied this resonant bunching process which gives rise to high current densities (0.01-5 kA/cm/sup 2/), high charge bunches (up to 100 nC/bunch), and short pulses (1-100 ps) for frequencies from 1 to 12 GHz. The beam pulse width is nominally ~5% of the RF period. The first project is the L-Band Micro-Pulse Gun (MPG). Measurements show ~40 ps long microbunches at ~20 A/cm/sup 2/ without contamination due to air exposure. Lifetime testing has been carried out for about 18 months operating at 1.25 GHz for almost 24 hours per day at a repetition rate of 300 Hz and 5 mu s-long macro- pulses. About 5.8*10/sup 13/ micro-bunches or 62,000 coulombs have pass...

Order out of Randomness: Self-Organization Processes in Astrophysics

Science.gov (United States)

Aschwanden, Markus J.; Scholkmann, Felix; Béthune, William; Schmutz, Werner; Abramenko, Valentina; Cheung, Mark C. M.; Müller, Daniel; Benz, Arnold; Chernov, Guennadi; Kritsuk, Alexei G.; Scargle, Jeffrey D.; Melatos, Andrew; Wagoner, Robert V.; Trimble, Virginia; Green, William H.

2018-03-01

Self-organization is a property of dissipative nonlinear processes that are governed by a global driving force and a local positive feedback mechanism, which creates regular geometric and/or temporal patterns, and decreases the entropy locally, in contrast to random processes. Here we investigate for the first time a comprehensive number of (17) self-organization processes that operate in planetary physics, solar physics, stellar physics, galactic physics, and cosmology. Self-organizing systems create spontaneous " order out of randomness", during the evolution from an initially disordered system to an ordered quasi-stationary system, mostly by quasi-periodic limit-cycle dynamics, but also by harmonic (mechanical or gyromagnetic) resonances. The global driving force can be due to gravity, electromagnetic forces, mechanical forces (e.g., rotation or differential rotation), thermal pressure, or acceleration of nonthermal particles, while the positive feedback mechanism is often an instability, such as the magneto-rotational (Balbus-Hawley) instability, the convective (Rayleigh-Bénard) instability, turbulence, vortex attraction, magnetic reconnection, plasma condensation, or a loss-cone instability. Physical models of astrophysical self-organization processes require hydrodynamic, magneto-hydrodynamic (MHD), plasma, or N-body simulations. Analytical formulations of self-organizing systems generally involve coupled differential equations with limit-cycle solutions of the Lotka-Volterra or Hopf-bifurcation type.

Tropospheric Ozonesonde Profiles at Long-term U.S. Monitoring Sites: 1. A Climatology Based on Self-Organizing Maps

Science.gov (United States)

Stauffer, Ryan M.; Thompson, Anne M.; Young, George S.

2016-01-01

Sonde-based climatologies of tropospheric ozone (O3) are vital for developing satellite retrieval algorithms and evaluating chemical transport model output. Typical O3 climatologies average measurements by latitude or region, and season. A recent analysis using self-organizing maps (SOM) to cluster ozonesondes from two tropical sites found that clusters of O3 mixing ratio profiles are an excellent way to capture O3variability and link meteorological influences to O3 profiles. Clusters correspond to distinct meteorological conditions, e.g., convection, subsidence, cloud cover, and transported pollution. Here the SOM technique is extended to four long-term U.S. sites (Boulder, CO; Huntsville, AL; Trinidad Head, CA; and Wallops Island, VA) with4530 total profiles. Sensitivity tests on k-means algorithm and SOM justify use of 3 3 SOM (nine clusters). Ateach site, SOM clusters together O3 profiles with similar tropopause height, 500 hPa height temperature, and amount of tropospheric and total column O3. Cluster means are compared to monthly O3 climatologies.For all four sites, near-tropopause O3 is double (over +100 parts per billion by volume; ppbv) the monthly climatological O3 mixing ratio in three clusters that contain 1316 of profiles, mostly in winter and spring.Large midtropospheric deviations from monthly means (6 ppbv, +710 ppbv O3 at 6 km) are found in two of the most populated clusters (combined 3639 of profiles). These two clusters contain distinctly polluted(summer) and clean O3 (fall-winter, high tropopause) profiles, respectively. As for tropical profiles previously analyzed with SOM, O3 averages are often poor representations of U.S. O3 profile statistics.

Lunar remnant magnetic field mapping from orbital observations of mirrored electrons

Energy Technology Data Exchange (ETDEWEB)

McCoy, J E [National Aeronautics and Space Administration, Houston, Tex. (USA). Johnson Space Center; Anderson, K A; Lin, R P; Howe, H C; McGuire, R E [California Univ., Berkeley (USA). Space Sciences Lab.

1975-09-01

Areas of lunar surface magnetic field are observed to ''mirror'' low energy electrons present in the normal lunar space environment. The ambient electrons provide, in effect, a probe along the ambient magnetic field lines down to the lunar surface for remote sensing of the presence of surface fields. Use of the on-board vector magnetometer measurements of the ambient magnetic field orientation allows accurate projection of such mapping onto the lunar surface. Preliminary maps of the lunar surface magnetic areas underlying the orbit of the ''Particles and Fields Satellite deployed from Apollo 16'' have been generated, obtaining 40% coverage from partial data to demonstrate feasibility of the technique. These maps reveal many previously unreported areas of surface magnetism. The method is sensitive to fields of less than 0.1..gamma.. at the surface. The surface field regions observed are generally due to sources smaller than 10-50km in size, although many individual regions are often so close together as to give much larger regions of effectively continuous mirroring. Absence of consistent mirroring by any global field places an upper limit on the size of any net lunar dipole moment of less than 10/sup 10/..gamma..km/sup 3/. Much additional information regarding the magnetic regions can be obtained by correlated analysis of both the electron return and vector magnetometer measurements at orbital altitude, the two techniques providing each other with directly complimentary measurements at the satellite and along the ambient field lines to the surface.

On the genesis of spatio-temporal self-organized structures in plasma devices

International Nuclear Information System (INIS)

Talasman, S.J.; Sanduloviciu, M.

1995-01-01

The genesis of luminous sharply defined nearly spherical space charges structures formed in an Argon plasma column was experimental investigated. The results reveal spatio-temporal characteristics proper to systems resulting after a self-organization process. Their phenomenology involves electrical charges separation produced by symmetry breaking and spatial separation of the excitation and ionization cross sections functions in a region where electrons are accelerated and, as a result, the appearance of electrostatic forces that, acting as long range correlations, assures, together with dissipative effects, its stability. (Author) 8 Figs., 31 Refs

Self-field effects on electron dynamics in free-electron lasers with axial magnetic field

International Nuclear Information System (INIS)

Mirzanejhad, S.; Maraghechi, B.; Mohsenpour, T.

2004-01-01

A self-consistent method for the analysis of self-magnetic field for a free-electron laser with a one-dimensional helical wiggler and an axial guide magnetic field is presented. The equilibrium orbits and their stability, under the influence of self-electric and self-magnetic fields, are analyzed. New unstable orbits, in the first part of the Group I orbits and in the resonance region of the Group II orbits, are found. It is shown that an increase in the defocusing effect of self-fields will widen the unstable orbits. An anomalous self-field regime is found where an increase in the defocusing effect of self-fields can have stabilizing effect on the resonance region

Reciprocal space mapping by spot profile analyzing low energy electron diffraction

International Nuclear Information System (INIS)

Meyer zu Heringdorf, Frank-J.; Horn-von Hoegen, Michael

2005-01-01

We present an experimental approach for the recording of two-dimensional reciprocal space maps using spot profile analyzing low energy electron diffraction (SPA-LEED). A specialized alignment procedure eliminates the shifting of LEED patterns on the screen which is commonly observed upon variation of the electron energy. After the alignment, a set of one-dimensional sections through the diffraction pattern is recorded at different energies. A freely available software tool is used to assemble the sections into a reciprocal space map. The necessary modifications of the Burr-Brown computer interface of the two Leybold and Omicron type SPA-LEED instruments are discussed and step-by-step instructions are given to adapt the SPA 4.1d software to the changed hardware. Au induced faceting of 4 deg. vicinal Si(001) is used as an example to demonstrate the technique

The Effect of College Students' Self-Generated Computerized Mind Mapping on Their Reading Achievement

Science.gov (United States)

Sabbah, Sabah Salman

2015-01-01

This study explored the potential effect of college students' self-generated computerized mind maps on their reading comprehension. It also investigated the subjects' attitudes toward generating computerized mind maps for reading comprehension. The study was conducted in response to the inability of the foundation-level students, who were learning…

Contorted Organic Semiconductors for Molecular Electronics

Science.gov (United States)

Zhong, Yu

This thesis focuses on the synthesis, properties and applications of two types of contorted organic molecules: contorted molecular ribbons and conjugated corrals. We utilized the power of reaction chemistry to writing information into conjugated molecules with contorted structures and studied "structure-property" relationships. The unique properties of the molecules were expressed in electronic and optoelectronic devices such as field-effect transistors, solar cells, photodetectors, etc. In Chapter 2, I describe the design and synthesis of a new graphene ribbon architecture that consists of perylenediimide (PDI) subunits fused together by ethylene bridges. We created a prototype series of oligomers consisting of the dimer, trimer, and tetramer. The steric congestion at the fusion point between the PDI units creates helical junctions, and longer oligomers form helical ribbons. Thin films of these oligomers form the active layer in n-type field effect transistors. UV-vis spectroscopy reveals the emergence of an intense long-wavelength transition in the tetramer. From DFT calculations, we find that the HOMO-2 to LUMO transition is isoenergetic with the HOMO to LUMO transition in the tetramer. We probe these transitions directly using femtosecond transient absorption spectroscopy. The HOMO-2 to LUMO transition electronically connects the PDI subunits with the ethylene bridges, and its energy depends on the length of the oligomer. In Chapter 3, I describe an efficiency of 6.1% for a solution processed non-fullerene solar cell using a helical PDI dimer as the electron acceptor. Femtosecond transient absorption spectroscopy revealed both electron and hole transfer processes at the donor-acceptor interfaces, indicating that charge carriers are created from photogenerated excitons in both the electron donor and acceptor phases. Light-intensity-dependent current?voltage measurements suggested different recombination rates under short-circuit and open-circuit conditions. In

Misfit-guided self-organization of anticorrelated Ge quantum dot arrays on Si nanowires.

Science.gov (United States)

Kwon, Soonshin; Chen, Zack C Y; Kim, Ji-Hun; Xiang, Jie

2012-09-12

Misfit-strain guided growth of periodic quantum dot (QD) arrays in planar thin film epitaxy has been a popular nanostructure fabrication method. Engineering misfit-guided QD growth on a nanoscale substrate such as the small curvature surface of a nanowire represents a new approach to self-organized nanostructure preparation. Perhaps more profoundly, the periodic stress underlying each QD and the resulting modulation of electro-optical properties inside the nanowire backbone promise to provide a new platform for novel mechano-electronic, thermoelectronic, and optoelectronic devices. Herein, we report a first experimental demonstration of self-organized and self-limited growth of coherent, periodic Ge QDs on a one-dimensional Si nanowire substrate. Systematic characterizations reveal several distinctively different modes of Ge QD ordering on the Si nanowire substrate depending on the core diameter. In particular, Ge QD arrays on Si nanowires of around 20 nm diameter predominantly exhibit an anticorrelated pattern whose wavelength agrees with theoretical predictions. The correlated pattern can be attributed to propagation and correlation of misfit strain across the diameter of the thin nanowire substrate. The QD array growth is self-limited as the wavelength of the QDs remains unchanged even after prolonged Ge deposition. Furthermore, we demonstrate a direct kinetic transformation from a uniform Ge shell layer to discrete QD arrays by a postgrowth annealing process.

Reading the maps: Organization and function of chromatin types in Drosophila

NARCIS (Netherlands)

Braunschweig, U.

2010-01-01

The work presented in this thesis shows that the Drosophila genome is organized in chromatin domains with many implications for gene regulation, nuclear organization, and evolution. Furthermore it provides examples of how maps of chromatin protein binding, combined with computational approaches, can

Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

Science.gov (United States)

Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

2010-01-01

Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

Self-organized topology of recurrence-based complex networks

International Nuclear Information System (INIS)

Yang, Hui; Liu, Gang

2013-01-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks

Self-organized critical neural networks

International Nuclear Information System (INIS)

Bornholdt, Stefan; Roehl, Torsten

2003-01-01

A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

Self-organized quantum rings : Physical characterization and theoretical modeling

NARCIS (Netherlands)

Fomin, V.M.; Gladilin, V.N.; Devreese, J.T.; Koenraad, P.M.; Fomin, V.M.

2014-01-01

An adequate modeling of the self-organized quantum rings is possible only on the basis of the modern characterization of those nanostructures.We discuss an atomic-scale analysis of the indium distribution of self-organized InGaAs quantum rings (QRs). The analysis of the shape, size and composition

IDENTIFYING LOCAL SCALE CLIMATE ZONES OF URBAN HEAT ISLAND FROM HJ-1B SATELLITE DATA USING SELF-ORGANIZING MAPS

Directory of Open Access Journals (Sweden)

C. Z. Wei

2016-10-01

Full Text Available With the increasing acceleration of urbanization, the degeneration of the environment and the Urban Heat Island (UHI has attracted more and more attention. Quantitative delineation of UHI has become crucial for a better understanding of the interregional interaction between urbanization processes and the urban environment system. First of all, our study used medium resolution Chinese satellite data-HJ-1B as the Earth Observation data source to derive parameters, including the percentage of Impervious Surface Areas, Land Surface Temperature, Land Surface Albedo, Normalized Differential Vegetation Index, and object edge detector indicators (Mean of Inner Border, Mean of Outer border in the city of Guangzhou, China. Secondly, in order to establish a model to delineate the local climate zones of UHI, we used the Principal Component Analysis to explore the correlations between all these parameters, and estimate their contributions to the principal components of UHI zones. Finally, depending on the results of the PCA, we chose the most suitable parameters to classify the urban climate zones based on a Self-Organization Map (SOM. The results show that all six parameters are closely correlated with each other and have a high percentage of cumulative (95% in the first two principal components. Therefore, the SOM algorithm automatically categorized the city of Guangzhou into five classes of UHI zones using these six spectral, structural and climate parameters as inputs. UHI zones have distinguishable physical characteristics, and could potentially help to provide the basis and decision support for further sustainable urban planning.

Interface Engineering for Organic Electronics; Manufacturing of Hybrid Inorganic-Organic Molecular Crystal Devices

NARCIS (Netherlands)

de Veen, P.J.

2011-01-01

Organic semiconductors are at the basis of Organic Electronics. Objective of this dissertation is “to fabricate high-quality organic molecular single-crystal devices”, to explore the intrinsic properties of organic semiconductors. To achieve this, the in situ fabrication of complete field-effect

Conjugated material self-assembly : towards supramolecular electronics

NARCIS (Netherlands)

Leclère, P.E.L.G.; Surin, M.; Cavallini, M.; Jonkheijm, P.; Henze, O.; Schenning, A.P.H.J.; Biscarini, F.; Grimsdale, A.C.; Feast, W.J.; Meijer, E.W.; Müllen, K.; Brédas, J.L.; Lazzaroni, R.

2004-01-01

Properties of organic electronic materials in solid-state are determined as individual molecules and molecular assembly. It is essential to optimize conjugated materials to control performance of molecular assembly that constitute electronic devices such as light-emitting diodes and solar cells, and

Electron, hole and exciton self-trapping in germanium doped silica glass from DFT calculations with self-interaction correction

International Nuclear Information System (INIS)

Du Jincheng; Rene Corrales, L.; Tsemekhman, Kiril; Bylaska, Eric J.

2007-01-01

Density functional theory (DFT) calculations were employed to understand the refractive index change in germanium doped silica glasses for the trapped states of electronic excitations induced by UV irradiation. Local structure relaxation and excess electron density distribution were calculated upon self-trapping of an excess electron, hole, and exciton in germanium doped silica glass. The results show that both the trapped exciton and excess electron are highly localized on germanium ion and, to some extent, on its oxygen neighbors. Exciton self-trapping is found to lead to the formation of a Ge E' center and a non-bridging hole center. Electron trapping changes the GeO 4 tetrahedron structure into trigonal bi-pyramid with the majority of the excess electron density located along the equatorial line. The self-trapped hole is localized on bridging oxygen ions that are not coordinated to germanium atoms that lead to elongation of the Si-O bonds and change of the Si-O-Si bond angles. We carried out a comparative study of standard DFT versus DFT with a hybrid PBE0 exchange and correlation functional. The results show that the two methods give qualitatively similar relaxed structure and charge distribution for electron and exciton trapping in germanium doped silica glass; however, only the PBE0 functional produces the self-trapped hole

Subwavelength Microstructures Fabrication by Self-Organization Processes in Photopolymerizable Nanocomposite

Directory of Open Access Journals (Sweden)

I. Yu. Denisyuk

2012-01-01

Full Text Available This paper describes our research results on nanometers sizes subwavelength nanostructure fabrication by UV curing of special nanocomposite material with self-organization and light self-focusing effects. For this purpose, special UV curable nanocomposite material with a set of effects was developing: light self-focusing in the photopolymer with positive refractive index change, self-organization based on photo-induced nanoparticles transportation, and oxygen-based polymerization threshold. Both holographic and projection lithography writing methods application for microstructure making shows geometrical optical laws perturbation as result of nanocomposite self-organization effects with formation of nanometers-sized high-aspect-ratio structures. Obtained results will be useful for diffraction limit overcoming in projection lithography as well as for deep lithography technique.

Thought analysis on self-organization theories of MHD plasma

International Nuclear Information System (INIS)

Kondoh, Yoshiomi; Sato, Tetsuya.

1992-08-01

A thought analysis on the self-organization theories of dissipative MHD plasma is presented to lead to three groups of theories that lead to the same relaxed state of ∇ x B = λB, in order to find an essential physical picture embedded in the self-organization phenomena due to nonlinear and dissipative processes. The self-organized relaxed state due to the dissipation by the Ohm loss is shown to be formulated generally as the state such that yields the minimum dissipation rate of global auto-and/or cross-correlations between two quantities in j, B, and A for their own instantaneous values of the global correlations. (author)

Self-organized criticality in fragmenting

DEFF Research Database (Denmark)

Oddershede, L.; Dimon, P.; Bohr, J.

1993-01-01

The measured mass distributions of fragments from 26 fractured objects of gypsum, soap, stearic paraffin, and potato show evidence of obeying scaling laws; this suggests the possibility of self-organized criticality in fragmenting. The probability of finding a fragment scales inversely to a power...

Exploring the magnetic and organic microstructures with photoemission electron microscope

Energy Technology Data Exchange (ETDEWEB)

Wei, D.H., E-mail: dhw@nsrrc.org.tw [National Synchrotron Radiation Research Center, Hsinchu Science Park, 30076 Hsinchu, Taiwan (China); Chan, Yuet-Loy; Hsu, Yao-Jane [National Synchrotron Radiation Research Center, Hsinchu Science Park, 30076 Hsinchu, Taiwan (China)

2012-10-15

Highlights: Black-Right-Pointing-Pointer PEEM with polarized photon enables additional image contrasts and physical insights. Black-Right-Pointing-Pointer XMCD-based images reveal the shape-dependent domains in Ni80Fe20 microstructures. Black-Right-Pointing-Pointer XLD-based images confirm the success of molecular orientation controls. Black-Right-Pointing-Pointer The two interfaces in Co-Pn-Co structures are magnetically and chemically different. -- Abstract: We present photoemission electron microscopy (PEEM) studies on geometrically constrained ferromagnetic, organic, and organics-ferromagnet hybrid structures. Powered by an elliptically polarized undulator, the PEEM at Taiwan Light Source (TLS) is capable of recording polarization enhanced X-ray images and has been employed to examine the domain configurations in a lithographically patterned permalloy film as well as the orientations of pentacene molecules adsorbed on self-assembled monolayers (SAMs) modified gold surfaces. In addition, magnetic images acquired on cobalt/pentacene and pentacene/cobalt bilayers reveal that in hybrid structures the order of thin film deposition can lead to distinct domain configurations. Spectroscopic evidence further suggests that there is significant orbital hybridization at the interface where metallic cobalt was deposited directly on organic pentacene.

A principle of fractal-stochastic dualism and Gompertzian dynamics of growth and self-organization.

Science.gov (United States)

Waliszewski, Przemyslaw

2005-10-01

The emergence of Gompertzian dynamics at the macroscopic, tissue level during growth and self-organization is determined by the existence of fractal-stochastic dualism at the microscopic level of supramolecular, cellular system. On one hand, Gompertzian dynamics results from the complex coupling of at least two antagonistic, stochastic processes at the molecular cellular level. It is shown that the Gompertz function is a probability function, its derivative is a probability density function, and the Gompertzian distribution of probability is of non-Gaussian type. On the other hand, the Gompertz function is a contraction mapping and defines fractal dynamics in time-space; a prerequisite condition for the coupling of processes. Furthermore, the Gompertz function is a solution of the operator differential equation with the Morse-like anharmonic potential. This relationship indicates that distribution of intrasystemic forces is both non-linear and asymmetric. The anharmonic potential is a measure of the intrasystemic interactions. It attains a point of the minimum (U(0), t(0)) along with a change of both complexity and connectivity during growth and self-organization. It can also be modified by certain factors, such as retinoids.

Self-organization in cathode boundary layer discharges in xenon

International Nuclear Information System (INIS)

Takano, Nobuhiko; Schoenbach, Karl H

2006-01-01

Self-organization of direct current xenon microdischarges in cathode boundary layer configuration has been studied for pressures in the range 30-140 Torr and for currents in the range 50 μA-1 mA. Side-on and end-on observations of the discharge have provided information on the structure and spatial arrangement of the plasma filaments. The regularly spaced filaments, which appear in the normal glow mode when the current is lowered, have a length which is determined by the cathode fall. It varies, dependent on pressure and current, between 50 and 70 μm. The minimum diameter is approximately 80 μm, as determined from the radiative emission in the visible. The filaments are sources of extensive excimer emission. Measurements of the cathode fall length have allowed us to determine the secondary emission coefficient for the discharge in the normal glow mode and to estimate the cathode fall voltage at the transition from normal glow mode to filamentary mode. It was found that the cathode fall voltage at this transition decreases, indicating the onset of additional electron gain processes at the cathode. The regular arrangement of the filaments, self-organization, is assumed to be due to Coulomb interactions between the positively charged cathode fall channels and positive space charges on the surface of the surrounding dielectric spacer. Calculations based on these assumptions showed good agreement with experimentally observed filament patterns

Sugar-Based Polyamides: Self-Organization in Strong Polar Organic Solvents.

Science.gov (United States)

Rosu, Cornelia; Russo, Paul S; Daly, William H; Cueto, Rafael; Pople, John A; Laine, Roger A; Negulescu, Ioan I

2015-09-14

Periodic patterns resembling spirals were observed to form spontaneously upon unassisted cooling of d-glucaric acid- and d-galactaric acid-based polyamide solutions in N-methyl-N-morpholine oxide (NMMO) monohydrate. Similar observations were made in d-galactaric acid-based polyamide/ionic liquid (IL) solutions. The morphologies were investigated by optical, polarized light and confocal microscopy assays to reveal pattern details. Differential scanning calorimetry was used to monitor solution thermal behavior. Small- and wide-angle X-ray scattering data reflected the complex and heterogeneous nature of the self-organized patterns. Factors such as concentration and temperature were found to influence spiral dimensions and geometry. The distance between rings followed a first-order exponential decay as a function of polymer concentration. Fourier-Transform Infrared Microspectroscopy analysis of spirals pointed to H-bonding between the solvent and the pendant hydroxyl groups of the glucose units from the polymer backbone. Tests on self-organization into spirals of ketal-protected d-galactaric acid polyamides in NMMO monohydrate confirmed the importance of the monosaccharide's pendant free hydroxyl groups on the formation of these patterns. Rheology performed on d-galactaric-based polyamides at high concentration in NMMO monohydrate solution revealed the optimum conditions necessary to process these materials as fibers by spinning. The self-organization of these sugar-based polyamides mimics certain biological materials.

Enabling Self-Organization in Embedded Systems with Reconfigurable Hardware

Directory of Open Access Journals (Sweden)

Christophe Bobda

2009-01-01

Full Text Available We present a methodology based on self-organization to manage resources in networked embedded systems based on reconfigurable hardware. Two points are detailed in this paper, the monitoring system used to analyse the system and the Local Marketplaces Global Symbiosis (LMGS concept defined for self-organization of dynamically reconfigurable nodes.

Nonadiabatic dynamics of electron injection into organic molecules

International Nuclear Information System (INIS)