Modeling study on the flow patterns of gas-liquid flow for fast decarburization during the RH process

Science.gov (United States)

Li, Yi-hong; Bao, Yan-ping; Wang, Rui; Ma, Li-feng; Liu, Jian-sheng

2018-02-01

A water model and a high-speed video camera were utilized in the 300-t RH equipment to study the effect of steel flow patterns in a vacuum chamber on fast decarburization and a superior flow-pattern map was obtained during the practical RH process. There are three flow patterns with different bubbling characteristics and steel surface states in the vacuum chamber: boiling pattern (BP), transition pattern (TP), and wave pattern (WP). The effect of the liquid-steel level and the residence time of the steel in the chamber on flow patterns and decarburization reaction were investigated, respectively. The liquid-steel level significantly affected the flow-pattern transition from BP to WP, and the residence time and reaction area were crucial to evaluate the whole decarburization process rather than the circulation flow rate and mixing time. A superior flow-pattern map during the practical RH process showed that the steel flow pattern changed from BP to TP quickly, and then remained as TP until the end of decarburization.

Identification of 3-phase flow patterns of heavy oil from pressure drop and flow rate data

Energy Technology Data Exchange (ETDEWEB)

Pacheco, F.; Bannwart, A.C.; Mendes, J.R.P. [Campinas State Univ., Sao Paulo (Brazil); Serapiao, A.B.S. [Sao Paulo State Univ., Sao Paulo (Brazil)

2008-07-01

Pipe flow of oil-gas-water mixtures poses a complex thermo-fluid dynamical problem. This paper examined the relationship between phase flow rates, flow pattern identification, and pressure drop in 3-phase water-assisted heavy oil in the presence of a gaseous phase. An artificial intelligence program called a support vector machine (SVM) was used to determine relevant parameters for flow pattern classification. Data from a 3-phase flow of heavy oil with gas and water in a vertical pipe was used in the study. The data were used to train the machine, which then predicted the flow pattern of the remaining data. Tests with different parameters and training data were then performed. The study showed that the proposed SVM flow pattern identification process accurately predicted flow patterns. It was concluded that the SVM took a relatively short amount of time to train. Future research is needed to apply the tool to larger flow datasets. 5 refs., 1 tab., 2 figs.

The Case of Flow and Learning Revisited

Science.gov (United States)

Ro, Young K.; Guo, Yi Maggie; Klein, Barbara D.

2018-01-01

Many business schools are criticized for being ineffective in helping students learn proper management skills and knowledge. Flow theory has been cited as being helpful in many learning environments in that flow experience can enhance student learning. The authors conducted a study of 315 students in an undergraduate operations management (OM)…

Two-phase flow patterns in adiabatic and diabatic corrugated plate gaps

Science.gov (United States)

Polzin, A.-E.; Kabelac, S.; de Vries, B.

2016-09-01

Correlations for two-phase heat transfer and pressure drop can be improved considerably, when they are adapted to specific flow patterns. As plate heat exchangers find increasing application as evaporators and condensers, there is a need for flow pattern maps for corrugated plate gaps. This contribution presents experimental results on flow pattern investigations for such a plate heat exchanger background, using an adiabatic visualisation setup as well as a diabatic setup. Three characteristic flow patterns were observed in the considered range of two-phase flow: bubbly flow, film flow and slug flow. The occurrence of these flow patterns is a function of mass flux, void fraction, fluid properties and plate geometry. Two different plate geometries having a corrugation angle of 27° and 63°, respectively and two different fluids (water/air and R365mfc liquid/vapor) have been analysed. A flow pattern map using the momentum flux is presented.

Multiagent-Based Simulation of Temporal-Spatial Characteristics of Activity-Travel Patterns Using Interactive Reinforcement Learning

Directory of Open Access Journals (Sweden)

Min Yang

2014-01-01

Full Text Available We propose a multiagent-based reinforcement learning algorithm, in which the interactions between travelers and the environment are considered to simulate temporal-spatial characteristics of activity-travel patterns in a city. Road congestion degree is added to the reinforcement learning algorithm as a medium that passes the influence of one traveler’s decision to others. Meanwhile, the agents used in the algorithm are initialized from typical activity patterns extracted from the travel survey diary data of Shangyu city in China. In the simulation, both macroscopic activity-travel characteristics such as traffic flow spatial-temporal distribution and microscopic characteristics such as activity-travel schedules of each agent are obtained. Comparing the simulation results with the survey data, we find that deviation of the peak-hour traffic flow is less than 5%, while the correlation of the simulated versus survey location choice distribution is over 0.9.

Deep Learning For Sequential Pattern Recognition

OpenAIRE

Safari, Pooyan

2013-01-01

Projecte realitzat en el marc d’un programa de mobilitat amb la Technische Universität München (TUM) In recent years, deep learning has opened a new research line in pattern recognition tasks. It has been hypothesized that this kind of learning would capture more abstract patterns concealed in data. It is motivated by the new findings both in biological aspects of the brain and hardware developments which have made the parallel processing possible. Deep learning methods come along with ...

Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

Science.gov (United States)

2008-09-01

Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.

Science.gov (United States)

Gao, Zhongke; Jin, Ningde

2009-06-01

The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.

A system for learning statistical motion patterns.

Science.gov (United States)

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

A Model for Predicting Learning Flow and Achievement in Corporate e-Learning

Science.gov (United States)

Joo, Young Ju; Lim, Kyu Yon; Kim, Su Mi

2012-01-01

The primary objective of this study was to investigate the determinants of learning flow and achievement in corporate online training. Self-efficacy, intrinsic value, and test anxiety were selected as learners' motivational factors, while perceived usefulness and ease of use were also selected as learning environmental factors. Learning flow was…

Doctoral Student Learning Patterns: Learning about Active Knowledge Creation or Passive Production

Science.gov (United States)

Vekkaila, Jenna; Pyhältö, Kirsi

2016-01-01

Doctoral studies are about learning to create new knowledge and to become a researcher. Yet surprisingly little is known about the individual learning patterns of doctoral students. The study aims to explore learning patterns among natural science doctoral students. The participants included 19 doctoral students from a top-level natural science…

Learning from correlated patterns by simple perceptrons

Energy Technology Data Exchange (ETDEWEB)

Shinzato, Takashi; Kabashima, Yoshiyuki [Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502 (Japan)], E-mail: shinzato@sp.dis.titech.ac.jp, E-mail: kaba@dis.titech.ac.jp

2009-01-09

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Learning from correlated patterns by simple perceptrons

Science.gov (United States)

Shinzato, Takashi; Kabashima, Yoshiyuki

2009-01-01

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Learning from correlated patterns by simple perceptrons

International Nuclear Information System (INIS)

Shinzato, Takashi; Kabashima, Yoshiyuki

2009-01-01

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance

Eliciting design patterns for e-learning systems

Science.gov (United States)

Retalis, Symeon; Georgiakakis, Petros; Dimitriadis, Yannis

2006-06-01

Design pattern creation, especially in the e-learning domain, is a highly complex process that has not been sufficiently studied and formalized. In this paper, we propose a systematic pattern development cycle, whose most important aspects focus on reverse engineering of existing systems in order to elicit features that are cross-validated through the use of appropriate, authentic scenarios. However, an iterative pattern process is proposed that takes advantage of multiple data sources, thus emphasizing a holistic view of the teaching learning processes. The proposed schema of pattern mining has been extensively validated for Asynchronous Network Supported Collaborative Learning (ANSCL) systems, as well as for other types of tools in a variety of scenarios, with promising results.

Deep learning of unsteady laminar flow over a cylinder

Science.gov (United States)

Lee, Sangseung; You, Donghyun

2017-11-01

Unsteady flow over a circular cylinder is reconstructed using deep learning with a particular emphasis on elucidating the potential of learning the solution of the Navier-Stokes equations. A deep neural network (DNN) is employed for deep learning, while numerical simulations are conducted to produce training database. Instantaneous and mean flow fields which are reconstructed by deep learning are compared with the simulation results. Fourier transform of flow variables has been conducted to validate the ability of DNN to capture both amplitudes and frequencies of flow motions. Basis decomposition of learned flow is performed to understand the underlying mechanisms of learning flow through DNN. The present study suggests that a deep learning technique can be utilized for reconstruction and, potentially, for prediction of fluid flow instead of solving the Navier-Stokes equations. This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(Ministry of Science, ICT and Future Planning) (No. 2014R1A2A1A11049599, No. 2015R1A2A1A15056086, No. 2016R1E1A2A01939553).

Multiple flow patterns and heat transfer in confined jet impingement

International Nuclear Information System (INIS)

Li Xianchang; Gaddis, J. Leo; Wang Ting

2005-01-01

The flow field of a 2-D laminar confined impinging slot jet is investigated. Numerical results indicate that there exist two different solutions in some range of geometric and flow parameters. The two steady flow patterns are obtained under identical boundary conditions but only with different initial flow fields. Two different exit boundary conditions are investigated with two commercial software packages to eliminate artificial or computational effects. The different flow patterns are observed to significantly affect the heat transfer. A flow visualization experiment is carried out to verify the computational results and both flow patterns are observed. The bifurcation mechanism is interpreted and discussed

Catalog Learning: Carabid Beetles Learn to Manipulate with Innate Coherent Behavioral Patterns

Directory of Open Access Journals (Sweden)

Zhanna Reznikova

2013-07-01

Full Text Available One of the most fascinating problems in comparative psychology is how learning contributes to solving specific functional problems in animal life, and which forms of learning our species shares with non-human animals. Simulating a natural situation of territorial conflicts between predatory carabids and red wood ants in field and laboratory experiments, we have revealed a relatively simple and quite natural form of learning that has been overlooked. We call it catalog learning, the name we give to the ability of animals to establish associations between stimuli and coherent behavioral patterns (patterns consist of elementary motor acts that have a fixed order. Instead of budgeting their motor acts gradually, from chaotic to rational sequences in order to learn something new, which is characteristic for a conditioning response, animals seem to be “cataloguing” their repertoire of innate coherent behavioral patterns in order to optimize their response to a certain repetitive event. This form of learning can be described as “stimulus-pattern” learning. In our experiments four “wild” carabid species, whose cognitive abilities have never been studied before, modified their behavior in a rather natural manner in order to avoid damage from aggressive ants. Beetles learned to select the relevant coherent behavioral patterns from the set of seven patterns, which are common to all four species and apparently innate. We suggest that this form of learning differs from the known forms of associative learning, and speculate that it is quite universal and can be present in a wide variety of species, both invertebrate and vertebrate. This study suggests a new link between the concepts of cognition and innateness.

Investigation on flow patterns and transition characteristics in a tube-bundle channel

International Nuclear Information System (INIS)

Xiang Wenyuan; Lu Yonghong; Zhao Guisheng

2012-01-01

Tube-bundle channels have been widely used in condenser-evaporator and other industrial heat-exchange equipment. The characteristics of two-phase flow patterns and their transitions for refrigerant R-113 through a vertical tube-bundle channel are experimentally investigated using high-speed camera. Experiments show that there are four main flow patterns in the tube-bundle channel, which are bubbly flow, bubbly-churn flow, churn flow and annular flow. And in the same cross-section of tube- bundle channels, it is shown that there might be different flow patterns in different sub-channels. The flow pattern transitions exhibit unsynchronized in different sub-channels. On the basis of experimental research, the flow pattern map is drawn and analyses are made on the comparison of differences between boiling flow patterns in a circular tube and those in a tube-bundle channel. (authors)

Experimental investigation on flow patterns of gas-liquid two-phase upward flow through packed channel with spheres

International Nuclear Information System (INIS)

Zhang Nan; Sun Zhongning; Zhao Zhongnan

2011-01-01

Experiments of visualized two-phase upward flow were conducted in the packed channel, which filled with 3, 5, 8 mm in diameter of glass sphere respectively. The gas superficial velocity ranges from 0.005 to 1.172 m/s. The liquid superficial velocity ranges from 0.004 to 0.093 m/s. Four representative flow patterns were observed as bubbly flow, cluster flow, liquid-pulse flow and churn-pulse flow, and corresponding flow pattern maps were also presented. It is found that the pulse flow region is dominant. The comparisons of flow pattern map between packed channel and non-packed channel show that the bubbly flow region in packed channel is narrower than that of non-packed channel due to the packing. The comparisons of flow pattern maps for three different packing sizes show that the cluster flow region expands with the increase of the packing diameter. In the low liquid superficial velocity, the cluster flow directly changes to churn-pulse flow in the packed channel with 8 mm packing. (authors)

Streamline topology: Patterns in fluid flows and their bifurcations

DEFF Research Database (Denmark)

Brøns, Morten

2007-01-01

Using dynamical systems theory, we consider structures such as vortices and separation in the streamline patterns of fluid flows. Bifurcation of patterns under variation of external parameters is studied using simplifying normal form transformations. Flows away from boundaries, flows close to fix...... walls, and axisymmetric flows are analyzed in detail. We show how to apply the ideas from the theory to analyze numerical simulations of the vortex breakdown in a closed cylindrical container....

PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

Science.gov (United States)

Lutich, Andrey

2017-07-01

This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

Two-phase flow patterns in a four by four rod bundle

International Nuclear Information System (INIS)

Mizutani, Yoshitaka; Tomiyama, Akio; Hosokawa, Shigeo; Sou, Akira; Kudo, Yoshiro; Mishima, Kaichiro

2007-01-01

Air-water two-phase flow patterns in a four by four square lattice rod bundle consisting of an acrylic channel box of 68 mm in width and transparent rods of 12mm in diameter were observed by utilizing a high speed video camera, FEP (fluorinated ethylene propylene) tubes for rods, and a fiberscope inserted in a rod. The FEP possesses the same refractive index as water, and thereby, whole flow patterns in the bundle and local flow patterns in subchannels were successfully visualized with little optical distortion. The ranges of gas and liquid volume fluxes, (J G ) and (J L ), in the present experiments were 0.1 L ) G ) G )-(J L ) flow pattern diagram is so narrow that it can be regarded as a boundary between bubbly and churn flows. (2) the boundary between bubbly and churn flows is close to the boundary between bubbly and slug flows of the Mishima and Ishii's flow pattern transition model, and (3) the boundary between churn and annular flow is close to the Mishima and Ishii's model. (author)

Two-Phase Flow Patterns in a Four by Four Rod Bundle

International Nuclear Information System (INIS)

Yoshitaka Mizutani; Shigeo Hosokawa; Akio Tomiyama

2006-01-01

Air-water two-phase flow patterns in a four by four square lattice rod bundle consisting of an acrylic channel box of 68 mm in width and transparent rods of 12 mm in diameter were observed by utilizing a high speed video camera, FEP (fluorinated ethylene propylene) tubes for rods, and a fiber-scope inserted in a rod. The FEP possesses the same refractive index as water, and thereby, whole flow patterns in the bundle and local flow patterns in subchannels were successfully visualized with little optical distortion. The ranges of liquid and gas volume fluxes, G > and L >, in the present experiments were 0.1 L > G > G > - L > flow pattern diagram is so narrow that it can be regarded as a boundary between bubbly and churn flows, (2) the boundary between bubbly and churn flows is close to the boundary between bubbly and slug flows of the Mishima and Ishii's flow pattern transition model, and (3) the boundary between churn and annular flows is well predicted by the Mishima and Ishii's model. (authors)

experimental investigation of flow pattern around repelling

African Journals Online (AJOL)

A. Mahdieh NajafAbadi and M. M. Bateni

2017-09-01

Sep 1, 2017 ... FLOW-3D® software used to simulate flow pattern. The simulation was .... separated into separation zone, shear layer, vortices zone, end point of vorticity zone and primary flow zone. In the figure, b1 and b2 denote ... closer to the wall for the attractive spur dike. For case of the repelling spur dike, transverse.

Flow patterns in a cylindrical porous enclosure

International Nuclear Information System (INIS)

Sezai, I.

2005-01-01

Natural convection in a 3-D vertical cylinder containing an isotropic porous media is studied numerically using the Brinkman and Forcheimer's extensions to the Darcy law. The cylinder is heated from below and cooled from top while the vertical wall is insulated. The formation of multiple flow patterns are investigated by varying the Rayleigh number. Altogether, six different steady flow patterns are found exhibiting different symmetries. The results are presented in terms of projection of streamlines and Nusselt number distributions on the heated plate. (authors)

Flow patterns in a cylindrical porous enclosure

Energy Technology Data Exchange (ETDEWEB)

Sezai, I. [Eastern Mediterranean Univ., Dept. Mechanical Engineering(Turkey)

2005-07-01

Natural convection in a 3-D vertical cylinder containing an isotropic porous media is studied numerically using the Brinkman and Forcheimer's extensions to the Darcy law. The cylinder is heated from below and cooled from top while the vertical wall is insulated. The formation of multiple flow patterns are investigated by varying the Rayleigh number. Altogether, six different steady flow patterns are found exhibiting different symmetries. The results are presented in terms of projection of streamlines and Nusselt number distributions on the heated plate. (authors)

Altered doppler flow patterns in cirrhosis patients: An overview

Energy Technology Data Exchange (ETDEWEB)

Iranpour, Pooya; Lall, Chandana; Houshyar, Roozbeh; Helmy, Mohammad; Yang, Albert; Ward, Garrett; Goodwin, Scott C. [Dept. of Radiology, University of California Irvine, Orange (United States); Choi, Joon Il [Dept. of Radiology, Seoul St. Mary' s Hospital, College of Medicine, The Catholic University of Korea, Seoul (Korea, Republic of)

2016-01-15

Doppler ultrasonography of the hepatic vasculature is an integral part of evaluating precirrhotic and cirrhotic patients. While the reversal of the portal venous flow is a well-recognized phenomenon, other flow patterns, although not as easily understood, may play an important role in assessing the disease status. This article discusses the different characteristic flow patterns observed from the portal vein, hepatic artery, and hepatic vein in patients with liver cirrhosis or related complications and procedures. Knowledge of these different flow patterns provides additional information that may reinforce the diagnosis of cirrhosis, help in staging, and offer prognostic information for determining the direction of therapy. Doppler ultrasonography is invaluable when liver transplantation is being considered and aids in the diagnosis of cirrhosis and portal hypertension.

A Flow of Entrepreneurial Learning Elements in Experiential Learning Settings

DEFF Research Database (Denmark)

Ramsgaard, Michael Breum; Christensen, Marie Ernst

This paper explored the concept of learning in an experiential learning setting and whether the learning process can be understood as a flow of learning factors influencing the outcome. If many constituting factors lead to the development of learning outcomes, there might need to be developed...... that are a part of experiential learning settings and curriculum development....... a differentiated approach to facilitate experiential learning. Subsequently the paper investigated how facilitators of learning processes can design a learning space where the boundary of what is expected from the learner is challenged. In other words the aim was to explore the transformative learning processes...

Churn-annular flow pattern transition in a vertical upward gas-liquid two-phase flow in various conduits

International Nuclear Information System (INIS)

Takenaka, Nobuyuki; Ueda, Tadanobu; Asano, Hitoshi

2008-01-01

Void fraction was measured by neutron radiography for a vertical upward gas-water two-phase flow in a concentric annular tube with and with out a spacer, 4x4 rod bundle with and without a spacer and a tight rod bundle with and without a wrapping wire for various gas and liquid flow rates. The flow patterns of these two-phase flows were determined by the Mishima-Ishii flow pattern map and void fraction was calculated by the Ishii's drift flux model. The predicted values were compared with the experimental results. The void fraction was well predicted by the Mishima-Ishii flow pattern map and the Ishii's drift flux model except the annular flow region with void fraction lower than 0.8 for conduits with small equivalent diameter. A new churn-annular flow pattern transition condition of the void fraction equal to 0.8 was added. The void fraction for the present experimental condition was successful predicted with the new transition model. (author)

Relationship between thermal stratification and flow patterns in steam-quenching suppression pool

International Nuclear Information System (INIS)

Song, Daehun; Erkan, Nejdet; Jo, Byeongnam; Okamoto, Koji

2015-01-01

Highlights: • Thermal stratification mechanism by direct contact condensation is investigated. • Thermal stratification condition changes according to the flow pattern. • Thermal stratification depends on the force balance between buoyancy and momentum. • Flow pattern change was observed even in the same regime. • Flow pattern is affected by the sensitive force balance. - Abstract: This study aims to examine the relationship between thermal stratification and flow patterns in a steam-quenching suppression pool using particle image velocimetry. Thermal stratification was experimentally evaluated in a depressurized water pool under different steam mass flux conditions. The time evolution of the temperature profile of the suppression pool was presented with the variation of condensation regimes, and steam condensation processes were visualized using a high-speed camera. The thermal stratification condition was classified into full mixing, gradual thermal stratification, and developed thermal stratification. It was found that the condition was determined by the flow patterns depending on the force balance between buoyancy and momentum. The force balance affected both the condensation regime and the flow pattern, and hence, the flow pattern was changed with the condensation regime. However, the force balance had a sensitive influence on the flow in the pool; therefore, distinct flow patterns were observed even in the same condensation regime.

Effect of friction on pebble flow pattern in pebble bed reactor

International Nuclear Information System (INIS)

Li, Yu; Gui, Nan; Yang, Xingtuan; Tu, Jiyuan; Jiang, Shengyao

2016-01-01

Highlights: • A 3D DEM study on particle–wall/particle friction in pebble bed reactor is carried out. • Characteristic values are defined to evaluate features of pebble flow pattern quantitatively. • Particle–wall friction is dominant to determine flow pattern in a specific pebble bed. • Friction effect of hopper part on flow field is more critical than that of cylinder part. • Three cases of 1:1 full scale practical pebble beds are simulated for demonstration. - Abstract: Friction affects pebble flow pattern in pebble-bed high temperature gas-cooled reactor (HTGR) significantly. Through a series of three dimensional DEM (discrete element method) simulations it is shown that reducing friction can be beneficial and create a uniform and consistent flow field required by nuclear engineering. Particle–wall friction poses a decisive impact on flow pattern, and particle–particle friction usually plays a secondary role; relation between particle–wall friction and flow pattern transition is also concluded. Moreover, new criteria are created to describe flow patterns quantitatively according to crucial issues in HTGR like stagnant zone, radial uniformity and flow sequence. Last but not least, it is proved that friction control of hopper part is more important than that of cylinder part in practical pebble beds, so reducing friction between pebbles and hopper surface is the engineering priority.

Flow Driven by an Archimedean Helical Permanent Magnetic Field. Part I: Flow Patterns and Their Transitions

Science.gov (United States)

Wang, Bo; Wang, Xiaodong; Etay, Jacqueline; Na, Xianzhao; Zhang, Xinde; Fautrelle, Yves

2016-04-01

In this study, an Archimedean helical permanent magnetic field was constructed and its driving effects on liquid metal were examined. A magnetic stirrer was constructed using a series of arc-like magnets. The helical distribution of its magnetic field, which was confirmed via Gauss probe measurements and numerical simulations, can be considered a combination of rotating and traveling magnetic fields. The characteristics of the flow patterns, particularly the transitions between the meridian secondary flow (two vortices) and the global axial flow (one vortex), driven by this magnetic field were quantitatively measured using ultrasonic Doppler velocimetry. The transient and modulated flow behaviors will be presented in a companion article. The D/ H dimension ratio was used to characterize the transitions of these two flow patterns. The results demonstrated that the flow patterns depend on not only the intrinsic structure of the magnetic field, e.g., the helix lead angle, but also the performance parameters, e.g., the dimensional ratio of the liquid bulk. The notable opposing roles of these two flow patterns in the improvement of macrosegregations when imposing such magnetic fields near the solidifying front were qualitatively addressed.

Flow Pattern Identification of Horizontal Two-Phase Refrigerant Flow Using Neural Networks

Science.gov (United States)

2015-12-31

classification of liquid–vapor structures into flow patterns is useful for predicting heat transfer rates and, ultimately, system performance. Most flow and...Here, ~x represents the spa- tial variables, x and y, and t is time. This normalization assigns εð~x; tÞ to be zero for only vapor (εg) and one for...tube surface [17,22]. As in stratified wavy flow, interfacial waves were also present in stratified wavy transitional flow. The waves were more fre

A novel drag force coefficient model for gas–water two-phase flows under different flow patterns

Energy Technology Data Exchange (ETDEWEB)

Shang, Zhi, E-mail: shangzhi@tsinghua.org.cn

2015-07-15

Graphical abstract: - Highlights: • A novel drag force coefficient model was established. • This model realized to cover different flow patterns for CFD. • Numerical simulations were performed under wide range flow regimes. • Validations were carried out through comparisons to experiments. - Abstract: A novel drag force coefficient model has been developed to study gas–water two-phase flows. In this drag force coefficient model, the terminal velocities were calculated through the revised drift flux model. The revised drift flux is different from the traditional drift flux model because the natural curve movement of the bubble was revised through considering the centrifugal force. Owing to the revisions, the revised drift flux model was to extend to 3D. Therefore it is suitable for CFD applications. In the revised drift flux model, the different flow patterns of the gas–water two-phase flows were able to be considered. This model innovatively realizes the drag force being able to cover different flow patterns of gas–water two-phase flows on bubbly flow, slug flow, churn flow, annular flow and mist flow. Through the comparisons of the numerical simulations to the experiments in vertical upward and downward pipe flows, this model was validated.

Pattern-Induced Covert Category Learning in Songbirds.

Science.gov (United States)

Comins, Jordan A; Gentner, Timothy Q

2015-07-20

Language is uniquely human, but its acquisition may involve cognitive capacities shared with other species. During development, language experience alters speech sound (phoneme) categorization. Newborn infants distinguish the phonemes in all languages but by 10 months show adult-like greater sensitivity to native language phonemic contrasts than non-native contrasts. Distributional theories account for phonetic learning by positing that infants infer category boundaries from modal distributions of speech sounds along acoustic continua. For example, tokens of the sounds /b/ and /p/ cluster around different mean voice onset times. To disambiguate overlapping distributions, contextual theories propose that phonetic category learning is informed by higher-level patterns (e.g., words) in which phonemes normally occur. For example, the vowel sounds /Ι/ and /e/ can occupy similar perceptual spaces but can be distinguished in the context of "with" and "well." Both distributional and contextual cues appear to function in speech acquisition. Non-human species also benefit from distributional cues for category learning, but whether category learning benefits from contextual information in non-human animals is unknown. The use of higher-level patterns to guide lower-level category learning may reflect uniquely human capacities tied to language acquisition or more general learning abilities reflecting shared neurobiological mechanisms. Using songbirds, European starlings, we show that higher-level pattern learning covertly enhances categorization of the natural communication sounds. This observation mirrors the support for contextual theories of phonemic category learning in humans and demonstrates a general form of learning not unique to humans or language. Copyright © 2015 Elsevier Ltd. All rights reserved.

TensorFlow Agents: Efficient Batched Reinforcement Learning in TensorFlow

OpenAIRE

Hafner, Danijar; Davidson, James; Vanhoucke, Vincent

2017-01-01

We introduce TensorFlow Agents, an efficient infrastructure paradigm for building parallel reinforcement learning algorithms in TensorFlow. We simulate multiple environments in parallel, and group them to perform the neural network computation on a batch rather than individual observations. This allows the TensorFlow execution engine to parallelize computation, without the need for manual synchronization. Environments are stepped in separate Python processes to progress them in parallel witho...

Analysis of blood flow patterns in aortic aneurysm by cine magnetic resonance imaging

International Nuclear Information System (INIS)

Matsuoka, Hiroshi

1993-01-01

Cine MRI (0.5 T) using rephased gradient echo technique was performed to study the patterns of blood flow in the aortic aneurysm of 16 patients with aortic aneurysm, and the data were compared with those of 5 healthy volunteers. In the transaxial section, the blood flow in normal aorta appeared as homogeneous high intensity during systole. On the other hand, the blood flow in the aneurysm appeared as inhomogeneous flow enhancement with flow void. In the sagittal scan, the homogeneous flow enhancement in a normal aorta was also observed during systole and its apex of flow enhancement was 'taper'. The blood flow patterns in the aneurysm were classified as 'irregular', 'zonal', 'eddy', and 'obscure' depending on the contrast of flow enhancement and flow void. Their apexes were 'taper' or 'round'. The blood flow patterns in the aneurysm were related to the size of aneurysm. In patients with a large size 'aneurysm, their flow patterns were 'eddy' or 'obscure' and the flow enhancement was 'round'. On the other hand, in patients with a small size aneurysm, their flow patterns were 'irregular' or 'zonal', and their flow enhancement was 'taper'. Though the exact mechanism of abnormal flow patterns in an aortic aneurysm remains to be determined, cine MRI gives helpful informations in assessing blood flow dynamics in the aneurysm. (author)

An experimental study on two-phase flow pattern in low pressure natural circulation system

International Nuclear Information System (INIS)

Wu Shaorong; Han Bing; Zhou Lei; Zhang Youjie; Jiang Shengyao; Wu Xinxin

1991-10-01

An experimental study on two-phase flow pattern in the riser of low pressure natural circulation system was performed. The local differential pressure signal was analysed for flow pattern. It is considered that Sr f·d/v can be used to distinguish different flow patterns and it has clear and definite physical meaning. Flow patterns at different inlet temperature with different system pressures (1.5 MPa, 0.24 MPa and 0.1 MPa) are described. It is considered that the flow pattern is only bubble flow without flow pattern change during the period of low quality density-wave instability at 1.5 MPa. There is no density-wave oscillation in the system, when flow pattern is in bubble-intermittent transition area. The effect of flash vaporization on stability at low pressure is discussed

Modeling on bubbly to churn flow pattern transition for vertical upward flows in narrow rectangular channel

International Nuclear Information System (INIS)

Wang Yanlin; Chen Bingde; Huang Yanping; Wang Junfeng

2011-01-01

A theoretical model was developed to predict the bubbly to churn flow pattern transition for vertical upward flows in narrow rectangular channel. The model was developed based on the imbalance theory of Helmholtz and some reasonable assumptions. The maximum ideal bubble in narrow rectangular channel and the thermal hydraulics boundary condition leading to bubbly flow to churn flow pattern transition was calculated. The model was validated by experimental data from previous researches. Comparison between predicted result and experimental result shows a reasonable good agreement. (author)

Blood flow patterns underlie developmental heart defects.

Science.gov (United States)

Midgett, Madeline; Thornburg, Kent; Rugonyi, Sandra

2017-03-01

Although cardiac malformations at birth are typically associated with genetic anomalies, blood flow dynamics also play a crucial role in heart formation. However, the relationship between blood flow patterns in the early embryo and later cardiovascular malformation has not been determined. We used the chicken embryo model to quantify the extent to which anomalous blood flow patterns predict cardiac defects that resemble those in humans and found that restricting either the inflow to the heart or the outflow led to reproducible abnormalities with a dose-response type relationship between blood flow stimuli and the expression of cardiac phenotypes. Constricting the outflow tract by 10-35% led predominantly to ventricular septal defects, whereas constricting by 35-60% most often led to double outlet right ventricle. Ligation of the vitelline vein caused mostly pharyngeal arch artery malformations. We show that both cardiac inflow reduction and graded outflow constriction strongly influence the development of specific and persistent abnormal cardiac structure and function. Moreover, the hemodynamic-associated cardiac defects recapitulate those caused by genetic disorders. Thus our data demonstrate the importance of investigating embryonic blood flow conditions to understand the root causes of congenital heart disease as a prerequisite to future prevention and treatment. NEW & NOTEWORTHY Congenital heart defects result from genetic anomalies, teratogen exposure, and altered blood flow during embryonic development. We show here a novel "dose-response" type relationship between the level of blood flow alteration and manifestation of specific cardiac phenotypes. We speculate that abnormal blood flow may frequently underlie congenital heart defects. Copyright © 2017 the American Physiological Society.

Flow Patterns in an Open Channel Confluence with Increasingly Dominant Tributary Inflow

Directory of Open Access Journals (Sweden)

Laurent Schindfessel

2015-08-01

Full Text Available Despite the ratio of incoming discharges being recognized as a key parameter in open-channel confluence hydrodynamics, little is known about the flow patterns when the tributary provides more than 90% of the total discharge. This paper offers a systematic study of flow features when the tributary becomes increasingly dominant in a 90° confluence with a fixed concordant bed. Large-eddy simulations are used to investigate the three-dimensional complex flow patterns for three different discharge ratios. It is found that the tributary flow impinges on the opposing bank when the tributary flow becomes sufficiently dominant, causing a recirculating eddy in the upstream channel of the confluence, which induces significant changes in the incoming velocity distribution. Moreover, it results in stronger helicoidal cells in the downstream channel, along with zones of upwelling flow. In turn, the changed flow patterns also influence the mixing layer and the flow recovery. Finally, intermittent events of stronger upwelling flow are discerned. Improved understanding of flow patterns at confluences where the tributary is dominant is applicable to both engineering and earth sciences.

Flow experience in game based learning – a systematic literature review

Directory of Open Access Journals (Sweden)

Arttu Perttula

2017-03-01

Full Text Available The entertaining elements implemented in a serious game are key factors in determining whether a player will be engaged in a play-learn process and able to achieve the desired learning outcomes. Thus, optimization of subjective playing experience is a crucial part of a game design process. Flow theory can be adopted for measuring user experience and analyzing the quality of serious game designs. In addition, flow seems to have a positive influence on performance enhancement, learning and engagement. The focus of this review is especially on examining the meaning of flow in the context of serious games as well as exploring the relationship between flow and learning, factors that influence occurrence of flow and how flow is operationalized. The review revealed that there are mainly conceptual considerations about flow in serious games, but no robust empirical evidence about the meaning of flow. This is in line with other studies. We argue that research on flow should focus on the specific aspects related to the very nature of serious games that combine enjoyment and learning. Furthermore, new methods to measure flow and analyse the data need to be developed and studied.

Patterns in Teacher Learning in Different Phases of the Professional Career

Science.gov (United States)

Vermunt, Jan D.; Endedijk, Maaike D.

2011-01-01

This paper reviews recent research on learning patterns of student teachers and experienced teachers, mostly in the context of educational innovation and teachers' professional development. The discussion is structured along a model of teacher learning patterns comprising learning activities, regulation of learning, beliefs on own learning about…

Subcutaneous blood flow in early male pattern baldness

International Nuclear Information System (INIS)

Klemp, P.; Peters, K.; Hansted, B.

1989-01-01

The subcutaneous blood flow (SBF) was measured by the 133 Xe washout method in the scalp of 14 patients with early male pattern baldness. Control experiments were performed in 14 normal haired men matched for age. The SBF in the scalp of the normal individuals was about 10 times higher than previously reported SBF values in other anatomical regions. In patients with early male pattern baldness, SBF was 2.6 times lower than the values found in the normal individuals (13.7 +/- 9.6 vs 35.7 +/- 10.5 ml/100 g/min-1). This difference was statistically significant (p much less than 0.001). A reduced nutritive blood flow to the hair follicles might be a significant event in the pathogenesis of early male pattern baldness

Blood flow patterns during incremental and steady-state aerobic exercise.

Science.gov (United States)

Coovert, Daniel; Evans, LeVisa D; Jarrett, Steven; Lima, Carla; Lima, Natalia; Gurovich, Alvaro N

2017-05-30

Endothelial shear stress (ESS) is a physiological stimulus for vascular homeostasis, highly dependent on blood flow patterns. Exercise-induced ESS might be beneficial on vascular health. However, it is unclear what type of ESS aerobic exercise (AX) produces. The aims of this study are to characterize exercise-induced blood flow patterns during incremental and steady-state AX. We expect blood flow pattern during exercise will be intensity-dependent and bidirectional. Six college-aged students (2 males and 4 females) were recruited to perform 2 exercise tests on cycleergometer. First, an 8-12-min incremental test (Test 1) where oxygen uptake (VO2), heart rate (HR), blood pressure (BP), and blood lactate (La) were measured at rest and after each 2-min step. Then, at least 48-hr. after the first test, a 3-step steady state exercise test (Test 2) was performed measuring VO2, HR, BP, and La. The three steps were performed at the following exercise intensities according to La: 0-2 mmol/L, 2-4 mmol/L, and 4-6 mmol/L. During both tests, blood flow patterns were determined by high-definition ultrasound and Doppler on the brachial artery. These measurements allowed to determine blood flow velocities and directions during exercise. On Test 1 VO2, HR, BP, La, and antegrade blood flow velocity significantly increased in an intensity-dependent manner (repeated measures ANOVA, pflow velocity did not significantly change during Test 1. On Test 2 all the previous variables significantly increased in an intensity-dependent manner (repeated measures ANOVA, pflow patterns during incremental and steady-state exercises include both antegrade and retrograde blood flows.

A Learning Patterns Perspective on Student Learning in Higher Education: State of the Art and Moving Forward

Science.gov (United States)

Vermunt, Jan D.; Donche, Vincent

2017-01-01

The aim of this article is to review the state of the art of research and theory development on student learning patterns in higher education and beyond. First, the learning patterns perspective and the theoretical framework are introduced. Second, research published since 2004 on student learning patterns is systematically identified and…

Optimizing a Workplace Learning Pattern: A Case Study from Aviation

Science.gov (United States)

Mavin, Timothy John; Roth, Wolff-Michael

2015-01-01

Purpose: This study aims to contribute to current research on team learning patterns. It specifically addresses some negative perceptions of the job performance learning pattern. Design/methodology/approach: Over a period of three years, qualitative and quantitative data were gathered on pilot learning in the workplace. The instructional modes…

Surface Patterning: Controlling Fluid Flow Through Dolphin and Shark Skin Biomimicry

Science.gov (United States)

Gamble, Lawren; Lang, Amy; Bradshaw, Michael; McVay, Eric

2013-11-01

Dolphin skin is characterized by circumferential ridges, perpendicular to fluid flow, present from the crest of the head until the tail fluke. When observing a cross section of skin, the ridges have a sinusoidal pattern. Sinusoidal grooves have been proven to induce vortices in the cavities that can help control flow separation which can reduce pressure drag. Shark skin, however, is patterned with flexible scales that bristle up to 50 degrees with reversed flow. Both dolphin ridges and shark scales are thought to help control fluid flow and increase swimming efficiency by delaying the separation of the boundary layer. This study investigates how flow characteristics can be altered with bio-inspired surface patterning. A NACA 4412 hydrofoil was entirely patterned with transverse sinusoidal grooves, inspired by dolphin skin but scaled so the cavities on the model have the same Reynolds number as the cavities on a swimming shark. Static tests were conducted at a Reynolds number of approximately 100,000 and at varying angles of attack. The results were compared to the smooth hydrofoil case. The flow data was quantified using Digital Particle Image Velocimetry (DPIV). The results of this study demonstrated that the patterned hydrofoil experienced greater separation than the smooth hydrofoil. It is hypothesize that this could be remediated if the pattern was placed only after the maximum thickness of the hydrofoil. Funding through NSF REU grant 1062611 is gratefully acknowledged.

Comparison of detection pattern of HCC by ferumoxide-enhanced MRI and intratumoral blood flow pattern

International Nuclear Information System (INIS)

Itou, Naoki; Kotake, Fumio; Saitou, Kazuhiro; Abe, Kimihiko

2000-01-01

We compared the detection rate and pattern of ferumoxide-enhanced magnetic resonance imaging (Fe-MRI) with the intratumoral blood flow pattern determined by CT angiography (CTA) and CT portography (CTAP) in 124 nodes (34 cases) diagnosed as hepatocellular carcinoma (HCC) or borderline HCC, based on the clinical course. Sequences to obtain a T1-weighted images (T1W), proton density-weighted images (PDW), T2-weighted images (T2W), T2*-weighted images (T2*W) were used in Fe-MRI. In nodes shown to be hypervascular on CTA, the detection rate by Fe-MRI was 69.7%. In nodes shown to be avascular by CTAP, the detection rate by Fe-MRI was 67.3%. These rates were higher than with other flow patterns. In nodes showing high signal intensity (HSI) on any sequences, arterial blood flow was increased and portal blood flow decreased in comparison with nodes without high signal intensity. All nodes showing HSI, both on Fe-MRI T2W and T2*W, were hypervascular on CTA, and portal blood flow was absent on CTAP. Nodes showing HSI on both T2*W and T2W were considered to have greater arterial blood flow and decreased portal blood flow compared with nodes appearing as HSI on T2*W, but only as iso- or low signal intensity on T2W (Mann-Whitney U-test; p<0.05). (author)

Experimental study of flow patterns near tube support structures

International Nuclear Information System (INIS)

Rummens, H.E.C.; Turner, C.W.

1994-07-01

Extensive blockage of broached support plates in steam generators has occurred at the Bruce A Nuclear Generating Station (NGS), forcing unit derating in 1988 March. Blockage has also been found on the lower broached plates of the Pickering B and Point Lepreau NGSs. Water chemistry and operating conditions are known to influence fouling directly. We suspect that flow patterns also play a role, that these patterns are influenced by the geometry of steam generator (SG) components, and that particularly the broached plate design actively creates an environment favorable to deposition. Experiments are in progress to examine the flow patterns near various tube supports: the broached plate, two types of lattice bars, and the formed bars. Preliminary tests in an air/water loop with 1/2- and 7-tube SG mockups containing the tube supports have been completed. Flow patterns were visualized using injected air bubbles. Local velocities and turbulence levels were measured using a laser technique, which confirmed observations of flow recirculation and stagnation. Axial pressure profiles were measured to determine overall resistance coefficients, and to identify local pressure extremes. Some visualization tests were also carried out on an artificially fouled broached plate. Based on results to date, several deposition mechanisms are proposed: deposition of particles in stagnant regions, deposition of solubles due to flashing in low-pressure regions, and deposition in smaller channels due to steam migration toward larger channels. A qualitative assessment of the tube support designs based on these mechanisms implies that the relative resistances to fouling are: (WORST) broach plate << lattice bars << formed bars (BEST). As the air/water simulation shows only hydraulic flow patterns, further tests will be done in a simple liquid/vapor Freon loop to examine thermal effects. (author). 3 refs., 10 figs

Critical heat flux and flow pattern for water flow in annular geometry

International Nuclear Information System (INIS)

Park, Jae Wook; Baek, Won Pil; Chang, Soon Heung

1996-01-01

An experimental study on critical heat flux (CHF) and two-phase flow visualization has been performed for water flow in internally-heated, vertical, concentric annuli under near atmospheric pressure. Tests have been done under stable forced-circulation, upward and downward flow conditions with three test sections of relatively large gap widths (heated length = 0.6 m, inner diameter = 19 mm, outer diameter = 29, 35 and 51 mm). The outer wall of the test section was made up of the transparent Pyrex tube to allow the observation of flow patterns near the CHF occurrence. The CHF mechanism was changed in the order of flooding, churn-to-annular flow transition, and local dryout under a large bubble in churn flow as the flow rate was increased from zero to higher values. Observed parametric trends are consistent with the previous understanding except that the CHF for downward flow is considerably lower than that for upward flow

Two-phase flow patterns in horizontal rectangular minichannel

Directory of Open Access Journals (Sweden)

Ron’shin Fedor

2016-01-01

Full Text Available The two-phase flow in a short horizontal channel of rectangular cross-section of 1 × 19 mm2 has been studied experimentally. Five conventional two-phase flow patterns have been detected (bubble, churn, stratified, annular and jet and transitions between them have been determined. It is shown that a change in the width of the horizontal channels has a substantial effect on the boundaries between the flow regimes.

Factors Impacting Corporate E-Learners' Learning Flow, Satisfaction, and Learning Persistence

Science.gov (United States)

Joo, Young Ju; Joung, Sunyong; Kim, Nam Hee; Chung, Hyun Min

2012-01-01

This study aimed to investigate the structural relationships among teaching presence, cognitive presence, usage, learning flow, satisfaction, and learning persistence in corporate e-learners. The research participants were 462 e-learners registered for e-lectures through an electronics company in South Korea. First, the sense of teaching presence,…

Gas-liquid-liquid three-phase flow pattern and pressure drop in a microfluidic chip : similarities with gas-liquid/liquid-liquid flows

NARCIS (Netherlands)

Yue, J.; Rebrov, E.; Schouten, J.C.

2014-01-01

We report a three-phase slug flow and parallel-slug flow as two major flow patterns found under the nitrogen-decane-water flow through a glass microfluidic chip which features a long microchannel with a hydraulic diameter of 98 µm connected to a cross-flow mixer. The three-phase slug flow pattern is

An efficient flow-based botnet detection using supervised machine learning

DEFF Research Database (Denmark)

Stevanovic, Matija; Pedersen, Jens Myrup

2014-01-01

Botnet detection represents one of the most crucial prerequisites of successful botnet neutralization. This paper explores how accurate and timely detection can be achieved by using supervised machine learning as the tool of inferring about malicious botnet traffic. In order to do so, the paper...... introduces a novel flow-based detection system that relies on supervised machine learning for identifying botnet network traffic. For use in the system we consider eight highly regarded machine learning algorithms, indicating the best performing one. Furthermore, the paper evaluates how much traffic needs...... to accurately and timely detect botnet traffic using purely flow-based traffic analysis and supervised machine learning. Additionally, the results show that in order to achieve accurate detection traffic flows need to be monitored for only a limited time period and number of packets per flow. This indicates...

Magnetic field induced flow pattern reversal in a ferrofluidic Taylor-Couette system.

Science.gov (United States)

Altmeyer, Sebastian; Do, Younghae; Lai, Ying-Cheng

2015-12-21

We investigate the dynamics of ferrofluidic wavy vortex flows in the counter-rotating Taylor-Couette system, with a focus on wavy flows with a mixture of the dominant azimuthal modes. Without external magnetic field flows are stable and pro-grade with respect to the rotation of the inner cylinder. More complex behaviors can arise when an axial or a transverse magnetic field is applied. Depending on the direction and strength of the field, multi-stable wavy states and bifurcations can occur. We uncover the phenomenon of flow pattern reversal as the strength of the magnetic field is increased through a critical value. In between the regimes of pro-grade and retrograde flow rotations, standing waves with zero angular velocities can emerge. A striking finding is that, under a transverse magnetic field, a second reversal in the flow pattern direction can occur, where the flow pattern evolves into pro-grade rotation again from a retrograde state. Flow reversal is relevant to intriguing phenomena in nature such as geomagnetic reversal. Our results suggest that, in ferrofluids, flow pattern reversal can be induced by varying a magnetic field in a controlled manner, which can be realized in laboratory experiments with potential applications in the development of modern fluid devices.

Effect of the mitral valve on diastolic flow patterns

International Nuclear Information System (INIS)

Seo, Jung Hee; Vedula, Vijay; Mittal, Rajat; Abraham, Theodore; Dawoud, Fady; Luo, Hongchang; Lardo, Albert C.

2014-01-01

The leaflets of the mitral valve interact with the mitral jet and significantly impact diastolic flow patterns, but the effect of mitral valve morphology and kinematics on diastolic flow and its implications for left ventricular function have not been clearly delineated. In the present study, we employ computational hemodynamic simulations to understand the effect of mitral valve leaflets on diastolic flow. A computational model of the left ventricle is constructed based on a high-resolution contrast computed-tomography scan, and a physiological inspired model of the mitral valve leaflets is synthesized from morphological and echocardiographic data. Simulations are performed with a diode type valve model as well as the physiological mitral valve model in order to delineate the effect of mitral-valve leaflets on the intraventricular flow. The study suggests that a normal physiological mitral valve promotes the formation of a circulatory (or “looped”) flow pattern in the ventricle. The mitral valve leaflets also increase the strength of the apical flow, thereby enhancing apical washout and mixing of ventricular blood. The implications of these findings on ventricular function as well as ventricular flow models are discussed

Measurements of two-phase flow patterns in a 4 x 4 rod bundle

International Nuclear Information System (INIS)

Akio tomiyama; Akira Sou; Shigeo Hosokawa; Masato Mitsuhashi; Kohei Noda; Yasushi Tsubo; Kaichiro Mishima; Yoshiro Kudo

2005-01-01

Air-water two-phase flow patterns in a 4 x 4 square lattice rod bundle consisting of an acrylic channel box of 68 mm in width and transparent rods of 12 mm in diameter were measured by utilizing FEP (fluorinated ethylene propylene) tubes for the rods. The FEP possesses the same refractive index with water, and therefore, whole flow patterns in the bundle and local flow patterns in subchannels were visualized with little optical distortion. In addition to the visualization, transmission rates of laser beam from one rod to its opponent rod and two-point correlation coefficients of phase indicator functions were measured to examine the feasibility of objective identification of flow patterns in subchannels. The ranges of liquid and gas volume fluxes, JL and JG, were 0.1 < JL < 2.0 m/s and 0.04 < JG < 8.85 m/s, respectively. As a result, the following conclusions were obtained: (1) slug flow pattern does not appear in the rod bundle and bubbly flow would directly transit to churn flow, (2) the measured boundary between bubbly and churn flows is close to the boundary between bubbly and slug flows given by Mishima and Ishii's flow pattern transition model, (3) critical void fraction causing bubbly to churn flow transition depends on a subchannel, i.e., about 0.3 for inner subchannels, about 0.2 for side subchannels and about 0.1 for corner subchannels, and (4) the two-point correlation coefficient of phase indicator functions for two inner subchannels shows a steep increase at the bubbly to churn flow transition, which, in turn, means that the two-point correlation is an appropriate indicator for detecting this transition. (authors)

Doing ecohydrology backward: Inferring wetland flow and hydroperiod from landscape patterns

Science.gov (United States)

Acharya, Subodh; Kaplan, David A.; Jawitz, James W.; Cohen, Matthew J.

2017-07-01

Human alterations to hydrology have globally impacted wetland ecosystems. Preventing or reversing these impacts is a principal focus of restoration efforts. However, restoration effectiveness is often hampered by limited information on historical landscape properties and hydrologic regime. To help address this gap, we developed a novel statistical approach for inferring flows and inundation frequency (i.e., hydroperiod, HP) in wetlands where changes in spatial vegetation and geomorphic patterns have occurred due to hydrologic alteration. We developed an analytical expression for HP as a transformation of the landscape-scale stage-discharge relationship. We applied this model to the Everglades "ridge-slough" (RS) landscape, a patterned, lotic peatland in southern Florida that has been drastically degraded by compartmentalization, drainage, and flow diversions. The new method reliably estimated flow and HP for a range of RS landscape patterns. Crucially, ridge-patch anisotropy and elevation above sloughs were strong drivers of flow-HP relationships. Increasing ridge heights markedly increased flow required to achieve sufficient HP to support peat accretion. Indeed, ridge heights inferred from historical accounts would require boundary flows 3-4 times greater than today, which agrees with restoration flow estimates from more complex, spatially distributed models. While observed loss of patch anisotropy allows HP targets to be met with lower flows, such landscapes likely fail to support other ecological functions. This work helps inform restoration flows required to restore stable ridge-slough patterning and positive peat accretion in this degraded ecosystem, and, more broadly, provides tools for exploring interactions between landscape and hydrology in lotic wetlands and floodplains.

Transductive Pattern Learning for Information Extraction

National Research Council Canada - National Science Library

McLernon, Brian; Kushmerick, Nicholas

2006-01-01

.... We present TPLEX, a semi-supervised learning algorithm for information extraction that can acquire extraction patterns from a small amount of labelled text in conjunction with a large amount of unlabelled text...

Echocardiographic and hemodynamic determinants of right coronary artery flow reserve and phasic flow pattern in advanced non-ischemic cardiomyopathy

Directory of Open Access Journals (Sweden)

Mady Charles

2007-09-01

Full Text Available Abstract Background In patients with advanced non-ischemic cardiomyopathy (NIC, right-sided cardiac disturbances has prognostic implications. Right coronary artery (RCA flow pattern and flow reserve (CFR are not well known in this setting. The purpose of this study was to assess, in human advanced NIC, the RCA phasic flow pattern and CFR, also under right-sided cardiac disturbances, and compare with left coronary circulation. As well as to investigate any correlation between the cardiac structural, mechanical and hemodynamic parameters with RCA phasic flow pattern or CFR. Methods Twenty four patients with dilated severe NIC were evaluated non-invasively, even by echocardiography, and also by cardiac catheterization, inclusive with Swan-Ganz catheter. Intracoronary Doppler (Flowire data was obtained in RCA and left anterior descendent coronary artery (LAD before and after adenosine. Resting RCA phasic pattern (diastolic/systolic was compared between subgroups with and without pulmonary hypertension, and with and without right ventricular (RV dysfunction; and also with LAD. RCA-CFR was compared with LAD, as well as in those subgroups. Pearson's correlation analysis was accomplished among echocardiographic (including LV fractional shortening, mass index, end systolic wall stress more hemodynamic parameters with RCA phasic flow pattern or RCA-CFR. Results LV fractional shortening and end diastolic diameter were 15.3 ± 3.5 % and 69.4 ± 12.2 mm. Resting RCA phasic pattern had no difference comparing subgroups with vs. without pulmonary hypertension (1.45 vs. 1.29, p = NS either with vs. without RV dysfunction (1.47 vs. 1.23, p = NS; RCA vs. LAD was 1.35 vs. 2.85 (p Conclusion In patients with chronic advanced NIC, RCA phasic flow pattern has a mild diastolic predominance, less marked than in LAD, with no effects from pulmonary artery hypertension or RV dysfunction. There is no significant correlation between any cardiac mechanical-structural or

Design of flow-field patterns for proton exchange membrane fuel cell application

International Nuclear Information System (INIS)

Rosli, M.I.; Wan Ramli Wan Daud; Kamaruzzaman Sopian; Jaafar Sahari

2006-01-01

Fuel cells are electrochemical devices that produce electricity at high efficiency without combustion. Fuel cells are emerging as viable candidates as power sources in many applications, including road vehicles, small-scale power stations, and possibly even portable electronics. This paper addresses the design of flow-field patterns for proton exchange membrane fuel cell (PEMFC). The PEMFC is a low-temperature fuel cell, in which a proton conductive polymer membrane is used as the electrolyte. In PEMFC, flow-field pattern is one important thing that effects the performance of PEMFC. This paper present three types of flow-field pattern that will be consider to be testing using CFD analysis and by experimental. The design look detail on to their shape and dimension to get the best pattern in term of more active electrode area compare to electrode area that will be used. Another advantage and disadvantage for these three type of flow-field patterns from literature also compared in this paper

The art and learning patterns of knowing in nursing

Directory of Open Access Journals (Sweden)

Cristina Lavareda Baixinho

2014-12-01

Full Text Available Objective To identify the perception of the students about the use of art as a pedagogical strategy in learning the patterns of knowing in nursing; to identify the dimensions of each pattern valued in the analysis of pieces of art. Method Descriptive mixed study. Data collection used a questionnaire applied to 31 nursing students. Results In the analysis of the students’ discourse, it was explicit that empirical knowledge includes scientific knowledge, tradition and nature of care. The aesthetic knowledge implies expressiveness, subjectivity and sensitivity. Self-knowledge, experience, reflective attitude and relationships with others are the subcategories of personal knowledge and the moral and ethics support ethical knowledge. Conclusion It is possible to learn patterns of knowledge through art, especially the aesthetic, ethical and personal. It is necessary to investigate further pedagogical strategies that contribute to the learning patterns of nursing knowledge.

Identification of two-phase flow pattern by using specific spatial frequency of differential pressure signal

International Nuclear Information System (INIS)

Han Bin; Tong Yunxian; Wu Shaorong

1992-11-01

It is a classical method by using analysis of differential pressure fluctuation signal to identify two-phase flow pattern. The method which uses trait peak in the frequency-domain will result confusion between bubble flow and intermittent flow due to the influence of gas speed. Considering the spatial geometric significance of two-phase slow patterns and using the differential pressure gauge as a sensor, the Strouhal number 'Sr' is taken as the basis for distinguishing flow patterns. Using Strouhal number 'Sr' to identify flow pattern has clear physical meaning. The experimental results using the spatial analytical technique to measure the flow pattern are also given

Periodic flow patterns of the magnetic fluid in microchannel

International Nuclear Information System (INIS)

Chang, C.-W.; Cheng, Y.-T.; Tsai, C.-Y.; Chien, J.-H.; Wang, P.-Y.; Chen, P.-H.

2007-01-01

In this study, of interests are the periodic flow patterns of the oil-based magnetic fluid in microchannels. A microfluidic chip is made of poly-dimethylsiloxane (PDMS) and contains cross-shape microchannels. The microchannels are 1000 μm in width and 200 μm in depth. A syringe pump was used to drive the fluids. Periodic flow patterns were seen and the slugs of magnetic fluid and DI water were generated. The operating factors discussed in the present work are the flow rates and the magnetic field. The frequency of generation of the slugs increases with increase in the flow rates. Besides, by settling the permanent magnet around the microchannel, the periods of the slug generation are changed. Different positions of the magnet lead to different periods for generating the slugs. By adjusting operating conditions, to control the frequency and the volume of the slugs is practical

PATTERNS OF FLOWS IN AN INTERMEDIATE PROMINENCE OBSERVED BY HINODE

International Nuclear Information System (INIS)

Ahn, Kwangsu; Chae, Jongchul; Cao Wenda; Goode, Philip R.

2010-01-01

The investigation of plasma flows in filaments/prominences gives us clues to understanding their magnetic structures. We studied the patterns of flows in an intermediate prominence observed by Hinode/SOT. By examining a time series of Hα images and Ca II H images, we have found horizontal flows in the spine and vertical flows in the barb. Both of these flows have a characteristic speed of 10-20 km s -1 . The horizontal flows displayed counterstreaming. Our detailed investigation revealed that most of the moving fragments in fact reversed direction at the end point of the spine near a footpoint close to the associated active region. These returning flows may be one possible explanation of the well-known counterstreaming flows in prominences. In contrast, we have found vertical flows-downward and upward-in the barb. Most of the horizontal flows in the spine seem to switch into vertical flows when they approach the barb, and vice versa. We propose that the net force resulting from a small deviation from magnetohydrostatic equilibrium, where magnetic fields are predominantly horizontal, may drive these patterns of flow. In the prominence studied here, the supposed magnetohydrostatic configuration is characterized by magnetic field lines sagging with angles of 13 0 and 39 0 in the spine and the barb, respectively.

Living with diabetes—Development of learning patterns over a 3-year period

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Åsa Kneck

2014-07-01

Full Text Available Background: Learning involves acquiring new knowledge and skills, and changing our ways of thinking, acting, and feeling. Learning in relation to living with diabetes is a lifelong process where there is limited knowledge of how it is experienced and established over time. It was considered important to explore how learning was developed over time for persons living with diabetes. Aim: The aim of the study was to identify patterns in learning when living with diabetes, from recently being diagnosed, and over a 3-year period. Materials and methods: A longitudinal qualitative descriptive design was used. Thirteen participants, with both type I and type II diabetes, were interviewed at three different occasions during a 3-year period. Qualitative content analysis was used in different steps in order to distinguish patterns. Findings: Five main patterns of learning were identified. Two of the patterns (I and II were characterized by gradually becoming comfortable living with diabetes, whereas for one pattern (IV living with diabetes became gradually more difficult. For pattern V living with diabetes was making only a limited impact on life, whereas for Pattern III there was a constant management of obstacles related to illness. The different patterns in the present study showed common and different ways of learning and using different learning strategies at different timespans. Conclusion: The present study showed that duration of illness is not of importance for how far a person has come in his own learning process. A person-centered care is needed to meet the different and changing needs of persons living with diabetes in relation to learning to live with a lifelong illness.

Entropy feature extraction on flow pattern of gas/liquid two-phase flow based on cross-section measurement

International Nuclear Information System (INIS)

Han, J; Dong, F; Xu, Y Y

2009-01-01

This paper introduces the fundamental of cross-section measurement system based on Electrical Resistance Tomography (ERT). The measured data of four flow regimes of the gas/liquid two-phase flow in horizontal pipe flow are obtained by an ERT system. For the measured data, five entropies are extracted to analyze the experimental data according to the different flow regimes, and the analysis method is examined and compared in three different perspectives. The results indicate that three different perspectives of entropy-based feature extraction are sensitive to the flow pattern transition in gas/liquid two-phase flow. By analyzing the results of three different perspectives with the changes of gas/liquid two-phase flow parameters, the dynamic structures of gas/liquid two-phase flow is obtained, and they also provide an efficient supplementary to reveal the flow pattern transition mechanism of gas/liquid two-phase flow. Comparison of the three different methods of feature extraction shows that the appropriate entropy should be used for the identification and prediction of flow regimes.

Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method

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Yuhan Jia

2017-01-01

Full Text Available Accurate traffic flow prediction is increasingly essential for successful traffic modeling, operation, and management. Traditional data driven traffic flow prediction approaches have largely assumed restrictive (shallow model architectures and do not leverage the large amount of environmental data available. Inspired by deep learning methods with more complex model architectures and effective data mining capabilities, this paper introduces the deep belief network (DBN and long short-term memory (LSTM to predict urban traffic flow considering the impact of rainfall. The rainfall-integrated DBN and LSTM can learn the features of traffic flow under various rainfall scenarios. Experimental results indicate that, with the consideration of additional rainfall factor, the deep learning predictors have better accuracy than existing predictors and also yield improvements over the original deep learning models without rainfall input. Furthermore, the LSTM can outperform the DBN to capture the time series characteristics of traffic flow data.

Visualisation of cerebrospinal fluid flow patterns in albino Xenopus larvae in vivo

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Mogi Kazue

2012-04-01

Full Text Available Abstract Background It has long been known that cerebrospinal fluid (CSF, its composition and flow, play an important part in normal brain development, and ependymal cell ciliary beating as a possible driver of CSF flow has previously been studied in mammalian fetuses in vitro. Lower vertebrate animals are potential models for analysis of CSF flow during development because they are oviparous. Albino Xenopus laevis larvae are nearly transparent and have a straight, translucent brain that facilitates the observation of fluid flow within the ventricles. The aim of these experiments was to study CSF flow and circulation in vivo in the developing brain of living embryos, larvae and tadpoles of Xenopus laevis using a microinjection technique. Methods The development of Xenopus larval brain ventricles and the patterns of CSF flow were visualised after injection of quantum dot nanocrystals and polystyrene beads (3.1 or 5.8 μm in diameter into the fourth cerebral ventricle at embryonic/larval stages 30-53. Results The fluorescent nanocrystals showed the normal development of the cerebral ventricles from embryonic/larval stages 38 to 53. The polystyrene beads injected into stage 47-49 larvae revealed three CSF flow patterns, left-handed, right-handed and non-biased, in movement of the beads into the third ventricle from the cerebral aqueduct (aqueduct of Sylvius. In the lateral ventricles, anterior to the third ventricle, CSF flow moved anteriorly along the outer wall of the ventricle to the inner wall and then posteriorly, creating a semicircle. In the cerebral aqueduct, connecting the third and fourth cerebral ventricles, CSF flow moved rostrally in the dorsal region and caudally in the ventral region. Also in the fourth ventricle, clear dorso-ventral differences in fluid flow pattern were observed. Conclusions This is the first visualisation of the orchestrated CSF flow pattern in developing vertebrates using a live animal imaging approach. CSF flow

Research Issues in Evaluating Learning Pattern Development in Higher Education

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Richardson, John T. E.

2013-01-01

This article concludes the special issue of "Studies in Educational Evaluation" concerned with "Evaluating learning pattern development in higher education" by discussing research issues that have emerged from the previous contributions. The article considers in turn: stability versus variability in learning patterns; old versus new analytic…

Modeling on bubbly to churn flow pattern transition in narrow rectangular channel

International Nuclear Information System (INIS)

Wang Yanlin; Chen Bingde; Huang Yanping; Wang Junfeng

2012-01-01

A theoretical model based on some reasonable concepts was developed to predict the bubbly flow to churn flow pattern transition in vertical narrow rectangular channel under flow boiling condition. The maximum size of ideal bubble in narrow rectangular channel was calculated based on previous literature. The thermal hydraulics boundary condition of bubbly to churn flow pattern transition was exported from Helmholtz and maximum size of ideal bubble. The theoretical model was validated by existent experimental data. (authors)

Children's Brain Responses to Optic Flow Vary by Pattern Type and Motion Speed.

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Rick O Gilmore

Full Text Available Structured patterns of global visual motion called optic flow provide crucial information about an observer's speed and direction of self-motion and about the geometry of the environment. Brain and behavioral responses to optic flow undergo considerable postnatal maturation, but relatively little brain imaging evidence describes the time course of development in motion processing systems in early to middle childhood, a time when psychophysical data suggest that there are changes in sensitivity. To fill this gap, electroencephalographic (EEG responses were recorded in 4- to 8-year-old children who viewed three time-varying optic flow patterns (translation, rotation, and radial expansion/contraction at three different speeds (2, 4, and 8 deg/s. Modulations of global motion coherence evoked coherent EEG responses at the first harmonic that differed by flow pattern and responses at the third harmonic and dot update rate that varied by speed. Pattern-related responses clustered over right lateral channels while speed-related responses clustered over midline channels. Both children and adults show widespread responses to modulations of motion coherence at the second harmonic that are not selective for pattern or speed. The results suggest that the developing brain segregates the processing of optic flow pattern from speed and that an adult-like pattern of neural responses to optic flow has begun to emerge by early to middle childhood.

Simulation of Flow Pattern around Inclined Bridge Group Pier using FLOW-3D Software

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Malihesadat Jafari

2017-03-01

Full Text Available Introduction: Bridges are certainly one of the most important structures but costly service elements in a transport system. The bridges are very required to access the damaged areas in emergency situations such as floods and earthquakes. Scour around the foundations of bridge piers exposed to the flowing water than can destroy the bridge itself is a subject of major concern. Flow pattern is known as responsible for all changes in stream bed. Any obstacle in the channel can form new flow patterns causing additional shear stress exerted on the bed than the equilibrium condition of the absence of the obstacle. Appropriate shaping of flow pattern and proper selecting of pier geometry and the location of bridge piers can be one of the proper methods in reduction of scour amount which is the main subject of the present study. Materials and Methods: Inclined bridge group pier is a type of bridges with modern geometry based on development in building technology of structures. Many of these bridges have been built all around the world and the 8th bridge built crossing the Karun River in Ahvaz is a sample of the Iranian ones considered in this research. Hydrodynamic behavior of flow is investigated around the inclined bridge group pier settled on foundation using the FLOW-3D numerical model. Inclined bridge group pier investigated in this study, includes two rectangular piers which are 2.5 cm long and 3.5 cm wide and set in an angle of 28 degree on rectangular foundation which is 16 cm long and 10 cm wide and installed in three different foundation levels namely at, above and below the bed levels. The physical model of prototype pier considered in this study was constructed to the scale of 1:190 of the Ahvaz 8th bridge. In order to verify the accuracy of the numerical model, velocity data obtained from image processing technique were used. Results and Discussion: Due to non- linearity and interactions between various phenomena involved, flow pattern

Visualization and analysis of flow patterns of human carotid bifurcation by computational fluid dynamics

International Nuclear Information System (INIS)

Xue Yunjing; Gao Peiyi; Lin Yan

2007-01-01

Objective: To investigate flow patterns at carotid bifurcation in vivo by combining computational fluid dynamics (CFD)and MR angiography imaging. Methods: Seven subjects underwent contrast-enhanced MR angiography of carotid artery in Siemens 3.0 T MR. Flow patterns of the carotid artery bifurcation were calculated and visualized by combining MR vascular imaging post-processing and CFD. Results: The flow patterns of the carotid bifurcations in 7 subjects were varied with different phases of a cardiac cycle. The turbulent flow and back flow occurred at bifurcation and proximal of internal carotid artery (ICA) and external carotid artery (ECA), their occurrence and conformation were varied with different phase of a cardiac cycle. The turbulent flow and back flow faded out quickly when the blood flow to the distal of ICA and ECA. Conclusion: CFD combined with MR angiography can be utilized to visualize the cyclical change of flow patterns of carotid bifurcation with different phases of a cardiac cycle. (authors)

Flow Navigation by Smart Microswimmers via Reinforcement Learning

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Colabrese, Simona; Biferale, Luca; Celani, Antonio; Gustavsson, Kristian

2017-11-01

We have numerically modeled active particles which are able to acquire some limited knowledge of the fluid environment from simple mechanical cues and exert a control on their preferred steering direction. We show that those swimmers can learn effective strategies just by experience, using a reinforcement learning algorithm. As an example, we focus on smart gravitactic swimmers. These are active particles whose task is to reach the highest altitude within some time horizon, exploiting the underlying flow whenever possible. The reinforcement learning algorithm allows particles to learn effective strategies even in difficult situations when, in the absence of control, they would end up being trapped by flow structures. These strategies are highly nontrivial and cannot be easily guessed in advance. This work paves the way towards the engineering of smart microswimmers that solve difficult navigation problems. ERC AdG NewTURB 339032.

Evaluation of flow volume and flow patterns in the patent false lumen of chronic aortic dissections using velocity-encoded cine magnetic resonance imaging

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Inoue, Toshihisa; Watanabe, Shigeru; Sakurada, Hideki; Ono, Katsuhiro; Urano, Miharu; Hijikata, Yasuyoshi; Saito, Isao; Masuda, Yoshiaki [Chiba Univ. (Japan). School of Medicine

2000-10-01

In 21 patients with chronic aortic dissections and proven patent false lumens, the flow volume and flow patterns in the patent false lumens was evaluated using velocity-encoded cine magnetic resonance imaging (VENC-MRI) and the relationship between the flow characteristics and aortic enlargement was retrospectively examined. Flow patterns in the false lumen were divided into 3 groups: pattern A with primarily antegrade flow (n=6), pattern R with primarily retrograde flow (n=3), and pattern B with bidirectional flow (n=12). In group A, the rate of flow volume in the false lumen compared to the total flow volume in true and false lumens (%TFV) and the average rate of enlargement of the maximum diameter of the dissected aorta per year ({delta}D) were significantly greater than in groups R and B (%TFV: 74.1{+-}0.07 vs 15.2{+-}0.03 vs 11.8{+-}0.04, p<0.01; {delta}D: 3.62{+-}0.82 vs 0 vs 0.58{+-}0.15 mm/year, p<0.05, respectively). There was a significant correlation between %TFV and {delta}D (r=0.79, p<0.0001). Evaluation of flow volume and flow patterns in the patent false lumen using VENC-MRI may be useful for predicting enlargement of the dissected aorta. (author)

Learning-induced pattern classification in a chaotic neural network

International Nuclear Information System (INIS)

Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki

2012-01-01

In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.

Classification of natural circulation two-phase flow patterns using fuzzy inference on image analysis

International Nuclear Information System (INIS)

Mesquita, R.N. de; Masotti, P.H.F.; Penha, R.M.L.; Andrade, D.A.; Sabundjian, G.; Torres, W.M.

2012-01-01

Highlights: ► A fuzzy classification system for two-phase flow instability patterns is developed. ► Flow patterns are classified based on images of natural circulation experiments. ► Fuzzy inference is optimized to use single grayscale profiles as input. - Abstract: Two-phase flow on natural circulation phenomenon has been an important theme on recent studies related to nuclear reactor designs. The accuracy of heat transfer estimation has been improved with new models that require precise prediction of pattern transitions of flow. In this work, visualization of natural circulation cycles is used to study two-phase flow patterns associated with phase transients and static instabilities of flow. A Fuzzy Flow-type Classification System (FFCS) was developed to classify these patterns based only on image extracted features. Image acquisition and temperature measurements were simultaneously done. Experiments in natural circulation facility were adjusted to generate a series of characteristic two-phase flow instability periodic cycles. The facility is composed of a loop of glass tubes, a heat source using electrical heaters, a cold source using a helicoidal heat exchanger, a visualization section and thermocouples positioned over different loop sections. The instability cyclic period is estimated based on temperature measurements associated with the detection of a flow transition image pattern. FFCS shows good results provided that adequate image acquisition parameters and pre-processing adjustments are used.

The impact of traffic-flow patterns on air quality in urban street canyons

International Nuclear Information System (INIS)

Thaker, Prashant; Gokhale, Sharad

2016-01-01

We investigated the effect of different urban traffic-flow patterns on pollutant dispersion in different winds in a real asymmetric street canyon. Free-flow traffic causes more turbulence in the canyon facilitating more dispersion and a reduction in pedestrian level concentration. The comparison of with and without a vehicle-induced-turbulence revealed that when winds were perpendicular, the free-flow traffic reduced the concentration by 73% on the windward side with a minor increase of 17% on the leeward side, whereas for parallel winds, it reduced the concentration by 51% and 29%. The congested-flow traffic increased the concentrations on the leeward side by 47% when winds were perpendicular posing a higher risk to health, whereas reduced it by 17–42% for parallel winds. The urban air quality and public health can, therefore, be improved by improving the traffic-flow patterns in street canyons as vehicle-induced turbulence has been shown to contribute significantly to dispersion. - Highlights: • CFD is used to study impact of traffic-flow patterns on urban air quality. • Facilitating free-flow patterns induce more turbulence in street canyons. • Traffic-generated turbulence alters pollutant levels in urban street canyons. - This study investigates the effect of vehicle-induced-turbulence generated during free-flow traffic pattern in reduction of air pollutant concentrations in urban street canyons.

Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

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Gardner, Brian; Sporea, Ioana; Grüning, André

2015-12-01

Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we examine how multilayered networks of spiking neurons can learn to encode for input patterns using a fully temporal coding scheme. To this end, we introduce a new supervised learning rule, MultilayerSpiker, that can train spiking networks containing hidden layer neurons to perform transformations between spatiotemporal input and output spike patterns. The performance of the proposed learning rule is demonstrated in terms of the number of pattern mappings it can learn, the complexity of network structures it can be used on, and its classification accuracy when using multispike-based encodings. In particular, the learning rule displays robustness against input noise and can generalize well on an example data set. Our approach contributes to both a systematic understanding of how computations might take place in the nervous system and a learning rule that displays strong technical capability.

Effect of induced cross flow on flow pattern and performance of proton exchange membrane fuel cell

International Nuclear Information System (INIS)

Jiao, Kui; Bachman, John; Zhou, Yibo; Park, Jae Wan

2014-01-01

Highlights: • 3D numerical works to study the effect of cross flow on the PEMFC performance. • The cross flow ensure more evenly distributed water and oxygen in the CL. • The optimal net power output can be identified by controlling the back pressure. • Results confirm that present design is effective in improving performance. - Abstract: The cross flow in proton exchange membrane fuel cells (PEMFCs) plays an important role in changing the transport pattern and performance. In this study, three-dimensional numerical simulations are carried out to investigate the effect of induced cross flow on the flow pattern and performance of a PEMFC with a previously proposed and experimentally studied novel parallel flow channel design. The numerical results indicate that the liquid water and oxygen become more evenly distributed in the catalyst layer (CL) as the pressure difference between the low-pressure and high-pressure flow channels increases. It has been found that, in the low-pressure channels, the cross flow drives a convective flow from the CL to the flow channel resulting in improved liquid water removal. The optimal net power output can be identified by controlling the back pressure on the high-pressure flow channels. The numerical results confirm that this novel parallel flow channel design is effective in improving PEMFC performance

Velocity measurements and identification of the flow pattern of vertical air-water flows with light-beam detectors

International Nuclear Information System (INIS)

Luebbesmeyer, D.; Leoni, B.

1980-07-01

A new detector for measuring fluid velocities in two-phase flows by means of Noise-Analysis (especially Transient-Cross-Correlation-technique) has been developed. The detector utilizes a light-beam which is modulated by changes in the transparency of the two-phase flow. The results of nine measurements for different flow-regimes of vertical air/water-flows are shown. A main topic of these investigations was to answer the question if it is possible to identify the flow-pattern by looking at the shape of different 'Noise-Analytical-functions' (like APSD, CPSD, CCF etc.). The results prove that light-beam sensors are good detectors for fluid-velocity measurements in different flow regimes and in a wide range of fluid velocities starting with values of about 0.08 m/s up to values of 40 m/s. With respect to flow-pattern identification only the time-signals and the shape of the cross-power-density-function (CPSD) seem to be useful. (Auth.)

Assessment of theoretical flow pattern maps for vertical upward two-phase flow

International Nuclear Information System (INIS)

Khare, Rajesh; Vijayan, P.K.; Saha, D.; Venkat Raj, V.

1997-04-01

Taitel-Dukler (1980), Mishima-Ishii (1984) and Solbrig (1986) flow pattern maps have been assessed against an experimental data bank compiled from different sources. The data bank consisted of a total of 1411 data points with 368 bubbly, 474 slug/churn and 545 annular flow points, the rest being transition points. The data bank consisted of mainly steam water data; some amount of air-water data are included as there were no steam-water data at low pressure ( gs - U ls plane. (author)

Evaluation of flow volume and flow patterns in the patent false lumen of chronic aortic dissections using velocity-encoded cine magnetic resonance imaging

International Nuclear Information System (INIS)

Inoue, Toshihisa; Watanabe, Shigeru; Sakurada, Hideki; Ono, Katsuhiro; Urano, Miharu; Hijikata, Yasuyoshi; Saito, Isao; Masuda, Yoshiaki

2000-01-01

In 21 patients with chronic aortic dissections and proven patent false lumens, the flow volume and flow patterns in the patent false lumens was evaluated using velocity-encoded cine magnetic resonance imaging (VENC-MRI) and the relationship between the flow characteristics and aortic enlargement was retrospectively examined. Flow patterns in the false lumen were divided into 3 groups: pattern A with primarily antegrade flow (n=6), pattern R with primarily retrograde flow (n=3), and pattern B with bidirectional flow (n=12). In group A, the rate of flow volume in the false lumen compared to the total flow volume in true and false lumens (%TFV) and the average rate of enlargement of the maximum diameter of the dissected aorta per year (ΔD) were significantly greater than in groups R and B (%TFV: 74.1±0.07 vs 15.2±0.03 vs 11.8±0.04, p<0.01; ΔD: 3.62±0.82 vs 0 vs 0.58±0.15 mm/year, p<0.05, respectively). There was a significant correlation between %TFV and ΔD (r=0.79, p<0.0001). Evaluation of flow volume and flow patterns in the patent false lumen using VENC-MRI may be useful for predicting enlargement of the dissected aorta. (author)

Inspiratory flow pattern in humans.

Science.gov (United States)

Lafortuna, C L; Minetti, A E; Mognoni, P

1984-10-01

The theoretical estimation of the mechanical work of breathing during inspiration at rest is based on the common assumption that the inspiratory airflow wave is a sine function of time. Different analytical studies have pointed out that from an energetic point of view a rectangular wave is more economical than a sine wave. Visual inspection of inspiratory flow waves recorded during exercise in humans and various animals suggests that a trend toward a rectangular flow wave may be a possible systematic response of the respiratory system. To test this hypothesis, the harmonic content of inspiratory flow waves that were recorded in six healthy subjects at rest, during exercise hyperventilation, and during a maximum voluntary ventilation (MVV) maneuver were evaluated by a Fourier analysis, and the results were compared with those obtained on sinusoidal and rectangular models. The dynamic work inherent in the experimental waves and in the sine-wave model was practically the same at rest; during exercise hyperventilation and MVV, the experimental wave was approximately 16-20% more economical than the sinusoidal one. It was concluded that even though at rest the sinusoidal model is a reasonably good approximation of inspiratory flow, during exercise and MVV, a physiological controller is probably operating in humans that can select a more economical inspiratory pattern. Other peculiarities of airflow wave during hyperventilation and some optimization criteria are also discussed.

Structure of two-phase air-water flows. Study of average void fraction and flow patterns

International Nuclear Information System (INIS)

Roumy, R.

1969-01-01

This report deals with experimental work on a two phase air-water mixture in vertical tubes of different diameters. The average void fraction was measured in a 2 metre long test section by means of quick-closing valves. Using resistive probes and photographic techniques, we have determined the flow patterns and developed diagrams to indicate the boundaries between the various patterns: independent bubbles, agglomerated bubbles, slugs, semi-annular, annular. In the case of bubble flow and slug flow, it is shown that the relationship between the average void fraction and the superficial velocities of the phases is given by: V sg = f( ) * g(V sl ). The function g(V sl ) for the case of independent bubbles has been found to be: g(V sl ) = V sl + 20. For semi-annular and annular flow conditions; it appears that the average void fraction depends, to a first approximation only on the ratio V sg /V sl . (author) [fr

Analyzing Unsaturated Flow Patterns in Fractured Rock Using an Integrated Modeling Approach

International Nuclear Information System (INIS)

Y.S. Wu; G. Lu; K. Zhang; L. Pan; G.S. Bodvarsson

2006-01-01

Characterizing percolation patterns in unsaturated fractured rock has posed a greater challenge to modeling investigations than comparable saturated zone studies, because of the heterogeneous nature of unsaturated media and the great number of variables impacting unsaturated flow. This paper presents an integrated modeling methodology for quantitatively characterizing percolation patterns in the unsaturated zone of Yucca Mountain, Nevada, a proposed underground repository site for storing high-level radioactive waste. The modeling approach integrates a wide variety of moisture, pneumatic, thermal, and isotopic geochemical field data into a comprehensive three-dimensional numerical model for modeling analyses. It takes into account the coupled processes of fluid and heat flow and chemical isotopic transport in Yucca Mountain's highly heterogeneous, unsaturated fractured tuffs. Modeling results are examined against different types of field-measured data and then used to evaluate different hydrogeological conceptualizations and their results of flow patterns in the unsaturated zone. In particular, this model provides a much clearer understanding of percolation patterns and flow behavior through the unsaturated zone, both crucial issues in assessing repository performance. The integrated approach for quantifying Yucca Mountain's flow system is demonstrated to provide a practical modeling tool for characterizing flow and transport processes in complex subsurface systems

Patterns in clinical students' self-regulated learning behavior: a Q-methodology study.

Science.gov (United States)

Berkhout, Joris J; Teunissen, Pim W; Helmich, Esther; van Exel, Job; van der Vleuten, Cees P M; Jaarsma, Debbie A D C

2017-03-01

Students feel insufficiently supported in clinical environments to engage in active learning and achieve a high level of self-regulation. As a result clinical learning is highly demanding for students. Because of large differences between students, supervisors may not know how to support them in their learning process. We explored patterns in undergraduate students' self-regulated learning behavior in the clinical environment, to improve tailored supervision, using Q-methodology. Q-methodology uses features of both qualitative and quantitative methods for the systematic investigation of subjective issues by having participants sort statements along a continuum to represent their opinion. We enrolled 74 students between December 2014 and April 2015 and had them characterize their learning behavior by sorting 52 statements about self-regulated learning behavior and explaining their response. The statements used for the sorting were extracted from a previous study. The data was analyzed using by-person factor analysis to identify clusters of individuals with similar sorts of the statements. The resulting factors and qualitative data were used to interpret and describe the patterns that emerged. Five resulting patterns were identified in students' self-regulated learning behavior in the clinical environment, which we labelled: Engaged, Critically opportunistic, Uncertain, Restrained and Effortful. The five patterns varied mostly regarding goals, metacognition, communication, effort, and dependence on external regulation for learning. These discrete patterns in students' self-regulated learning behavior in the clinical environment are part of a complex interaction between student and learning context. The results suggest that developing self-regulated learning behavior might best be supported regarding individual students' needs.

Particle Swarm Optimization with Double Learning Patterns.

Science.gov (United States)

Shen, Yuanxia; Wei, Linna; Zeng, Chuanhua; Chen, Jian

2016-01-01

Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP) is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants.

Particle Swarm Optimization with Double Learning Patterns

Science.gov (United States)

Shen, Yuanxia; Wei, Linna; Zeng, Chuanhua; Chen, Jian

2016-01-01

Particle Swarm Optimization (PSO) is an effective tool in solving optimization problems. However, PSO usually suffers from the premature convergence due to the quick losing of the swarm diversity. In this paper, we first analyze the motion behavior of the swarm based on the probability characteristic of learning parameters. Then a PSO with double learning patterns (PSO-DLP) is developed, which employs the master swarm and the slave swarm with different learning patterns to achieve a trade-off between the convergence speed and the swarm diversity. The particles in the master swarm and the slave swarm are encouraged to explore search for keeping the swarm diversity and to learn from the global best particle for refining a promising solution, respectively. When the evolutionary states of two swarms interact, an interaction mechanism is enabled. This mechanism can help the slave swarm in jumping out of the local optima and improve the convergence precision of the master swarm. The proposed PSO-DLP is evaluated on 20 benchmark functions, including rotated multimodal and complex shifted problems. The simulation results and statistical analysis show that PSO-DLP obtains a promising performance and outperforms eight PSO variants. PMID:26858747

Involvement of Working Memory in College Students' Sequential Pattern Learning and Performance

Science.gov (United States)

Kundey, Shannon M. A.; De Los Reyes, Andres; Rowan, James D.; Lee, Bern; Delise, Justin; Molina, Sabrina; Cogdill, Lindsay

2013-01-01

When learning highly organized sequential patterns of information, humans and nonhuman animals learn rules regarding the hierarchical structures of these sequences. In three experiments, we explored the role of working memory in college students' sequential pattern learning and performance in a computerized task involving a sequential…

Different protein-protein interface patterns predicted by different machine learning methods.

Science.gov (United States)

Wang, Wei; Yang, Yongxiao; Yin, Jianxin; Gong, Xinqi

2017-11-22

Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.

Pattern recognition techniques for horizontal and vertically upward multiphase flow measurement

Science.gov (United States)

Arubi, Tesi I. M.; Yeung, Hoi

2012-03-01

The oil and gas industry need for high performing and low cost multiphase meters is ever more justified given the rapid depletion of conventional oil reserves that has led oil companies to develop smaller and marginal fields and reservoirs in remote locations and deep offshore, thereby placing great demands for compact and more cost effective solutions of on-line continuous multiphase flow measurement for well testing, production monitoring, production optimisation, process control and automation. The pattern recognition approach for clamp-on multiphase measurement employed in this study provides one means for meeting this need. High speed caesium-137 radioisotope-based densitometers were installed vertically at the top of a 50.8mm and 101.6mm riser as well as horizontally at the riser base in the Cranfield University multiphase flow test facility. A comprehensive experimental campaign comprising flow conditions typical of operating conditions found in the Petroleum Industry was conducted. The application of a single gamma densitometer unit, in conjunction with pattern recognition techniques to determine both the phase volume fractions and velocities to yield the individual phase flow rates of horizontal and vertically upward multiphase flows was investigated. The pattern recognition systems were trained to map the temporal fluctuations in the multiphase mixture density with the individual phase flow rates using statistical features extracted from the gamma counts signals as their inputs. Initial results yielded individual phase flow rate predictions to within ±5% relative error for the two phase airwater flows and ±10% for three phase air-oil-water flows data.

Influence of fast advective flows on pattern formation of Dictyostelium discoideum

Science.gov (United States)

Bae, Albert; Zykov, Vladimir; Bodenschatz, Eberhard

2018-01-01

We report experimental and numerical results on pattern formation of self-organizing Dictyostelium discoideum cells in a microfluidic setup under a constant buffer flow. The external flow advects the signaling molecule cyclic adenosine monophosphate (cAMP) downstream, while the chemotactic cells attached to the solid substrate are not transported with the flow. At high flow velocities, elongated cAMP waves are formed that cover the whole length of the channel and propagate both parallel and perpendicular to the flow direction. While the wave period and transverse propagation velocity are constant, parallel wave velocity and the wave width increase linearly with the imposed flow. We also observe that the acquired wave shape is highly dependent on the wave generation site and the strength of the imposed flow. We compared the wave shape and velocity with numerical simulations performed using a reaction-diffusion model and found excellent agreement. These results are expected to play an important role in understanding the process of pattern formation and aggregation of D. discoideum that may experience fluid flows in its natural habitat. PMID:29590179

Critical heat flux and flow pattern for water flow in annular geometry

International Nuclear Information System (INIS)

Park, J.-W.; Baek, W.-P.; Chang, S.H.

1997-01-01

An experimental study on critical heat flux (CHF) and two-phase flow visualization has been performed for water flow in internally-heated, vertical, concentric annuli under near atmospheric pressure. Tests have been done under stable forced-circulation, upward and downward flow conditions with three test sections of relatively large gap widths (heated length = 0.6 m, inner diameter 19 mm, outer diameter = 29, 35 and 51 mm). The outer wall of the test section was made up of the transparent Pyrex tube to allow the observation of flow patterns near the CHF occurrence. The CHF mechanism was changed in the order of flooding, churn-to-annular flow transition and local dryout under a large bubble in churn flow as the flow rate was increased from zero to higher values. Observed parametric trends are consistent with the previous understanding except that the CHF for downward flow is considerably lower than that for the upward flow. In addition to the experiment, selected CHF correlations for annuli are assessed based on 1156 experimental data from various sources. The Doerffer et al. (1994); Barnett (1966); Jannsen and Kervinen (1963); Levitan and Lantsman (1977) correlations show reasonable predictions for wide parameter ranges, among which the Doerffer et al. (1994) correlation shows the widest parameter ranges and a possibility of further improvement. However, there is no correlation predicting the low-pressure, low-flow CHF satisfactorily. (orig.)

Using artificial intelligence to improve identification of nanofluid gas–liquid two-phase flow pattern in mini-channel

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Jian Xiao

2018-01-01

Full Text Available This work combines fuzzy logic and a support vector machine (SVM with a principal component analysis (PCA to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas–liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

Using artificial intelligence to improve identification of nanofluid gas-liquid two-phase flow pattern in mini-channel

Science.gov (United States)

Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin

2018-01-01

This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

Flow Patterns and Thermal Drag in a One-Dimensional Inviscid Channel with Heating or Cooling

Institute of Scientific and Technical Information of China (English)

无

1993-01-01

In this paper investigations on the flow patterns and the thermal drag phenomenon in one -dimensional inviscid channel flow with heating or cooling are described and discussed:expressions of flow rate ratio and thermal drag coefficient for different flow patterns and its physical mechanism are presented.

Machine learning of the reactor core loading pattern critical parameters

International Nuclear Information System (INIS)

Trontl, K.; Pevec, D.; Smuc, T.

2007-01-01

The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employed a recently introduced machine learning technique, Support Vector Regression (SVR), which has a strong theoretical background in statistical learning theory. Superior empirical performance of the method has been reported on difficult regression problems in different fields of science and technology. SVR is a data driven, kernel based, nonlinear modelling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modelling. The starting set of experimental data for training and testing of the machine learning algorithm was obtained using a two-dimensional diffusion theory reactor physics computer code. We illustrate the performance of the solution and discuss its applicability, i.e., complexity, speed and accuracy, with a projection to a more realistic scenario involving machine learning from the results of more accurate and time consuming three-dimensional core modelling code. (author)

A study on effects of cash flow patterns and auditors’ opinions in predicting financial distress

Directory of Open Access Journals (Sweden)

Fatemeh Namvar

2013-07-01

Full Text Available Bankruptcy has been one of the most important issues among investors in stock market and there are literally different techniques for predicting bankruptcy. In this paper, we study on effects of cash flow patterns and auditors’ opinions in predicting financial distress on some 80 selected firms traded on Tehran Stock Exchange over the period 2005-2011. In this study, the combination of cash flow patterns represent firm’s resource allocations and operational capabilities interacted with their strategy choices. In additions, predictions about each individual cash flow components, operational, investment, financial, are derived from economic theory, which forms a basis for the life proxy. We use cash flow patterns in the decline stage and compare the results with auditors’ opinions. The results indicate that cash flow patterns could predict financial distress companies in Iran. In addition, the effective cash flow patterns in predicting financial distress is more than auditors’ feedbacks.

Supervised Learning for Visual Pattern Classification

Science.gov (United States)

Zheng, Nanning; Xue, Jianru

This chapter presents an overview of the topics and major ideas of supervised learning for visual pattern classification. Two prevalent algorithms, i.e., the support vector machine (SVM) and the boosting algorithm, are briefly introduced. SVMs and boosting algorithms are two hot topics of recent research in supervised learning. SVMs improve the generalization of the learning machine by implementing the rule of structural risk minimization (SRM). It exhibits good generalization even when little training data are available for machine training. The boosting algorithm can boost a weak classifier to a strong classifier by means of the so-called classifier combination. This algorithm provides a general way for producing a classifier with high generalization capability from a great number of weak classifiers.

Flow regime and deposition pattern of evaporating binary mixture droplet suspended with particles.

Science.gov (United States)

Zhong, Xin; Duan, Fei

2016-02-01

The flow regimes and the deposition pattern have been investigated by changing the ethanol concentration in a water-based binary mixture droplet suspended with alumina nanoparticles. To visualize the flow patterns, Particle Image Velocimetry (PIV) has been applied in the binary liquid droplet containing the fluorescent microspheres. Three distinct flow regimes have been revealed in the evaporation. In Regime I, the vortices and chaotic flows are found to carry the particles to the liquid-vapor interface and to promote the formation of particle aggregation. The aggregates move inwards in Regime II as induced by the Marangoni flow along the droplet free surface. Regime III is dominated by the drying of the left water and the capillary flow driving particles radially outward is observed. The relative weightings of Regimes I and II, which are enhanced with an increasing load of ethanol, determine the motion of the nanoparticles and the formation of the final drying pattern.

An active, collaborative approach to learning skills in flow cytometry.

Science.gov (United States)

Fuller, Kathryn; Linden, Matthew D; Lee-Pullen, Tracey; Fragall, Clayton; Erber, Wendy N; Röhrig, Kimberley J

2016-06-01

Advances in science education research have the potential to improve the way students learn to perform scientific interpretations and understand science concepts. We developed active, collaborative activities to teach skills in manipulating flow cytometry data using FlowJo software. Undergraduate students were given compensated clinical flow cytometry listmode output (FCS) files and asked to design a gating strategy to diagnose patients with different hematological malignancies on the basis of their immunophenotype. A separate cohort of research trainees was given uncompensated data files on which they performed their own compensation, calculated the antibody staining index, designed a sequential gating strategy, and quantified rare immune cell subsets. Student engagement, confidence, and perceptions of flow cytometry were assessed using a survey. Competency against the learning outcomes was assessed by asking students to undertake tasks that required understanding of flow cytometry dot plot data and gating sequences. The active, collaborative approach allowed students to achieve learning outcomes not previously possible with traditional teaching formats, for example, having students design their own gating strategy, without forgoing essential outcomes such as the interpretation of dot plots. In undergraduate students, favorable perceptions of flow cytometry as a field and as a potential career choice were correlated with student confidence but not the ability to perform flow cytometry data analysis. We demonstrate that this new pedagogical approach to teaching flow cytometry is beneficial for student understanding and interpretation of complex concepts. It should be considered as a useful new method for incorporating complex data analysis tasks such as flow cytometry into curricula. Copyright © 2016 The American Physiological Society.

Systematic Assessment of the Impact of User Roles on Network Flow Patterns

Science.gov (United States)

2017-09-01

a system at IP address c_IPj can be expressed as D[ui][c_ip j]. Specifying use of a specific protocol ( prk ), server port (spl) and distant end IP...address (e_ipm) can be expressed as D[ui][c_ip j][ prk ][spl][e_ipm]. 3.2 Patterns Within Flow Sets We define patterns within a set of Netflow records as...address, protocol, server port, and endpoint IP address (D[ui][c_ip j][ prk ][spl][e_ipm]) we identified sequential flow pairs, matching each flow with

Spatio-temporal flow maps for visualizing movement and contact patterns

Directory of Open Access Journals (Sweden)

Bing Ni

2017-03-01

Full Text Available The advanced telecom technologies and massive volumes of intelligent mobile phone users have yielded a huge amount of real-time data of people’s all-in-one telecommunication records, which we call telco big data. With telco data and the domain knowledge of an urban city, we are now able to analyze the movement and contact patterns of humans in an unprecedented scale. Flow map is widely used to display the movements of humans from one single source to multiple destinations by representing locations as nodes and movements as edges. However, it fails the task of visualizing both movement and contact data. In addition, analysts often need to compare and examine the patterns side by side, and do various quantitative analysis. In this work, we propose a novel spatio-temporal flow map layout to visualize when and where people from different locations move into the same places and make contact. We also propose integrating the spatiotemporal flow maps into existing spatiotemporal visualization techniques to form a suite of techniques for visualizing the movement and contact patterns. We report a potential application the proposed techniques can be applied to. The results show that our design and techniques properly unveil hidden information, while analysis can be achieved efficiently. Keywords: Spatio-temporal data, Flow map, Urban mobility

Effects of rainfall patterns and land cover on the subsurface flow generation of sloping Ferralsols in southern China.

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Jian Duan

Full Text Available Rainfall patterns and land cover are two important factors that affect the runoff generation process. To determine the surface and subsurface flows associated with different rainfall patterns on sloping Ferralsols under different land cover types, observational data related to surface and subsurface flows from 5 m × 15 m plots were collected from 2010 to 2012. The experiment was conducted to assess three land cover types (grass, litter cover and bare land in the Jiangxi Provincial Soil and Water Conservation Ecological Park. During the study period, 114 natural rainfall events produced subsurface flow and were divided into four groups using k-means clustering according to rainfall duration, rainfall depth and maximum 30-min rainfall intensity. The results showed that the total runoff and surface flow values were highest for bare land under all four rainfall patterns and lowest for the covered plots. However, covered plots generated higher subsurface flow values than bare land. Moreover, the surface and subsurface flows associated with the three land cover types differed significantly under different rainfall patterns. Rainfall patterns with low intensities and long durations created more subsurface flow in the grass and litter cover types, whereas rainfall patterns with high intensities and short durations resulted in greater surface flow over bare land. Rainfall pattern I had the highest surface and subsurface flow values for the grass cover and litter cover types. The highest surface flow value and lowest subsurface flow value for bare land occurred under rainfall pattern IV. Rainfall pattern II generated the highest subsurface flow value for bare land. Therefore, grass or litter cover are able to convert more surface flow into subsurface flow under different rainfall patterns. The rainfall patterns studied had greater effects on subsurface flow than on total runoff and surface flow for covered surfaces, as well as a greater effect on surface

Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

Science.gov (United States)

Schäfer, Mirko; Tranberg, Bo; Hempel, Sabrina; Schramm, Stefan; Greiner, Martin

2017-08-01

The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

4D flow MRI assessment of right atrial flow patterns in the normal heart - influence of caval vein arrangement and implications for the patent foramen ovale.

Directory of Open Access Journals (Sweden)

Jehill D Parikh

Full Text Available To investigate atrial flow patterns in the normal adult heart, to explore whether caval vein arrangement and patency of the foramen ovale (PFO may be associated with flow pattern.Time-resolved, three-dimensional velocity encoded magnetic resonance imaging (4D flow was employed to assess atrial flow patterns in thirteen healthy subjects (6 male, 40 years, range 25-50 and thirteen subjects (6 male, 40 years, range 21-50 with cryptogenic stroke and patent foramen ovale (CS-PFO. Right atrial flow was defined as vortical, helico-vortical, helical and multiple vortices. Time-averaged and peak systolic and diastolic flows in the caval and pulmonary veins and their anatomical arrangement were compared.A spectrum of right atrial flow was observed across the four defined categories. The right atrial flow patterns were strongly associated with the relative position of the caval veins. Right atrial flow patterns other than vortical were more common (p = 0.015 and the separation between the superior and inferior vena cava greater (10±5mm versus 3±3mm, p = 0.002 in the CS-PFO group. In the left atrium all subjects except one had counter-clockwise vortical flow. Vortex size varied and was associated with left lower pulmonary vein flow (systolic r = 0.61, p = 0.001, diastolic r = 0.63 p = 0.002. A diastolic vortex was less common and time-averaged left atrial velocity was greater in the CS-PFO group (17±2cm/sec versus 15±1, p = 0.048. One CS-PFO subject demonstrated vortical retrograde flow in the descending aortic arch; all other subjects had laminar descending aortic flow.Right atrial flow patterns in the normal heart are heterogeneous and are associated with the relative position of the caval veins. Patterns, other than 'typical' vortical flow, are more prevalent in the right atrium of those with cryptogenic stroke in the context of PFO. Left atrial flow patterns are more homogenous in normal hearts and show a relationship with flow arising from the left

A study of flow patterns for staggered cylinders at low Reynolds number by spectral element method

Energy Technology Data Exchange (ETDEWEB)

Hsu, Li-Chieh; Chen, Chien-Lin; Ye, Jian-Zhi [National Yunlin University of Science and Technology, Taiwan (China)

2017-06-15

This study investigates the pattern of flow past two staggered array cylinders using the spectral element method by varying the distance between the cylinders and the angle of incidence (α) at low Reynolds numbers (Re = 100-800). Six flow patterns are identified as Shear layer reattachment (SLR), Induced separation (IS), Vortex impingement (VI), Synchronized vortex shedding (SVS), Vortex pairing and enveloping (VPE), and Vortex pairing splitting and enveloping (VPSE). These flow patterns can be transformed from one to another by changing the distance between the cylinders, the angle of incidence, or Re. SLR, IS and VI flow patterns appear in regimes with small angles of incidence (i.e., α ≤ 30° ) and hold only a single von Karman vortex shedding in a wake with one shedding frequency. SVS, VPE and VPSE flow patterns appear in regimes with large angles of incidence (i.e., 30° ≤ α ≤ 50° ) and present two synchronized von Karman vortices. Quantitative analyses and physical interpretation are also conducted to determine the generation mechanisms of the said flow patterns.

Investigating flow patterns in a channel with complex obstacles using the lattice Boltzmann method

Energy Technology Data Exchange (ETDEWEB)

Yojina, Jiraporn; Ngamsaad, Waipot; Nuttavut, Narin; Triampo, Darapond; Lenbury, Yongwimon; Sriyab, Somchai; Triampo, Wannapong [Faculty of Science, Mahidol University, Bangkok (Thailand); Kanthang, Paisan [Rajamangala University of Technology, Bangkok (Thailand)

2010-10-15

In this work, mesoscopic modeling via a computational lattice Boltzmann method (LBM) is used to investigate the flow pattern phenomena and the physical properties of the flow field around one and two square obstacles inside a two-dimensional channel with a fixed blockage ratio,{beta} =14 , centered inside a 2D channel, for a range of Reynolds numbers (Re) from 1 to 300. The simulation results show that flow patterns can initially exhibit laminar flow at low Re and then make a transition to periodic, unsteady, and, finally, turbulent flow as the Re get higher. Streamlines and velocity profiles and a vortex shedding pattern are observed. The Strouhal numbers are calculated to characterize the shedding frequency and flow dynamics. The effect of the layouts or configurations of the obstacles are also investigated, and the possible connection between the mixing process and the appropriate design of a chemical mixing system is discussed

The Role of Statistical Learning and Working Memory in L2 Speakers' Pattern Learning

Science.gov (United States)

McDonough, Kim; Trofimovich, Pavel

2016-01-01

This study investigated whether second language (L2) speakers' morphosyntactic pattern learning was predicted by their statistical learning and working memory abilities. Across three experiments, Thai English as a Foreign Language (EFL) university students (N = 140) were exposed to either the transitive construction in Esperanto (e.g., "tauro…

Individual Difference Factors in the Learning and Transfer of Patterning Discriminations

Directory of Open Access Journals (Sweden)

Elisa Maes

2017-07-01

Full Text Available In an associative patterning task, some people seem to focus more on learning an overarching rule, whereas others seem to focus on acquiring specific relations between the stimuli and outcomes involved. Building on earlier work, we further investigated which cognitive factors are involved in feature- vs. rule-based learning and generalization. To this end, we measured participants' tendency to generalize according to the rule of opposites after training on negative and positive patterning problems (i.e., A+/B+/AB− and C−/D−/CD+, their tendency to attend to global aspects or local details of stimuli, their systemizing disposition and their score on the Raven intelligence test. Our results suggest that while intelligence might have some influence on patterning learning and generalization, visual processing style and systemizing disposition do not. We discuss our findings in the light of previous observations on patterning.

Patterns in Elementary School Students' Strategic Actions in Varying Learning Situations

Science.gov (United States)

Malmberg, Jonna; Järvenoja, Hanna; Järvelä, Sanna

2013-01-01

This study uses log file traces to examine differences between high-and low-achieving students' strategic actions in varying learning situations. In addition, this study illustrates, in detail, what strategic and self-regulated learning constitutes in practice. The study investigates the learning patterns that emerge in learning situations…

An Examination of Game-Based Learning from Theories of Flow Experience and Cognitive Load

Science.gov (United States)

Lai, Chih-Hung; Chu, Chih-Ming; Liu, Hsiang-Hsuan; Yang, Shun-Bo; Chen, Wei-Hsuan

2013-01-01

This study aims to discuss whether game-based learning with the integration of games and digital learning could enhance not only the flow experience in learning but achieve the same flow experience in pure games. In addition, the authors discovered that whether the game-based learning could make learners to reveal higher cognitive load. The…

Drag Reduction of an Airfoil Using Deep Learning

Science.gov (United States)

Jiang, Chiyu; Sun, Anzhu; Marcus, Philip

2017-11-01

We reduced the drag of a 2D airfoil by starting with a NACA-0012 airfoil and used deep learning methods. We created a database which consists of simulations of 2D external flow over randomly generated shapes. We then developed a machine learning framework for external flow field inference given input shapes. Past work which utilized machine learning in Computational Fluid Dynamics focused on estimations of specific flow parameters, but this work is novel in the inference of entire flow fields. We further showed that learned flow patterns are transferable to cases that share certain similarities. This study illustrates the prospects of deeper integration of data-based modeling into current CFD simulation frameworks for faster flow inference and more accurate flow modeling.

Effect of Flood Water Diffuser on Flow Pattern of Water during Road Crossing

Directory of Open Access Journals (Sweden)

Abdul Ghani A.N.

2014-03-01

Full Text Available One of the methods to reduce the velocity of flood water flow across roads is to design obstacle objects as diffusers and place them alongside the road shoulder. The velocity reduction of water flow depends on the diffusion pattern of water. The pattern of diffused water depends on the design of the obstacle objects. The main purpose of this study is to investigate the design of obstacle objects and their water diffusing patterns and their capability to reduce the velocity of the flood water flow during road crossing. Variety of designs and orientation of the obstacle objects were tested in the environmental laboratory on a scale of 1:20. The results are classified into three distinguishable patterns of diffusion. Finally, two diffuser shapes and arrangements are recommended for further investigations in full scale or CFD model.

The use of magnetic resonance imaging to quantify multi-phase flow patterns and transitions

International Nuclear Information System (INIS)

Reyes, J.N. Jr.; Lafi, A.Y.; Saloner, D.

1998-01-01

Conventional measurement techniques have given limited insights into the complex structure of multi-phase flows. This has led to highly subjective flow pattern classifications which have been cast in terms of flow regime maps. Rather than using static flow regime maps, some of the next generation of multi-phase flow analysis codes will implement interfacial area transport equations that would calculate the flow patterns that evolve spatially and temporally. To assess these new codes, a large data base needs to be established to quantify the essential characteristics of multi-phase flow structure. One such characteristic is the interfacial area concentration. In this paper, we discuss the current benefits and limitations of using Magnetic Resonance Imaging (MRI) to examine multi- phase flow patterns and transitions. Of particular interest, are the MRI measurements of interfacial area concentration for slug flow in an air-water system. These tests were performed at the University of California, San Francisco (UCSF) School of Medicine MRI Center as a collaborative research effort with Oregon State University (OSU). The special scanning sequences designed by UCSF were capable of imaging at repetition intervals as fast as 7 milliseconds. (author)

The use of magnetic resonance imaging to quantify multi-phase flow patterns and transitions

Energy Technology Data Exchange (ETDEWEB)

Reyes, Jr, J N; Lafi, A Y [Department of Nuclear Engineering, Oregon State University, Corvallis, OR (United States); Saloner, D [University of California, San Francisco School of Medicine, Veterans Administration Medical Center, San Francisco, CA (United States)

1998-09-01

Conventional measurement techniques have given limited insights into the complex structure of multi-phase flows. This has led to highly subjective flow pattern classifications which have been cast in terms of flow regime maps. Rather than using static flow regime maps, some of the next generation of multi-phase flow analysis codes will implement interfacial area transport equations that would calculate the flow patterns that evolve spatially and temporally. To assess these new codes, a large data base needs to be established to quantify the essential characteristics of multi-phase flow structure. One such characteristic is the interfacial area concentration. In this paper, we discuss the current benefits and limitations of using Magnetic Resonance Imaging (MRI) to examine multi- phase flow patterns and transitions. Of particular interest, are the MRI measurements of interfacial area concentration for slug flow in an air-water system. These tests were performed at the University of California, San Francisco (UCSF) School of Medicine MRI Center as a collaborative research effort with Oregon State University (OSU). The special scanning sequences designed by UCSF were capable of imaging at repetition intervals as fast as 7 milliseconds. (author)

An artificial intelligence based improved classification of two-phase flow patterns with feature extracted from acquired images.

Science.gov (United States)

Shanthi, C; Pappa, N

2017-05-01

Flow pattern recognition is necessary to select design equations for finding operating details of the process and to perform computational simulations. Visual image processing can be used to automate the interpretation of patterns in two-phase flow. In this paper, an attempt has been made to improve the classification accuracy of the flow pattern of gas/ liquid two- phase flow using fuzzy logic and Support Vector Machine (SVM) with Principal Component Analysis (PCA). The videos of six different types of flow patterns namely, annular flow, bubble flow, churn flow, plug flow, slug flow and stratified flow are recorded for a period and converted to 2D images for processing. The textural and shape features extracted using image processing are applied as inputs to various classification schemes namely fuzzy logic, SVM and SVM with PCA in order to identify the type of flow pattern. The results obtained are compared and it is observed that SVM with features reduced using PCA gives the better classification accuracy and computationally less intensive than other two existing schemes. This study results cover industrial application needs including oil and gas and any other gas-liquid two-phase flows. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Two-phase flow patterns and their relationship to two-phase heat transfer

International Nuclear Information System (INIS)

Hewitt, G.F.

1977-01-01

The objective of this lecture was to discuss the general nature of two phase flows, to define the various regimes of flow and to discuss the influence of these regimes on the heat transfer processes taking place. The methods of regime delineation are briefly described and regime descriptions introduced for both vertical and horizontal flows in tubes. ''Flow regime maps'' have been widely used as an aid to determination of the regime which occurs in a given situation. Some of the more widely used maps are described and the limitations of this approach discussed. There have been many attempts to obtain a better phenomenological description of two phase flow patterns. In this lecture, these attempts will be reviewed in the context of the bubble/plug, plug/churn and churn/annular flow transitions in vertical flow. The latter two transitions are related to the flooding/flow reversal phenomena. For horizontal flows, recent work on the onset of slugging will be reviewed. In flows with evaporation or condensation, the situation is influenced by departures from thermodynamic equilibrium and the types of departure observed are discuss briefly. Flow patterns and their relationships with heat transfer regimes are then reviewed for the case of condensation in horizontal tubes and evaporation in vertical tubes

Parametric study of flow patterns behind the standing accretion shock wave for core-collapse supernovae

Energy Technology Data Exchange (ETDEWEB)

Iwakami, Wakana; Nagakura, Hiroki [Yukawa Institute for Theoretical Physics, Kyoto University, Oiwake-cho, Kitashirakawa, Sakyo-ku, Kyoto 606-8502 (Japan); Yamada, Shoichi, E-mail: wakana@heap.phys.waseda.ac.jp [Advanced Research Institute for Science and Engineering, Waseda University, 3-4-1, Okubo, Shinjuku, Tokyo 169-8555 (Japan)

2014-05-10

In this study, we conduct three-dimensional hydrodynamic simulations systematically to investigate the flow patterns behind the accretion shock waves that are commonly formed in the post-bounce phase of core-collapse supernovae. Adding small perturbations to spherically symmetric, steady, shocked accretion flows, we compute the subsequent evolutions to find what flow pattern emerges as a consequence of hydrodynamical instabilities such as convection and standing accretion shock instability for different neutrino luminosities and mass accretion rates. Depending on these two controlling parameters, various flow patterns are indeed realized. We classify them into three basic patterns and two intermediate ones; the former includes sloshing motion (SL), spiral motion (SP), and multiple buoyant bubble formation (BB); the latter consists of spiral motion with buoyant-bubble formation (SPB) and spiral motion with pulsationally changing rotational velocities (SPP). Although the post-shock flow is highly chaotic, there is a clear trend in the pattern realization. The sloshing and spiral motions tend to be dominant for high accretion rates and low neutrino luminosities, and multiple buoyant bubbles prevail for low accretion rates and high neutrino luminosities. It is interesting that the dominant pattern is not always identical between the semi-nonlinear and nonlinear phases near the critical luminosity; the intermediate cases are realized in the latter case. Running several simulations with different random perturbations, we confirm that the realization of flow pattern is robust in most cases.

Effect of solar chimney inclination angle on space flow pattern and ventilation rate

Energy Technology Data Exchange (ETDEWEB)

Bassiouny, Ramadan; Korah, Nader S.A. [Department of Mechanical Power Engineering and Energy, Minia University, Minia 61111 (Egypt)

2009-02-15

The solar chimney is a simple and practical idea that is applied to enhance space natural ventilation. The chimney could be vertical or inclined. The chimney inclination angle is an important parameter that greatly affects space flow pattern and ventilation rate. In the present study, the effect of chimney inclination angle on air change per hour and indoor flow pattern was numerically and analytically investigated. A numerical simulation using Ansys, a FEM-based code, was used to predict flow pattern. Then the results were compared with published experimental measurements. A FORTRAN program was developed to iteratively solve the mathematical model that was obtained through an overall energy balance on the solar chimney. The analytical results showed that an optimum air flow rate value was achieved when the chimney inclination is between 45 and 70 for latitude of 28.4 . The numerically predicted flow pattern inside the space supports this finding. Moreover, in the present study a correlation to predict the air change per hour was developed. The correlation was tested within a solar intensity greater than or equal to 500 W/m{sup 2}, and chimney width from 0.1 m to 0.35 m for different inclination angles with acceptable values. (author)

Patterns of Internet Usage: Learning Sphere and the Socio-cultural Context

Directory of Open Access Journals (Sweden)

Hossein Ebrahimabadi

2009-11-01

Full Text Available In addition to the curriculum and the learning targets, there are some other points –as “the culture of the real life”, “patterns of communication and virtual-life’s experiencing”, and generally “pattern of communication and internet usage”- should be considered in evaluating internet. Applying results of a survey on the impacts of both the web-based and the traditional educational methods on students’ learning and motivation, the present study explores the patterns of internet usage. Research method is experimental, using the t test for independent groups and analyzing multi-variable regression, and some points as the population, method of sampling and data gathering is explained in the article. Results show that there is a meaningful difference between the grades of the test group and the witness group; thus variable of “the internet usage” could predict changes in learning. In other words, supra-usage of internet would decrease learning and curriculum development. However, using internet for scientific and schooling would cause students to correlate their patterns of computer and internet usage. As results show, decline in entertaining usage of internet is related to the socio-cultural context, way and amount of participating in the web, and the quality of virtual learning sphere, rather than the interest or disinterest of the users.

Velocity bias induced by flow patterns around ADCPs and associated deployment platforms

Science.gov (United States)

Mueller, David S.

2015-01-01

Velocity measurements near the Acoustic Doppler Current Profiler (ADCP) are important for mapping surface currents, measuring velocity and discharge in shallow streams, and providing accurate estimates of discharge in the top unmeasured portion of the water column. Improvements to ADCP performance permit measurement of velocities much closer (5 cm) to the transducer than has been possible in the past (25 cm). Velocity profiles collected by the U.S. Geological Survey (USGS) with a 1200 kHz Rio Grande Zedhead ADCP in 2002 showed a negative bias in measured velocities near the transducers. On the basis of these results, the USGS initiated a study combining field, laboratory, and numerical modeling data to assess the effect of flow patterns caused by flow around the ADCP and deployment platforms on velocities measured near the transducers. This ongoing study has shown that the negative bias observed in the field is due to the flow pattern around the ADCP. The flow pattern around an ADCP violates the basic assumption of flow homogeneity required for an accurate three-dimensional velocity solution. Results, to date (2014), have indicated velocity biases within the measurable profile, due to flow disturbance, for the TRDI 1200 kHz Rio Grande Zedhead and the SonTek RiverSurveyor M9 ADCPs. The flow speed past the ADCP, the mount and the deployment platform have also been shown to play an important role in the magnitude and extent of the velocity bias.

Possible effects of two-phase flow pattern on the mechanical behavior of mudstones

Science.gov (United States)

Goto, H.; Tokunaga, T.; Aichi, M.

2016-12-01

To investigate the influence of two-phase flow pattern on the mechanical behavior of mudstones, laboratory experiments were conducted. In the experiment, air was injected from the bottom of the water-saturated Quaternary Umegase mudstone sample under hydrostatic external stress condition. Both axial and circumferential strains at half the height of the sample and volumetric discharge of water at the outlet were monitored during the experiment. Numerical simulation of the experiment was tried by using a simulator which can solve coupled two-phase flow and poroelastic deformation assuming the extended-Darcian flow with relative permeability and capillary pressure as functions of the wetting-phase fluid saturation. In the numerical simulation, the volumetric discharge of water was reproduced well while both strains were not. Three dimensionless numbers, i.e., the viscosity ratio, the Capillary number, and the Bond number, which characterize the two-phase flow pattern (Lenormand et al., 1988; Ewing and Berkowitz, 1998) were calculated to be 2×10-2, 2×10-11, and 7×10-11, respectively, in the experiment. Because the Bond number was quite small, it was possible to apply Lenormand et al. (1988)'s diagram to evaluate the flow regime, and the flow regime was considered to be capillary fingering. While, in the numerical simulation, air moved uniformly upward with quite low non-wetting phase saturation conditions because the fluid flow obeyed the two-phase Darcy's law. These different displacement patterns developed in the experiment and assumed in the numerical simulation were considered to be the reason why the deformation behavior observed in the experiment could not be reproduced by numerical simulation, suggesting that the two-phase flow pattern could affect the changes of internal fluid pressure patterns during displacement processes. For further studies, quantitative analysis of the experimental results by using a numerical simulator which can solve the coupled

Pattern formation and three-dimensional instability in rotating flows

Science.gov (United States)

Christensen, Erik A.; Aubry, Nadine; Sorensen, Jens N.

1997-03-01

A fluid flow enclosed in a cylindrical container where fluid motion is created by the rotation of one end wall as a centrifugal fan is studied. Direct numerical simulations and spatio-temporal analysis have been performed in the early transition scenario, which includes a steady-unsteady transition and a breakdown of axisymmetric to three-dimensional flow behavior. In the early unsteady regime of the flow, the central vortex undergoes a vertical beating motion, accompanied by axisymmetric spikes formation on the edge of the breakdown bubble. As traveling waves, the spikes move along the central vortex core toward the rotating end-wall. As the Reynolds number is increased further, the flow undergoes a three-dimensional instability. The influence of the latter on the previous patterns is studied.

Characterizing Groundwater Level and Flow Pattern in a Shallow ...

African Journals Online (AJOL)

Bheema

This study characterize groundwater yield and flow pattern on a shallow ... simple process of weathering, fractured fissure systems, networks of joints and ..... lowest yield in wells that are deeper than the mean well depth in the study area.

Exploring the roles of interaction and flow in explaining nurses' e-learning acceptance.

Science.gov (United States)

Cheng, Yung-Ming

2013-01-01

To provide safe and competent patient care, it is very important that medical institutions should provide nurses with continuing education by using appropriate learning methods. As compared to traditional learning, electronic learning (e-learning) is a more flexible method for nurses' in-service learning. Hence, e-learning is expected to play a pivotal role in providing continuing education for nurses. This study's purpose was to explore the role and relevance of interaction factors, intrinsic motivator (i.e., flow), and extrinsic motivators (i.e., perceived usefulness (PU) and perceived ease of use (PEOU)) in explaining nurses' intention to use the e-learning system. Based on the technology acceptance model (TAM) with the flow theory, this study's research model presents three types of interaction factors, learner-system interaction, instructor-learner interaction, and learner-learner interaction to construct an extended TAM to explore nurses' intention to use the e-learning system. Sample data were gathered from nurses at two regional hospitals in Taiwan. A total of 320 questionnaires were distributed, 254 (79.375%) questionnaires were returned. Consequently, 218 usable questionnaires were analyzed in this study, with a usable response rate of 68.125%. First, confirmatory factor analysis was used to develop the measurement model. Second, to explore the causal relationships among all constructs, the structural model for the research model was tested by using structural equation modeling. First, learner-system interaction, instructor-learner interaction, and learner-learner interaction respectively had significant effects on PU, PEOU, and flow. Next, flow had significant effects on PU and PEOU, and PEOU had a significant effect on PU. Finally, the effects of flow, PU, and PEOU on intention to use were significant. Synthetically speaking, learner-system interaction, instructor-learner interaction, and learner-learner interaction can indirectly make significant

Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning

Directory of Open Access Journals (Sweden)

Md. Abdullah-al-mamun

2015-08-01

Full Text Available Abstract Humans are capable to identifying diverse shape in the different pattern in the real world as effortless fashion due to their intelligence is grow since born with facing several learning process. Same way we can prepared an machine using human like brain called Artificial Neural Network that can be recognize different pattern from the real world object. Although the various techniques is exists to implementation the pattern recognition but recently the artificial neural network approaches have been giving the significant attention. Because the approached of artificial neural network is like a human brain that is learn from different observation and give a decision the previously learning rule. Over the 50 years research now a days pattern recognition for machine learning using artificial neural network got a significant achievement. For this reason many real world problem can be solve by modeling the pattern recognition process. The objective of this paper is to present the theoretical concept for pattern recognition design using Multi-Layer Perceptorn neural networkin the algorithm of artificial Intelligence as the best possible way of utilizing available resources to make a decision that can be a human like performance.

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

Science.gov (United States)

Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio

2015-07-08

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.

Relationship between spontaneous expiratory flow-volume curve pattern and air-flow obstruction in elderly COPD patients.

Science.gov (United States)

Nozoe, Masafumi; Mase, Kyoshi; Murakami, Shigefumi; Okada, Makoto; Ogino, Tomoyuki; Matsushita, Kazuhiro; Takashima, Sachie; Yamamoto, Noriyasu; Fukuda, Yoshihiro; Domen, Kazuhisa

2013-10-01

Assessment of the degree of air-flow obstruction is important for determining the treatment strategy in COPD patients. However, in some elderly COPD patients, measuring FVC is impossible because of cognitive dysfunction or severe dyspnea. In such patients a simple test of airways obstruction requiring only a short run of tidal breathing would be useful. We studied whether the spontaneous expiratory flow-volume (SEFV) curve pattern reflects the degree of air-flow obstruction in elderly COPD patients. In 34 elderly subjects (mean ± SD age 80 ± 7 y) with stable COPD (percent-of-predicted FEV(1) 39.0 ± 18.5%), and 12 age-matched healthy subjects, we measured FVC and recorded flow-volume curves during quiet breathing. We studied the SEFV curve patterns (concavity/convexity), spirometry results, breathing patterns, and demographics. The SEFV curve concavity/convexity prediction accuracy was examined by calculating the receiver operating characteristic curves, cutoff values, area under the curve, sensitivity, and specificity. Fourteen subjects with COPD had a concave SEFV curve. All the healthy subjects had convex SEFV curves. The COPD subjects who had concave SEFV curves often had very severe airway obstruction. The percent-of-predicted FEV(1)% (32.4%) was the most powerful SEFV curve concavity predictor (area under the curve 0.92, 95% CI 0.83-1.00), and had the highest sensitivity (0.93) and specificity (0.88). Concavity of the SEFV curve obtained during tidal breathing may be a useful test for determining the presence of very severe obstruction in elderly patients unable to perform a satisfactory FVC maneuver.

CFD simulation of flow pattern in a bubble column reactor for forming aerobic granules and its development.

Science.gov (United States)

Fan, Wenwen; Yuan, LinJiang; Li, Yonglin

2018-06-04

The flow pattern is considered to play an important role in the formation of aerobic granular sludge in a bubble column reactor; therefore, it is necessary to understand the behavior of the flow in the reactor. A three-dimensional computational fluid dynamics (CFD) simulation for bubble column reactor was established to visualize the flow patterns of two-phase air-liquid flow and three-phase air-liquid-sludge flow under different ratios of height to diameter (H/D ratio) and superficial gas upflow velocities (SGVs). Moreover, a simulation of the three-phase flow pattern at the same SGV and different characteristics of the sludge was performed in this study. The results show that not only SGV but also properties of sludge involve the transformation of flow behaviors and relative velocity between liquid and sludge. For the original activated sludge floc to cultivate aerobic granules, the flow pattern has nothing to do with sludge, but is influenced by SGV, and the vortices is occurred and the relative velocity is increased with an increase in SGV; the two-phase flow can simplify the three-phase flow that predicts the flow pattern development in bubble column reactor (BCR) for aerobic granulation. For the aerobic granules, the liquid flow behavior developed from the symmetrical circular flow to numbers and small-size vortices with an increase in the sludge diameter, the relative velocity is amount up to u r =5.0, it is 29.4 times of original floc sludge.

Machine Learning of the Reactor Core Loading Pattern Critical Parameters

Directory of Open Access Journals (Sweden)

Krešimir Trontl

2008-01-01

Full Text Available The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR, which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy.

Machine Learning of the Reactor Core Loading Pattern Critical Parameters

International Nuclear Information System (INIS)

Trontl, K.; Pevec, D.; Smuc, T.

2008-01-01

The usual approach to loading pattern optimization involves high degree of engineering judgment, a set of heuristic rules, an optimization algorithm, and a computer code used for evaluating proposed loading patterns. The speed of the optimization process is highly dependent on the computer code used for the evaluation. In this paper, we investigate the applicability of a machine learning model which could be used for fast loading pattern evaluation. We employ a recently introduced machine learning technique, support vector regression (SVR), which is a data driven, kernel based, nonlinear modeling paradigm, in which model parameters are automatically determined by solving a quadratic optimization problem. The main objective of the work reported in this paper was to evaluate the possibility of applying SVR method for reactor core loading pattern modeling. We illustrate the performance of the solution and discuss its applicability, that is, complexity, speed, and accuracy

Mode pattern of internal flow in a water droplet on a vibrating hydrophobic surface.

Science.gov (United States)

Kim, Hun; Lim, Hee-Chang

2015-06-04

The objective of this study is to understand the mode pattern of the internal flow in a water droplet placed on a hydrophobic surface that periodically and vertically vibrates. As a result, a water droplet on a vibrating hydrophobic surface has a typical shape that depends on each resonance mode, and, additionally, we observed a diversified lobe size and internal flows in the water droplet. The size of each lobe at the resonance frequency was relatively greater than that at the neighboring frequencies, and the internal flow of the nth order mode was also observed in the flow visualization. In general, large symmetrical flow streams were generated along the vertical axis in each mode, with a large circulating movement from the bottom to the top, and then to the triple contact line along the droplet surface. In contrast, modes 2 and 4 generated a Y-shaped flow pattern, in which the flow moved to the node point in the lower part of the droplet, but modes 6 and 8 had similar patterns, with only a little difference. In addition, as a result of the PIV measurement, while the flow velocity of mode 4 was faster than that of model 2, those of modes 6 and 8 were almost similar.

Experimental and visual study on flow patterns and pressure drops in U-tubes

International Nuclear Information System (INIS)

Da Silva Lima, J. R.

2011-01-01

In single- and two-phase flow heat exchangers (in particular 'coils'), besides the straight tubes there are also many singularities, in particular the 180° return bends (also called return bends or U-bends). However, contrary to the literature concerning pressure drops and heat transfer in straight tubes, where many experimental data and predicting methods are available, only a limited number of studies concerning U-bends can be found. Neither reliable experimental data nor proven prediction methods are available. Indeed, flow structure, pressure drop and heat transfer in U-bends are an old unresolved design problem in the heat transfer industry. Thus, the present study aims at providing further insight on two-phase pressure drops and flows patterns in U-bends. Based on a new type of U-bend test section, an extensive experimental study was conducted. The experimental campaign covered five test sections with three internal diameters (7.8, 10.8 and 13.4 mm), five bend diameters (24.8, 31.7, 38.1, 54.8 and 66.1 mm), tested for three orientations (horizontal, vertical upflow and vertical downflow), two fluids (R134a and R410A), two saturation temperatures (5 and 10 °C) and mass velocities ranging from 150 to 1000 kg s -1 m -2 . The flow pattern observations identified were stratified-wavy, slug-stratified-wavy, intermittent, annular, dryout and mist flows. The effects of the U-bend on the flow patterns were also observed. A total of 5655 pressure drop data were measured at seven different locations in the test section ( straight tubes and U-bend) providing a total of almost 40,000 data points. The straight tube data were first used to improve the actual two-phase straight tube model of Moreno-Quibén and Thome. This updated model was then used to developed a two-phase U-bend pressure drop model. Based on a comparison between experimental and predicted values, it is concluded that the new two-phase frictional pressure drop model for U-bends successfully

Identification of two-phase flow patterns in a nuclear reactor by the high-frequency contribution fraction

International Nuclear Information System (INIS)

Wang, Y.W.; Pei, B.S.; King, C.H.; Lee, S.C.

1989-01-01

Recently, King et al. and Wang et al. analyzed the fluctuating characteristics of differential pressure and void fraction by the optimum modeling method and by spectral analysis, respectively. These two investigations presented some new concepts and deterministic criteria, which are based on purely empirical formulas, to identify two-phase flow patterns. These deterministic criteria on two-phase flow patterns' identification seem to show reasonable performance. In King's and Wang's studies, there are at least three problems that need further investigations for the applications to the nuclear reactor engineering field. These three problems are the following: 1. Is the response to a certain two-phase flow pattern, i.e., the fluctuating characteristics, of neutrons the same as that of differential pressure or void fraction? 2. Could those criteria developed from air/water flow be allowed to identify steam/water two-phase flow patterns? 3. Could those criteria be applied to identify two-phase flow patterns in rod bundles? In this paper, parts of the investigated results answer the first problem, and detailed comparisons with the previous work of the authors are given on a variety of items

Heat transfer and flow pattern during two-phase flow boiling of R-134a in horizontal smooth and microfin tubes

Energy Technology Data Exchange (ETDEWEB)

Yu, Minghuei; Lin, Tsunkuo; Tseng, Chyuanchyi [National Sun Yat Sen Univ., Taiwan (China). Dept. of Mechanical Engineering

2002-09-01

Flow pattern and heat transfer during evaporation in a 10.7 mm diameter smooth tube and a micro-fin tube are presented. The tubes were tested in the ranges of mass flux between 163 and 408 kg m{sup -2}s{sup -1} and heat flux between 2200 and 56 000 W m{sup -2}. The evaporation temperature was 6{sup o}C. Flow maps for both the tubes are plotted in the coordinates of mass flux and vapor quality. The relations of flow pattern and local heat transfer coefficient are discussed. The heat transfer coefficients for intermittent and annular flows in both the smooth tube and the micro-fin tube are shown to agree well with Gungor and Winterton's correlation with modified constants. (author)

A study of the cerebral blood flow pattern and cognitive deficit in Parkinson's disease

International Nuclear Information System (INIS)

Tamaru, Fuyuhiko

1997-01-01

Cerebral blood flow pattern in Parkinson's disease was examined by 123 I-IMP SPECT to determine whether the deficit in cognitive function is reflected in it. The patient group with Parkinson's disease showed deterioration in intelligence (Minimental state examination, Raven's Colored Progressive Matrices) and frontal lobe test (the Wisconsin Card Sorting Test). Though the uptake ratio of prefrontal area/occipital area in 123 I-IMP SPECT study varied widely in the Parkinson's disease group compared to the normal control group, there was no significant difference in the mean. Selective depletion of frontal lobe blood flow was not confirmed in this study. There was no correlation between cerebral blood flow pattern and cognitive functions including frontal lobe function and intelligence. We concluded that the deficit in cognitive function was not reflected in the cerebral blood flow pattern in Parkinson's disease. (author)

Exploring the Behavioural Patterns of Entrepreneurial Learning: A Competency Approach

Science.gov (United States)

Man, Thomas Wing Yan

2006-01-01

Purpose: The purpose of this study is to empirically explore the behavioural patterns involved in entrepreneurial learning through a conceptualization of entrepreneurial learning as a "competency". Design/methodology/approach: Semi-structured interviews to 12 entrepreneurs were conducted with a focus on the critical incidents in which…

Effect of a flow-corrective insert on the flow pattern in a pebble bed reactor

Energy Technology Data Exchange (ETDEWEB)

Li, Yu; Gui, Nan; Yang, Xingtuan [Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084 (China); Tu, Jiyuan [Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084 (China); School of Aerospace, Mechanical & Manufacturing Engineering, RMIT University, Melbourne 3083, VIC (Australia); Jiang, Shengyao, E-mail: shengyaojiang@sina.com [Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advanced Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084 (China)

2016-04-15

Highlights: • Effect of an insert on improving flow uniformity and eliminating stagnant zone is studied. • Three values concerned with the stagnant zone, radial uniformity and flow sequence are used. • Outlet diameter is a critical parameter that determines balancing mechanism of the insert. • Height/location is varied to let the insert work in unbalanced region and avoid adverse effect. - Abstract: A flow-corrective insert is adopted in the pebble-bed high temperature gas-cooled reactor (HTGR) to improve flow performance of the pebble flow for the first time. 3D discrete element method (DEM) modeling is employed to study this slow and dense granular flow. It is verified that locating a properly designed insert in the bed can help transform unsatisfactory flow field to the preferred flow pattern for pebble bed reactors. Three characteristic values on the stagnant zone, radial uniformity and flow sequence of pebble flow are defined to evaluate uniformity of the overall flow field quantitatively. The results demonstrate that the pebble bed equipped with an insert performs better than normal beds from all these three aspects. Moreover, based on numerical experiments, several universal tips for insert design on height, location and outlet diameter are suggested.

Learning patterns of life from intelligence analyst chat

Science.gov (United States)

Schneider, Michael K.; Alford, Mark; Babko-Malaya, Olga; Blasch, Erik; Chen, Lingji; Crespi, Valentino; HandUber, Jason; Haney, Phil; Nagy, Jim; Richman, Mike; Von Pless, Gregory; Zhu, Howie; Rhodes, Bradley J.

2016-05-01

Our Multi-INT Data Association Tool (MIDAT) learns patterns of life (POL) of a geographical area from video analyst observations called out in textual reporting. Typical approaches to learning POLs from video make use of computer vision algorithms to extract locations in space and time of various activities. Such approaches are subject to the detection and tracking performance of the video processing algorithms. Numerous examples of human analysts monitoring live video streams annotating or "calling out" relevant entities and activities exist, such as security analysis, crime-scene forensics, news reports, and sports commentary. This user description typically corresponds with textual capture, such as chat. Although the purpose of these text products is primarily to describe events as they happen, organizations typically archive the reports for extended periods. This archive provides a basis to build POLs. Such POLs are useful for diagnosis to assess activities in an area based on historical context, and for consumers of products, who gain an understanding of historical patterns. MIDAT combines natural language processing, multi-hypothesis tracking, and Multi-INT Activity Pattern Learning and Exploitation (MAPLE) technologies in an end-to-end lab prototype that processes textual products produced by video analysts, infers POLs, and highlights anomalies relative to those POLs with links to "tracks" of related activities performed by the same entity. MIDAT technologies perform well, achieving, for example, a 90% F1-value on extracting activities from the textual reports.

Patterns and stability of a whirlpool flow

Energy Technology Data Exchange (ETDEWEB)

Carrión, Luis [Universidad de las Fuerzas Armadas-ESPE, Av. Gral. Rumiñahui s/n Sangolquí 171103 (Ecuador); Herrada, Miguel A; María López-Herrera, José [E.S.I, Universidad de Sevilla, Camino de los Descubrimientos s/n 41092 (Spain); Shtern, Vladimir N [Shtern Research and Consulting, Houston, Texas 77096, United States of America (United States)

2017-04-15

This numerical study reveals stable multi-eddy patterns of a steady axisymmetric air–water flow driven by the rotating bottom disk in a vertical sealed cylindrical container. As rotation strength Re increases, eddies emerge, coalesce, separate, and disappear in both air and water. The topological scenario varies with water volume fraction H{sub w} according to the results obtained for H{sub w}  = 0.3, 0.5, and 0.8. Interesting features are: (a) zipper-like chains of air and water eddies forming as the interface bends and (b) bubble-ring air eddies existing in the Re ranges specified in the paper. The stability analysis, performed with the help of a novel efficient technique for two-fluid flows, shows that these multi-eddy motions are stable. The shear-layer instability develops as the interface approaches either the top or bottom of the container and some eddies vanish. The physical reasoning behind the eddy formation and the flow instability is provided. The results are of fundamental interest and can have applications in bioreactors. (paper)

Numerical Study of Flow Motion and Patterns Driven by a Rotating Permanent Helical Magnetic Field

Science.gov (United States)

Yang, Wenzhi; Wang, Xiaodong; Wang, Bo; Baltaretu, Florin; Etay, Jacqueline; Fautrelle, Yves

2016-10-01

Liquid metal magnetohydrodynamic flow driven by a rotating permanent helical magnetic field in a cylindrical container is numerically studied. A three-dimensional numerical simulation provides insight into the visualization of the physical fields, including the magnetic field, the Lorentz force density, and the flow structures, especially the flow patterns in the meridional plane. Because the screen parameter is sufficiently small, the model is decoupled into electromagnetic and hydrodynamic components. Two flow patterns in the meridional plane, i.e., the global flow and the secondary flow, are discovered and the impact of several system parameters on their transition is investigated. Finally, a verifying model is used for comparison with the previous experiment.

Effects of mobile gaming patterns on learning outcomes: a literature review

NARCIS (Netherlands)

Schmitz, Birgit; Klemke, Roland; Specht, Marcus

2013-01-01

Schmitz, B., Klemke, R., & Specht, M. (2012). Effects of mobile gaming patterns on learning outcomes: A literature review. International Journal of Technology Enhanced Learning, 4(5-6), 345-358. doi:10.1504/IJTEL.2012.051817

Pattern Extraction Algorithm for NetFlow-Based Botnet Activities Detection

Directory of Open Access Journals (Sweden)

Rafał Kozik

2017-01-01

Full Text Available As computer and network technologies evolve, the complexity of cybersecurity has dramatically increased. Advanced cyber threats have led to current approaches to cyber-attack detection becoming ineffective. Many currently used computer systems and applications have never been deeply tested from a cybersecurity point of view and are an easy target for cyber criminals. The paradigm of security by design is still more of a wish than a reality, especially in the context of constantly evolving systems. On the other hand, protection technologies have also improved. Recently, Big Data technologies have given network administrators a wide spectrum of tools to combat cyber threats. In this paper, we present an innovative system for network traffic analysis and anomalies detection to utilise these tools. The systems architecture is based on a Big Data processing framework, data mining, and innovative machine learning techniques. So far, the proposed system implements pattern extraction strategies that leverage batch processing methods. As a use case we consider the problem of botnet detection by means of data in the form of NetFlows. Results are promising and show that the proposed system can be a useful tool to improve cybersecurity.

Continuous flow chemistry: a discovery tool for new chemical reactivity patterns.

Science.gov (United States)

Hartwig, Jan; Metternich, Jan B; Nikbin, Nikzad; Kirschning, Andreas; Ley, Steven V

2014-06-14

Continuous flow chemistry as a process intensification tool is well known. However, its ability to enable chemists to perform reactions which are not possible in batch is less well studied or understood. Here we present an example, where a new reactivity pattern and extended reaction scope has been achieved by transferring a reaction from batch mode to flow. This new reactivity can be explained by suppressing back mixing and precise control of temperature in a flow reactor set up.

Continuous flow chemistry: a discovery tool for new chemical reactivity patterns

OpenAIRE

Hartwig, Jan; Metternich, Jan B.; Nikbin, Nikzad; Kirschning, Andreas; Ley, Steven V.

2014-01-01

Continuous flow chemistry as a process intensification tool is well known. However, its ability to enable chemists to perform reactions which are not possible in batch is less well studied or understood. Here we present an example, where a new reactivity pattern and extended reaction scope has been achieved by transferring a reaction from batch mode to flow. This new reactivity can be explained by suppressing back mixing and precise control of temperature in a flow reactor set up.

Pressure-flow characteristics of normal and disordered esophageal motor patterns.

Science.gov (United States)

Singendonk, Maartje M J; Kritas, Stamatiki; Cock, Charles; Ferris, Lara F; McCall, Lisa; Rommel, Nathalie; van Wijk, Michiel P; Benninga, Marc A; Moore, David; Omari, Taher I

2015-03-01

To perform pressure-flow analysis (PFA) in a cohort of pediatric patients who were referred for diagnostic manometric investigation. PFA was performed using purpose designed Matlab-based software. The pressure-flow index (PFI), a composite measure of bolus pressurization relative to flow and the impedance ratio, a measure of the extent of bolus clearance failure were calculated. Tracings of 76 pediatric patients (32 males; 9.1 ± 0.7 years) and 25 healthy adult controls (7 males; 36.1 ± 2.2 years) were analyzed. Patients mostly had normal motility (50%) or a category 4 disorder and usually weak peristalsis (31.5%) according to the Chicago Classification. PFA of healthy controls defined reference ranges for PFI ≤142 and impedance ratio ≤0.49. Pediatric patients with pressure-flow (PF) characteristics within these limits had normal motility (62%), most patients with PF characteristics outside these limits also had an abnormal Chicago Classification (61%). Patients with high PFI and disordered motor patterns all had esophagogastric junction outflow obstruction. Disordered PF characteristics are associated with disordered esophageal motor patterns. By defining the degree of over-pressurization and/or extent of clearance failure, PFA may be a useful adjunct to esophageal pressure topography-based classification. Copyright © 2015 Elsevier Inc. All rights reserved.

Pro deep learning with TensorFlow a mathematical approach to advanced artificial intelligence in Python

CERN Document Server

Pattanayak, Santanu

2017-01-01

Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applications. The code presented in the book is available in the form of iPython notebooks and scripts which allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community.

Nonlinear waves and pattern dynamics

CERN Document Server

Pelinovsky, Efim; Mutabazi, Innocent

2018-01-01

This book addresses the fascinating phenomena associated with nonlinear waves and spatio-temporal patterns. These appear almost everywhere in nature from sand bed forms to brain patterns, and yet their understanding still presents fundamental scientific challenges. The reader will learn here, in particular, about the current state-of-the art and new results in: Nonlinear water waves: resonance, solitons, focusing, Bose-Einstein condensation, as well as and their relevance for the sea environment (sea-wind interaction, sand bed forms, fiber clustering) Pattern formation in non-equilibrium media: soap films, chimera patterns in oscillating media, viscoelastic Couette-Taylor flow, flow in the wake behind a heated cylinder, other pattern formation. The editors and authors dedicate this book to the memory of Alexander Ezersky, Professor of Fluid Mechanics at the University of Caen Normandie (France) from September 2007 to July 2016. Before 2007, he had served as a Senior Scientist at the Institute of Applied Physi...

Pattern database applications from design to manufacturing

Science.gov (United States)

Zhuang, Linda; Zhu, Annie; Zhang, Yifan; Sweis, Jason; Lai, Ya-Chieh

2017-03-01

Pattern-based approaches are becoming more common and popular as the industry moves to advanced technology nodes. At the beginning of a new technology node, a library of process weak point patterns for physical and electrical verification are starting to build up and used to prevent known hotspots from re-occurring on new designs. Then the pattern set is expanded to create test keys for process development in order to verify the manufacturing capability and precheck new tape-out designs for any potential yield detractors. With the database growing, the adoption of pattern-based approaches has expanded from design flows to technology development and then needed for mass-production purposes. This paper will present the complete downstream working flows of a design pattern database(PDB). This pattern-based data analysis flow covers different applications across different functional teams from generating enhancement kits to improving design manufacturability, populating new testing design data based on previous-learning, generating analysis data to improve mass-production efficiency and manufacturing equipment in-line control to check machine status consistency across different fab sites.

Selection of Two-Phase Flow Patterns at a Simple Junction in Microfluidic Devices

Science.gov (United States)

Engl, W.; Ohata, K.; Guillot, P.; Colin, A.; Panizza, P.

2006-04-01

We study the behavior of a confined stream made of two immiscible fluids when it reaches a T junction. Two flow patterns are witnessed: the stream is either directed in only one sidearm, yielding a preferential flow pathway for the dispersed phase, or splits between both. We show that the selection of these patterns is not triggered by the shape of the junction nor by capillary effects, but results from confinement. It can be anticipated in terms of the hydrodynamic properties of the flow. A simple model yielding universal behavior in terms of the relevant adimensional parameters of the problem is presented and discussed.

Patterns of regional cerebral blood flow in acute stroke

DEFF Research Database (Denmark)

Olsen, T S; Skriver, E B

1981-01-01

In a consecutive group of 56 stroke patients the regional cerebral blood flow was measured within 84 hours after stroke. A 254 multidetector scintillation camera and the intracarotid Xenon-133 injection method was used to study rCBF. Typical rCBF-patterns are described and compared to the findings...

Application of ICT supported learning in fluid mechanics

DEFF Research Database (Denmark)

Brohus, Henrik; Svidt, Kjeld

2004-01-01

of tools for knowledge transfer facilitates deep understanding and increases learning efficiency. Air flow is by nature invisible and represents a further challenge in the effort of providing sufficient understanding of typical flow patterns and behaviour of room air flow. An example of visualisation......This paper focuses on the application of ICT, Information & Communication Technology, supported learning in the area of fluid mechanics education. Taking a starting point in a course in Ventilation Technology, including room air flow and contaminant distribution, it explains how ICT may be used...... actively in the learning environment to increase efficiency in the learning process. The paper comprises past experiences and lessons learnt as well as prospect for future development in the area. A model is presented that describes a high efficiency learning environment where ICT plays an important role...

Features of two-phase flow patterns in horizontal rectangular microchannels of height 50 μm

Directory of Open Access Journals (Sweden)

Ron’shin Fedor

2016-01-01

Full Text Available The horizontal microchannel with the height of 50 micrometres and width of 40 mm of a rectangular cross-section has been used to study two-phase flow. The classical patterns of two-phase flow in the channel (bubble, stratified, churn, jet, and annular have been detected. Experimental information allows us to define the characteristics of the regimes and to determine precisely the boundaries between the patterns of the two-phase flows.

An Examination of the Effects of Flow on Learning in a Graduate-Level Introductory Operations Management Course

Science.gov (United States)

Klein, Barbara D.; Rossin, Don; Guo, Yi Maggie; Ro, Young K.

2010-01-01

The authors investigated the effects of flow on learning outcomes in a graduate-level operations management course. Flow was assessed through an overall flow score, four dimensions of flow, and three characteristics of flow activities. Learning outcomes were measured objectively through multiple-choice quiz scores and subjectively using measures…

Periodic and aperiodic flow patterns around an airfoil with leading-edge protuberances

Science.gov (United States)

Cai, Chang; Zuo, Zhigang; Maeda, Takao; Kamada, Yasunari; Li, Qing'an; Shimamoto, Kensei; Liu, Shuhong

2017-11-01

Recently leading-edge protuberances have attracted great attention as a passive method for separation control. In this paper, the effect of multiple leading-edge protuberances on the performance of a two-dimensional airfoil is investigated through experimental measurement of aerodynamic forces, surface tuft visualization, and numerical simulation. In contrast to the sharp stall of the baseline airfoil with large hysteresis effect during AOA (angle of attack) increasing and decreasing, the stall process of the modified airfoil with leading-edge protuberances is gentle and stable. Flow visualization revealed that the flow past each protuberance is periodic and symmetric at small AOAs. Streamwise vortices are generated on the shoulders of the protuberance, leading to a larger separation around the valley sections and a longer attachment along the peak sections. When some critical AOA is exceeded, aperiodic and asymmetric flow patterns occur on the protuberances at different spanwise positions, with leading-edge separation on some of the valley sections and non-stalled condition elsewhere. A combined mechanism, involving both the compartmentalization effect of the slender momentum-enhanced attached flows on the protuberance peaks and the downwash effect of the local stalled region with low circulation, is proposed to explain the generation of the aperiodic flow patterns. The influence of the number of protuberances is also investigated, which shows similar aperiodic flow patterns. The distance between the neighboring local stalled valley sections is found to be in the range of 4-7 times the protuberance wavelength. According to the proposed mechanism, it is speculated that the distance between the neighboring local stalled valley sections is inclined to increase with a smaller protuberance amplitude or at a larger AOA.

Flow patterns of GaInSn liquid on inclined stainless steel plate under a range of magnetic field

Energy Technology Data Exchange (ETDEWEB)

Yang, Juan-Cheng, E-mail: yangjc@xjtu.edu.cn [State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace, Xi’an Jiaotong University, Xi’an, Shanxi 710049 (China); Qi, Tian-Yu [School of Engineering Sciences, University of Chinese Academy and Sciences, Beijing 100049 (China); Ni, Ming-Jiu, E-mail: mjni@ucas.ac.cn [School of Engineering Sciences, University of Chinese Academy and Sciences, Beijing 100049 (China); Wang, Zeng-Hui [School of Engineering Sciences, University of Chinese Academy and Sciences, Beijing 100049 (China)

2016-11-01

Highlights: • The liquid GaInSn metal flow loop was built to study some fusion related liquid metal MHD phenomenon. • The flow patterns of GaInSn free surface flow with the change of Re number and Ha number were got by lot of experiments. • Some detailed descriptions of these flow patterns were also made, and a solid conclusion which agreed with some previous studies was got. - Abstract: In the present paper, some preliminary experimental studies have been conducted to show the flow pattern of liquid metal flow using visualization method. For the convenience of experiments in lab, Ga{sup 67}In{sup 20.5}Sn{sup 12.5} in liquid state at room temperature is used. A test section made by stainless steel is inserted in a traverse magnetic field with strength (B{sub 0}) varies from 0 to 1.28 T. The inclined angle of stainless steel plate in test section is about 9°. Visualization results obtained by high-speed camera (Phantom M/LC 310) shown that GaInSn liquid flow on inclined stainless steel plate behaved unstable liquid column flow pattern in the low flow rate, while behaved large area spreading flow pattern with small waves on the free surface in the large flow rate. However, in the magnetic field, under the action of electromagnetic force, the flow patterns of GaInSn liquid have some significant changes on the spreading width and surface structure of free surface. Some detailed analyses on these changes have been also showed in the present paper. Plans for future work are also presented.

The impact of traffic-flow patterns on air quality in urban street canyons.

Science.gov (United States)

Thaker, Prashant; Gokhale, Sharad

2016-01-01

We investigated the effect of different urban traffic-flow patterns on pollutant dispersion in different winds in a real asymmetric street canyon. Free-flow traffic causes more turbulence in the canyon facilitating more dispersion and a reduction in pedestrian level concentration. The comparison of with and without a vehicle-induced-turbulence revealed that when winds were perpendicular, the free-flow traffic reduced the concentration by 73% on the windward side with a minor increase of 17% on the leeward side, whereas for parallel winds, it reduced the concentration by 51% and 29%. The congested-flow traffic increased the concentrations on the leeward side by 47% when winds were perpendicular posing a higher risk to health, whereas reduced it by 17-42% for parallel winds. The urban air quality and public health can, therefore, be improved by improving the traffic-flow patterns in street canyons as vehicle-induced turbulence has been shown to contribute significantly to dispersion. Copyright © 2015 Elsevier Ltd. All rights reserved.

Short-range dynamics and prediction of mesoscale flow patterns in the MISTRAL field experiment

Energy Technology Data Exchange (ETDEWEB)

Weber, R.O.; Kaufmann, P.; Talkner, P. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

1997-06-01

In a limited area of about 50 km by 50 km with complex topography, wind measurements on a dense network were performed during the MISTRAL field experiment in 1991-1992. From these data the characteristic wind fields were identified by an automated classification method. The dynamics of the resulting twelve typical regional flow patterns is studied. It is discussed how transitions between the flow patterns take place and how well the transition probabilities can be described in the framework of a Markov model. Guided by this discussion, a variety of prediction models were tested which allow a short-term forecast of the flow pattern type. It is found that a prediction model which uses forecast information from the synoptic scale has the best forecast skill. (author) 2 figs., 7 refs.

Temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern based on image texture spectrum descriptor

Science.gov (United States)

Zhou, Xi-Guo; Jin, Ning-De; Wang, Zhen-Ya; Zhang, Wen-Yin

2009-11-01

The dynamic image information of typical gas-liquid two-phase flow patterns in vertical upward pipe is captured by a highspeed dynamic camera. The texture spectrum descriptor is used to describe the texture characteristics of the processed images whose content is represented in the form of texture spectrum histogram, and four time-varying characteristic parameter indexes which represent image texture structure of different flow patterns are extracted. The study results show that the amplitude fluctuation of texture characteristic parameter indexes of bubble flow is lowest and shows very random complex dynamic behavior; the amplitude fluctuation of slug flow is higher and shows intermittent motion behavior between gas slug and liquid slug, and the amplitude fluctuation of churn flow is the highest and shows better periodicity; the amplitude fluctuation of bubble-slug flow is from low to high and oscillating frequence is higher than that of slug flow, and includes the features of both slug flow and bubble flow; the slug-churn flow loses the periodicity of slug flow and churn flow, and the amplitude fluctuation is high. The results indicate that the image texture characteristic parameter indexes of different flow pattern can reflect the flow characteristics of gas-liquid two-phase flow, which provides a new approach to understand the temporal and spatial evolution of flow pattern dynamics.

Localized electric field induced transition and miniaturization of two-phase flow patterns inside microchannels.

Science.gov (United States)

Sharma, Abhinav; Tiwari, Vijeet; Kumar, Vineet; Mandal, Tapas Kumar; Bandyopadhyay, Dipankar

2014-10-01

Strategic application of external electrostatic field on a pressure-driven two-phase flow inside a microchannel can transform the stratified or slug flow patterns into droplets. The localized electrohydrodynamic stress at the interface of the immiscible liquids can engender a liquid-dielectrophoretic deformation, which disrupts the balance of the viscous, capillary, and inertial forces of a pressure-driven flow to engender such flow morphologies. Interestingly, the size, shape, and frequency of the droplets can be tuned by varying the field intensity, location of the electric field, surface properties of the channel or fluids, viscosity ratio of the fluids, and the flow ratio of the phases. Higher field intensity with lower interfacial tension is found to facilitate the oil droplet formation with a higher throughput inside the hydrophilic microchannels. The method is successful in breaking down the regular pressure-driven flow patterns even when the fluid inlets are exchanged in the microchannel. The simulations identify the conditions to develop interesting flow morphologies, such as (i) an array of miniaturized spherical or hemispherical or elongated oil drops in continuous water phase, (ii) "oil-in-water" microemulsion with varying size and shape of oil droplets. The results reported can be of significance in improving the efficiency of multiphase microreactors where the flow patterns composed of droplets are preferred because of the availability of higher interfacial area for reactions or heat and mass exchange. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Altered Precipitation and Flow Patterns in the Dunajec River Basin

Directory of Open Access Journals (Sweden)

Mariola Kędra

2017-01-01

Full Text Available This study analyzes changes in long-term patterns of precipitation and river flow, as well as changes in their variability over the most recent 60 years (1956–2015. The study area is situated in the mountain basin of the Dunajec River, encompassing streams draining the Tatra Mountains in southern Poland. The focus of the study was to evaluate how regional warming translates into precipitation changes in the studied mountain region, and how changes in climate affect sub-regional hydrology. Monthly time series of precipitation measured at several sites were compared for two 30-year periods (1986–2015 versus 1956–1985. The significance of the difference between the periods in question was evaluated by means of the Wilcoxon signed rank test with the Bonferroni correction. The identified shifts in precipitation for 6 months are statistically significant and largely consistent with the revealed changes in river flow patterns. Moreover, significant differences in precipitation variability were noted in the study area, resulting in a significant decrease in the repeatability of precipitation over the most recent 30 years (1986–2015. Changes in the variability of the river flow studied were less visible in this particular mountain region (while significant for two months; however, the overall repeatability of river flow decreased significantly at the same rate as for precipitation.

Quantitative cerebral blood flow patterns with the short lived isotope 195m Au

International Nuclear Information System (INIS)

Lindner, P.; Nickel, O.

1984-01-01

A previously reported theory for quantitative cerebral blood flow measurements using intravenously injected nondiffusible radiotracers has been applied on patients after stroke and on volunteers undergoing a mental stimulation exercise. Quantitative measurements of cerebral blood flow patterns (in ml/min/100g) not only in p.a. but also in lateral views of the brain are possible by using of the short-lived (30 sec) isotope Au 195m. The energy spectrum of the eluate of the generator shows two strong photon peaks, one at 68 keV and a second at 262 keV. The 68 keV peak is suitable for perfusion studies in lateral views of the hemispheres, no 'look through' effect is seen. The 262 keV peak is good for studies in p.a. positions. The studies last less than 1 minute and can be repeated after 3 minutes. Parametric images for quantitative regional cerebral blood flow can be generated. The area of occluded vessels in the case of stroke can be made visible. Quantitative activation patterns of cerebral blood flow during mental stimulation can be generated. After optical stimulation a clear increase of blood flow was seen in the visual cortex. The results prove that not only with freely diffusible (like Xenon) but also with nondiffusible indicators like 195m Au it is possible to measure quantitatively cerebral blood flow patterns. Au 195m is very advantageous for quantitative clinical investigations of cerebrovascular disease. (Author)

Effect of diameter and axial location on upward gas–liquid two-phase flow patterns in intermediate-scale vertical tubes

International Nuclear Information System (INIS)

Ansari, M.R.; Azadi, R.

2016-01-01

Highlights: • A vertical two-phase flow system is manufactured to study flow behavior adiabatically. • Two test sections are studied with inner diameters of 40 mm and 70 mm at two locations. • Flow pattern maps are presented for both tubes. • Effects of tube diameter and heights on pattern transition boundaries are investigated. • Three sub-patterns bubbly flow and two types of slug pattern are recognized. - Abstract: In the present research, a two-phase flow system is designed, manufactured, assembled and adjusted to study two-phase flow behavior isothermally. Test sections are tubes standing in vertical position and are made of transparent acrylic with inner diameters of 40 mm and 70 mm. Two axial locations of 1.73 m and 3.22 m are chosen for data acquisition. Flow pattern maps are presented for both tubes. Effects of tube diameter and axial location on pattern transition boundaries are investigated. Air and water are chosen as working fluids. The range of air and water superficial velocities are 0.054–9.654 m/s and 0.015–0.877 m/s for the 40 mm diameter tube, but these values are 0.038–20.44 m/s and 0.036–1.530 m/s for 70 mm diameter tube. The results show that for both tubes, increasing axial location does not affect flow transition boundaries significantly. However, slug pattern region shrinks considerably by changing tube diameter from 40 mm to 70 mm. Using image processing techniques, recorded high speed movies were investigated accurately. As a result, bubbly flow in the 40 mm tube can be divided into three sub-patterns as dispersed, agitated and agglomerated bubbly. Also, two types of slug pattern are also recognized in the same tube diameter which are called small and large slugs. Semi-annular flow is observed as an independent pattern in the 70 mm tube that does not behave as known churn or annular patterns.

CFD flow pattern analysis on primaryside of IHX for fast reactors

International Nuclear Information System (INIS)

Takano, Masahito; Mochizuki, Hiroyasu

2011-01-01

The present paper describes the CFD analysis on the primary-side of an intermediate heat exchange (IHX) which has the similar configurations as the IHX for the fast breeder reactor 'Monju'. The IHX is precisely modeled based on the discussion about meshing system. The present model is used for the heat transfer analysis under low-flowrate and natural circulation conditions. The IHX is a shell-and-tube type and counter-flow heat exchanger which has more than 3000 heat transfer tubes on the secondary side. Therefore, the flow pattern on the primary side gets complex. Measurement of flow pattern and temperature distribution on the primary-side of the real IHX are almost impossible. Since the heat transfer tubes of approximately 5 m in length are fixed at 7 plates with many flow holes and placed on the 23 circles with an appropriate lattice pitch, the number of meshes becomes enormous size. In order to overcome these problems, a separate model is discussed. In the present study, two models are discussed. The first one is a precise full-sector model with one flow entrance, 6 windows on the primary-side. The flow distributions are calculated changing inlet flow rate from 100% to 0.1% which is equivalent to 10 6 to 10 3 in the Reynolds numbers. The other model is a sector model with 8 chamber separated by 7 flow-rectifying plats. Pressure losses at each plate and chamber are calculated using this model. As a result of the analysis, since there is only a small flow deviation between the flow from the 6 windows under turbulent flow and laminar flow conditions, the sector model with one window is possible model in the calculation. The small radial velocity gradient is calculated from 23rd layer (outer heat transfer tube) to 10th layer. The distribution is not dependent on the flow rate. Axial flow distributions through the rectifying plates are unified from the entrance to the down-stream. The sector model is applicable to calculate the primary-side flow distributions

The transition criteria of circulating flow pattern of moderator in the calandria tank of CANDU nuclear power plant

International Nuclear Information System (INIS)

Jung, Yun Sik; Lee, Jae Young; Kim, Man Woong

2004-01-01

The moderator cooling system to the Calandria tank of CANDU nuclear power plant provides an alternative pass of heat sink during the hypothetical loss of coolant accident. Also, the neutron population in the CANDU plant can be affected by the moderator temperature change which strongly depends on the circulating flow pattern in the Calandria tank. It has been known that there are three distinguished flow patterns: the buoyancy dominated flow, the momentum dominated flow, and the mixed type flow. The Canadian Nuclear Safety Commission (CNSC) recommended that a series of experimental works should be performed to verify the three dimensional codes. Two existing facilities, SPEL (1982) and STERN (1990), have produced experimental data for these purposes. The present work is also motivated to build up a new scaled experimental facility named HGU for the same purposes. CANDU-6 was selected as the target plant to be scaled down. In the design for the scaled facility, the knowledge on the flow regime transitions in the circulating flow was imperative. In the present study, to pave the way for the scaling, the flow pattern maps of circulating flow were constructed based on the Reynolds number and Archimedes number. The CFX code was employed with real meshes to represent all calandria tubes in the tank. The flow pattern maps were constructed for SPEL, STERN, HGU, and CANDU6. As the key transition criterion useful for scaling law, a new Archimedes number considering the jet impingement of the feed water in the Calandria tank was found. The transition of flow patterns was made with the same Archimedes number for CANDU6, STERN and HGU. However, SPEL which has third of the modified Archimedes number showed different maps in the wider region of mixed flow pattern was observed. It was found that the Archimedes number considering the inlet nozzle velocity plays the key role in patterns classification. Also, it can be suggested that the moderator cooling system needs to be designed

Flow pattern in the ventricle of brain with cilia beating and CSF circulation

Science.gov (United States)

Wang, Yong; Westendorf, Christian; Faubel, Regina; Eichele, Gregor; Bodenschatz, Eberhard

We recently discovered that cilia of the ventral third ventricle (v3V) of mammalian brain generate a complex flow network close to the wall. However, the flow pattern in the overall three dimensional v3V, especially under physiological condition, remains to be investigated. Computational fluid dynamics is arguably the best approach for such investigations. Several v3V geometries are reconstructed from different data for comparison study. The lattice Boltzmann method and immersed boundary method are used to reproduce the experimental set-up for an opened v3V firstly. The experimentally recorded cilia induced flow network is projected on the curved v3V wall. The flow maps obtained numerically at different heights from the v3V wall agree with the experimental data qualitatively. We then consider the entire v3V with ciliary flow network along the wall for boundary condition. Moreover, we add a time dependent flow rate to represent the CSF circulation, and study flow pattern in the ventricle. We thank the Max Planck Society (MPG) for financial support. This work is conducted within the Physics and Medicine Initiative at Goettingen Campus between MPG and University Medical Center.

Experimental study of circle grid fractal pattern on turbulent intensity in pipe flow

International Nuclear Information System (INIS)

Manshoor, B; Zaman, I; Othman, M F; Khalid, Amir

2013-01-01

Fractal turbulence is deemed much more efficient than grid turbulence in terms of a turbulence generation. In this paper, the hotwire experimental results for the circle grids fractal pattern as a turbulent generator will be presented. The self-similar edge characteristic of the circle grid fractal pattern is thought to play a vital role in the enhancement of turbulent intensity. Three different beta ratios of perforated plates based on circle grids fractal pattern were used in the experimental work and each paired with standard circle grids with similar porosity. The objectives were to study the fractal scaling influence on the flow and also to explore the potential of the circle grids fractal pattern in enhancing the turbulent intensity. The results provided an excellent insight of the fractal generated turbulence and the fractal flow physics. Across the circle grids fractal pattern, the pressure drop was lower but the turbulent intensity was higher than those across the paired standard circle grids

Visualized study on specific points on demand curves and flow patterns in a single-side heated narrow rectangular channel

International Nuclear Information System (INIS)

Wang Junfeng; Huang Yanping; Wang Yanlin

2011-01-01

Highlights: → Specific points on the demand curve and flow patterns are visually studied. → Bubbly, churn, and annular flows were observed. → Onset of flow instability and bubbly-churn transition occurs at the same time. → The evolution of specific points and flow pattern transitions were examined. - Abstract: A simultaneous visualization and measurement study on some specific points on demand curves, such as onset of nucleate boiling (ONB), onset of significant void (OSV), onset of flow instability (OFI), and two-phase flow patterns in a single-side heated narrow rectangular channel, having a width of 40 mm and a gap of 3 mm, was carried out. New experimental approaches were adopted to identify OSV and OFI in a narrow rectangular channel. Under experimental conditions, the ONB could be predicted well by the Sato and Matsumura model. The OSV model of Bowring can reasonably predict the OSV if the single-side heated condition is considered. The OFI was close to the saturated boiling point and could be described accurately by Kennedy's correlation. The two-phase flow patterns observed in this experiment could be classified into bubbly, churn, and annular flow. Slug flow was never observed. The OFI always occurred when the bubbles at the channel exit began to coalesce, which corresponded to the beginning of the bubbly-churn transition in flow patterns. Finally, the evolution of specific points and flow pattern transitions were examined in a single-side heated narrow rectangular channel.

Dynamics of baroclinic wave pattern in transition zones between different flow regimes

International Nuclear Information System (INIS)

Larcher, Thomas von; Egbers, Christoph

2005-01-01

Baroclinic waves, both steady and time-dependent, are studied experimentally in a differentially heated rotating cylindrical gap with a free surface, cooled from within. Water is used as working fluid. We focus especially on transition zones between different flow regimes, where complex flow pattern like mixed-mode states are found. The transition from steady wave regime to irregular flow is also of particular interest. The surface flow is observed with visualisation techniques. Velocity time series are measured with the optical laser-Doppler-velocimetry technique. Thermographic measurements are applied for temperature field visualisations

Uncertainty Flow Facilitates Zero-Shot Multi-Label Learning in Affective Facial Analysis

Directory of Open Access Journals (Sweden)

Wenjun Bai

2018-02-01

Full Text Available Featured Application: The proposed Uncertainty Flow framework may benefit the facial analysis with its promised elevation in discriminability in multi-label affective classification tasks. Moreover, this framework also allows the efficient model training and between tasks knowledge transfer. The applications that rely heavily on continuous prediction on emotional valance, e.g., to monitor prisoners’ emotional stability in jail, can be directly benefited from our framework. Abstract: To lower the single-label dependency on affective facial analysis, it urges the fruition of multi-label affective learning. The impediment to practical implementation of existing multi-label algorithms pertains to scarcity of scalable multi-label training datasets. To resolve this, an inductive transfer learning based framework, i.e.,Uncertainty Flow, is put forward in this research to allow knowledge transfer from a single labelled emotion recognition task to a multi-label affective recognition task. I.e., the model uncertainty—which can be quantified in Uncertainty Flow—is distilled from a single-label learning task. The distilled model uncertainty ensures the later efficient zero-shot multi-label affective learning. On the theoretical perspective, within our proposed Uncertainty Flow framework, the feasibility of applying weakly informative priors, e.g., uniform and Cauchy prior, is fully explored in this research. More importantly, based on the derived weight uncertainty, three sets of prediction related uncertainty indexes, i.e., soft-max uncertainty, pure uncertainty and uncertainty plus are proposed to produce reliable and accurate multi-label predictions. Validated on our manual annotated evaluation dataset, i.e., the multi-label annotated FER2013, our proposed Uncertainty Flow in multi-label facial expression analysis exhibited superiority to conventional multi-label learning algorithms and multi-label compatible neural networks. The success of our

From lag synchronization to pattern formation in one-dimensional open flow models

International Nuclear Information System (INIS)

Liu Zengrong; Luo Jigui

2006-01-01

In this paper, the relation between synchronization and pattern formation in one-dimensional discrete and continuous open flow models is investigated in detail. Firstly a sufficient condition for globally asymptotical stability of lag/anticipating synchronization among lattices of these models is proved by analytic method. Then, by analyzing and simulating lag/anticipating synchronization in discrete case, three kinds of pattern of wave (it is called wave pattern) travelling in the lattices are discovered. Finally, a proper definition for these kinds of pattern is proposed

Differential theory of learning for efficient neural network pattern recognition

Science.gov (United States)

Hampshire, John B., II; Vijaya Kumar, Bhagavatula

1993-09-01

We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

TensorFlow: A system for large-scale machine learning

OpenAIRE

Abadi, Martín; Barham, Paul; Chen, Jianmin; Chen, Zhifeng; Davis, Andy; Dean, Jeffrey; Devin, Matthieu; Ghemawat, Sanjay; Irving, Geoffrey; Isard, Michael; Kudlur, Manjunath; Levenberg, Josh; Monga, Rajat; Moore, Sherry; Murray, Derek G.

2016-01-01

TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general-purpose GPUs, and custom designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexib...

Student Media Usage Patterns and Non-Traditional Learning in Higher Education

Directory of Open Access Journals (Sweden)

Olaf Zawacki-Richter

2015-04-01

Full Text Available A total of 2,338 students at German universities participated in a survey, which investigated media usage patterns of so-called traditional and non-traditional students (Schuetze & Wolter, 2003. The students provided information on the digital devices that they own or have access to, and on their usage of media and e-learning tools and services for their learning. A distinction was made between external, formal and internal, informal tools and services. Based on the students’ responses, a typology of media usage patterns was established by means of a latent class analysis (LCA. Four types or profiles of media usage patterns were identified. These types were labeled entertainment users, peripheral users, advanced users and instrumental users. Among non-traditional students, the proportion of instrumental users was rather high. Based on the usage patterns of traditional and non-traditional students, implications for media selection in the instructional design process are outlined in the paper.

Simulated Flow Pattern in Massive Pulmonary Embolism: Significance for Selective Intrapulmonary Thrombolysis

International Nuclear Information System (INIS)

Schmitz-Rode, Thomas; Kilbinger, Markus; Guenther, Rolf W.

1998-01-01

Purpose: The flow pattern in the central pulmonary arteries proximal to large pulmonary emboli was studied experimentally. The currents to which thrombolytic agents are exposed when administered via an intrapulmonary catheter were visualized in order to explain the lack of benefit of local versus systemic administration. Methods: By illumination of suspended microspheres, the flow pattern proximal to an obstructing embolus was visualized in an in vitro pulmonary arterial flow model. In six dogs massive pulmonary embolism was created. A pigtail catheter was positioned in the pulmonary artery immediately proximal to the central edge of the occluding embolus. To allow visualization of the local flow pattern, a small amount of contrast material (4 ml) was injected through the catheter at a high flow rate (25 ml/sec). The course of the radiopaque spot that emerged from the catheter tip within 160 msec was monitored with digital subtraction angiography at a frame rate of 12.5 frames/sec. In two dogs, the study was repeated after embolus fragmentation with the same catheter position. Results: The flow model study revealed formation of a vortex proximal to the occluding embolus. In vivo experiments showed that the radiopaque spot was whirled by the vortex proximal to the embolus and made only evanescent contact with the edge of the embolus. Regardless of the embolus location, the contrast spot was washed into the non-occluded ipsilateral and contralateral pulmonary arteries within 0.40-0.64 sec. After embolus fragmentation, the contrast spot was carried completely into the formerly occluded artery. Conclusion: Flow studies explain why thrombolytic agents administered via a catheter positioned adjacent to the embolus may have no more effect than systemically administered agents. An enhanced local effect is precluded by the rapid washout into the non-occluded pulmonary arteries and subsequent systemic dilution. These results support the practice of direct intrathrombic

Learning Based Approach for Optimal Clustering of Distributed Program's Call Flow Graph

Science.gov (United States)

Abofathi, Yousef; Zarei, Bager; Parsa, Saeed

Optimal clustering of call flow graph for reaching maximum concurrency in execution of distributable components is one of the NP-Complete problems. Learning automatas (LAs) are search tools which are used for solving many NP-Complete problems. In this paper a learning based algorithm is proposed to optimal clustering of call flow graph and appropriate distributing of programs in network level. The algorithm uses learning feature of LAs to search in state space. It has been shown that the speed of reaching to solution increases remarkably using LA in search process, and it also prevents algorithm from being trapped in local minimums. Experimental results show the superiority of proposed algorithm over others.

WISC-R Subtest Pattern Stability and Learning Disabilities: A Profile Analysis.

Science.gov (United States)

Mealor, David J.; Abrams, Pamela F.

Profile analysis was performed on Wechsler Intelligence Scale for Children-Revised (WISC-R) scores of 29 learning disabled students (6-10 years old) in a Specific Learning Disabilities (SLD) program, to determine whether subtest patterns for initial and re-evaluation WISC-R administrations would differ significantly. Profile analysis was applied…

The role of consolidation in learning context-dependent phonotactic patterns in speech and digital sequence production.

Science.gov (United States)

Anderson, Nathaniel D; Dell, Gary S

2018-04-03

Speakers implicitly learn novel phonotactic patterns by producing strings of syllables. The learning is revealed in their speech errors. First-order patterns, such as "/f/ must be a syllable onset," can be distinguished from contingent, or second-order, patterns, such as "/f/ must be an onset if the vowel is /a/, but a coda if the vowel is /o/." A metaanalysis of 19 experiments clearly demonstrated that first-order patterns affect speech errors to a very great extent in a single experimental session, but second-order vowel-contingent patterns only affect errors on the second day of testing, suggesting the need for a consolidation period. Two experiments tested an analogue to these studies involving sequences of button pushes, with fingers as "consonants" and thumbs as "vowels." The button-push errors revealed two of the key speech-error findings: first-order patterns are learned quickly, but second-order thumb-contingent patterns are only strongly revealed in the errors on the second day of testing. The influence of computational complexity on the implicit learning of phonotactic patterns in speech production may be a general feature of sequence production.

Experimental investigation on flow patterns of RP-3 kerosene under sub-critical and supercritical pressures

Science.gov (United States)

Wang, Ning; Zhou, Jin; Pan, Yu; Wang, Hui

2014-02-01

Active cooling with endothermic hydrocarbon fuel is proved to be one of the most promising approaches to solve the thermal problem for hypersonic aircraft such as scramjet. The flow patterns of two-phase flow inside the cooling channels have a great influence on the heat transfer characteristics. In this study, phase transition processes of RP-3 kerosene flowing inside a square quartz-glass tube were experimentally investigated. Three distinct phase transition phenomena (liquid-gas two phase flow under sub-critical pressures, critical opalescence under critical pressure, and corrugation under supercritical pressures) were identified. The conventional flow patterns of liquid-gas two phase flow, namely bubble flow, slug flow, churn flow and annular flow are observed under sub-critical pressures. Dense bubble flow and dispersed flow are recognized when pressure is increased towards the critical pressure whilst slug flow, churn flow and annular flow disappear. Under critical pressure, the opalescence phenomenon is observed. Under supercritical pressures, no conventional phase transition characteristics, such as bubbles are observed. But some kind of corrugation appears when RP-3 transfers from liquid to supercritical. The refraction index variation caused by sharp density gradient near the critical temperature is thought to be responsible for this corrugation.

Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules

Science.gov (United States)

Ranganathan, Rajiv; Krishnan, Chandramouli; Dhaher, Yasin Y.; Rymer, William Z.

2018-01-01

The motor module hypothesis in motor control proposes that the nervous system can simplify the problem of controlling a large number of muscles in human movement by grouping muscles into a smaller number of modules. Here, we tested one prediction of the modular organization hypothesis by examining whether there is preferential exploration along these motor modules during the learning of a new gait pattern. Healthy college-aged participants learned a new gait pattern which required increased hip and knee flexion during the swing phase while walking in a lower-extremity robot (Lokomat). The new gait pattern was displayed as a foot trajectory in the sagittal plane and participants attempted to match their foot trajectory to this template. We recorded EMG from 8 lower-extremity muscles and we extracted motor modules during both baseline walking and target-tracking using non-negative matrix factorization (NMF). Results showed increased trajectory variability in the first block of learning, indicating that participants were engaged in exploratory behavior. Critically, when we examined the muscle activity during this exploratory phase, we found that the composition of motor modules changed significantly within the first few strides of attempting the new gait pattern. The lack of persistence of the motor modules under even short time scales suggests that motor modules extracted during locomotion may be more indicative of correlated muscle activity induced by the task constraints of walking, rather than reflecting a modular control strategy. PMID:26916510

The influence of different diffusion pattern to the sub- and super-critical fluid flow in brown coal

Science.gov (United States)

Peng, Peihuo

2018-03-01

Sub- and super-critical CO2 flowing in nanoscale pores are recently becoming of great interest due to that it is closely related to many engineering applications, such as geological burial and sequestration of carbon dioxide, Enhanced Coal Bed Methane recovery ( ECBM), super-critical CO2 fracturing and so on. Gas flow in nanopores cannot be described simply by the Darcy equation. Different diffusion pattern such as Fick diffusion, Knudsen diffusion, transitional diffusion and slip flow at the solid matrix separate the seepage behaviour from Darcy-type flow. According to the principle of different diffusion pattern, the flow of sub- and super-critical CO2 in brown coal was simulated by numerical method, and the results were compared with the experimental results to explore the contribution of different diffusion pattern and swelling effect in sub- and super-critical CO2 flow in nanoscale pores.

Identification of microfluidic two-phase flow patterns in lab-on-chip devices.

Science.gov (United States)

Yang, Zhaochu; Dong, Tao; Halvorsen, Einar

2014-01-01

This work describes a capacitive sensor for identification of microfluidic two-phase flow in lab-on-chip devices. With interdigital electrodes and thin insulation layer utilized, this sensor is capable of being integrated with the microsystems easily. Transducing principle and design considerations are presented with respect to the microfluidic gas/liquid flow patterns. Numerical simulation results verify the operational principle. And the factors affecting the performance of the sensor are discussed. Besides, a feasible process flow for the fabrication is also proposed.

Methods for discriminating gas-liquid two phase flow patterns based on gray neural networks and SVM

International Nuclear Information System (INIS)

Li Jingjing; Zhou Tao; Duan Jun; Zhang Lei

2013-01-01

Background: The flow patterns of two phase flow will directly influence the heat transfer and mass transfer of the flow. Purpose: By wavelet analysis of the pressure drop experimental data, the wavelet coefficients of different frequency can be obtained. Methods: Get the wavelet energy and then train them in the model of BP neural network to distinguish the flow patterns. Introduced the implant gray neural networks model and use it for the two phase flow for the first time. At the same time, set up the method of training the pressure data and wavelet energy data in the support vector machine. Results: Through treatment of the gray layer, the result of the neural network is more accuracy. It can obviously reduce the effect of data marginalization. The accuracy of the pressure drop Lib-SVM method is 95.2%. Conclusions: The results show that these three methods can make a distinction among the different flow patterns and the Lib-SVM method gets the best result, then the gray neural networks, and at last the BP neural networks. (authors)

Flow Patterns in the Sedimentation of a Capsule-Shaped Particle

International Nuclear Information System (INIS)

Nie De-Ming; Lin Jian-Zhong; Zhang Kai

2012-01-01

The main objective of this study is to numerically investigate the settling of a capsule-shaped particle in an infinitely long channel by the newly developed LB-DF/FD method. This work will focus on the effects of the particle orientation and particle/fluid density ratio on the flow patterns during sedimentation. As the density ratio is varied, our results show that there are four distinct modes of sedimentation: vertical sedimentation, horizontal sedimentation, periodically oscillating sedimentation and chaotic mode where the particle is released from the center of the domain with an initial inclination of π/4 to break the symmetry. Furthermore, we also numerically investigate the flow patterns where the particle is released with an initial inclination of 0, π/6, π/3 and π/2. We conduct a detailed study on the effects of density ratio on the transition from the vertical sedimentation mode to horizontal sedimentation mode. (fundamental areas of phenomenology(including applications))

Cryptic species? Patterns of maternal and paternal gene flow in eight neotropical bats.

Directory of Open Access Journals (Sweden)

Elizabeth L Clare

Full Text Available Levels of sequence divergence at mitochondrial loci are frequently used in phylogeographic analysis and species delimitation though single marker systems cannot assess bi-parental gene flow. In this investigation I compare the phylogeographic patterns revealed through the maternally inherited mitochondrial COI region and the paternally inherited 7(th intron region of the Dby gene on the Y-chromosome in eight common Neotropical bat species. These species are diverse and include members of two families from the feeding guilds of sanguivores, nectarivores, frugivores, carnivores and insectivores. In each case, the currently recognized taxon is comprised of distinct, substantially divergent intraspecific mitochondrial lineages suggesting cryptic species complexes. In Chrotopterus auritus, and Saccopteryx bilineata I observed congruent patterns of divergence in both genetic regions suggesting a cessation of gene flow between intraspecific groups. This evidence supports the existence of cryptic species complexes which meet the criteria of the genetic species concept. In Glossophaga soricina two intraspecific groups with largely sympatric South American ranges show evidence for incomplete lineage sorting or frequent hybridization while a third group with a Central American distribution appears to diverge congruently at both loci suggesting speciation. Within Desmodus rotundus and Trachops cirrhosus the paternally inherited region was monomorphic and thus does not support or refute the potential for cryptic speciation. In Uroderma bilobatum, Micronycteris megalotis and Platyrrhinus helleri the gene regions show conflicting patterns of divergence and I cannot exclude ongoing gene flow between intraspecific groups. This analysis provides a comprehensive comparison across taxa and employs both maternally and paternally inherited gene regions to validate patterns of gene flow. I present evidence for previously unrecognized species meeting the criteria of

Effect of Flow on Cultured Cell at Micro-Pattern of Ridge Lines

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Haruka Hino

2017-10-01

Full Text Available A flow channel with a micro-pattern of ridge lines of a scaffold has been designed to study quantitatively the effect of flow on an oriented cell in vitro. The lines of parallel micro ridges (0.001 mm height, 0.003 mm width, and 0.003 mm interval are made by the lithography technique on the lower surface of the channel as the scaffold to make orientation of each cell. Variation is made about the angle between the longitudinal direction of the ridge line and the direction of the flow: zero, 0.79 and 1.6 rad. The suspension of C2C12 (mouse myoblast cell line was injected to the channel, and incubated for two hours on the micro ridges before the flow test for four hours. The flow rate of 3/hour is controlled by a syringe pump to make variation of the wall shear stress of < 3 Pa. The action of each cell adhered on the micro pattern was analyzed at the time lapse images. The experimental results show that both the migration and the deformation of each myoblast along the micro ridge are restricted by the wall shear stress higher than 3 Pa.

Complex blood flow patterns in an idealized left ventricle: A numerical study

Science.gov (United States)

Tagliabue, Anna; Dedè, Luca; Quarteroni, Alfio

2017-09-01

In this paper, we study the blood flow dynamics in a three-dimensional (3D) idealized left ventricle of the human heart whose deformation is driven by muscle contraction and relaxation in coordination with the action of the mitral and aortic valves. We propose a simplified but realistic mathematical treatment of the valves function based on mixed time-varying boundary conditions (BCs) for the Navier-Stokes equations modeling the flow. These switchings in time BCs, from natural to essential and vice versa, model either the open or the closed configurations of the valves. At the numerical level, these BCs are enforced by means of the extended Nitsche's method (Tagliabue et al., Int. J. Numer. Methods Fluids, 2017). Numerical results for the 3D idealized left ventricle obtained by means of Isogeometric Analysis are presented, discussed in terms of both instantaneous and phase-averaged quantities of interest and validated against those available in the literature, both experimental and computational. The complex blood flow patterns are analysed to describe the characteristic fluid properties, to show the transitional nature of the flow, and to highlight its main features inside the left ventricle. The sensitivity of the intraventricular flow patterns to the mitral valve properties is also investigated.

Motif distributions in phase-space networks for characterizing experimental two-phase flow patterns with chaotic features.

Science.gov (United States)

Gao, Zhong-Ke; Jin, Ning-De; Wang, Wen-Xu; Lai, Ying-Cheng

2010-07-01

The dynamics of two-phase flows have been a challenging problem in nonlinear dynamics and fluid mechanics. We propose a method to characterize and distinguish patterns from inclined water-oil flow experiments based on the concept of network motifs that have found great usage in network science and systems biology. In particular, we construct from measured time series phase-space complex networks and then calculate the distribution of a set of distinct network motifs. To gain insight, we first test the approach using time series from classical chaotic systems and find a universal feature: motif distributions from different chaotic systems are generally highly heterogeneous. Our main finding is that the distributions from experimental two-phase flows tend to be heterogeneous as well, suggesting the underlying chaotic nature of the flow patterns. Calculation of the maximal Lyapunov exponent provides further support for this. Motif distributions can thus be a feasible tool to understand the dynamics of realistic two-phase flow patterns.

Identifying Learning Patterns of Children at Risk for Specific Reading Disability

Science.gov (United States)

Barbot, Baptiste; Krivulskaya, Suzanna; Hein, Sascha; Reich, Jodi; Thuma, Philip E.; Grigorenko, Elena L.

2016-01-01

Differences in learning patterns of vocabulary acquisition in children at risk (+SRD) and not at risk (-SRD) for Specific Reading Disability (SRD) were examined using a microdevelopmental paradigm applied to the multi-trial Foreign Language Learning Task (FLLT; Baddeley et al., 1995). The FLLT was administered to 905 children from rural…

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

Directory of Open Access Journals (Sweden)

Qiang Yu

Full Text Available A new learning rule (Precise-Spike-Driven (PSD Synaptic Plasticity is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

Science.gov (United States)

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Parallel patterns determination in solving cyclic flow shop problem with setups

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Bożejko Wojciech

2017-06-01

Full Text Available The subject of this work is the new idea of blocks for the cyclic flow shop problem with setup times, using multiple patterns with different sizes determined for each machine constituting optimal schedule of cities for the traveling salesman problem (TSP. We propose to take advantage of the Intel Xeon Phi parallel computing environment during so-called ’blocks’ determination basing on patterns, in effect significantly improving the quality of obtained results.

Near-Horizontal, Two-Phase Flow Patterns of Nitrogen and Hydrogen at Low Mass Heat and Flux (on CD-ROM)

Science.gov (United States)

VanDresar, N. T.; Siegwarth, J. D.

2001-01-01

One reason for NASA's interest in cryogenic two-phase flow with low mass and heat flux is the need to design spacecraft heat exchangers used for vaporizing cryogenic propellants. The CD-ROM provides digitized movies of particular flow patterns observed in experimental work. The movies have been provided in (QuickTime9Trademark) format, encoded at 320w x 240h pixels, 15 fps, using the Sorenson(Trademark) Video Codec for compression. Experiments were conducted to obtain data on the two-phase (liquid and vapor) flow behavior of cryogenic nitrogen and hydrogen under low mass and heat flux conditions. Tests were performed in normal gravity with a 1.5 degree up flow configuration. View ports in the apparatus permitted visual observation of the two-phase flow patterns. Computer codes to predict flow patterns were developed from theoretical/empirical models reported in the literature. Predictions from the computer codes were compared with experimental flow pattern observations. Results are presented employing the traditional two-dimensional flow pattern map format using the liquid and gas superficial velocities as coordinates. In general, the agreement between the experimental results and the analytical predictive methods is reasonably good. Small regions of the flow pattern maps are identified where the models are deficient as a result of neglecting phase change phenomena. Certain regions of the maps were beyond the range of the experiments and could not be completely validated. Areas that could benefit from further work include modeling of the transition from separated flow, collection of additional data in the bubble and annular flow regimes, and collection of experimental data at other inclination angles, tube diameters and high heat flux.

Three-dimensional flow structure and patterns of bed shear stress in an evolving compound meander bend

Science.gov (United States)

Engel, Frank; Rhoads, Bruce L.

2016-01-01

Compound meander bends with multiple lobes of maximum curvature are common in actively evolving lowland rivers. Interaction among spatial patterns of mean flow, turbulence, bed morphology, bank failures and channel migration in compound bends is poorly understood. In this paper, acoustic Doppler current profiler (ADCP) measurements of the three-dimensional (3D) flow velocities in a compound bend are examined to evaluate the influence of channel curvature and hydrologic variability on the structure of flow within the bend. Flow structure at various flow stages is related to changes in bed morphology over the study timeframe. Increases in local curvature within the upstream lobe of the bend reduce outer bank velocities at morphologically significant flows, creating a region that protects the bank from high momentum flow and high bed shear stresses. The dimensionless radius of curvature in the upstream lobe is one-third less than that of the downstream lobe, with average bank erosion rates less than half of the erosion rates for the downstream lobe. Higher bank erosion rates within the downstream lobe correspond to the shift in a core of high velocity and bed shear stresses toward the outer bank as flow moves through the two lobes. These erosion patterns provide a mechanism for continued migration of the downstream lobe in the near future. Bed material size distributions within the bend correspond to spatial patterns of bed shear stress magnitudes, indicating that bed material sorting within the bend is governed by bed shear stress. Results suggest that patterns of flow, sediment entrainment, and planform evolution in compound meander bends are more complex than in simple meander bends. Moreover, interactions among local influences on the flow, such as woody debris, local topographic steering, and locally high curvature, tend to cause compound bends to evolve toward increasing planform complexity over time rather than stable configurations.

Flow patterns from metallic vascular endoprostheses: in vitro results

Energy Technology Data Exchange (ETDEWEB)

Mueller-Huelsbeck, S.; Grimm, J.; Jahnke, T.; Haeselbarth, G.; Heller, M. [Dept. of Radiology, University Hospital, Kiel (Germany)

2001-05-01

The aim of this study was to determine flow characteristics and pressure gradients of different balloon- and self-expandable stents in an in vitro flow-model. Seven vascular stents (Bridge, Cragg, Memotherm, Palmaz PS 784, Sinus, Symphony, Wallstent), equal in length (60 mm) and diameter (10 mm), were deployed in a closed flow model. The inner diameter of the tube measured 9 mm. Flow at 1.5 and 6 l/min was applied. Flow patterns were visualized by anionic particles illuminated with two helium-neon lasers. Late laminary flow characteristics and pre- /post-stent pressure gradients were determined in either expanded stent, 25 and 50 % tube stenosis. Stent implantation induced a decrease of laminary flow when compared with an unstented tube with and without concentric 25 % stenosis (p < 0.01) at all flow rates and an increase of pressure gradients when compared with an unstented tube for a flow rate of 6 l/min and all stenoses (p < 0.01). At 1.5 l/min most stents revealed no significant change of pressure gradient, the highest gradient measured 4.0 mmHg. Sinus permitted maximum (expanded: 82.1 % and 76.9 % at 25 % stenosis at 1.5 l/min; p < 0.01) and Palmaz minimum of laminary flow at all flow rates and stenoses (70.2 and 52.4 % at 25 % stenosis at 1.5 l/min; p < 0.01). At 6 l/min, when completely expanded, Sinus is equal to Bridge and Memotherm; in 25 % stenosis Sinus is equal to Bridge, Memotherm, and additionally to Cragg and Wall. None of the endoprostheses revealed laminary flow at 50 % stenosis. Inadequate stent deployment bears the risk of creating less laminary flow and pressure gradients. Since flow disturbances and pressure gradients may influence neointimal hyperplasia, stent design and completeness of stent expansion are important factors regarding the appearance of thrombus formation and postinterventional restenosis. (orig.)

Application of Deep Learning and Supervised Learning Methods to Recognize Nonlinear Hidden Pattern in Water Stress Levels from Spatiotemporal Datasets across Rural and Urban US Counties

Science.gov (United States)

Eisenhart, T.; Josset, L.; Rising, J. A.; Devineni, N.; Lall, U.

2017-12-01

In the wake of recent water crises, the need to understand and predict the risk of water stress in urban and rural areas has grown. This understanding has the potential to improve decision making in public resource management, policy making, risk management and investment decisions. Assuming an underlying relationship between urban and rural water stress and observable features, we apply Deep Learning and Supervised Learning models to uncover hidden nonlinear patterns from spatiotemporal datasets. Results of interest includes prediction accuracy on extreme categories (i.e. urban areas highly prone to water stress) and not solely the average risk for urban or rural area, which adds complexity to the tuning of model parameters. We first label urban water stressed counties using annual water quality violations and compile a comprehensive spatiotemporal dataset that captures the yearly evolution of climatic, demographic and economic factors of more than 3,000 US counties over the 1980-2010 period. As county-level data reporting is not done on a yearly basis, we test multiple imputation methods to get around the issue of missing data. Using Python libraries, TensorFlow and scikit-learn, we apply and compare the ability of, amongst other methods, Recurrent Neural Networks (testing both LSTM and GRU cells), Convolutional Neural Networks and Support Vector Machines to predict urban water stress. We evaluate the performance of those models over multiple time spans and combine methods to diminish the risk of overfitting and increase prediction power on test sets. This methodology seeks to identify hidden nonlinear patterns to assess the predominant data features that influence urban and rural water stress. Results from this application at the national scale will assess the performance of deep learning models to predict water stress risk areas across all US counties and will highlight a predominant Machine Learning method for modeling water stress risk using spatiotemporal

Lack of strategy holding: a new pattern of learning deficit in cortical dementias.

Science.gov (United States)

Benedet, María J; Lauro-Grotto, Rosapia; Giotti, Chiara

2009-09-01

The aim of this study was to demonstrate, by means of systematic research and qualitative data analysis, the presence, among a group of patients with fronto-temporal lobar degeneration of a subgroup that, at variance with the standard pattern, is able to devise and implement learning strategies, but appear impaired at carrying them on from a trial to the next. In order to provide evidence of the existence of a group of patients showing this type of learning disability, that we refer to as lack of strategy holding, we performed a stepwise hierarchical cluster analysis of a set of variables whose scores were selected from the subject's performance at the Test de Aprendizaje Verbal España-Complutense. Results substantiate the segregation of three groups of subjects characterized by the following patterns of performance: normal elderly individuals, who show a quite preserved ability to discover a semantic strategy along the learning trials and to carry it from a trial to the next, patients presenting with a deficit in implementing semantic learning strategies and possibly use of serial and/or phonological strategies to perform the task, and to patients who, although able to generate and implement appropriate learning strategies, appear unable to carry them over the learning trials. The presence of this new pattern raises a few questions that seem worth trying to address.

A pedagogical design pattern framework for sharing experiences and enhancing communities of practice within online and blended learning

DEFF Research Database (Denmark)

May, Michael; Neutszky-Wulff, Chresteria; Rosthøj, Susanne

2016-01-01

for teachers at the University of Copenhagen a new and simpler pedagogical design pattern framework was developed for interfaculty sharing of experiences and enhancing communities of practice in relation to online and blended learning across the university. The framework of pedagogical design patterns were...... applied to describe the learning design in four online and blended learning courses within different academic disciplines: Classical Greek, Biostatistics, Environmental Management in Europe, and Climate Change Impacts, Adaptation and Mitigation. Future perspectives for using the framework for developing...... new E-learning patterns for online and blended learning courses are discussed....

Evaluation of Spatial Pattern of Altered Flow Regimes on a River Network Using a Distributed Hydrological Model.

Science.gov (United States)

Ryo, Masahiro; Iwasaki, Yuichi; Yoshimura, Chihiro; Saavedra V, Oliver C

2015-01-01

Alteration of the spatial variability of natural flow regimes has been less studied than that of the temporal variability, despite its ecological importance for river ecosystems. Here, we aimed to quantify the spatial patterns of flow regime alterations along a river network in the Sagami River, Japan, by estimating river discharge under natural and altered flow conditions. We used a distributed hydrological model, which simulates hydrological processes spatiotemporally, to estimate 20-year daily river discharge along the river network. Then, 33 hydrologic indices (i.e., Indicators of Hydrologic Alteration) were calculated from the simulated discharge to estimate the spatial patterns of their alterations. Some hydrologic indices were relatively well estimated such as the magnitude and timing of maximum flows, monthly median flows, and the frequency of low and high flow pulses. The accuracy was evaluated with correlation analysis (r > 0.4) and the Kolmogorov-Smirnov test (α = 0.05) by comparing these indices calculated from both observed and simulated discharge. The spatial patterns of the flow regime alterations varied depending on the hydrologic indices. For example, both the median flow in August and the frequency of high flow pulses were reduced by the maximum of approximately 70%, but these strongest alterations were detected at different locations (i.e., on the mainstream and the tributary, respectively). These results are likely caused by different operational purposes of multiple water control facilities. The results imply that the evaluation only at discharge gauges is insufficient to capture the alteration of the flow regime. Our findings clearly emphasize the importance of evaluating the spatial pattern of flow regime alteration on a river network where its discharge is affected by multiple water control facilities.

A Cross-Cultural Comparison of Student Learning Patterns in Higher Education

Science.gov (United States)

Marambe, Kosala N.; Vermunt, Jan D.; Boshuizen, Henny P. A.

2012-01-01

The aim of this study was to compare student learning patterns in higher education across different cultures. A meta-analysis was performed on three large-scale studies that had used the same research instrument: the Inventory of learning Styles (ILS). The studies were conducted in the two Asian countries Sri Lanka and Indonesia and the European…

Patterns of gene flow define species of thermophilic Archaea.

Directory of Open Access Journals (Sweden)

Hinsby Cadillo-Quiroz

2012-02-01

Full Text Available Despite a growing appreciation of their vast diversity in nature, mechanisms of speciation are poorly understood in Bacteria and Archaea. Here we use high-throughput genome sequencing to identify ongoing speciation in the thermoacidophilic Archaeon Sulfolobus islandicus. Patterns of homologous gene flow among genomes of 12 strains from a single hot spring in Kamchatka, Russia, demonstrate higher levels of gene flow within than between two persistent, coexisting groups, demonstrating that these microorganisms fit the biological species concept. Furthermore, rates of gene flow between two species are decreasing over time in a manner consistent with incipient speciation. Unlike other microorganisms investigated, we do not observe a relationship between genetic divergence and frequency of recombination along a chromosome, or other physical mechanisms that would reduce gene flow between lineages. Each species has its own genetic island encoding unique physiological functions and a unique growth phenotype that may be indicative of ecological specialization. Genetic differentiation between these coexisting groups occurs in large genomic "continents," indicating the topology of genomic divergence during speciation is not uniform and is not associated with a single locus under strong diversifying selection. These data support a model where species do not require physical barriers to gene flow but are maintained by ecological differentiation.

Patterns of gene flow define species of thermophilic Archaea.

Science.gov (United States)

Cadillo-Quiroz, Hinsby; Didelot, Xavier; Held, Nicole L; Herrera, Alfa; Darling, Aaron; Reno, Michael L; Krause, David J; Whitaker, Rachel J

2012-02-01

Despite a growing appreciation of their vast diversity in nature, mechanisms of speciation are poorly understood in Bacteria and Archaea. Here we use high-throughput genome sequencing to identify ongoing speciation in the thermoacidophilic Archaeon Sulfolobus islandicus. Patterns of homologous gene flow among genomes of 12 strains from a single hot spring in Kamchatka, Russia, demonstrate higher levels of gene flow within than between two persistent, coexisting groups, demonstrating that these microorganisms fit the biological species concept. Furthermore, rates of gene flow between two species are decreasing over time in a manner consistent with incipient speciation. Unlike other microorganisms investigated, we do not observe a relationship between genetic divergence and frequency of recombination along a chromosome, or other physical mechanisms that would reduce gene flow between lineages. Each species has its own genetic island encoding unique physiological functions and a unique growth phenotype that may be indicative of ecological specialization. Genetic differentiation between these coexisting groups occurs in large genomic "continents," indicating the topology of genomic divergence during speciation is not uniform and is not associated with a single locus under strong diversifying selection. These data support a model where species do not require physical barriers to gene flow but are maintained by ecological differentiation.

The effect of bowl-in-piston geometry layout on fluid flow pattern

Directory of Open Access Journals (Sweden)

Jovanovic Zoran S.

2011-01-01

Full Text Available In this paper some results concerning the evolution of 3D fluid flow pattern through all four strokes in combustion chambers with entirely different bowl-in-piston geometry layouts ranging from ”omega” to “simple cylinder” were presented. All combustion chambers i.e. those with „omega“ bowls, with different profiles, and those with „cylinder“ bowls, with different squish area ranging from 44% to 62%, were with flat head, vertical valves and identical elevation of intake and exhaust ports. A bunch of results emerged by dint of multidimensional modeling of nonreactive fluid flow in arbitrary geometry with moving objects and boundaries. The fluid flow pattern during induction and compression in all cases was extremely complicated and entirely three-dimensional. It should be noted that significant differences due to geometry of the bowl were encountered only in the vicinity of TDC. Namely, in the case of “omega” bowl all three types of organized macro flows were observed while in the case of “cylinder” bowl no circumferential velocity was registered at all. On the contrary, in the case of “cylinder” bowl some interesting results concerning reverse tumble and its center of rotation shifting from exhaust valve zone to intake valve zone during induction stroke and vice-verse from intake valve zone to exhaust valve zone during compression were observed while in the case of “omega” bowl no such a displacement was legible. During expansion the fluid flow pattern is fully controlled by piston motion and during exhaust it is mainly one-dimensional, except in the close proximity of exhaust valve. For that reason it is not affected by the geometry of the bowl.

Rethinking Hearing Aid Fitting by Learning From Behavioral Patterns

DEFF Research Database (Denmark)

Johansen, Benjamin; Petersen, Michael Kai; Pontoppidan, Niels Henrik

2017-01-01

users to remotely enhance auditory focus and attenuate background noise to improve speech intelligibility. N=5, participants changed program settings and adjusted volume on their hearing instruments using their smartphones. We found that individual behavioral patterns affected the usage of the devices....... A significant difference between program usage, and weekdays versus weekends, were found. Users not only changed programs to modify aspects of directionality and noise reduction, but also continuously adjusted the volume. Rethinking hearing instruments as devices that adaptively learn behavioral patterns based...

The Effect of Confluence Angle on the Flow Pattern at a Rectangular Open-Channel

Directory of Open Access Journals (Sweden)

F. Rooniyan

2014-02-01

Full Text Available Flow connection in channels is a phenomenon which frequently happens in rivers, water and drainage channels and urban sewage systems. The phenomenon appears to be more complex in rivers than in channels, especially at the y-junction bed joint that causes erosion and sedimentation at some areas resulting to morphological changes. Flow behavior at the channel junction area depends on variables such as channel geometry, discharge ratio, tributary width and y-junction connection angle of the channel, bed level changes at the bed joint, flow characteristic at the bed joint upstream and flow Froude number in different sections. In this research, fluent numerical model and junction angles of 30o, 45o & 60o are used to analyze and evaluate the effect of channel junction geometry on the flow pattern and the flow separation zone dimensions in different ratios of flow discharge (upstream channel discharge to total discharge of the flow. Results for two ratios of flow discharge are represented. Results are in agreement with earlier studies and it is shown that the change of the channel crossing angle affects the flow pattern in the main channel and also that the dimensions of the created separation zone in the main channel become larger when the crossing angle increases. This phenomenon can also be observed when the flow discharge ratio is lower. Analysis showed that the least dimension of the separation zone will be at the crossing angle of 45o .

Flow Pattern in Ventilated Rooms with Large Depth and Width

DEFF Research Database (Denmark)

Yue, Zou; Nielsen, Peter V.

In this paper both model experiments and Computational Fluid Dynamics (CFD) are employed to study the isothennal flow pattern in the ventilated room with different UH and inlet velocities. The maximum size of the model is 1.4* 0.72*0.0714m and the measurement is made by a Laser Doppler anemometer....

MODFLOW 2.0: A program for predicting moderator flow patterns

Science.gov (United States)

Peterson, P. F.; Paik, I. K.

1991-07-01

Sudden changes in the temperature of flowing liquids can result in transient buoyancy forces which strongly impact the flow hydrodynamics via flow stratification. These effects have been studied for the case of potential flow of stratified liquids to line sinks, but not for moderator flow in SRS reactors. Standard codes, such as TRAC and COMMIX, do not have the capability to capture the stratification effect, due to strong numerical diffusion which smears away the hot/cold fluid interface. A related problem with standard codes is the inability to track plumes injected into the liquid flow, again due to numerical diffusion. The combined effects of buoyant stratification and plume dispersion have been identified as being important in the operation of the Supplementary Safety System which injects neutron-poison ink into SRS reactors to provide safe shutdown in the event of safety rod failure. The MODFLOW code discussed here provides transient moderator flow pattern information with stratification effects, and tracks the location of ink plumes in the reactor. The code, written in Fortran, is compiled for Macintosh II computers, and includes subroutines for interactive control and graphical output. Removing the graphics capabilities, the code can also be compiled on other computers. With graphics, in addition to the capability to perform safety related computations, MODFLOW also provides an easy tool for becoming familiar with flow distributions in SRS reactors.

Depth distribution of preferential flow patterns in a sandy loam soil as affected by tillage

Directory of Open Access Journals (Sweden)

C. T. Petersen

1997-01-01

Full Text Available Dye-tracer studies using the anionic dye Brilliant Blue FCF were conducted on a structured sandy loam soil (Typic Agrudalf. 25 mm of dye solution was applied to the surface of 11 1.6 x 1.6 m field plots, some of which had been subjected to conventional seed bed preparation (harrowing while others had been rotovated to either 5 or 15 cm depth before sowing. The soil was excavated to about 160 cm depth one or two days after dye application. Flow patterns and structural features appearing on vertical or horizontal cross sections were examined and photographed. The flow patterns were digitized, and depth functions for the number of activated flow pathways and the degree of dye coverage were calculated. Dye was found below 100 cm depth on 26 out of 33 vertical cross sections made in conventionally tilled plots showing that preferential flow was a prevailing phenomenon. The depth-averaged number of stained flow pathways in the 25-100 cm layer was significantly smaller in a plot rotovated to 5 cm depth than in a conventionally tilled plot, both under relatively dry initial soil conditions and when the entire soil profiles were initially at field capacity. There were no examples of dye penetration below 25 cm depth one month after deep rotovation. Distinct horizontal structures in flow patterns appearing at 20-40 cm depth coupled with changes in flow domains indicated soil layering with abrupt changes in soil structure and hydraulic properties.

Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.

Science.gov (United States)

Chuk, Tim; Chan, Antoni B; Hsiao, Janet H

2017-12-01

The hidden Markov model (HMM)-based approach for eye movement analysis is able to reflect individual differences in both spatial and temporal aspects of eye movements. Here we used this approach to understand the relationship between eye movements during face learning and recognition, and its association with recognition performance. We discovered holistic (i.e., mainly looking at the face center) and analytic (i.e., specifically looking at the two eyes in addition to the face center) patterns during both learning and recognition. Although for both learning and recognition, participants who adopted analytic patterns had better recognition performance than those with holistic patterns, a significant positive correlation between the likelihood of participants' patterns being classified as analytic and their recognition performance was only observed during recognition. Significantly more participants adopted holistic patterns during learning than recognition. Interestingly, about 40% of the participants used different patterns between learning and recognition, and among them 90% switched their patterns from holistic at learning to analytic at recognition. In contrast to the scan path theory, which posits that eye movements during learning have to be recapitulated during recognition for the recognition to be successful, participants who used the same or different patterns during learning and recognition did not differ in recognition performance. The similarity between their learning and recognition eye movement patterns also did not correlate with their recognition performance. These findings suggested that perceptuomotor memory elicited by eye movement patterns during learning does not play an important role in recognition. In contrast, the retrieval of diagnostic information for recognition, such as the eyes for face recognition, is a better predictor for recognition performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design of a High Viscosity Couette Flow Facility for Patterned Surface Drag Measurements

Science.gov (United States)

Johnson, Tyler; Lang, Amy

2009-11-01

Direct drag measurements can be difficult to obtain with low viscosity fluids such as air or water. In this facility, mineral oil is used as the working fluid to increase the shear stress across the surface of experimental models. A mounted conveyor creates a flow within a plexiglass tank. The experimental model of a flat or patterned surface is suspended above a moving belt. Within the gap between the model and moving belt a Couette flow with a linear velocity profile is created. PIV measurements are used to determine the exact velocities and the Reynolds numbers for each experiment. The model is suspended by bars that connect to the pillow block housing of each bearing. Drag is measured by a force gauge connected to linear roller bearings that slide along steel rods. The patterned surfaces, initially consisting of 2-D cavities, are embedded in a plexiglass plate so as to keep the total surface area constant for each experiment. First, the drag across a flat plate is measured and compared to theoretical values for laminar Couette flow. The drag for patterned surfaces is then measured and compared to a flat plate.

Pattern transitions of oil-water two-phase flow with low water content in rectangular horizontal pipes probed by terahertz spectrum.

Science.gov (United States)

Feng, Xin; Wu, Shi-Xiang; Zhao, Kun; Wang, Wei; Zhan, Hong-Lei; Jiang, Chen; Xiao, Li-Zhi; Chen, Shao-Hua

2015-11-30

The flow-pattern transition has been a challenging problem in two-phase flow system. We propose the terahertz time-domain spectroscopy (THz-TDS) to investigate the behavior underlying oil-water flow in rectangular horizontal pipes. The low water content (0.03-2.3%) in oil-water flow can be measured accurately and reliably from the relationship between THz peak amplitude and water volume fraction. In addition, we obtain the flow pattern transition boundaries in terms of flow rates. The critical flow rate Qc of the flow pattern transitions decreases from 0.32 m3 h to 0.18 m3 h when the corresponding water content increases from 0.03% to 2.3%. These properties render THz-TDS particularly powerful technology for investigating a horizontal oil-water two-phase flow system.

Learning causes reorganization of neuronal firing patterns to represent related experiences within a hippocampal schema.

Science.gov (United States)

McKenzie, Sam; Robinson, Nick T M; Herrera, Lauren; Churchill, Jordana C; Eichenbaum, Howard

2013-06-19

According to schema theory as proposed by Piaget and Bartlett, learning involves the assimilation of new memories into networks of preexisting knowledge, as well as alteration of the original networks to accommodate the new information. Recent evidence has shown that rats form a schema of goal locations and that the hippocampus plays an essential role in adding new memories to the spatial schema. Here we examined the nature of hippocampal contributions to schema updating by monitoring firing patterns of multiple CA1 neurons as rats learned new goal locations in an environment in which there already were multiple goals. Before new learning, many neurons that fired on arrival at one goal location also fired at other goals, whereas ensemble activity patterns also distinguished different goal events, thus constituting a neural representation that linked distinct goals within a spatial schema. During new learning, some neurons began to fire as animals approached the new goals. These were primarily the same neurons that fired at original goals, the activity patterns at new goals were similar to those associated with the original goals, and new learning also produced changes in the preexisting goal-related firing patterns. After learning, activity patterns associated with the new and original goals gradually diverged, such that initial generalization was followed by a prolonged period in which new memories became distinguished within the ensemble representation. These findings support the view that consolidation involves assimilation of new memories into preexisting neural networks that accommodate relationships among new and existing memories.

Patterns of Indigenous Learning: An Ethnographic Study on How Kindergartners Learn in Mana, Fiji

Science.gov (United States)

Lee, Chih-Yih; Sparks, Paul

2015-01-01

Technology has greatly impacted educational systems around the world, even in the most geographically isolated places. This study utilizes an ethnographic approach to examine the patterns of learning in a kindergarten in Mana, Fiji. Data comprised of interviews, observations and examination of related artifacts. The results provide baseline data…

Exploring Elementary-School Students' Engagement Patterns in a Game-Based Learning Environment

Science.gov (United States)

Hsieh, Ya-Hui; Lin, Yi-Chun; Hou, Huei-Tse

2015-01-01

Unlike most research, which has primarily examined the players' interest in or attitude toward game-based learning through questionnaires, the purpose of this empirical study is to explore students' engagement patterns by qualitative observation and sequential analysis to visualize and better understand their game-based learning process. We…

Discharge characteristics and hydrodynamics behaviors of atmospheric plasma jets produced in various gas flow patterns

Science.gov (United States)

Setsuhara, Yuichi; Uchida, Giichiro; Nakajima, Atsushi; Takenaka, Kosuke; Koga, Kazunori; Shiratani, Masaharu

2015-09-01

Atmospheric nonequilibrium plasma jets have been widely employed in biomedical applications. For biomedical applications, it is an important issue to understand the complicated mechanism of interaction of the plasma jet with liquid. In this study, we present analysis of the discharge characteristics of a plasma jet impinging onto the liquid surface under various gas flow patterns such as laminar and turbulence flows. For this purpose, we analyzed gas flow patters by using a Schlieren gas-flow imaging system in detail The plasma jet impinging into the liquid surface expands along the liquid surface. The diameter of the expanded plasma increases with gas flow rate, which is well explained by an increase in the diameter of the laminar gas-flow channel. When the gas flow rate is further increased, the gas flow mode transits from laminar to turbulence in the gas flow channel, which leads to the shortening of the plasm-jet length. Our experiment demonstrated that the gas flow patterns strongly affect the discharge characteristics in the plasma-jet system. This study was partly supported by a Grant-in-Aid for Scientific Research on Innovative Areas ``Plasma Medical Innovation'' (24108003) from the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT).

Ambient Displays and Game Design Patterns for Social Learning

NARCIS (Netherlands)

Kelle, Sebastian; Börner, Dirk; Kalz, Marco; Specht, Marcus; Glahn, Christian

2011-01-01

Kelle, S., Börner, D., Kalz, M., Specht, M., & Glahn, C. (2010). Ambient Displays and Game Design Patterns for Social Learning. In B. Chang, T. Hirashima, & H. Ogata (Eds.), Joint Proceedings of the Work-in-Progress Poster and Invited Young Researcher Symposium for the 18th International Conference

Novice medical students: individual patterns in the use of learning strategies and how they change during the first academic year.

Science.gov (United States)

Fabry, Götz; Giesler, Marianne

2012-01-01

Adequate use of different learning strategies is one of the most important prerequisites of academic success. The actual use of learning strategies is the result of an interaction between individual and situational variables. Against this background we conducted a longitudinal study with first year medical students to investigate whether individuals show different patterns in their use of learning strategies and whether these patterns change during the first academic year. Medical students (N=175, 58% female) were surveyed three times in their first academic year regarding their use of learning strategies. A hierarchical cluster analysis (Ward) was conducted in order to identify groups of students with different patterns of learning strategies. We identified four different patterns in approaches to learning among novice medical students ("easy-going", "flexible", "problematic" and "hardworking" learners). Compared to their peers, the problematic learners had the worst final school grades. In addition changes in the use of learning strategies were identified, most of them occurred during the first term. Students start their academic studies with different patterns of learning strategies; the characteristics of these patterns change during the first academic year. Further research is necessary to better understand how individual and situational variables determine students' learning.

Acceptance of Game-Based Learning and Intrinsic Motivation as Predictors for Learning Success and Flow Experience

Directory of Open Access Journals (Sweden)

Manuel Ninaus

2017-09-01

Full Text Available There is accumulating evidence that engagement with digital math games can improve students’ learning. However, in what way individual variables critical to game-based learning influence students' learning success still needs to be explored. Therefore, the aim of this study was to investigate the influence of students’ acceptance of game-based learning (e.g., perceived usefulness of a game as a learning tool, perceived ease of use, as well as their intrinsic motivation for math (e.g., their math interest, self-efficacy and quality of playing experience on learning success in a game-based rational number training. Additionally, we investigated the influence of the former variables on quality of playing experience (operationalized as perceived flow. Results indicated that the game-based training was effective. Moreover, students’ learning success and their quality of playing experience were predicted by measures of acceptance of game-based learning and intrinsic motivation for math. These findings indicated that learning success in game-based learning approaches are driven by students’ acceptance of the game as a learning tool and content-specific intrinsic motivation. Therefore, the present work is of particular interest to researchers, developers, and practitioners working with game-based learning environments.

INVESTIGATION OF CONTINGENCY PATTERNS OF TEACHERS’ SCAFFOLDING IN TEACHING AND LEARNING MATHEMATICS

Directory of Open Access Journals (Sweden)

Anwar Anwar

2016-12-01

Full Text Available The purpose of this study is to investigate the patterns of scaffolding contingency in teaching and learning mathematics carried out by three teachers. Contingency patterns are obtained by examining the transcription from video recording of conversation fragments between teachers and students during the provision of scaffolding. The contingency patterns are drawn in three strategies: diagnostic strategy, intervention strategy, and checking diagnosis. The result shows that the three teachers expressed different interaction contingencies in their scaffolding activities: contingent dominant, non-contingent dominant, and pseudo-contingent. It is also found that the learning interaction performed by experienced teachers tends to be contingent dominant compared to novice teachers. Keywords: Contingency, Contingent Dominant, Non-Contingent Dominant, Pseudo Contingent, Scaffolding DOI: http://dx.doi.org/10.22342/jme.8.1.3410.65-76

Probabilistically-Cued Patterns Trump Perfect Cues in Statistical Language Learning.

Science.gov (United States)

Lany, Jill; Gómez, Rebecca L

2013-01-01

Probabilistically-cued co-occurrence relationships between word categories are common in natural languages but difficult to acquire. For example, in English, determiner-noun and auxiliary-verb dependencies both involve co-occurrence relationships, but determiner-noun relationships are more reliably marked by correlated distributional and phonological cues, and appear to be learned more readily. We tested whether experience with co-occurrence relationships that are more reliable promotes learning those that are less reliable using an artificial language paradigm. Prior experience with deterministically-cued contingencies did not promote learning of less reliably-cued structure, nor did prior experience with relationships instantiated in the same vocabulary. In contrast, prior experience with probabilistically-cued co-occurrence relationships instantiated in different vocabulary did enhance learning. Thus, experience with co-occurrence relationships sharing underlying structure but not vocabulary may be an important factor in learning grammatical patterns. Furthermore, experience with probabilistically-cued co-occurrence relationships, despite their difficultly for naïve learners, lays an important foundation for learning novel probabilistic structure.

English-learning infants' perception of word stress patterns.

Science.gov (United States)

Skoruppa, Katrin; Cristià, Alejandrina; Peperkamp, Sharon; Seidl, Amanda

2011-07-01

Adult speakers of different free stress languages (e.g., English, Spanish) differ both in their sensitivity to lexical stress and in their processing of suprasegmental and vowel quality cues to stress. In a head-turn preference experiment with a familiarization phase, both 8-month-old and 12-month-old English-learning infants discriminated between initial stress and final stress among lists of Spanish-spoken disyllabic nonwords that were segmentally varied (e.g. ['nila, 'tuli] vs [lu'ta, pu'ki]). This is evidence that English-learning infants are sensitive to lexical stress patterns, instantiated primarily by suprasegmental cues, during the second half of the first year of life. © 2011 Acoustical Society of America

A pedagogical design pattern framework for sharing experiences and enhancing communities of practice within online and blended learning

Directory of Open Access Journals (Sweden)

Chresteria Neutszky-Wulff

2016-12-01

Full Text Available ”Design patterns” were originally proposed in architecture and later in software engineering as a methodology to sketch and share solutions to recurring design problems. In recent years ”pedagogical design patterns” have been introduced as a way to sketch and share good practices in teaching and learning; specifically in the context of technology-enhanced learning (e-learning. Several attempts have been made to establish a framework for describing and sharing such e-learning patterns, but so far they have had limited success. At a series of workshops in a competence-development project for teachers at the University of Copenhagen a new and simpler pedagogical design pattern framework was developed for interfaculty sharing of experiences and enhancing communities of practice in relation to online and blended learning across the university. In this study, the new pedagogical design pattern framework is applied to describe the learning design in four online and blended learning courses within different academic disciplines: Classical Greek, Biostatistics, Environmental Management in Europe, and Climate Change Impacts, Adaptation and Mitigation. Future perspectives for using the framework for developing new E-learning patterns for online and blended learning courses are discussed.

Can Sap Flow Help Us to Better Understand Transpiration Patterns in Landscapes?

Science.gov (United States)

Hassler, S. K.; Weiler, M.; Blume, T.

2017-12-01

Transpiration is a key process in the hydrological cycle and a sound understanding and quantification of transpiration and its spatial variability is essential for management decisions and for improving the parameterisation of hydrological and soil-vegetation-atmosphere transfer models. At the tree scale, transpiration is commonly estimated by measuring sap flow. Besides evaporative demand and water availability, tree-specific characteristics such as species, size or social status, stand-specific characteristics such as basal area or stand density and site-specific characteristics such as geology, slope position or aspect control sap flow of individual trees. However, little is known about the relative importance or the dynamic interplay of these controls. We studied these influences with multiple linear regression models to explain the variability of sap velocity measurements in 61 beech and oak trees, located at 24 sites spread over a 290 km²-catchment in Luxembourg. For each of 132 consecutive days of the growing season of 2014 we applied linear models to the daily spatial pattern of sap velocity and determined the importance of the different predictors. By upscaling sap velocities to the tree level with the help of species-dependent empirical estimates for sapwood area we also examined patterns of sap flow as a more direct representation of transpiration. Results indicate that a combination of mainly tree- and site-specific factors controls sap velocity patterns in this landscape, namely tree species, tree diameter, geology and aspect. For sap flow, the site-specific predictors provided the largest contribution to the explained variance, however, in contrast to the sap velocity analysis, geology was more important than aspect. Spatial variability of atmospheric demand and soil moisture explained only a small fraction of the variance. However, the temporal dynamics of the explanatory power of the tree-specific characteristics, especially species, were

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices.

Science.gov (United States)

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B

2017-06-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support.

A D-Shaped Bileaflet Bioprosthesis which Replicates Physiological Left Ventricular Flow Patterns.

Directory of Open Access Journals (Sweden)

Sean Guo-Dong Tan

Full Text Available Prior studies have shown that in a healthy heart, there exist a large asymmetric vortex structure that aids in establishing a steady flow field in the left ventricle. However, the implantation of existing artificial heart valves at the mitral position is found to have a negative effect on this physiological flow pattern. In light of this, a novel D-shaped bileaflet porcine bioprosthesis (GD valve has been designed based on the native geometry mitral valve, with the hypothesis that biomimicry in valve design can restore physiological left ventricle flow patterns after valve implantation. An in-vitro experiment using two dimensional particle velocimetry imaging was carried out to determine the hemodynamic performance of the new bileaflet design and then compared to that of the well-established St. Jude Epic valve which functioned as a control in the experiment. Although both valves were found to have similar Reynolds shear stress and Turbulent Kinetic Energy levels, the novel D-shape valve was found to have lower turbulence intensity and greater mean kinetic energy conservation.

A D-Shaped Bileaflet Bioprosthesis which Replicates Physiological Left Ventricular Flow Patterns

Science.gov (United States)

Tan, Sean Guo-Dong; Kim, Sangho; Hon, Jimmy Kim Fatt; Leo, Hwa Liang

2016-01-01

Prior studies have shown that in a healthy heart, there exist a large asymmetric vortex structure that aids in establishing a steady flow field in the left ventricle. However, the implantation of existing artificial heart valves at the mitral position is found to have a negative effect on this physiological flow pattern. In light of this, a novel D-shaped bileaflet porcine bioprosthesis (GD valve) has been designed based on the native geometry mitral valve, with the hypothesis that biomimicry in valve design can restore physiological left ventricle flow patterns after valve implantation. An in-vitro experiment using two dimensional particle velocimetry imaging was carried out to determine the hemodynamic performance of the new bileaflet design and then compared to that of the well-established St. Jude Epic valve which functioned as a control in the experiment. Although both valves were found to have similar Reynolds shear stress and Turbulent Kinetic Energy levels, the novel D-shape valve was found to have lower turbulence intensity and greater mean kinetic energy conservation. PMID:27258099

An objective indicator for two-phase flow pattern transition

International Nuclear Information System (INIS)

Hervieu, E.; Seleghim, P. Jr.

1998-01-01

This work concerns the development of a methodology which objective is to characterize and diagnose two-phase flow regime transitions. The approach is based on the fundamental assumption that a transition flow is less stationary than a flow with an established regime. In a first time, the efforts focused on: the design and construction of an experimental loop, allowing to reproduce the main horizontal two-phase flow patterns, in a stable and controlled way; the design and construction of an electrical impedance probe, providing an imaged information of the spatial phase distribution in the pipe; the systematic study of the joint time-frequency and time-scale analysis methods, which permitted to define an adequate parameter quantifying the unstationarity degree. In a second time, in order to verify the fundamental assumption, a series of experiments were conducted, which objective was to demonstrate the correlation between unstationarity and regime transition. The unstationarity degree was quantified by calculating the Gabor's transform time-frequency covariance of the impedance probe signals. Furthermore, the phenomenology of each transition was characterized by the joint moments and entropy. The results clearly show that the regime transitions are correlated with local time-frequency covariance peaks, which demonstrates that these regime transitions are characterized by a loss of stationarity. Consequently, the time-frequency covariance constitutes an objective two-phase flow regime transition indicator. (author)

Two-phase flow pattern measurements with a wire mesh sensor in a direct steam generating solar thermal collector

Science.gov (United States)

Berger, Michael; Mokhtar, Marwan; Zahler, Christian; Willert, Daniel; Neuhäuser, Anton; Schleicher, Eckhard

2017-06-01

At Industrial Solar's test facility in Freiburg (Germany), two phase flow patterns have been measured by using a wire mesh sensor from Helmholtz Zentrum Dresden-Rossendorf (HZDR). Main purpose of the measurements was to compare observed two-phase flow patterns with expected flow patterns from models. The two-phase flow pattern is important for the design of direct steam generating solar collectors. Vibrations should be avoided in the peripheral piping, and local dry-outs or large circumferential temperature gradients should be prevented in the absorber tubes. Therefore, the choice of design for operation conditions like mass flow and steam quality are an important step in the engineering process of such a project. Results of a measurement with the wire mesh sensor are the flow pattern and the plug or slug frequency at the given operating conditions. Under the assumption of the collector power, which can be assumed from previous measurements at the same collector and adaption with sun position and incidence angle modifier, also the slip can be evaluated for a wire mesh sensor measurement. Measurements have been performed at different mass flows and pressure levels. Transient behavior has been tested for flashing, change of mass flow, and sudden changes of irradiation (cloud simulation). This paper describes the measurements and the method of evaluation. Results are shown as extruded profiles in top view and in side view. Measurement and model are compared. The tests have been performed at low steam quality, because of the limits of the test facility. Conclusions and implications for possible future measurements at larger collectors are also presented in this paper.

Flow Pattern in a Fluidized Bed with a Non-fluidized Zone

DEFF Research Database (Denmark)

Lin, Weigang; Dam-Johansen, Kim; Van den Bleek, Cor. M.

1997-01-01

is introduced. However, once the gas velocity exceeds the minimum fluidization velocity in the zone where the air is introduced, the cross-flow hardly changes upon further increase of the gas velocity. A continuity equation and Ergun's equation are used to describe the flow pattern and pressure distribution...... over the bed. Very good agreement between the experimental and calculated results is achieved without any fitting parameter. The results are relevant to the understanding of heat transfer behaviour of a fluidized bed combustor (FBC) that is only partly fluidized to control its load....

Arrangement and Applying of Movement Patterns in the Cerebellum Based on Semi-supervised Learning.

Science.gov (United States)

Solouki, Saeed; Pooyan, Mohammad

2016-06-01

Biological control systems have long been studied as a possible inspiration for the construction of robotic controllers. The cerebellum is known to be involved in the production and learning of smooth, coordinated movements. Therefore, highly regular structure of the cerebellum has been in the core of attention in theoretical and computational modeling. However, most of these models reflect some special features of the cerebellum without regarding the whole motor command computational process. In this paper, we try to make a logical relation between the most significant models of the cerebellum and introduce a new learning strategy to arrange the movement patterns: cerebellar modular arrangement and applying of movement patterns based on semi-supervised learning (CMAPS). We assume here the cerebellum like a big archive of patterns that has an efficient organization to classify and recall them. The main idea is to achieve an optimal use of memory locations by more than just a supervised learning and classification algorithm. Surely, more experimental and physiological researches are needed to confirm our hypothesis.

Active Learning in Fluid Mechanics: Youtube Tube Flow and Puzzling Fluids Questions

Science.gov (United States)

Hrenya, Christine M.

2011-01-01

Active-learning exercises appropriate for a course in undergraduate fluid mechanics are presented. The first exercise involves an experiment in gravity-driven tube flow, with small groups of students partaking in a contest to predict the experimental flow rates using the mechanical energy balance. The second exercise takes the form of an…

Two-phase flow measurement based on oblique laser scattering

Science.gov (United States)

Vendruscolo, Tiago P.; Fischer, Robert; Martelli, Cícero; Rodrigues, Rômulo L. P.; Morales, Rigoberto E. M.; da Silva, Marco J.

2015-07-01

Multiphase flow measurements play a crucial role in monitoring productions processes in many industries. To guarantee the safety of processes involving multiphase flows, it is important to detect changes in the flow conditions before they can cause damage, often in fractions of seconds. Here we demonstrate how the scattering pattern of a laser beam passing a two-phase flow under an oblique angle to the flow direction can be used to detect derivations from the desired flow conditions in microseconds. Applying machine-learning techniques to signals obtained from three photo-detectors we achieve a compact, versatile, low-cost sensor design for safety applications.

Ice Flows: A Game-based Learning approach to Science Communication

Science.gov (United States)

Le Brocq, Anne

2017-04-01

Game-based learning allows people to become immersed in an environment, and learn how the system functions and responds to change through playing a game. Science and gaming share a similar characteristic: they both involve learning and understanding the rules of the environment you are in, in order to achieve your objective. I will share experiences of developing and using the educational game "Ice Flows" for science communication. The game tasks the player with getting a penguin to its destination, through controlling the size of the ice sheet via ocean temperature and snowfall. Therefore, the game aims to educate the user about the environmental controls on the behaviour of the ice sheet, whilst they are enjoying playing a game with penguins. The game was funded by a NERC Large Grant entitled "Ice shelves in a warming world: Filchner Ice Shelf system, Antarctica", so uses data from the Weddell Sea sector of the West Antarctic Ice Sheet to generate unique levels. The game will be easily expandable to other regions of Antarctica and beyond, with the ultimate aim of giving a full understanding to the user of different ice flow regimes across the planet.

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

OpenAIRE

Abadi, Martín; Agarwal, Ashish; Barham, Paul; Brevdo, Eugene; Chen, Zhifeng; Citro, Craig; Corrado, Greg S.; Davis, Andy; Dean, Jeffrey; Devin, Matthieu; Ghemawat, Sanjay; Goodfellow, Ian; Harp, Andrew; Irving, Geoffrey; Isard, Michael

2016-01-01

TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed with little or no change on a wide variety of heterogeneous systems, ranging from mobile devices such as phones and tablets up to large-scale distributed systems of hundreds of machines and thousands of computational devices such as GPU cards. The system is flexible and can be used to express a wide variety of algo...

A supervised learning rule for classification of spatiotemporal spike patterns.

Science.gov (United States)

Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

2016-08-01

This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

An objective indicator for two-phase flow pattern transition

International Nuclear Information System (INIS)

Hervieua, E.; Seleghim, P. Jr.

1998-01-01

This work concerns the development of a methodology the objective of which is to characterize and diagnose two-phase flow regime transitions. The approach is based on the fundamental assumption that a transition flow is less stationary than a flow with an established regime. During the first time, the efforts focused on: (1) the design and construction of an experimental loop, allowing to reproduce the main horizontal two-phase flow patterns, in a stable and controlled way; (2) the design and construction of an electrical impedance probe, providing an imaged information of the spatial phase distribution in the pipe; and (3) the systematic study of the joint time-frequency and time-scale analysis methods, which permitted to define an adequate parameter quantifying the unstationarity degree. During the second time, in order to verify the fundamental assumption, a series of experiments were conducted, the objective of which was to demonstrate the correlation between unstationarity and regime transition. The unstationarity degree was quantified by calculating the Gabor's transform time-frequency covariance of the impedance probe signals. Furthermore, the phenomenology of each transition was characterized by the joint moments and entropy. The results clearly show that the regime transitions are correlated with local time-frequency covariance peaks, which demonstrates that these regime transitions are characterized by a loss of stationarity. Consequently, the time-frequency covariance constitutes an objective two-phase flow regime transition indicator. (orig.)

Optimized Structure of the Traffic Flow Forecasting Model With a Deep Learning Approach.

Science.gov (United States)

Yang, Hao-Fan; Dillon, Tharam S; Chen, Yi-Ping Phoebe

2017-10-01

Forecasting accuracy is an important issue for successful intelligent traffic management, especially in the domain of traffic efficiency and congestion reduction. The dawning of the big data era brings opportunities to greatly improve prediction accuracy. In this paper, we propose a novel model, stacked autoencoder Levenberg-Marquardt model, which is a type of deep architecture of neural network approach aiming to improve forecasting accuracy. The proposed model is designed using the Taguchi method to develop an optimized structure and to learn traffic flow features through layer-by-layer feature granulation with a greedy layerwise unsupervised learning algorithm. It is applied to real-world data collected from the M6 freeway in the U.K. and is compared with three existing traffic predictors. To the best of our knowledge, this is the first time that an optimized structure of the traffic flow forecasting model with a deep learning approach is presented. The evaluation results demonstrate that the proposed model with an optimized structure has superior performance in traffic flow forecasting.

Two-phase flow patterns recognition and parameters estimation through natural circulation test loop image analysis

Energy Technology Data Exchange (ETDEWEB)

Mesquita, R.N.; Libardi, R.M.P.; Masotti, P.H.F.; Sabundjian, G.; Andrade, D.A.; Umbehaun, P.E.; Torres, W.M.; Conti, T.N.; Macedo, L.A. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil). Nuclear Engineering Center], e-mail: rnavarro@ipen.br

2009-07-01

Visualization of natural circulation test loop cycles is used to study two-phase flow patterns associated with phase transients and static instabilities of flow. Experimental studies on natural circulation flow were originally related to accidents and transient simulations relative to nuclear reactor systems with light water refrigeration. In this regime, fluid circulation is mainly caused by a driving force ('thermal head') which arises from density differences due to temperature gradient. Natural circulation phenomenon has been important to provide residual heat removal in cases of 'loss of pump power' or plant shutdown in nuclear power plant accidents. The new generation of compact nuclear reactors includes natural circulation of their refrigerant fluid as a security mechanism in their projects. Two-phase flow patterns have been studied for many decades, and the related instabilities have been object of special attention recently. Experimental facility is an all glass-made cylindrical tubes loop which contains about twelve demineralized water liters, a heat source by an electrical resistor immersion heater controlled by a Variac, and a helicoidal heat exchanger working as cold source. Data is obtained through thermo-pairs distributed over the loop and CCD cameras. Artificial intelligence based algorithms are used to improve (bubble) border detection and patterns recognition, in order to estimate and characterize, phase transitions patterns and correlate them with the periodic static instability (chugging) cycle observed in this circuit. Most of initial results show good agreement with previous numerical studies in this same facility. (author)

Two-phase flow patterns recognition and parameters estimation through natural circulation test loop image analysis

International Nuclear Information System (INIS)

Mesquita, R.N.; Libardi, R.M.P.; Masotti, P.H.F.; Sabundjian, G.; Andrade, D.A.; Umbehaun, P.E.; Torres, W.M.; Conti, T.N.; Macedo, L.A.

2009-01-01

Visualization of natural circulation test loop cycles is used to study two-phase flow patterns associated with phase transients and static instabilities of flow. Experimental studies on natural circulation flow were originally related to accidents and transient simulations relative to nuclear reactor systems with light water refrigeration. In this regime, fluid circulation is mainly caused by a driving force ('thermal head') which arises from density differences due to temperature gradient. Natural circulation phenomenon has been important to provide residual heat removal in cases of 'loss of pump power' or plant shutdown in nuclear power plant accidents. The new generation of compact nuclear reactors includes natural circulation of their refrigerant fluid as a security mechanism in their projects. Two-phase flow patterns have been studied for many decades, and the related instabilities have been object of special attention recently. Experimental facility is an all glass-made cylindrical tubes loop which contains about twelve demineralized water liters, a heat source by an electrical resistor immersion heater controlled by a Variac, and a helicoidal heat exchanger working as cold source. Data is obtained through thermo-pairs distributed over the loop and CCD cameras. Artificial intelligence based algorithms are used to improve (bubble) border detection and patterns recognition, in order to estimate and characterize, phase transitions patterns and correlate them with the periodic static instability (chugging) cycle observed in this circuit. Most of initial results show good agreement with previous numerical studies in this same facility. (author)

Axial flow velocity patterns in a normal human pulmonary artery model: pulsatile in vitro studies.

Science.gov (United States)

Sung, H W; Yoganathan, A P

1990-01-01

It has been clinically observed that the flow velocity patterns in the pulmonary artery are directly modified by disease. The present study addresses the hypothesis that altered velocity patterns relate to the severity of various diseases in the pulmonary artery. This paper lays a foundation for that analysis by providing a detailed description of flow velocity patterns in the normal pulmonary artery, using flow visualization and laser Doppler anemometry techniques. The studies were conducted in an in vitro rigid model in a right heart pulse duplicator system. In the main pulmonary artery, a broad central flow field was observed throughout systole. The maximum axial velocity (150 cm s-1) was measured at peak systole. In the left pulmonary artery, the axial velocities were approximately evenly distributed in the perpendicular plane. However, in the bifurcation plane, they were slightly skewed toward the inner wall at peak systole and during the deceleration phase. In the right pulmonary artery, the axial velocity in the perpendicular plane had a very marked M-shaped profile at peak systole and during the deceleration phase, due to a pair of strong secondary flows. In the bifurcation plane, higher axial velocities were observed along the inner wall, while lower axial velocities were observed along the outer wall and in the center. Overall, relatively low levels of turbulence were observed in all the branches during systole. The maximum turbulence intensity measured was at the boundary of the broad central flow field in the main pulmonary artery at peak systole.

Analysis of serial coronary artery flow patterns early after primary angioplasty: new insights into the dynamics of the microcirculation.

Science.gov (United States)

Sharif, Dawod; Rofe, Guy; Sharif-Rasslan, Amal; Goldhammer, Ehud; Makhoul, Nabeel; Shefer, Arie; Hassan, Amin; Rauchfleisch, Shmuel; Rosenschein, Uri

2008-06-01

The temporal behavior of the coronary microcirculation in acute myocardial infarction may affect outcome. Diastolic deceleration time and early systolic flow reversal derived from coronary artery blood flow velocity patterns reflect microcirculatory function. To assess left anterior descending coronary artery flow velocity patterns using Doppler transthoracic echocardiography after primary percutaneous coronary intervention, in patients with anterior AMI. Patterns of flow velocity patterns of the LAD were obtained using transthoracic echocardiography-Doppler in 31 consecutive patients who presented with anterior AMI. Measurements were done at 6 hours, 36-48 hours, and 5 days after successful PPCI. Measurements of DDT and pressure half times (Pt%), as well as observation for ESFR were performed. In the first 2 days following PPCI, the average DDT (600 +/- 340 msec) was shorter than on day 5 (807 +/- 332 msec) (P 600 msec) and vice versa. On day 5 most DDTs became longer. Pt1/2 at 6 hours was not different than at day 2 (174 +/- 96 vs. 193 +/- 99 msec, P = NS) and became longer on day 5 (235 +/- 98 msec, P = 0.012). Bidirectional patterns were also observed in the ESFR in 6 patients (19%) at baseline, in 4 (13%) at 36 hours, and in 2 (6.5%) on day 5 after PPCI. Flow velocity patterns of the LAD after PPCI in AMI are dynamic and reflect unpredictable changes in microcirculation.

The RiverFish Approach to Business Process Modeling: Linking Business Steps to Control-Flow Patterns

Science.gov (United States)

Zuliane, Devanir; Oikawa, Marcio K.; Malkowski, Simon; Alcazar, José Perez; Ferreira, João Eduardo

Despite the recent advances in the area of Business Process Management (BPM), today’s business processes have largely been implemented without clearly defined conceptual modeling. This results in growing difficulties for identification, maintenance, and reuse of rules, processes, and control-flow patterns. To mitigate these problems in future implementations, we propose a new approach to business process modeling using conceptual schemas, which represent hierarchies of concepts for rules and processes shared among collaborating information systems. This methodology bridges the gap between conceptual model description and identification of actual control-flow patterns for workflow implementation. We identify modeling guidelines that are characterized by clear phase separation, step-by-step execution, and process building through diagrams and tables. The separation of business process modeling in seven mutually exclusive phases clearly delimits information technology from business expertise. The sequential execution of these phases leads to the step-by-step creation of complex control-flow graphs. The process model is refined through intuitive table and diagram generation in each phase. Not only does the rigorous application of our modeling framework minimize the impact of rule and process changes, but it also facilitates the identification and maintenance of control-flow patterns in BPM-based information system architectures.

A cross-cultural comparison of student learning patterns in higher education

NARCIS (Netherlands)

Marambe, Kosala; Vermunt, Jan; Boshuizen, Els

2012-01-01

Marambe, K. N., Vermunt, J. D., & Boshuizen, H. P. A. (2012). A cross-cultural comparison of student learning patterns in higher education. Higher Education, 64(3), 299-316. doi:10.1007/s10734-011-9494-z

Learning alternative movement coordination patterns using reinforcement feedback.

Science.gov (United States)

Lin, Tzu-Hsiang; Denomme, Amber; Ranganathan, Rajiv

2018-05-01

One of the characteristic features of the human motor system is redundancy-i.e., the ability to achieve a given task outcome using multiple coordination patterns. However, once participants settle on using a specific coordination pattern, the process of learning to use a new alternative coordination pattern to perform the same task is still poorly understood. Here, using two experiments, we examined this process of how participants shift from one coordination pattern to another using different reinforcement schedules. Participants performed a virtual reaching task, where they moved a cursor to different targets positioned on the screen. Our goal was to make participants use a coordination pattern with greater trunk motion, and to this end, we provided reinforcement by making the cursor disappear if the trunk motion during the reach did not cross a specified threshold value. In Experiment 1, we compared two reinforcement schedules in two groups of participants-an abrupt group, where the threshold was introduced immediately at the beginning of practice; and a gradual group, where the threshold was introduced gradually with practice. Results showed that both abrupt and gradual groups were effective in shifting their coordination patterns to involve greater trunk motion, but the abrupt group showed greater retention when the reinforcement was removed. In Experiment 2, we examined the basis of this advantage in the abrupt group using two additional control groups. Results showed that the advantage of the abrupt group was because of a greater number of practice trials with the desired coordination pattern. Overall, these results show that reinforcement can be successfully used to shift coordination patterns, which has potential in the rehabilitation of movement disorders.

Statistical learning of recurring sound patterns encodes auditory objects in songbird forebrain.

Science.gov (United States)

Lu, Kai; Vicario, David S

2014-10-07

Auditory neurophysiology has demonstrated how basic acoustic features are mapped in the brain, but it is still not clear how multiple sound components are integrated over time and recognized as an object. We investigated the role of statistical learning in encoding the sequential features of complex sounds by recording neuronal responses bilaterally in the auditory forebrain of awake songbirds that were passively exposed to long sound streams. These streams contained sequential regularities, and were similar to streams used in human infants to demonstrate statistical learning for speech sounds. For stimulus patterns with contiguous transitions and with nonadjacent elements, single and multiunit responses reflected neuronal discrimination of the familiar patterns from novel patterns. In addition, discrimination of nonadjacent patterns was stronger in the right hemisphere than in the left, and may reflect an effect of top-down modulation that is lateralized. Responses to recurring patterns showed stimulus-specific adaptation, a sparsening of neural activity that may contribute to encoding invariants in the sound stream and that appears to increase coding efficiency for the familiar stimuli across the population of neurons recorded. As auditory information about the world must be received serially over time, recognition of complex auditory objects may depend on this type of mnemonic process to create and differentiate representations of recently heard sounds.

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

Science.gov (United States)

Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

2017-01-01

Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG Pattern Recognition

Directory of Open Access Journals (Sweden)

Qi Huang

2017-06-01

Full Text Available Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC, by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC. We compared PAC performance with incremental support vector classifier (ISVC and non-adapting SVC (NSVC in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05 and ISVC (13.38% ± 2.62%, p = 0.001, and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle.

A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.

Directory of Open Access Journals (Sweden)

Benjamin G Schultz

Full Text Available Implicit learning (IL occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigated in temporal pattern learning. Two experiments by Schultz, Stevens, Keller, and Tillmann demonstrated the IL of auditory temporal patterns using a serial reaction-time task and a generation task based on the process dissociation procedure. The generation task demonstrated that learning was implicit in both experiments via motor fluency, that is, the inability to suppress learned information. With the aim to disentangle conscious and unconscious processes, we analyze unreported recognition data associated with the Schultz et al. experiments using the sequence identification measurement model. The model assumes that perceptual fluency reflects unconscious processes and IL. For Experiment 1, the model indicated that conscious and unconscious processes contributed to recognition of temporal patterns, but that unconscious processes had a greater influence on recognition than conscious processes. In the model implementation of Experiment 2, there was equal contribution of conscious and unconscious processes in the recognition of temporal patterns. As Schultz et al. demonstrated IL in both experiments using a generation task, and the conditions reported here in Experiments 1 and 2 were identical, two explanations are offered for the discrepancy in model and behavioral results based on the two tasks: 1 perceptual fluency may not be necessary to infer IL, or 2 conscious control over implicitly learned information may vary as a function of perceptual fluency and motor fluency.

Prevalence and Patterns of Learning Disabilities in School Children.

Science.gov (United States)

Padhy, Susanta Kumar; Goel, Sonu; Das, Shyam Sinder; Sarkar, Siddharth; Sharma, Vijaylaxmi; Panigrahi, Mahima

2016-04-01

To assess the prevalence and patterns of learning disabilities (LD) in school going children in a northern city of India. The present cross-sectional study comprised of three-staged screening procedure for assessing learning disabilities of 3rd and 4th grade students studying in government schools. The first stage comprised of the teacher identifying at-risk student. In the second stage, teachers assessed at-risk students using Specific Learning Disability-Screening Questionnaire (SLD-SQ). The third stage comprised of assessment of the screen positive students using Brigance Diagnostic Inventory (BDI) part of NIMHANS Index of Specific Learning Disabilities for identifying the cases of LD. A total of 1211 (33.6%) children out of the total screened (n = 3600) were identified as at-risk by the teachers at the first stage. Of them, 360 were found to screen positive on the second stage using SLD-SQ. The most common deficits were missing out words or sentences while reading, misplacing letters or words while reading or writing, and making frequent mistake in spelling while writing or reading. Of these, 108 children were confirmed to have learning disability on the third stage using BDI, which represented 3.08% of the total population. Learning disability is an important concern in young school aged children. Early identification of such students can help in early institution of intervention and suitable modifications in teaching techniques.

Stress and Damage Induced Gas Flow Pattern and Permeability Variation of Coal from Songzao Coalfield in Southwest China

Directory of Open Access Journals (Sweden)

Minghui Li

2016-05-01

Full Text Available The permeability of coal is a critical parameter in estimating the performance of coal reservoirs. Darcy’s law describes the flow pattern that the permeability has a linear relationship with the flow velocity. However, the stress induced deformation and damage can significantly influence the gas flow pattern and permeability of coal. Coals from Songzao coalfield in Chongqing, southwest China were collected for the study. The gas flow velocities under different injection gas pressures and effective stresses in the intact coal and damaged coal were tested using helium, incorporating the role of gas flow pattern on the permeability of coal. The relationships between the flow velocity and square of gas pressure gradient were discussed, which can help us to investigate the transformation conditions of gas linear flow and gas nonlinear flow in the coal. The results showed that the gas flow in the intact coal existed pseudo-initial flow rate under low effective stress. The low-velocity non-Darcy gas flow gradually occurred and the start-up pressure gradient increased in the coal as the effective stress increased. The gas flow rate in the damaged coal increased nonlinearly as the square of pressure gradient increased under low effective stress. The instability of gas flow caused by high ratio of injection gas pressure over effective stress in the damaged coal contributed to the increase of the gas flow rate. As the effective stress increased, the increase of gas flow rate in coal turned to be linear. The mechanisms of the phenomena were explored according to the experimental results. The permeability of coal was corrected based on the relationships between the flow velocity and square of gas pressure gradient, which showed advantages in accurately estimating the performance of coal reservoirs.

Abnormal network flow detection based on application execution patterns from Web of Things (WoT) platforms.

Science.gov (United States)

Yoon, Young; Jung, Hyunwoo; Lee, Hana

2018-01-01

In this paper, we present a research work on a novel methodology of identifying abnormal behaviors at the underlying network monitor layer during runtime based on the execution patterns of Web of Things (WoT) applications. An execution pattern of a WoT application is a sequence of profiled time delays between the invocations of involved Web services, and it can be obtained from WoT platforms. We convert the execution pattern to a time sequence of network flows that are generated when the WoT applications are executed. We consider such time sequences as a whitelist. This whitelist reflects the valid application execution patterns. At the network monitor layer, our applied RETE algorithm examines whether any given runtime sequence of network flow instances does not conform to the whitelist. Through this approach, it is possible to interpret a sequence of network flows with regard to application logic. Given such contextual information, we believe that the administrators can detect and reason about any abnormal behaviors more effectively. Our empirical evaluation shows that our RETE-based algorithm outperforms the baseline algorithm in terms of memory usage.

Unsaturated Zone Flow Patterns and Analysis

International Nuclear Information System (INIS)

Ahlers, C.

2001-01-01

This Analysis/Model Report (AMR) documents the development of an expected-case model for unsaturated zone (UZ) flow and transport that will be described in terms of the representativeness of models of the natural system. The expected-case model will provide an evaluation of the effectiveness of the natural barriers, assess the impact of conservatism in the Total System Performance Assessment (TSPA), and support the development of further models and analyses for public confidence building. The present models used in ''Total System Performance Assessment for the Site Recommendation'' (Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M and O) 2000 [1532461]) underestimate the natural-barrier performance because of conservative assumptions and parameters and do not adequately address uncertainty and alternative models. The development of an expected case model for the UZ natural barrier addresses issues regarding flow-pattern analysis and modeling that had previously been treated conservatively. This is in line with the Repository Safety Strategy (RSS) philosophy of treating conservatively those aspects of the UZ flow and transport system that are not important for achieving regulatory dose (CRWMS M and O 2000 [153246], Section 1.1.1). The development of an expected case model for the UZ also provides defense-in-depth in areas requiring further analysis of uncertainty and alternative models. In general, the value of the conservative case is to provide a more easily defensible TSPA for behavior of UZ flow and transport processes at Yucca Mountain. This AMR has been prepared in accordance with the ''Technical Work Plan for Unsaturated Zone (UZ) Flow and Transport Process Model Report'' (Bechtel SAIC Company (BSC) 2001 [155051], Section 1.3 - Work Package 4301213UMG). The work scope is to examine the data and current models of flow and transport in the Yucca Mountain UZ to identify models and analyses where conservatism may be

Relationships among student attitudes, motivation, learning styles, learning strategies, patterns of learning, and achievement: A formative evaluation of distance education via Web-based courses

Science.gov (United States)

Shih, Ching-Chun

The World Wide Web (WWW) is the latest in a long line of educational technologies, and the list of courses on it is growing daily. Formative evaluations would help educators enhance teaching and learning in Web-based courses. This study analyzed the relationships between student achievement and the following variables: attitudes, motivation, learning strategies, patterns of learning, learning styles, and selected demographics. It was a population study that included 99 students taking two non-major introductory biology courses offered over the WWW by Iowa State University in the fall of 1997. Seventy-four (75%) students completed a learning style test, an on-line questionnaire, and received a grade by the end of the semester. The learning style test was the Group Embedded Figures Test (GEFT), which classified students as either field-dependent or field-independent. The on-line questionnaire consisted of four scales (attitude, motivation, learning strategies, and patterns of learning), whose pilot-test reliabilities ranged from .71 to .91. The selected demographic variables were gender, class level, previous experience in subject area, hours per week studying and working, computer access, and types of students as off-campus, on-campus, or adult students. Over two-thirds of the students taking the Web-based courses were field-independent learners; however, there were no significant differences (.05 level) in achievement by learning style. Also, different backgrounds of students with different learning styles learned equally well in Web-based courses. The students enjoyed the convenience and self-controlled learning pace and were motivated by competition and high expectations in Web-based learning. They used most the learning strategies of finding important ideas from lectures and memorizing key words of important concepts and least the learning strategy of making charts or tables to organize the material. They seemed more interested in checking their grades than in

Patterned Roughness for Cross-flow Transition Control at Mach 6

Science.gov (United States)

Arndt, Alexander; Matlis, Eric; Semper, Michael; Corke, Thomas

2017-11-01

Experiments are performed to investigate patterned discrete roughness for transition control on a sharp right-circular cone at an angle of attack at Mach 6.0. The approach to transition control is based on exciting less-amplified (subcritical) stationary cross-flow (CF) modes that suppress the growth of the more-amplified (critical) CF modes, and thereby delay transition. The experiments were performed in the Air Force Academy Ludwieg Tube which is a conventional (noisy) design. The cone model is equipped with a motorized 3-D traversing mechanism that mounts on the support sting. The traversing mechanism held a closely-spaced pair of fast-response total pressure Pitot probes. The model utilized a removable tip to exchange between different tip-roughness conditions. Mean flow distortion x-development indicated that the transition Reynolds number increased by 25% with the addition of the subcritical roughness. The energy in traveling disturbances was centered in the band of most amplified traveling CF modes predicted by linear theory. The spatial pattern in the amplitude of the traveling CF modes indicated a nonlinear (sum and difference) interaction between the stationary and traveling CF modes that might explain differences in Retrans between noisy and quiet environments. Air Force Grant FA9550-15-1-0278.

A study of grout flow pattern analysis

International Nuclear Information System (INIS)

Lee, S. Y.; Hyun, S.

2013-01-01

A new disposal unit, designated as Salt Disposal Unit no. 6 (SDU6), is being designed for support of site accelerated closure goals and salt nuclear waste projections identified in the new Liquid Waste System plan. The unit is cylindrical disposal vault of 380 ft diameter and 43 ft in height, and it has about 30 million gallons of capacity. Primary objective was to develop the computational model and to perform the evaluations for the flow patterns of grout material in SDU6 as function of elevation of grout discharge port, and slurry rheology. A Bingham plastic model was basically used to represent the grout flow behavior. A two-phase modeling approach was taken to achieve the objective. This approach assumes that the air-grout interface determines the shape of the accumulation mound. The results of this study were used to develop the design guidelines for the discharge ports of the Saltstone feed materials in the SDU6 facility. The focusing areas of the modeling study are to estimate the domain size of the grout materials radially spread on the facility floor under the baseline modeling conditions, to perform the sensitivity analysis with respect to the baseline design and operating conditions such as elevation of discharge port, discharge pipe diameter, and grout properties, and to determine the changes in grout density as it is related to grout drop height. An axi-symmetric two-phase modeling method was used for computational efficiency. Based on the nominal design and operating conditions, a transient computational approach was taken to compute flow fields mainly driven by pumping inertia and natural gravity. Detailed solution methodology and analysis results are discussed here

Characteristics of two-phase flow pattern transitions and pressure drop of five refrigerants in horizontal circular small tubes

Energy Technology Data Exchange (ETDEWEB)

Pamitran, A.S. [Department of Mechanical Engineering, University of Indonesia, Kampus Baru UI, Depok 16424 (Indonesia); Choi, Kwang-Il [Graduate School, Chonnam National University, San 96-1, Dunduk-Dong, Yeosu, Chonnam 550-749 (Korea); Oh, Jong-Taek [Department of Refrigeration and Air Conditioning Engineering, Chonnam National University, San 96-1, Dunduk-Dong, Yeosu, Chonnam 550-749 (Korea); Hrnjak, Pega [Department of Mechanical Science and Engineering, ACRC, University of Illinois at Urbana-Champaign, 1206 West Green Street, Urbana, IL 61801 (United States)

2010-05-15

An experimental investigation on the characteristics of two-phase flow pattern transitions and pressure drop of R-22, R-134a, R-410A, R-290 and R-744 in horizontal small stainless steel tubes of 0.5, 1.5 and 3.0 mm inner diameters is presented. Experimental data were obtained over a heat flux range of 5-40 kW/m{sup 2}, mass flux range of 50-600 kg/(m{sup 2} s), saturation temperature range of 0-15 C, and quality up to 1.0. Experimental data were evaluated with Wang et al. and Wojtan et al. [Wang, C.C., Chiang, C.S., Lu, D.C., 1997. Visual observation of two-phase flow pattern of R-22, R-134a, and R-407C in a 6.5-mm smooth tube. Exp. Therm. Fluid Sci. 15, 395-405; Wojtan, L., Ursenbacher, T., Thome, J.R., 2005. Investigation of flow boiling in horizontal tubes: part I - a new diabatic two-phase flow pattern map. Int. J. Heat Mass Transfer 48, 2955-2969.] flow pattern maps. The effects of mass flux, heat flux, saturation temperature and inner tube diameter on the pressure drop of the working refrigerants are reported. The experimental pressure drop was compared with the predictions from some existing correlations. A new two-phase pressure drop model that is based on a superposition model for two-phase flow boiling of refrigerants in small tubes is presented. (author)

Evaluation of early systolic flow pattern in left ventricle by tagging cine MRI in normal volunteers

International Nuclear Information System (INIS)

Sakakura, Kazuyoshi; Anno, Naoko; Kondo, Takeshi

1992-01-01

The tagging method is a new technique, which permits to apply discretionary lines (tags) on MR images. To evaluate intra left ventricular (LV) flow pattern, we performed ECG-gated gradient field echo cine MRI using tagging method in five normal male volunteers, aged 22-42 years. The horizontal long axis view of LV was imaged by multiphasic field echo pulse sequence. The three parallel tags (basal, middle and apical portion) were established on the horizontal long axis view of LV just after the triggered QRS waves. And the initial two images (70 ms and 120 ms after the triggered QRS waves) were analyzed. On the two tags (middle and apical portion) of these three tags, we measured the distance of displacement of the tags on three points (the near site of IVS, middle portion and the near site of free wall) respectively. At 70 ms after the trigger point, the only tagged blood at the near site of free wall flowed toward the apex. At 120 ms after the trigger point, all the tagged blood flowed toward the outflow tract of LV. And the maximum blood flow velocity was observed at the near site of IVS on middle portion of LV (166.0 mm/s). These results coincided with earlier studies by Doppler echocardiography. But we could not observe intra LV blood flow patterns throughout one cardiac cycle in this pulse sequence, because the tags had flowed out from LV and had become unclear due to spin relaxation and mixing. We concluded that the tagging method was useful to evaluate intra left ventricular blood flow patterns in early systolic phase. (author)

Determination of drift-flux velocity as a function of two-phase flow patterns

International Nuclear Information System (INIS)

Austregesilo Filho, H.

1986-01-01

A method is suggested for the calculation of drift-flux velocity as a function of two-phase flow patterns determined analytically. This model can be introduced in computer codes for thermal hydraulic analyses based mainly on homogeneous assumptions, in order to achieve a more realis tic description of two-phase flow phenomena, which is needed for the simulation of accidents in nuclear power plants for which phase separation effects are dominant, e.g., small break accidents. (Author) [pt

Wind-Induced Air-Flow Patterns in an Urban Setting: Observations and Numerical Modeling

Science.gov (United States)

Sattar, Ahmed M. A.; Elhakeem, Mohamed; Gerges, Bishoy N.; Gharabaghi, Bahram; Gultepe, Ismail

2018-04-01

City planning can have a significant effect on wind flow velocity patterns and thus natural ventilation. Buildings with different heights are roughness elements that can affect the near- and far-field wind flow velocity. This paper aims at investigating the impact of an increase in building height on the nearby velocity fields. A prototype urban setting of buildings with two different heights (25 and 62.5 cm) is built up and placed in a wind tunnel. Wind flow velocity around the buildings is mapped at different heights. Wind tunnel measurements are used to validate a 3D-numerical Reynolds averaged Naviers-Stokes model. The validated model is further used to calculate the wind flow velocity patterns for cases with different building heights. It was found that increasing the height of some buildings in an urban setting can lead to the formation of large horseshoe vortices and eddies around building corners. A separation area is formed at the leeward side of the building, and the recirculation of air behind the building leads to the formation of slow rotation vortices. The opposite effect is observed in the wake (cavity) region of the buildings, where both the cavity length and width are significantly reduced, and this resulted in a pronounced increase in the wind flow velocity. A significant increase in the wind flow velocity in the wake region of tall buildings with a value of up to 30% is observed. The spatially averaged velocities around short buildings also increased by 25% compared to those around buildings with different heights. The increase in the height of some buildings is found to have a positive effect on the wind ventilation at the pedestrian level.

Future climate and changes in flow patterns in Czech headwater catchments

Czech Academy of Sciences Publication Activity Database

Benčoková, A.; Krám, P.; Hruška, Jakub

2011-01-01

Roč. 49, č. 1 (2011), s. 1-15 ISSN 0936-577X R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073 Institutional research plan: CEZ:AV0Z60870520 Keywords : climate change impact * flow pattern * regional climate scenarios * Headwater catchments * hydrological modelling * Broo90 Subject RIV: DA - Hydrology ; Limnology Impact factor: 1.994, year: 2011

Flow pattern assessment in tubes with wire coil inserts in laminar and transition regimes

International Nuclear Information System (INIS)

Garcia, A.; Solano, J.P.; Vicente, P.G.; Viedma, A.

2007-01-01

The paper presents an analysis of the flow mechanisms in tubes with wire coils using hydrogen bubble visualization and PIV techniques. Results have been contrasted with experimental data on pressure drop. The relation between the observed flow patterns and the friction factor has been analysed. The experimental analysis that has been carried out allows one to state that at low Reynolds numbers (Re < 400) the flow in tubes with wire coils is basically similar to the flow in smooth tubes. At Reynolds numbers between 500 and 700 and in short pitch wire coils a recirculating flow appears. The insertion of wires coils in a smooth tube accelerates significantly the transition to turbulence. This is produced at Reynolds numbers between 700 and 1000 depending on the wire pitch

Dual-modality impairment of implicit learning of letter-strings versus color-patterns in patients with schizophrenia

OpenAIRE

Chiu, Ming-Jang; Liu, Kristina; Hsieh, Ming H; Hwu, Hai-Gwo

2005-01-01

Abstract Background Implicit learning was reported to be intact in schizophrenia using artificial grammar learning. However, emerging evidence indicates that artificial grammar learning is not a unitary process. The authors used dual coding stimuli and schizophrenia clinical symptom dimensions to re-evaluate the effect of schizophrenia on various components of artificial grammar learning. Methods Letter string and color pattern artificial grammar learning performances were compared between 63...

Visualisation of flow patterns in straight and C-shape thermosyphons

Science.gov (United States)

Ong, K. S.; Tshai, K. H.; Firwana, A.

2017-04-01

A heat pipe is a passive heat transfer device capable of transferring a large quantity of heat effectively and efficiently over a long distance and with a small temperature difference between the heat source and heat sink. A heat pipe consists of a metal pipe initially vacuumed and then filled with a small quantity of fluid inside. The pipe is separated into a heating (evaporator) section and a cooling (condenser) section by an adiabatic section. In a run-around-coil heating, ventilation and air conditioning system, a wrap-around heat pipe heat exchanger could be employed to increase dehumidification and to reduce cooling costs. The thermal performance of a thermosyphon is dependent upon type of fill liquid, fill ratio, power input, pipe inclination and pipe dimensions. The boiling and condensation processes that occur inside a thermosyphon are quite complex. During operation, dry-out, burn-out or boiling limit, entrainment or flooding limit and geysering occur. These phenomena would lead to non-uniform axial wall temperature distribution in the pipe, or worse still, ineffective operation. In order to have a better understanding of the internal heat transfer phenomena, a visual study using transparent glass tubes and high speed camera recording of the internal flow patterns would be most helpful. This paper reports on an experimental investigation conducted to visualise the flow patterns in straight and C-shape thermosyphons. The pictures recorded enabled the internal flow boiling and condensation pattern occurring inside a straight and a C-shape thermosyphon to be observed. The thermosyphons were fabricated from 10 mm O/D × 8 mm I/D × 300 mm long glass tubes and filled with water with fill ratios from 0.5 - 1.5. The evaporator sections of the thermosyphons were immersed into a hot water tank that was electrically heated from cold at ambient temperature till boiling. Cooling of the condenser section was achieved using a fan. Preliminary results showed that dry

Unsaturated Zone Flow Patterns and Analysis

Energy Technology Data Exchange (ETDEWEB)

C. Ahlers

2001-10-17

This Analysis/Model Report (AMR) documents the development of an expected-case model for unsaturated zone (UZ) flow and transport that will be described in terms of the representativeness of models of the natural system. The expected-case model will provide an evaluation of the effectiveness of the natural barriers, assess the impact of conservatism in the Total System Performance Assessment (TSPA), and support the development of further models and analyses for public confidence building. The present models used in ''Total System Performance Assessment for the Site Recommendation'' (Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) 2000 [1532461]) underestimate the natural-barrier performance because of conservative assumptions and parameters and do not adequately address uncertainty and alternative models. The development of an expected case model for the UZ natural barrier addresses issues regarding flow-pattern analysis and modeling that had previously been treated conservatively. This is in line with the Repository Safety Strategy (RSS) philosophy of treating conservatively those aspects of the UZ flow and transport system that are not important for achieving regulatory dose (CRWMS M&O 2000 [153246], Section 1.1.1). The development of an expected case model for the UZ also provides defense-in-depth in areas requiring further analysis of uncertainty and alternative models. In general, the value of the conservative case is to provide a more easily defensible TSPA for behavior of UZ flow and transport processes at Yucca Mountain. This AMR has been prepared in accordance with the ''Technical Work Plan for Unsaturated Zone (UZ) Flow and Transport Process Model Report'' (Bechtel SAIC Company (BSC) 2001 [155051], Section 1.3 - Work Package 4301213UMG). The work scope is to examine the data and current models of flow and transport in the Yucca Mountain UZ to identify models and analyses

Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI

Directory of Open Access Journals (Sweden)

Dieter Devlaminck

2011-01-01

Full Text Available Motor-imagery-based brain-computer interfaces (BCIs commonly use the common spatial pattern filter (CSP as preprocessing step before feature extraction and classification. The CSP method is a supervised algorithm and therefore needs subject-specific training data for calibration, which is very time consuming to collect. In order to reduce the amount of calibration data that is needed for a new subject, one can apply multitask (from now on called multisubject machine learning techniques to the preprocessing phase. Here, the goal of multisubject learning is to learn a spatial filter for a new subject based on its own data and that of other subjects. This paper outlines the details of the multitask CSP algorithm and shows results on two data sets. In certain subjects a clear improvement can be seen, especially when the number of training trials is relatively low.

Improved children's motor learning of the basketball free shooting pattern by associating subjective error estimation and extrinsic feedback.

Science.gov (United States)

Silva, Leandro de Carvalho da; Pereira-Monfredini, Carla Ferro; Teixeira, Luis Augusto

2017-09-01

This study aimed at assessing the interaction between subjective error estimation and frequency of extrinsic feedback in the learning of the basketball free shooting pattern by children. 10- to 12-year olds were assigned to 1 of 4 groups combining subjective error estimation and relative frequency of extrinsic feedback (33% × 100%). Analysis of performance was based on quality of movement pattern. Analysis showed superior learning of the group combining error estimation and 100% feedback frequency, both groups receiving feedback on 33% of trials achieved intermediate results, and the group combining no requirement of error estimation and 100% feedback frequency had the poorest learning. Our results show the benefit of subjective error estimation in association with high frequency of extrinsic feedback in children's motor learning of a sport motor pattern.

Quantitative activation patterns of cerebral blood flow during mental stimulation after intravenous injection of sup(195m)Au

International Nuclear Information System (INIS)

Lindner, P.; Nickel, O.

1983-01-01

A previously reported theory for quantitative cerebral blood flow measurement for nondiffusible radiotracers has been applied to patients after stroke and to volunteers undergoing a mental stimulation exercise. Quantitative measurements of cerebral blood flow pattern in p-a and lateral projections of the brain are obtained using the short lived (30s) isotope sup(195m)Au from the recently developed generator. The energy spectrum of the eluate from the generator shows two strong photon peaks, one at an energy level of 68 KeV and a second at 262 KeV. The low-energy peak is suitable for perfusion studies of the cerebral hemispheres in lateral projection, being without ''look through'' effect. The high-energy level is good for studies in p-a-projection. Studies last less than 1 min and can be repeated after 3 min. Parametric images for quantitative regional cerebral blood flow can be generated, in which the avascular region following stroke can be detected. Quantitative activation patterns of cerebral blood flow during mental stimulation can be generated. The results show that it is possible to measure cerebral blood-flow patterns not only with freely diffusible indicators like Xenon but also with nondiffusible indicators. (orig.)

Heating patterns during cancer heat therapy as a function of blood flow

International Nuclear Information System (INIS)

Mendecki, J.; Friedenthal, E.; Botstein, C.; Sterzer, F.; Paglione, R.W.

1984-01-01

Heating patterns as a function of regional blood flow were evaluated in healthy tissues with different vascular characteristics as well as in a variety of tumors submitted to microwave and RF-induced hyperthermia. Generally, faster heating and slower cooling was demonstrated for tumors. Definite correlation was found between the power needed to heat given tissue volume to a specific temperature and the ability of this tissue to dissipate heat via vascular flow. The measurements show that during the early phase of heating of tumors temperature rises slowly up to about 40 0 C. indicating good heat exchanges but that at this level rapid increase of temperature occurs for relatively small increments of power input. It is suggested that blood flow in malignant tissue remains competent and responsive to low grade heating, but that at higher temperature levels, in contrast to normal tissue, tumor blood flow rapidly decreases indicating compromised vascular system. Implication for treatment protocols are discussed

Integral Mindflow: A Process of Mindfulness-in-Flow to Enhance Individual and Organization Learning

Science.gov (United States)

Cacioppe, Ron Lewis

2017-01-01

Purpose: This paper aims to examine the differences in mindfulness, meditation and flow and the conditions in which each occurs. It summarizes research that demonstrates positive benefits of these three for employee and organizational learning. While mindfulness focuses awareness on what is occurring in the moment, flow involves total immersion in…

Decoding complex flow-field patterns in visual working memory.

Science.gov (United States)

Christophel, Thomas B; Haynes, John-Dylan

2014-05-01

There has been a long history of research on visual working memory. Whereas early studies have focused on the role of lateral prefrontal cortex in the storage of sensory information, this has been challenged by research in humans that has directly assessed the encoding of perceptual contents, pointing towards a role of visual and parietal regions during storage. In a previous study we used pattern classification to investigate the storage of complex visual color patterns across delay periods. This revealed coding of such contents in early visual and parietal brain regions. Here we aim to investigate whether the involvement of visual and parietal cortex is also observable for other types of complex, visuo-spatial pattern stimuli. Specifically, we used a combination of fMRI and multivariate classification to investigate the retention of complex flow-field stimuli defined by the spatial patterning of motion trajectories of random dots. Subjects were trained to memorize the precise spatial layout of these stimuli and to retain this information during an extended delay. We used a multivariate decoding approach to identify brain regions where spatial patterns of activity encoded the memorized stimuli. Content-specific memory signals were observable in motion sensitive visual area MT+ and in posterior parietal cortex that might encode spatial information in a modality independent manner. Interestingly, we also found information about the memorized visual stimulus in somatosensory cortex, suggesting a potential crossmodal contribution to memory. Our findings thus indicate that working memory storage of visual percepts might be distributed across unimodal, multimodal and even crossmodal brain regions. Copyright © 2014 Elsevier Inc. All rights reserved.

Prediction for flow boiling heat transfer in small diameter tube using deep learning

International Nuclear Information System (INIS)

Enoki, Koji; Sei, Yuichi; Okawa, Tomio; Saito, Kiyoshi

2017-01-01

The applications of Artificial Intelligence ie AI show diversity in any fields. On the other hand, research of the predicting heat transfer regardless of single-phase or two-phase flow is still untouched. Therefore, we have confirmed usefulness using AI's deep learning function on horizontal flow boiling heat transfer in flowing mini-channel that is actively researched. The effect of the surface tension in the mini-channel is large compared with conventional large tubes, and then the heat transfer mechanism is very complicated. For this reason, the numerical correlations of many existing researchers the prediction result is not good. However, the mechanistic correlation based on the visualization experiment, which the authors' research group published several years ago has very high precision. Therefore, in this research paper, we confirmed the effectiveness of using deep learning for predicting of the boiling heat transfer in mini-channel while comparing our correlation. (author)

Personality patterns and vocational interests of learning disabled and nonlearning disabled high school students

OpenAIRE

Ivy, Robert J.

1991-01-01

There is a lack of research based data in the field of learning disabilities, especially at the secondary level. The purpose of this study was to evaluate personality configuration patterns and vocational interests through the administration of the Myers-Briggs Type Indicator, Abbreviated Version (AV) and the Self-Directed Search, Form E (EASY) for learning disabled (LD) and non-learning disabled (NLD) students. The sample included 90 LD students and 100 Non-LD stud...

Thinking Aloud While Solving a Stock-Flow Task: Surfacing the Correlation Heuristic and Other Reasoning Patterns

NARCIS (Netherlands)

Korzilius, H.P.L.M.; Raaijmakers, S.F.J.M.; Rouwette, E.A.J.A.; Vennix, J.A.M.

2014-01-01

In the literature, it is assumed that individuals, while performing stock-flow tasks, often use a correlation heuristic, a form of pattern matching in which they think that the behavior of the stock resembles the (net) flow. To investigate this assumption and to increase our insight in the actual

Comparative Analysis of River Flow Modelling by Using Supervised Learning Technique

Science.gov (United States)

Ismail, Shuhaida; Mohamad Pandiahi, Siraj; Shabri, Ani; Mustapha, Aida

2018-04-01

The goal of this research is to investigate the efficiency of three supervised learning algorithms for forecasting monthly river flow of the Indus River in Pakistan, spread over 550 square miles or 1800 square kilometres. The algorithms include the Least Square Support Vector Machine (LSSVM), Artificial Neural Network (ANN) and Wavelet Regression (WR). The forecasting models predict the monthly river flow obtained from the three models individually for river flow data and the accuracy of the all models were then compared against each other. The monthly river flow of the said river has been forecasted using these three models. The obtained results were compared and statistically analysed. Then, the results of this analytical comparison showed that LSSVM model is more precise in the monthly river flow forecasting. It was found that LSSVM has he higher r with the value of 0.934 compared to other models. This indicate that LSSVM is more accurate and efficient as compared to the ANN and WR model.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

Science.gov (United States)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Carbon flow pattern in the forest zones of Nigeria as influenced by ...

African Journals Online (AJOL)

use

Forest in Nigeria plays a much wider role in the overall balance of issues ... Key words: Carbon flow pattern, forest life zone, land use, human activities, ... accounting about the forest is its contribution in relation to ... The scope of this work is limited to anthropogenic ... vegetation change, none of the natural factors is known.

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

Energy Technology Data Exchange (ETDEWEB)

Bornholdt, S. [Heidelberg Univ., (Germany). Inst., fuer Theoretische Physik; Graudenz, D. [Lawrence Berkeley Lab., CA (United States)

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.

General asymmetric neutral networks and structure design by genetic algorithms: A learning rule for temporal patterns

International Nuclear Information System (INIS)

Bornholdt, S.

1993-07-01

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback

The Influence of Prosodic Stress Patterns and Semantic Depth on Novel Word Learning in Typically Developing Children.

Science.gov (United States)

Gladfelter, Allison; Goffman, Lisa

2013-01-01

The goal of this study was to investigate the effects of prosodic stress patterns and semantic depth on word learning. Twelve preschool-aged children with typically developing speech and language skills participated in a word learning task. Novel words with either a trochaic or iambic prosodic pattern were embedded in one of two learning conditions, either in children's stories (semantically rich) or picture matching games (semantically sparse). Three main analyses were used to measure word learning: comprehension and production probes, phonetic accuracy, and speech motor stability. Results revealed that prosodic frequency and density influence the learnability of novel words, or that there are prosodic neighborhood density effects. The impact of semantic depth on word learning was minimal and likely depends on the amount of experience with the novel words.

Learning to classify wakes from local sensory information

Science.gov (United States)

Alsalman, Mohamad; Colvert, Brendan; Kanso, Eva; Kanso Team

2017-11-01

Aquatic organisms exhibit remarkable abilities to sense local flow signals contained in their fluid environment and to surmise the origins of these flows. For example, fish can discern the information contained in various flow structures and utilize this information for obstacle avoidance and prey tracking. Flow structures created by flapping and swimming bodies are well characterized in the fluid dynamics literature; however, such characterization relies on classical methods that use an external observer to reconstruct global flow fields. The reconstructed flows, or wakes, are then classified according to the unsteady vortex patterns. Here, we propose a new approach for wake identification: we classify the wakes resulting from a flapping airfoil by applying machine learning algorithms to local flow information. In particular, we simulate the wakes of an oscillating airfoil in an incoming flow, extract the downstream vorticity information, and train a classifier to learn the different flow structures and classify new ones. This data-driven approach provides a promising framework for underwater navigation and detection in application to autonomous bio-inspired vehicles.

A Data Flow Model to Solve the Data Distribution Changing Problem in Machine Learning

Directory of Open Access Journals (Sweden)

Shang Bo-Wen

2016-01-01

Full Text Available Continuous prediction is widely used in broad communities spreading from social to business and the machine learning method is an important method in this problem.When we use the machine learning method to predict a problem. We use the data in the training set to fit the model and estimate the distribution of data in the test set.But when we use machine learning to do the continuous prediction we get new data as time goes by and use the data to predict the future data, there may be a problem. As the size of the data set increasing over time, the distribution changes and there will be many garbage data in the training set.We should remove the garbage data as it reduces the accuracy of the prediction. The main contribution of this article is using the new data to detect the timeliness of historical data and remove the garbage data.We build a data flow model to describe how the data flow among the test set, training set, validation set and the garbage set and improve the accuracy of prediction. As the change of the data set, the best machine learning model will change.We design a hybrid voting algorithm to fit the data set better that uses seven machine learning models predicting the same problem and uses the validation set putting different weights on the learning models to give better model more weights. Experimental results show that, when the distribution of the data set changes over time, our time flow model can remove most of the garbage data and get a better result than the traditional method that adds all the data to the data set; our hybrid voting algorithm has a better prediction result than the average accuracy of other predict models

Patterning of ultrathin polymethylmethacrylate films by in-situ photodirecting of the Marangoni flow

Energy Technology Data Exchange (ETDEWEB)

Elashnikov, Roman [Department of Solid State Engineering, University of Chemistry and Technology, 16628 Prague, Czech Repuiblic (Czech Republic); Fitl, Premysl [Department of Physics and Measurements, University of Chemistry and Technology, 16628 Prague, Czech Repuiblic (Czech Republic); Svorcik, Vaclav [Department of Solid State Engineering, University of Chemistry and Technology, 16628 Prague, Czech Repuiblic (Czech Republic); Lyutakov, Oleksiy, E-mail: lyutakoo@vscht.cz [Department of Solid State Engineering, University of Chemistry and Technology, 16628 Prague, Czech Repuiblic (Czech Republic)

2017-02-01

Highlights: • The preparation of periodical structures on the polymer surface using photo-directing of Marangoni flow is described. • The surface tension gradient appears due to the spatial distribution of energy in the laser beam and leads to the creation of periodical structures. • The method allows the creation of surface structures with different symmetry, from simple line array to more complex geometries. - Abstract: Laser heating and Marangoni flow result in the formation of surface structures with different geometries and shape on thin polymer films. By laser beam irradiation combined with a sample movement the solid polymethylmethacrylate (PMMA) films are heated and undergo phase transition which leads to a material flow. Since the laser beam has a non-linear distribution of energy, the PMMA film is heated inhomogeneously and a surface tension gradient in a lateral direction is introduced. During this procedure additional phenomena such as “reversible” or cyclic polymer flow also take place. The careful choice of experimental conditions enables the preparation of patterns with sophisticated geometries and with hierarchical pattern organization. Depending on initial PMMA film thickness and speed of the sample movement line arrays are created, which can subsequently be transformed into the crimped lines or system of circular holes. In addition, the introduction of a constant acceleration in the sample movement or a laser beam distortion enables the preparation of regularly crimped lines, ordered hexagonal holes or overlapped plates.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

Directory of Open Access Journals (Sweden)

T. Blume

2009-07-01

Full Text Available Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale and binary indicator maps (for the long-term and hillslope scale. Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to

Impact of vegetation die-off on spatial flow patterns over a tidal marsh

NARCIS (Netherlands)

Temmerman, S.; Moonen, P.; Schoelynck, J.; Govers, G.; Bouma, T.J.

2012-01-01

Large-scale die-off of tidal marsh vegetation, caused by global change, is expected to change flow patterns over tidal wetlands, and hence to affect valuable wetland functions such as reduction of shoreline erosion, attenuation of storm surges, and sedimentation in response to sea level rise. This

Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?

DEFF Research Database (Denmark)

Harders, Stefan Walbom; Madsen, Hans Henrik; Nellemann, Hanne Marie

2017-01-01

with suspected lung cancer and a lung tumor on their chest radiograph were included for DCE-CT. The tumors were categorized using structured qualitative analysis of tumor blood flow patterns. Histopathology was used as reference standard. RESULTS: Using structured qualitative analysis of tumor blood flow...... using structured qualitative analysis of tumor blood flow patterns is accurate as well as somewhat reproducible. However, there are significant limitations to DCE-CT.......BACKGROUND: Dynamic contrast-enhanced computed tomography (DCE-CT) is a tool, which, in theory, can quantify the blood flow and blood volume of tissues. In structured qualitative analysis, parametric color maps yield a visual impression of the blood flow and blood volume within the tissue being...

Contrast-enhanced Harmonic power Doppler ultrasonography: Improved depiction of vascularity and characterization of flow pattern in hepatocellular carcinoma

International Nuclear Information System (INIS)

Baek, Hyung Chul; Yoon, Kwon Ha; Kim, Chang Guhn; Park, Ki Han; Won, Jong Jin

2000-01-01

To evaluate the value of contrast-enhanced harmonic power Doppler ultrasonography (PDUS) in depiction and characterization of tumoral vascularity in hepatocellular carcinoma (HCC). Thirty-three patients with HCC were prospectively evaluated with harmonic PDUS before and after injection of the contrast agent SH U 508A (2.5g, 300 mg/ml ). Unenhanced and serial dynamic scans at 15, 30, 45, 60, 90, 120, 150, 180, 240, 300 seconds after injection of contrast agents were obtained using a tissue harmonic technique with power Doppler imaging. The tumoral vascularity was expressed as percentage of power Doppler area, which was measured quantitatively by a computerized program (Ultrasonic Imaging Tool; Soongsil University, Seoul, Korea). The grade (0, no signal; 1, less than 5%; 2, 5-25%; 3, more than 25%) and flow pattern (intratumoral, detour, basket, and mixed) of tumoral vascularity were analyzed. Peak time of contrast-enhancement was measured on each tumor. After injection of contrast agent, tumoral flow signals increased in all lesions (100%). At unenhanced harmonic PDUS, flow signals were detected in 17 HCCs (52%); 15 tumors (46%) demonstrated grade 1 vascularity; and two (6%), grade 2. At contrast-enhanced harmonic PDUS, all tumors were detected vascularity; five (15%) were grade 1; eight (24%), grade 2; and 20 (61%), grade 3. Flow patterns were demonstated as follows at unenhanced harmonic PDUS; intratumoral pattern in 13 tumors (76%), detour in 2 (12%), and basket in 2 (12%). After injection of contrast agent, intratumoral pattern in 7 tumors (21%), detour 0 (0%), basket in 3 (9%) and mixed in 23 (70%) were demonstrated. Peak time of enhancement after injection of contrast agent was 30- 90 seconds in majority of the patients. Contrast-enhanced harmonic PDUS would be valuable in depiction of vascularity and characterization of flow pattern in HCC.

Contrast-enhanced Harmonic power Doppler ultrasonography: Improved depiction of vascularity and characterization of flow pattern in hepatocellular carcinoma

Energy Technology Data Exchange (ETDEWEB)

Baek, Hyung Chul; Yoon, Kwon Ha; Kim, Chang Guhn; Park, Ki Han; Won, Jong Jin [Wonkwang University School of Medicine, Iksa (Korea, Republic of)

2000-12-15

To evaluate the value of contrast-enhanced harmonic power Doppler ultrasonography (PDUS) in depiction and characterization of tumoral vascularity in hepatocellular carcinoma (HCC). Thirty-three patients with HCC were prospectively evaluated with harmonic PDUS before and after injection of the contrast agent SH U 508A (2.5g, 300 mg/ml ). Unenhanced and serial dynamic scans at 15, 30, 45, 60, 90, 120, 150, 180, 240, 300 seconds after injection of contrast agents were obtained using a tissue harmonic technique with power Doppler imaging. The tumoral vascularity was expressed as percentage of power Doppler area, which was measured quantitatively by a computerized program (Ultrasonic Imaging Tool; Soongsil University, Seoul, Korea). The grade (0, no signal; 1, less than 5%; 2, 5-25%; 3, more than 25%) and flow pattern (intratumoral, detour, basket, and mixed) of tumoral vascularity were analyzed. Peak time of contrast-enhancement was measured on each tumor. After injection of contrast agent, tumoral flow signals increased in all lesions (100%). At unenhanced harmonic PDUS, flow signals were detected in 17 HCCs (52%); 15 tumors (46%) demonstrated grade 1 vascularity; and two (6%), grade 2. At contrast-enhanced harmonic PDUS, all tumors were detected vascularity; five (15%) were grade 1; eight (24%), grade 2; and 20 (61%), grade 3. Flow patterns were demonstated as follows at unenhanced harmonic PDUS; intratumoral pattern in 13 tumors (76%), detour in 2 (12%), and basket in 2 (12%). After injection of contrast agent, intratumoral pattern in 7 tumors (21%), detour 0 (0%), basket in 3 (9%) and mixed in 23 (70%) were demonstrated. Peak time of enhancement after injection of contrast agent was 30- 90 seconds in majority of the patients. Contrast-enhanced harmonic PDUS would be valuable in depiction of vascularity and characterization of flow pattern in HCC.

Experience of Google's latest deep learning library, TensorFlow, in a large-scale WLCG cluster

Energy Technology Data Exchange (ETDEWEB)

Kawamura, Gen; Smith, Joshua Wyatt; Quadt, Arnulf [II. Physikalisches Institut, Georg-August-Universitaet Goettingen (Germany)

2016-07-01

The researchers at the Google Brain team released their second generation's Deep Learning library, TensorFlow, as an open-source package under the Apache 2.0 license in November, 2015. Google has already deployed the first generation's library using DistBlief in various systems such as Google Search, advertising systems, speech recognition systems, Google Images, Google Maps, Street View, Google Translate and many other latest products. In addition, many researchers in high energy physics have recently started to understand and use Deep Learning algorithms in their own research and analysis. We conceive a first use-case scenario of TensorFlow to create the Deep Learning models from high-dimensional inputs like physics analysis data in a large-scale WLCG computing cluster. TensorFlow carries out computations using a dataflow model and graph structure onto a wide variety of different hardware platforms and systems, such as many CPU architectures, GPUs and smartphone platforms. Having a single library that can distribute the computations to create a model to the various platforms and systems would significantly simplify the use of Deep Learning algorithms in high energy physics. We deploy TensorFlow with the Docker container environments and present the first use in our grid system.

Feeding alters blood flow patterns in the American alligator (Alligator mississippiensis).

Science.gov (United States)

Findsen, Anders; Crossley, Dane A; Wang, Tobias

2018-01-01

The crocodilian cardiovascular design with a four-chambered heart and a left aorta that emerge from the right ventricle allows blood to be shunted away from the lungs, a right-to-left (R-L) shunt. The adaptive significance of this R-L shunt remains both poorly understood and controversial with particular debate on its putative role during digestion. Here we measure blood flow patterns in the right aorta (RAo), left aorta (LAo) and the coeliac artery (CoA) of undisturbed American alligators (Alligator mississippiensis) during fasting and throughout most of the digestive period. Digestion doubled blood flow in the RAo (10.1±0.9 to 20.7±1.5mlmin -1 kg -1 ), whereas LAo increased approximately 3-fold (3.8±0.6 to 12.2±2.1mlmin -1 kg -1 ). Blood flow in the CoA increased more than four-fold during digestion (3.0±0.6 to 13.3±1.6mlmin -1 kg -1 ). The rise in blood flows was achieved by a doubling of heart rate (18.5±3.3 to 37.8±3.6mlmin -1 kg -1 ). Maximal flows measured in all arteries and heart rate occurred in the first hour of the postprandial period and continued for the next 7h. Copyright © 2017 Elsevier Inc. All rights reserved.

Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance

Directory of Open Access Journals (Sweden)

Benabbas Yassine

2011-01-01

Full Text Available Efficient analysis of human behavior in video surveillance scenes is a very challenging problem. Most traditional approaches fail when applied in real conditions and contexts like amounts of persons, appearance ambiguity, and occlusion. In this work, we propose to deal with this problem by modeling the global motion information obtained from optical flow vectors. The obtained direction and magnitude models learn the dominant motion orientations and magnitudes at each spatial location of the scene and are used to detect the major motion patterns. The applied region-based segmentation algorithm groups local blocks that share the same motion direction and speed and allows a subregion of the scene to appear in different patterns. The second part of the approach consists in the detection of events related to groups of people which are merge, split, walk, run, local dispersion, and evacuation by analyzing the instantaneous optical flow vectors and comparing the learned models. The approach is validated and experimented on standard datasets of the computer vision community. The qualitative and quantitative results are discussed.

Geographical patterns of adaptation within a species' range : Interactions between drift and gene flow

NARCIS (Netherlands)

Alleaume-Benharira, M; Pen, IR; Ronce, O

We use individual-based stochastic simulations and analytical deterministic predictions to investigate the interaction between drift, natural selection and gene flow on the patterns of local adaptation across a fragmented species' range under clinally varying selection. Migration between populations

Area PEc Neurons Use a Multiphasic Pattern of Activity to Signal the Spatial Properties of Optic Flow

Directory of Open Access Journals (Sweden)

Milena Raffi

2017-01-01

Full Text Available The cortical representation of visual perception requires the integration of several-signal processing distributed across many cortical areas, but the neural substrates of such perception are largely unknown. The type of firing pattern exhibited by single neurons is an important indicator of dynamic circuitry within or across cortical areas. Neurons in area PEc are involved in the spatial mapping of the visual field; thus, we sought to analyze the firing pattern of activity of PEc optic flow neurons to shed some light on the cortical processing of visual signals. We quantified the firing activity of 152 optic flow neurons using a spline interpolation function, which allowed determining onset, end, and latency of each neuronal response. We found that many PEc neurons showed multiphasic activity, which is strictly related to the position of the eye and to the position of the focus of expansion (FOE of the flow field. PEc neurons showed a multiphasic activity comprised of excitatory phases interspersed with inhibitory pauses. This phasic pattern seems to be a very efficient way to signal the spatial location of visual stimuli, given that the same neuron sends different firing patterns according to a specific combination of FOE/eye position.

Quantification of complex blood flow using real-time in vivo vector flow ultrasound

DEFF Research Database (Denmark)

Pedersen, Mads Møller; Pihl, Michael Johannes; Haugaard, Per

2010-01-01

A quantitative method for distinguishing complex from non-complex flow patterns in ultrasound is presented. A new commercial BK Medical ultrasound scanner uses the Transverse Oscillation vector flow technique for visualising flow patterns in real-time. In vivo vector flow data of the blood flow...... patterns of the common carotid artery and the carotid bulb were obtained simultaneously as the basis for quantifying complex flow. The carotid bifurcation of two healthy volunteers were scanned. The presence of complex flow patterns from eight cardiac cycles were evaluated by three experts in medical...... for automatic detection of complex flow patterns....

Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

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Jing Qu

2017-08-01

Full Text Available Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO and fusiform gyrus (FG before training was negatively associated with reaction time (RT in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory.

Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

Science.gov (United States)

Qu, Jing; Qian, Liu; Chen, Chuansheng; Xue, Gui; Li, Huiling; Xie, Peng; Mei, Leilei

2017-01-01

Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO) and fusiform gyrus (FG) before training was negatively associated with reaction time (RT) in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory. PMID:28878640

Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods

Science.gov (United States)

Cubuk, E. D.; Schoenholz, S. S.; Rieser, J. M.; Malone, B. D.; Rottler, J.; Durian, D. J.; Kaxiras, E.; Liu, A. J.

2015-03-01

We use machine-learning methods on local structure to identify flow defects—or particles susceptible to rearrangement—in jammed and glassy systems. We apply this method successfully to two very different systems: a two-dimensional experimental realization of a granular pillar under compression and a Lennard-Jones glass in both two and three dimensions above and below its glass transition temperature. We also identify characteristics of flow defects that differentiate them from the rest of the sample. Our results show it is possible to discern subtle structural features responsible for heterogeneous dynamics observed across a broad range of disordered materials.

Precipitation patterns during channel flow

Science.gov (United States)

Jamtveit, B.; Hawkins, C.; Benning, L. G.; Meier, D.; Hammer, O.; Angheluta, L.

2013-12-01

Mineral precipitation during channelized fluid flow is widespread in a wide variety of geological systems. It is also a common and costly phenomenon in many industrial processes that involve fluid flow in pipelines. It is often referred to as scale formation and encountered in a large number of industries, including paper production, chemical manufacturing, cement operations, food processing, as well as non-renewable (i.e. oil and gas) and renewable (i.e. geothermal) energy production. We have studied the incipient stages of growth of amorphous silica on steel plates emplaced into the central areas of the ca. 1 meter in diameter sized pipelines used at the hydrothermal power plant at Hellisheidi, Iceland (with a capacity of ca 300 MW electricity and 100 MW hot water). Silica precipitation takes place over a period of ca. 2 months at approximately 120°C and a flow rate around 1 m/s. The growth produces asymmetric ca. 1mm high dendritic structures ';leaning' towards the incoming fluid flow. A novel phase-field model combined with the lattice Boltzmann method is introduced to study how the growth morphologies vary under different hydrodynamic conditions, including non-laminar systems with turbulent mixing. The model accurately predicts the observed morphologies and is directly relevant for understanding the more general problem of precipitation influenced by turbulent mixing during flow in channels with rough walls and even for porous flow. Reference: Hawkins, C., Angheluta, L., Hammer, Ø., and Jamtveit, B., Precipitation dendrites in channel flow. Europhysics Letters, 102, 54001

Student Media Usage Patterns and Non-Traditional Learning in Higher Education

Science.gov (United States)

Zawacki-Richter, Olaf; Müskens, Wolfgang; Krause, Ulrike; Alturki, Uthman; Aldraiweesh, Ahmed

2015-01-01

A total of 2,338 students at German universities participated in a survey, which investigated media usage patterns of so-called traditional and non-traditional students (Schuetze & Wolter, 2003). The students provided information on the digital devices that they own or have access to, and on their usage of media and e-learning tools and…

Ultrasound imaging of flow patterns in liver metastases from colorectal cancer

DEFF Research Database (Denmark)

Rafaelsen, Søren Rafael; Solvig, Jan

2004-01-01

BACKGROUND: The ability of colour Doppler, power Doppler and echo-enhanced Doppler imaging to detect the blood flow in liver metastases from colorectal cancer was investigated. An evaluation was then made to determine whether the flow pattern could be used as an indication of disease elsewhere....... METHODS: Forty-two patients with hepatic metastases from colorectal cancer were examined, 8 of whom had local recurrence of their colorectal cancer. Seventy-seven liver metastases were evaluated with colour Doppler and power Doppler, and the presence or absence of a Doppler signal in the halo or centre...... was noted. Forty-three of these metastases were further examined after contrast media echo-enhancement. RESULTS: Signals from the peripheral halo were detected by colour Doppler imaging in 34% of the metastases, and in 77% by power Doppler (P power Doppler...

Dual-modality impairment of implicit learning of letter-strings versus color-patterns in patients with schizophrenia.

Science.gov (United States)

Chiu, Ming-Jang; Liu, Kristina; Hsieh, Ming H; Hwu, Hai-Gwo

2005-12-12

Implicit learning was reported to be intact in schizophrenia using artificial grammar learning. However, emerging evidence indicates that artificial grammar learning is not a unitary process. The authors used dual coding stimuli and schizophrenia clinical symptom dimensions to re-evaluate the effect of schizophrenia on various components of artificial grammar learning. Letter string and color pattern artificial grammar learning performances were compared between 63 schizophrenic patients and 27 comparison subjects. Four symptom dimensions derived from a Chinese Positive and Negative Symptom Scale ratings were correlated with patients' artificial grammar implicit learning performances along the two stimulus dimensions. Patients' explicit memory performances were assessed by verbal paired associates and visual reproduction subtests of the Wechsler Memory Scales Revised Version to provide a contrast to their implicit memory function. Schizophrenia severely hindered color pattern artificial grammar learning while the disease affected lexical string artificial grammar learning to a lesser degree after correcting the influences from age, education and the performance of explicit memory function of both verbal and visual modalities. Both learning performances correlated significantly with the severity of patients' schizophrenic clinical symptom dimensions that reflect poor abstract thinking, disorganized thinking, and stereotyped thinking. The results of this study suggested that schizophrenia affects various mechanisms of artificial grammar learning differently. Implicit learning, knowledge acquisition in the absence of conscious awareness, is not entirely intact in patients with schizophrenia. Schizophrenia affects implicit learning through an impairment of the ability of making abstractions from rules and at least in part decreasing the capacity for perceptual learning.

Dual-modality impairment of implicit learning of letter-strings versus color-patterns in patients with schizophrenia

Directory of Open Access Journals (Sweden)

Hwu Hai-Gwo

2005-12-01

Full Text Available Abstract Background Implicit learning was reported to be intact in schizophrenia using artificial grammar learning. However, emerging evidence indicates that artificial grammar learning is not a unitary process. The authors used dual coding stimuli and schizophrenia clinical symptom dimensions to re-evaluate the effect of schizophrenia on various components of artificial grammar learning. Methods Letter string and color pattern artificial grammar learning performances were compared between 63 schizophrenic patients and 27 comparison subjects. Four symptom dimensions derived from a Chinese Positive and Negative Symptom Scale ratings were correlated with patients' artificial grammar implicit learning performances along the two stimulus dimensions. Patients' explicit memory performances were assessed by verbal paired associates and visual reproduction subtests of the Wechsler Memory Scales Revised Version to provide a contrast to their implicit memory function. Results Schizophrenia severely hindered color pattern artificial grammar learning while the disease affected lexical string artificial grammar learning to a lesser degree after correcting the influences from age, education and the performance of explicit memory function of both verbal and visual modalities. Both learning performances correlated significantly with the severity of patients' schizophrenic clinical symptom dimensions that reflect poor abstract thinking, disorganized thinking, and stereotyped thinking. Conclusion The results of this study suggested that schizophrenia affects various mechanisms of artificial grammar learning differently. Implicit learning, knowledge acquisition in the absence of conscious awareness, is not entirely intact in patients with schizophrenia. Schizophrenia affects implicit learning through an impairment of the ability of making abstractions from rules and at least in part decreasing the capacity for perceptual learning.

Flow patterns and heat transfer coefficients in flow-boiling and convective condensation of R22 inside a micro fin of new design

International Nuclear Information System (INIS)

Muzzio, A.; Niro, A.; Garaviglia, M.

1998-01-01

Saturated flow boiling and convective condensation experiments for oil-free refrigerant R22 been carried out with a micro fin tube of new design and with a smooth tube. Both tube have the same outer diameter of 9.52 mm and are horizontally operated. Two-phase flow pattern data have been obtained in addition of heat transfer coefficient and pressure drops; more-over, adiabatic tests have been also performed in order for flow pattern map to cover even adiabatic flows. Data are for mass fluxes ranging from about 90 to 400 Kg/s m 2 . In boiling tests, the nominal saturation temperature is 5 degree C, with inlet quality varying from 0.2 to 0.6 and the quality change ranging from 0.1 to 0.5. In condensation, results are for saturation temperature equal to 35 degree C, with inlet quality between 0.8 and 0.4, and quality change within 0.6 and 0.2. The comparison shows a large heat transfer augmentation with a moderate increment of pressure drops, especially in evaporation were the enhancement factor comes up to 4 while the penalty factor is about 1.4 at the most. Heat transfer coefficients both in evaporation and condensation are compared to the predictions of some recent correlations specifically proposed or modified for micro fin tube

Pengalaman Flow dalam Belajar

Directory of Open Access Journals (Sweden)

Lucky Purwantini

2017-08-01

Full Text Available Flow is a condition when individual merges within his/her activity. When a person in flow state, he/she can develop his/her abilities and more success in learning. The purpose of the study is to understand flow experience in learning among undergraduate student. The study used case study qualitative approach. Informant of this research was an undergraduate student which had flow experience. Data was collected by an interview. According to the result, the subject did not experience flow in the learning process, as likes he was in meditation. It happened because when he learned something, he felt be pressed by tasks. It’s important for individual to relax when they are learning.

Code requirements document: MODFLOW 2.1: A program for predicting moderator flow patterns

International Nuclear Information System (INIS)

Peterson, P.F.

1992-03-01

Sudden changes in the temperature of flowing liquids can result in transient buoyancy forces which strongly impact the flow hydrodynamics via flow stratification. These effects have been studied for the case of potential flow of stratified liquids to line sinks, but not for moderator flow in SRS reactors. Standard codes, such as TRAC and COMMIX, do not have the capability to capture the stratification effect, due to strong numerical diffusion which smears away the hot/cold fluid interface. A related problem with standard codes is the inability to track plumes injected into the liquid flow, again due to numerical diffusion. The combined effects of buoyant stratification and plume dispersion have been identified as being important in operation of the Supplementary Safety System which injects neutron-poison ink into SRS reactors to provide safe shutdown in the event of safety rod failure. The MODFLOW code discussed here provides transient moderator flow pattern information with stratification effects, and tracks the location of ink plumes in the reactor. The code, written in Fortran, is compiled for Macintosh II computers, and includes subroutines for interactive control and graphical output. Removing the graphics capabilities, the code can also be compiled on other computers. With graphics, in addition to the capability to perform safety related computations, MODFLOW also provides an easy tool for becoming familiar with flow distributions in SRS reactors

The internal flow pattern analysis of a tidal power turbine operating on bidirectional generation-pumping

International Nuclear Information System (INIS)

Luo, Y Y; Xiao, Y X; Wang, Z W

2013-01-01

Using tidal energy can reduce environment pollution, save conventional energy and improve energy structure, hence it presents great advantage and is developing potential. Influenced by flood tide and low tide, a fully functional tidal power station needs to experience six operating modes, including bidirectional generation, pumping and sluice; the internal unsteady flow pattern and dynamic characters are very complicated. Based on a bidirectional tidal generator unit, three-dimensional unsteady flows in the flow path were calculated for four typical operating conditions with the pressure pulsation characteristics analyzed. According to the numerical results, the internal flow characteristics in the flow path were discussed. The influence of gravity to the hydraulic performance and flow characteristics were analysed. The results provide a theoretical analysis method of the hydraulic optimization design of the same type unit as well as a direction for stable operation and optimal scheduling of existing tidal power unit

Multiphase flow parameter estimation based on laser scattering

Science.gov (United States)

Vendruscolo, Tiago P.; Fischer, Robert; Martelli, Cicero; Rodrigues, Rômulo L. P.; Morales, Rigoberto E. M.; da Silva, Marco J.

2015-07-01

The flow of multiple constituents inside a pipe or vessel, known as multiphase flow, is commonly found in many industry branches. The measurement of the individual flow rates in such flow is still a challenge, which usually requires a combination of several sensor types. However, in many applications, especially in industrial process control, it is not necessary to know the absolute flow rate of the respective phases, but rather to continuously monitor flow conditions in order to quickly detect deviations from the desired parameters. Here we show how a simple and low-cost sensor design can achieve this, by using machine-learning techniques to distinguishing the characteristic patterns of oblique laser light scattered at the phase interfaces. The sensor is capable of estimating individual phase fluxes (as well as their changes) in multiphase flows and may be applied to safety applications due to its quick response time.

Multiphase flow parameter estimation based on laser scattering

International Nuclear Information System (INIS)

Vendruscolo, Tiago P; Fischer, Robert; Martelli, Cicero; Da Silva, Marco J; Rodrigues, Rômulo L P; Morales, Rigoberto E M

2015-01-01

The flow of multiple constituents inside a pipe or vessel, known as multiphase flow, is commonly found in many industry branches. The measurement of the individual flow rates in such flow is still a challenge, which usually requires a combination of several sensor types. However, in many applications, especially in industrial process control, it is not necessary to know the absolute flow rate of the respective phases, but rather to continuously monitor flow conditions in order to quickly detect deviations from the desired parameters. Here we show how a simple and low-cost sensor design can achieve this, by using machine-learning techniques to distinguishing the characteristic patterns of oblique laser light scattered at the phase interfaces. The sensor is capable of estimating individual phase fluxes (as well as their changes) in multiphase flows and may be applied to safety applications due to its quick response time. (paper)

Detection of tuberculosis patterns in digital photographs of chest X-ray images using Deep Learning: feasibility study.

Science.gov (United States)

Becker, A S; Blüthgen, C; Phi van, V D; Sekaggya-Wiltshire, C; Castelnuovo, B; Kambugu, A; Fehr, J; Frauenfelder, T

2018-03-01

To evaluate the feasibility of Deep Learning-based detection and classification of pathological patterns in a set of digital photographs of chest X-ray (CXR) images of tuberculosis (TB) patients. In this prospective, observational study, patients with previously diagnosed TB were enrolled. Photographs of their CXRs were taken using a consumer-grade digital still camera. The images were stratified by pathological patterns into classes: cavity, consolidation, effusion, interstitial changes, miliary pattern or normal examination. Image analysis was performed with commercially available Deep Learning software in two steps. Pathological areas were first localised; detected areas were then classified. Detection was assessed using receiver operating characteristics (ROC) analysis, and classification using a confusion matrix. The study cohort was 138 patients with human immunodeficiency virus (HIV) and TB co-infection (median age 34 years, IQR 28-40); 54 patients were female. Localisation of pathological areas was excellent (area under the ROC curve 0.82). The software could perfectly distinguish pleural effusions from intraparenchymal changes. The most frequent misclassifications were consolidations as cavitations, and miliary patterns as interstitial patterns (and vice versa). Deep Learning analysis of CXR photographs is a promising tool. Further efforts are needed to build larger, high-quality data sets to achieve better diagnostic performance.

New Techniques for Deep Learning with Geospatial Data using TensorFlow, Earth Engine, and Google Cloud Platform

Science.gov (United States)

Hancher, M.

2017-12-01

Recent years have seen promising results from many research teams applying deep learning techniques to geospatial data processing. In that same timeframe, TensorFlow has emerged as the most popular framework for deep learning in general, and Google has assembled petabytes of Earth observation data from a wide variety of sources and made them available in analysis-ready form in the cloud through Google Earth Engine. Nevertheless, developing and applying deep learning to geospatial data at scale has been somewhat cumbersome to date. We present a new set of tools and techniques that simplify this process. Our approach combines the strengths of several underlying tools: TensorFlow for its expressive deep learning framework; Earth Engine for data management, preprocessing, postprocessing, and visualization; and other tools in Google Cloud Platform to train TensorFlow models at scale, perform additional custom parallel data processing, and drive the entire process from a single familiar Python development environment. These tools can be used to easily apply standard deep neural networks, convolutional neural networks, and other custom model architectures to a variety of geospatial data structures. We discuss our experiences applying these and related tools to a range of machine learning problems, including classic problems like cloud detection, building detection, land cover classification, as well as more novel problems like illegal fishing detection. Our improved tools will make it easier for geospatial data scientists to apply modern deep learning techniques to their own problems, and will also make it easier for machine learning researchers to advance the state of the art of those techniques.

Investigation of Flow Behavior around Corotating Blades in a Double-Spindle Lawn Mower Deck

Directory of Open Access Journals (Sweden)

Chon W.

2005-01-01

Full Text Available When the airflow patterns inside a lawn mower deck are understood, the deck can be redesigned to be efficient and have an increased cutting ability. To learn more, a combination of computational and experimental studies was performed to investigate the effects of blade and housing designs on a flow pattern inside a 1.1m wide corotating double-spindle lawn mower deck with side discharge. For the experimental portion of the study, air velocities inside the deck were measured using a laser Doppler velocimetry (LDV system. A high-speed video camera was used to observe the flow pattern. Furthermore, noise levels were measured using a sound level meter. For the computational fluid dynamics (CFD work, several arbitrary radial sections of a two-dimensional blade were selected to study flow computations. A three-dimensional, full deck model was also developed for realistic flow analysis. The computational results were then compared with the experimental results.

Interdependencies of aortic arch secondary flow patterns, geometry, and age analysed by 4-dimensional phase contrast magnetic resonance imaging at 3 Tesla

Energy Technology Data Exchange (ETDEWEB)

Frydrychowicz, Alex [University Hospital Schleswig-Holstein, Clinic for Radiology and Nuclear Medicine, Luebeck (Germany); Berger, Alexander; Russe, Maximilian F.; Bock, Jelena [University Hospital Freiburg, Department of Radiology, Medical Physics, Freiburg (Germany); Munoz del Rio, Alejandro [University of Wisconsin - Madison, Departments of Radiology and Medical Physics, Madison, WI (United States); Harloff, Andreas [University Hospital Freiburg, Department of Neurology and Clinical Neurophysiology, Freiburg (Germany); Markl, Michael [University Hospital Freiburg, Department of Radiology, Medical Physics, Freiburg (Germany); Northwestern University, Departments of Radiology and Biomedical Engineering, Chicago, IL (United States)

2012-05-15

It was the aim to analyse the impact of age, aortic arch geometry, and size on secondary flow patterns such as helix and vortex flow derived from flow-sensitive magnetic resonance imaging (4D PC-MRI). 62 subjects (age range = 20-80 years) without circumscribed pathologies of the thoracic aorta (ascending aortic (AAo) diameter: 3.2 {+-} 0.6 cm [range 2.2-5.1]) were examined by 4D PC-MRI after IRB-approval and written informed consent. Blood flow visualisation based on streamlines and time-resolved 3D particle traces was performed. Aortic diameter, shape (gothic, crook-shaped, cubic), angle, and age were correlated with existence and extent of secondary flow patterns (helicity, vortices); statistical modelling was performed. Helical flow was the typical pattern in standard crook-shaped aortic arches. With altered shapes and increasing age, helicity was less common. AAo diameter and age had the highest correlation (r = 0.69 and 0.68, respectively) with number of detected vortices. None of the other arch geometric or demographic variables (for all, P {>=} 0.177) improved statistical modelling. Substantially different secondary flow patterns can be observed in the normal thoracic aorta. Age and the AAo diameter were the parameters correlating best with presence and amount of vortices. Findings underline the importance of age- and geometry-matched control groups for haemodynamic studies. (orig.)

Interdependencies of aortic arch secondary flow patterns, geometry, and age analysed by 4-dimensional phase contrast magnetic resonance imaging at 3 Tesla

International Nuclear Information System (INIS)

Frydrychowicz, Alex; Berger, Alexander; Russe, Maximilian F.; Bock, Jelena; Munoz del Rio, Alejandro; Harloff, Andreas; Markl, Michael

2012-01-01

It was the aim to analyse the impact of age, aortic arch geometry, and size on secondary flow patterns such as helix and vortex flow derived from flow-sensitive magnetic resonance imaging (4D PC-MRI). 62 subjects (age range = 20-80 years) without circumscribed pathologies of the thoracic aorta (ascending aortic (AAo) diameter: 3.2 ± 0.6 cm [range 2.2-5.1]) were examined by 4D PC-MRI after IRB-approval and written informed consent. Blood flow visualisation based on streamlines and time-resolved 3D particle traces was performed. Aortic diameter, shape (gothic, crook-shaped, cubic), angle, and age were correlated with existence and extent of secondary flow patterns (helicity, vortices); statistical modelling was performed. Helical flow was the typical pattern in standard crook-shaped aortic arches. With altered shapes and increasing age, helicity was less common. AAo diameter and age had the highest correlation (r = 0.69 and 0.68, respectively) with number of detected vortices. None of the other arch geometric or demographic variables (for all, P ≥ 0.177) improved statistical modelling. Substantially different secondary flow patterns can be observed in the normal thoracic aorta. Age and the AAo diameter were the parameters correlating best with presence and amount of vortices. Findings underline the importance of age- and geometry-matched control groups for haemodynamic studies. (orig.)

Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

Directory of Open Access Journals (Sweden)

Marc Wieland

2014-03-01

Full Text Available In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS and very high resolution (WorldView-2, Quickbird, Ikonos multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognition tasks. Four classification algorithms, Normal Bayes, K Nearest Neighbors, Random Trees and Support Vector Machines, which represent different concepts in machine learning (probabilistic, nearest neighbor, tree-based, function-based, have been selected and implemented on a free and open-source basis. Particular focus is given to assess the generalization ability of machine learning algorithms and the transferability of trained learning machines between different image types and image scenes. Moreover, the influence of the number and choice of training data, the influence of the size and composition of the feature vector and the effect of image segmentation on the classification accuracy is evaluated.

Affinity flow fractionation of cells via transient interactions with asymmetric molecular patterns

Science.gov (United States)

Bose, Suman; Singh, Rishi; Hanewich-Hollatz, Mikhail; Shen, Chong; Lee, Chia-Hua; Dorfman, David M.; Karp, Jeffrey M.; Karnik, Rohit

2013-07-01

Flow fractionation of cells using physical fields to achieve lateral displacement finds wide applications, but its extension to surface molecule-specific separation requires labeling. Here we demonstrate affinity flow fractionation (AFF) where weak, short-range interactions with asymmetric molecular patterns laterally displace cells in a continuous, label-free process. We show that AFF can directly draw neutrophils out of a continuously flowing stream of blood with an unprecedented 400,000-fold depletion of red blood cells, with the sorted cells being highly viable, unactivated, and functionally intact. The lack of background erythrocytes enabled the use of AFF for direct enumeration of neutrophils by a downstream detector, which could distinguish the activation state of neutrophils in blood. The compatibility of AFF with capillary microfluidics and its ability to directly separate cells with high purity and minimal sample preparation will facilitate the design of simple and portable devices for point-of-care diagnostics and quick, cost-effective laboratory analysis.

Can visual assessment of blood flow patterns by dynamic contrast-enhanced computed tomography distinguish between malignant and benign lung tumors?

Science.gov (United States)

Harders, Stefan Walbom; Madsen, Hans Henrik; Nellemann, Hanne Marie; Rasmussen, Torben Riis; Thygesen, Jesper; Hager, Henrik; Andersen, Niels Trolle; Rasmussen, Finn

2017-05-01

Dynamic contrast-enhanced computed tomography (DCE-CT) is a tool, which, in theory, can quantify the blood flow and blood volume of tissues. In structured qualitative analysis, parametric color maps yield a visual impression of the blood flow and blood volume within the tissue being studied, allowing for quick identification of the areas with the highest or lowest blood flow and blood volume. To examine whether DCE-CT could be used to distinguish between malignant and benign lung tumors in patients with suspected lung cancer. Fifty-nine patients with suspected lung cancer and a lung tumor on their chest radiograph were included for DCE-CT. The tumors were categorized using structured qualitative analysis of tumor blood flow patterns. Histopathology was used as reference standard. Using structured qualitative analysis of tumor blood flow patterns, it was possible to distinguish between malignant and benign lung tumors (Fisher-Freeman-Halton exact test, P  = 0.022). The inter-reader agreement of this method of analysis was slight to moderate (kappa = 0.30; 95% confidence interval [CI] = 0.13-0.46). DCE-CT in suspected lung cancer using structured qualitative analysis of tumor blood flow patterns is accurate as well as somewhat reproducible. However, there are significant limitations to DCE-CT.

Authoring and Enactment of Mobile Pyramid-Based Collaborative Learning Activities

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Manathunga, Kalpani; Hernández-Leo, Davinia

2018-01-01

Collaborative learning flow patterns (CLFPs) formulate best practices for the orchestration of activity sequences and collaboration mechanisms that can elicit fruitful social interactions. Mobile technology features offer opportunities to support interaction mediation and content accessibility. However, existing mobile collaborative learning…

Control Theoretic Modeling and Generated Flow Patterns of a Fish-Tail Robot

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Massey, Brian; Morgansen, Kristi; Dabiri, Dana

2003-11-01

Many real-world engineering problems involve understanding and manipulating fluid flows. One of the challenges to further progress in the area of active flow control is the lack of appropriate models that are amenable to control-theoretic studies and algorithm design and also incorporate reasonably realistic fluid dynamic effects. We focus here on modeling and model-verification of bio-inspired actuators (fish-fin type structures) used to control fluid dynamic artifacts that will affect speed, agility, and stealth of Underwater Autonomous Vehicles (UAVs). Vehicles using fish-tail type systems are more maneuverable, can turn in much shorter and more constrained spaces, have lower drag, are quieter and potentially more efficient than those using propellers. We will present control-theoretic models for a simple prototype coupled fluid and mechanical actuator where fluid effects are crudely modeled by assuming only lift, drag, and added mass, while neglecting boundary effects. These models will be tested with different control input parameters on an experimental fish-tail robot with the resulting flow captured with DPIV. Relations between the model, the control function choices, the obtained thrust and drag, and the corresponding flow patterns will be presented and discussed.

Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns

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H Kimura

2009-04-01

Full Text Available In climate research, pressure patterns are often very important. When a climatologists need to know the days of a specific pressure pattern, for example "low pressure in Western areas of Japan and high pressure in Eastern areas of Japan (Japanese winter-type weather," they have to visually check a huge number of surface weather charts. To overcome this problem, we propose an automatic classification system using a support vector machine (SVM, which is a machine-learning method. We attempted to classify pressure patterns into two classes: "winter type" and "non-winter type". For both training datasets and test datasets, we used the JRA-25 dataset from 1981 to 2000. An experimental evaluation showed that our method obtained a greater than 0.8 F-measure. We noted that variations in results were based on differences in training datasets.

A tool to estimate bar patterns and flow conditions in estuaries when limited data is available

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Leuven, J.; Verhoeve, S.; Bruijns, A. J.; Selakovic, S.; van Dijk, W. M.; Kleinhans, M. G.

2017-12-01

The effects of human interventions, natural evolution of estuaries and rising sea-level on food security and flood safety are largely unknown. In addition, ecologists require quantified habitat area to study future evolution of estuaries, but they lack predictive capability of bathymetry and hydrodynamics. For example, crucial input required for ecological models are values of intertidal area, inundation time, peak flow velocities and salinity. While numerical models can reproduce these spatial patterns, their computational times are long and for each case a new model must be developed. Therefore, we developed a comprehensive set of relations that accurately predict the hydrodynamics and the patterns of channels and bars, using a combination of the empirical relations derived from approximately 50 estuaries and theory for bars and estuaries. The first step is to predict local tidal prisms, which is the tidal prism that flows through a given cross-section. Second, the channel geometry is predicted from tidal prism and hydraulic geometry relations. Subsequently, typical flow velocities can be estimated from the channel geometry and tidal prism. Then, an ideal estuary shape is fitted to the measured planform: the deviation from the ideal shape, which is defined as the excess width, gives a measure of the locations where tidal bars form and their summed width (Leuven et al., 2017). From excess width, typical hypsometries can be predicted per cross-section. In the last step, flow velocities are calculated for the full range of occurring depths and salinity is calculated based on the estuary shape. Here, we will present a prototype tool that predicts equilibrium bar patterns and typical flow conditions. The tool is easy to use because the only input required is the estuary outline and tidal amplitude. Therefore it can be used by policy makers and researchers from multiple disciplines, such as ecologists, geologists and hydrologists, for example for paleogeographic

Thermal structure and flow patterns around Seychelles group of Islands (Indian Ocean) during austral autumn

Digital Repository Service at National Institute of Oceanography (India)

Vethamony, P.; RameshBabu, V.; RameshKumar, M.R.

Properties of thermal structure in the upper 750 m around the Seychelles group of islands in the Indian Ocean, based on Expendable Bathythermograph (XBT) data collected in March 1984, are presented along with the inferred flow patterns...

Cognitive Patterns of Learning Disability Subtypes as Measured by the Woodcock-Johnson Psycho-Educational Battery.

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Breen, Michael J.

1986-01-01

The cognitive patterns of three learning disability subtypes were studied: (1) students with higher math than reading skills, (2) students with higher reading than math skills, and (3) students with equally low math and reading skills. Results indicated that although the three groups were characterized by a number of discrete or unique patterns,…

Reverse inference of memory retrieval processes underlying metacognitive monitoring of learning using multivariate pattern analysis.

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Stiers, Peter; Falbo, Luciana; Goulas, Alexandros; van Gog, Tamara; de Bruin, Anique

2016-05-15

Monitoring of learning is only accurate at some time after learning. It is thought that immediate monitoring is based on working memory, whereas later monitoring requires re-activation of stored items, yielding accurate judgements. Such interpretations are difficult to test because they require reverse inference, which presupposes specificity of brain activity for the hidden cognitive processes. We investigated whether multivariate pattern classification can provide this specificity. We used a word recall task to create single trial examples of immediate and long term retrieval and trained a learning algorithm to discriminate them. Next, participants performed a similar task involving monitoring instead of recall. The recall-trained classifier recognized the retrieval patterns underlying immediate and long term monitoring and classified delayed monitoring examples as long-term retrieval. This result demonstrates the feasibility of decoding cognitive processes, instead of their content. Copyright © 2016 Elsevier Inc. All rights reserved.

4D cardiovascular magnetic resonance velocity mapping of alterations of right heart flow patterns and main pulmonary artery hemodynamics in tetralogy of Fallot

Science.gov (United States)

2012-01-01

Background To assess changes in right heart flow and pulmonary artery hemodynamics in patients with repaired Tetralogy of Fallot (rTOF) we used whole heart, four dimensional (4D) velocity mapping (VM) cardiovascular magnetic resonance (CMR). Methods CMR studies were performed in 11 subjects with rTOF (5M/6F; 20.1 ± 12.4 years) and 10 normal volunteers (6M/4F; 34.2 ± 13.4 years) on clinical 1.5T and 3.0T MR scanners. 4D VM-CMR was performed using PC VIPR (Phase Contrast Vastly undersampled Isotropic Projection Reconstruction). Interactive streamline and particle trace visualizations of the superior and inferior vena cava (IVC and SVC, respectively), right atrium (RA), right ventricle (RV), and pulmonary artery (PA) were generated and reviewed by three experienced readers. Main PA net flow, retrograde flow, peak flow, time-to-peak flow, peak acceleration, resistance index and mean wall shear stress were quantified. Differences in flow patterns between the two groups were tested using Fisher's exact test. Differences in quantitative parameters were analyzed with the Kruskal-Wallis rank sum test. Results 4D VM-CMR was successfully performed in all volunteers and subjects with TOF. Right heart flow patterns in rTOF subjects were characterized by (a) greater SVC/IVC flow during diastole than systole, (b) increased vortical flow patterns in the RA and in the RV during diastole, and (c) increased helical or vortical flow features in the PA's. Differences in main PA retrograde flow, resistance index, peak flow, time-to-peak flow, peak acceleration and mean wall shear stress were statistically significant. Conclusions Whole heart 4D VM-CMR with PC VIPR enables detection of both normal and abnormal right heart flow patterns, which may allow for comprehensive studies to evaluate interdependencies of post-surgically altered geometries and hemodynamics. PMID:22313680

Computational modeling of lava domes using particle dynamics to investigate the effect of conduit flow mechanics on flow patterns

Science.gov (United States)

Husain, Taha Murtuza

Large (1--4 x 106 m3) to major (> 4 x 106 m3) dome collapses for andesitic lava domes such as Soufriere Hills Volcano, Montserrat are observed for elevated magma discharge rates (6--13 m3/s). The gas rich magma pulses lead to pressure build up in the lava dome that result in structural failure of the over steepened canyon-like walls which may lead to rockfall or pyroclastic flow. This indicates that dome collapse intimately related to magma extrusion rate. Variation in magma extrusion rate for open-system magma chambers is observed to follow alternating periods of high and low activity. Periodic behavior of magma exhibits a rich diversity in the nature of its eruptive history due to variation in magma chamber size, total crystal content, linear crystal growth rate and magma replenishment rate. Distinguished patterns of growth were observed at different magma flow rates ranging from endogenous to exogenous dome growth for magma with varying strengths. Determining the key parameters that control the transition in flow pattern of the magma during its lava dome building eruption is the main focus. This dissertation examines the mechanical effects on the morphology of the evolving lava dome on the extrusion of magma from a central vent using a 2D particle dynamics model. The particle dynamics model is coupled with a conduit flow model that incorporates the kinetics of crystallization and rheological stiffening to investigate important mechanisms during lava dome building eruptions. Chapter I of this dissertation explores lava dome growth and failure mechanics using a two-dimensional particle-dynamics model. The model follows the evolution of fractured lava, with solidification driven by degassing induced crystallization of magma. The particle-dynamics model emulates the natural development of dome growth and rearrangement of the lava dome which is difficult in mesh-based analyses due to mesh entanglement effects. The deformable talus evolves naturally as a frictional

Boiling on a tube bundle: heat transfer, pressure drop and flow patterns

International Nuclear Information System (INIS)

Agostini, F.

2008-07-01

The complexity of the two-phase flow in a tube bundle presents important problems in the design and understanding of the physical phenomena taking place. The working conditions of an evaporator depend largely on the dynamics of the two-phase flow that in turn influence the heat exchange and the pressure drop of the system. A characterization of the flow dynamics, and possibly the identification of the flow pattern in the tube bundle, is thus expected to lead to a better understanding of the phenomena and to reveal on the mechanisms governing the tube bundle. Therefore, the present study aims at providing further insights into two-phase bundle flow through a new visualization system able to provide for the first time a view of the flow in the core of a tube bundle. In addition, the measurement of the light attenuation of a laser beam through the two-phase flow and measurement of the high frequency pressure fluctuations with a piezo-electric pressure transducer are used to characterize the flow. The design and the validation of this new instrumentation also provided a method for the detection of dry-out in tube bundles. This was achieved by a laser attenuation technique, flow visualization, and estimation of the power spectrum of the pressure fluctuation. The current investigation includes results for two different refrigerants, R134a and R236fa, three saturations temperatures T sat = 5, 10 and 15 °C, mass velocities ranging from 4 to 40 kg/sm² in adiabatic and diabatic conditions (several heat fluxes). Measurement of the local heat transfer coefficient and two-phase frictional pressure drop were obtained and utilized to improve the current prediction methods. The heat transfer and pressure drop data were supported by extensive characterization of the two-phase flow, which was to improve the understanding of the two-phase flow occurring in tube bundles. (author)

Fluid Flow Patterns During Production from Gas Hydrates in the Laboratory compared to Field Settings: LARS vs. Mallik

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Strauch, B.; Heeschen, K. U.; Priegnitz, M.; Abendroth, S.; Spangenberg, E.; Thaler, J.; Schicks, J. M.

2015-12-01

The GFZ's LArge Reservoir Simulator LARS allows for the simulation of the 2008 Mallik gas hydrate production test and the comparison of fluid flow patterns and their driving forces. Do we see the gas flow pattern described for Mallik [Uddin, M. et al., J. Can. Petrol Tech, 50, 70-89, 2011] in a pilot scale test? If so, what are the driving forces? LARS has a network of temperature sensors and an electric resistivity tomography (ERT) enabling a good spatial resolution of gas hydrate occurrences, water and gas distribution, and changes in temperature in the sample. A gas flow meter and a water trap record fluid flow patterns and a backpressure valve has controlled the depressurization equivalent to the three pressure stages (7.0 - 5.0 - 4.2 MPa) applied in the Mallik field test. The environmental temperature (284 K) and confining pressure (13 MPa) have been constant. The depressurization induced immediate endothermic gas hydrate dissociation until re-establishment of the stability conditions by a consequent temperature decrease. Slight gas hydrate dissociation continued at the top and upper lateral border due to the constant heat input from the environment. Here transport pathways were short and permeability higher due to lower gas hydrate saturation. At pressures of 7.0 and 5.0 MPa the LARS tests showed high water flow rates and short irregular spikes of gas production. The gas flow patterns at 4.2 MPa and 3.0MPa resembled those of the Mallik test. In LARS the initial gas surges overlap with times of hydrate instability while water content and lengths of pathways had increased. Water production was at a minimum. A rapidly formed continuous gas phase caused the initial gas surges and only after gas hydrate dissociation decreased to a minimum the single gas bubbles get trapped before slowly coalescing again. In LARS, where pathways were short and no additional water was added, a transport of microbubbles is unlikely to cause a gas surge as suggested for Mallik.

Systematic data mining using a pattern database to accelerate yield ramp

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Teoh, Edward; Dai, Vito; Capodieci, Luigi; Lai, Ya-Chieh; Gennari, Frank

2014-03-01

Pattern-based approaches to physical verification, such as DRC Plus, which use a library of patterns to identify problematic 2D configurations, have been proven to be effective in capturing the concept of manufacturability where traditional DRC fails. As the industry moves to advanced technology nodes, the manufacturing process window tightens and the number of patterns continues to rapidly increase. This increase in patterns brings about challenges in identifying, organizing, and carrying forward the learning of each pattern from test chip designs to first product and then to multiple product variants. This learning includes results from printability simulation, defect scans and physical failure analysis, which are important for accelerating yield ramp. Using pattern classification technology and a relational database, GLOBALFOUNDRIES has constructed a pattern database (PDB) of more than one million potential yield detractor patterns. In PDB, 2D geometries are clustered based on similarity criteria, such as radius and edge tolerance. Each cluster is assigned a representative pattern and a unique identifier (ID). This ID is then used as a persistent reference for linking together information such as the failure mechanism of the patterns, the process condition where the pattern is likely to fail and the number of occurrences of the pattern in a design. Patterns and their associated information are used to populate DRC Plus pattern matching libraries for design-for-manufacturing (DFM) insertion into the design flow for auto-fixing and physical verification. Patterns are used in a production-ready yield learning methodology to identify and score critical hotspot patterns. Patterns are also used to select sites for process monitoring in the fab. In this paper, we describe the design of PDB, the methodology for identifying and analyzing patterns across multiple design and technology cycles, and the use of PDB to accelerate manufacturing process learning. One such

Atypical performance patterns on Delis-Kaplan Executive Functioning System Color-Word Interference Test: Cognitive switching and learning ability in older adults.

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Berg, Jody-Lynn; Swan, Natasha M; Banks, Sarah J; Miller, Justin B

2016-09-01

Cognitive set shifting requires flexible application of lower level processes. The Delis-Kaplan Executive Functioning System (DKEFS) Color-Word Interference Test (CWIT) is commonly used to clinically assess cognitive set shifting. An atypical pattern of performance has been observed on the CWIT; a subset of individuals perform faster, with equal or fewer errors, on the more difficult inhibition/switching than the inhibition trial. This study seeks to explore the cognitive underpinnings of this atypical pattern. It is hypothesized that atypical patterns on CWIT will be associated with better performance on underlying cognitive measures of attention, working memory, and learning when compared to typical CWIT patterns. Records from 239 clinical referrals (age: M = 68.09 years, SD = 10.62; education: M = 14.87 years, SD = 2.73) seen for a neuropsychological evaluation as part of diagnostic work up in an outpatient dementia and movement disorders clinic were sampled. The standard battery of tests included measures of attention, learning, fluency, executive functioning, and working memory. Analyses of variance (ANOVAs) were conducted to compare the cognitive performance of those with typical versus atypical CWIT patterns. An atypical pattern of performance was confirmed in 23% of our sample. Analyses revealed a significant group difference in acquisition of information on both nonverbal (Brief Visuospatial Memory Test-Revised, BVMT-R total recall), F(1, 213) = 16.61, p < .001, and verbal (Hopkins Verbal Learning Test-Revised, HVLT-R total recall) learning tasks, F(1, 181) = 6.43, p < .01, and semantic fluency (Animal Naming), F(1, 232) = 7.57, p = .006, with the atypical group performing better on each task. Effect sizes were larger for nonverbal (Cohen's d = 0.66) than verbal learning (Cohen's d = 0.47) and semantic fluency (Cohen's d = 0.43). Individuals demonstrating an atypical pattern of performance on the CWIT inhibition/switching trial also demonstrated relative

Sensitivity of peak flow to the change of rainfall temporal pattern due to warmer climate

Science.gov (United States)

Fadhel, Sherien; Rico-Ramirez, Miguel Angel; Han, Dawei

2018-05-01

The widely used design storms in urban drainage networks has different drawbacks. One of them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. However, previous studies have shown that the temporal pattern may scale with temperature due to climate change, which consequently affects peak flow. Thus, in addition to the scaling of the rainfall volume, the scaling relationship for the rainfall temporal pattern with temperature needs to be investigated by deriving the scaling values for each fraction within storm events, which is lacking in many parts of the world including the UK. Therefore, this study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall temporal pattern becomes less uniform, with more intensive peak rainfall during higher intensive times and weaker rainfall during less intensive times. This is the case for storms with and without seasonal separations. In addition, the scaling values for both the rainfall volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the summer season were found to be higher than the corresponding results for the winter season. Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate. This study on the scaling of rainfall fractions is the first in the UK, and its findings are of importance to modellers and designers of sewer systems because it can provide more robust scenarios for flooding mitigation in urban areas.

In vivo visualization method by absolute blood flow velocity based on speckle and fringe pattern using two-beam multipoint laser Doppler velocimetry

Energy Technology Data Exchange (ETDEWEB)

Kyoden, Tomoaki, E-mail: kyouden@nc-toyama.ac.jp; Naruki, Shoji; Akiguchi, Shunsuke; Momose, Noboru; Homae, Tomotaka; Hachiga, Tadashi [National Institute of Technology, Toyama College, 1-2 Ebie-Neriya, Imizu, Toyama 933-0293 (Japan); Ishida, Hiroki [Department of Applied Physics, Faculty of Science, Okayama University of Science, 1-1 Ridai-cho, Okayama 700-0005 (Japan); Andoh, Tsugunobu [Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, 2630 Sugitani, Toyama 930-0194 (Japan); Takada, Yogo [Graduate School of Engineering, Osaka City University, 3-3-138 Sugimoto, Sumiyoshi, Osaka 558-8585 (Japan)

2016-08-28

Two-beam multipoint laser Doppler velocimetry (two-beam MLDV) is a non-invasive imaging technique able to provide an image of two-dimensional blood flow and has potential for observing cancer as previously demonstrated in a mouse model. In two-beam MLDV, the blood flow velocity can be estimated from red blood cells passing through a fringe pattern generated in the skin. The fringe pattern is created at the intersection of two beams in conventional LDV and two-beam MLDV. Being able to choose the depth position is an advantage of two-beam MLDV, and the position of a blood vessel can be identified in a three-dimensional space using this technique. Initially, we observed the fringe pattern in the skin, and the undeveloped or developed speckle pattern generated in a deeper position of the skin. The validity of the absolute velocity value detected by two-beam MLDV was verified while changing the number of layers of skin around a transparent flow channel. The absolute velocity value independent of direction was detected using the developed speckle pattern, which is created by the skin construct and two beams in the flow channel. Finally, we showed the relationship between the signal intensity and the fringe pattern, undeveloped speckle, or developed speckle pattern based on the skin depth. The Doppler signals were not detected at deeper positions in the skin, which qualitatively indicates the depth limit for two-beam MLDV.

A statistical learning strategy for closed-loop control of fluid flows

Science.gov (United States)

Guéniat, Florimond; Mathelin, Lionel; Hussaini, M. Yousuff

2016-12-01

This work discusses a closed-loop control strategy for complex systems utilizing scarce and streaming data. A discrete embedding space is first built using hash functions applied to the sensor measurements from which a Markov process model is derived, approximating the complex system's dynamics. A control strategy is then learned using reinforcement learning once rewards relevant with respect to the control objective are identified. This method is designed for experimental configurations, requiring no computations nor prior knowledge of the system, and enjoys intrinsic robustness. It is illustrated on two systems: the control of the transitions of a Lorenz'63 dynamical system, and the control of the drag of a cylinder flow. The method is shown to perform well.

Inverse Problems in Geodynamics Using Machine Learning Algorithms

Science.gov (United States)

Shahnas, M. H.; Yuen, D. A.; Pysklywec, R. N.

2018-01-01

During the past few decades numerical studies have been widely employed to explore the style of circulation and mixing in the mantle of Earth and other planets. However, in geodynamical studies there are many properties from mineral physics, geochemistry, and petrology in these numerical models. Machine learning, as a computational statistic-related technique and a subfield of artificial intelligence, has rapidly emerged recently in many fields of sciences and engineering. We focus here on the application of supervised machine learning (SML) algorithms in predictions of mantle flow processes. Specifically, we emphasize on estimating mantle properties by employing machine learning techniques in solving an inverse problem. Using snapshots of numerical convection models as training samples, we enable machine learning models to determine the magnitude of the spin transition-induced density anomalies that can cause flow stagnation at midmantle depths. Employing support vector machine algorithms, we show that SML techniques can successfully predict the magnitude of mantle density anomalies and can also be used in characterizing mantle flow patterns. The technique can be extended to more complex geodynamic problems in mantle dynamics by employing deep learning algorithms for putting constraints on properties such as viscosity, elastic parameters, and the nature of thermal and chemical anomalies.

Heavy oil, water and air three-phase flow patterns in horizontal pipes; Padroes de escoamento trifasico de oleo pesado, agua e ar em tubulacoes horizontais

Energy Technology Data Exchange (ETDEWEB)

Trevisan, Francisco Exaltacao; Bannwart, Antonio Carlos [Universidade Estadual de Campinas (UNICAMP), Campinas, SP (Brazil)

2004-07-01

A significant extent of the Brazilian oil reserves consists of heavy oil, and its importance and economic value have been increasing in the last years. However, these oils, besides their elevated densities (API degree lower than 20), have viscosities higher than 100 mPa.s, which make it more difficult their transportation in pipelines. A solution for this problem is the injection of water in the pipe, which causes a reduction of the friction factor and, consequently, of the energy expend for a given oil flow rate. The two-phase flow of heavy oil and water has been the object of a number of recent studies, and concepts such as the core-flow technology can be useful for heavy oil transportation. But in production operations, gas is also present, initially dissolved in the oil phase then leaving the solution to form a free gas phase if the pressure drops below the bubble point pressure, the study of three-phase flow of heavy oil, water and gas is in order. The present paper presents the experimental work developed to evaluate the effect that this third phase causes on the heavy oil-water two-phase flow pattern. Initially two-phase flow of heavy and gas-water was studied to establish the flow rate ranges that cover the main patterns already known. The superficial velocities used varied from 0,04 to 0,5 m/s for water, 0,01 to 22 m/s for gas and 0,02 to 1,2 m/s for oil. After that, three-phase flow patterns were visually determined through a 2,84 cm i.d. plexiglas tube using a high-speed camera. Nine three-phase flow patterns were identified which are presented visually and described. These flow-patterns are also presented in flow maps where the effect of the gas phase can be observed. Water was the continuous phase for all flow patterns observed, ensuring a low pressure drop along the pipe. (author)

A novel method for flow pattern identification in unstable operational conditions using gamma ray and radial basis function

International Nuclear Information System (INIS)

Roshani, G.H.; Nazemi, E.; Roshani, M.M.

2017-01-01

Changes of fluid properties (especially density) strongly affect the performance of radiation-based multiphase flow meter and could cause error in recognizing the flow pattern and determining void fraction. In this work, we proposed a methodology based on combination of multi-beam gamma ray attenuation and dual modality densitometry techniques using RBF neural network in order to recognize the flow regime and determine the void fraction in gas-liquid two phase flows independent of the liquid phase changes. The proposed system is consisted of one 137 Cs source, two transmission detectors and one scattering detector. The registered counts in two transmission detectors were used as the inputs of one primary Radial Basis Function (RBF) neural network for recognizing the flow regime independent of liquid phase density. Then, after flow regime identification, three RBF neural networks were utilized for determining the void fraction independent of liquid phase density. Registered count in scattering detector and first transmission detector were used as the inputs of these three RBF neural networks. Using this simple methodology, all the flow patterns were correctly recognized and the void fraction was predicted independent of liquid phase density with mean relative error (MRE) of less than 3.28%. - Highlights: • Flow regime and void fraction were determined in two phase flows independent of the liquid phase density changes. • An experimental structure was set up and the required data was obtained. • 3 detectors and one gamma source were used in detection geometry. • RBF networks were utilized for flow regime and void fraction determination.

Frequency and Pattern of Learner-Instructor Interaction in an Online English Language Learning Environment in Vietnam

Science.gov (United States)

Pham, Thach; Thalathoti, Vijay; Dakich, Eva

2014-01-01

This study examines the frequency and pattern of interpersonal interactions between the learners and instructors of an online English language learning course offered at a Vietnamese university. The paper begins with a review of literature on interaction type, pattern and model of interaction followed by a brief description of the online…

A gaming approach to learning medical microbiology: students' experiences of flow.

Science.gov (United States)

Beylefeld, Adriana A; Struwig, Magdalena C

2007-11-01

There is a growing awareness in medical education of general skills(1) required for lifelong learning. Such skills are best achieved when students experience positive affective states while they are learning, as put forth by the Csikszentmihalyian theory of flow. This study describes how a quiz-type board game was used in the School of Medicine of the Faculty of Health Sciences at the University of the Free State to address students' negativity towards medical microbiology. The study population consisted of third-year medical students who had recently completed the Infections module of the undergraduate Learning Programme for Professional Medicine. Data gathered by means of two questionnaire surveys and direct observation showed that the game impacted positively on students' perceptions of and attitudes towards medical microbiology as a subject. A high perceived probability of the game contributing to the acquisition of general skills was recorded, since the experience of positive affect during the process of informal learning went hand-in-hand with heightened team effort and spontaneous communication. This article may be of value to health educators who wish to supplement formal teaching with informal learning so as to enhance not only the recall of factual knowledge, but also the advancement of general skills.

A New Void Fraction Measurement Method for Gas-Liquid Two-Phase Flow in Small Channels

Directory of Open Access Journals (Sweden)

Huajun Li

2016-01-01

Full Text Available Based on a laser diode, a 12 × 6 photodiode array sensor, and machine learning techniques, a new void fraction measurement method for gas-liquid two-phase flow in small channels is proposed. To overcome the influence of flow pattern on the void fraction measurement, the flow pattern of the two-phase flow is firstly identified by Fisher Discriminant Analysis (FDA. Then, according to the identification result, a relevant void fraction measurement model which is developed by Support Vector Machine (SVM is selected to implement the void fraction measurement. A void fraction measurement system for the two-phase flow is developed and experiments are carried out in four different small channels. Four typical flow patterns (including bubble flow, slug flow, stratified flow and annular flow are investigated. The experimental results show that the development of the measurement system is successful. The proposed void fraction measurement method is effective and the void fraction measurement accuracy is satisfactory. Compared with the conventional laser measurement systems using standard laser sources, the developed measurement system has the advantages of low cost and simple structure. Compared with the conventional void fraction measurement methods, the proposed method overcomes the influence of flow pattern on the void fraction measurement. This work also provides a good example of using low-cost laser diode as a competent replacement of the expensive standard laser source and hence implementing the parameter measurement of gas-liquid two-phase flow. The research results can be a useful reference for other researchers’ works.

A New Void Fraction Measurement Method for Gas-Liquid Two-Phase Flow in Small Channels.

Science.gov (United States)

Li, Huajun; Ji, Haifeng; Huang, Zhiyao; Wang, Baoliang; Li, Haiqing; Wu, Guohua

2016-01-27

Based on a laser diode, a 12 × 6 photodiode array sensor, and machine learning techniques, a new void fraction measurement method for gas-liquid two-phase flow in small channels is proposed. To overcome the influence of flow pattern on the void fraction measurement, the flow pattern of the two-phase flow is firstly identified by Fisher Discriminant Analysis (FDA). Then, according to the identification result, a relevant void fraction measurement model which is developed by Support Vector Machine (SVM) is selected to implement the void fraction measurement. A void fraction measurement system for the two-phase flow is developed and experiments are carried out in four different small channels. Four typical flow patterns (including bubble flow, slug flow, stratified flow and annular flow) are investigated. The experimental results show that the development of the measurement system is successful. The proposed void fraction measurement method is effective and the void fraction measurement accuracy is satisfactory. Compared with the conventional laser measurement systems using standard laser sources, the developed measurement system has the advantages of low cost and simple structure. Compared with the conventional void fraction measurement methods, the proposed method overcomes the influence of flow pattern on the void fraction measurement. This work also provides a good example of using low-cost laser diode as a competent replacement of the expensive standard laser source and hence implementing the parameter measurement of gas-liquid two-phase flow. The research results can be a useful reference for other researchers' works.