scholarly journals Neuronal Population Responses in the Human Ventral Temporal and Lateral Parietal Cortex during Arithmetic Processing with Digits and Number Words

2018 ◽  
Vol 30 (9) ◽  
pp. 1315-1322 ◽  
Author(s):  
Sori Baek ◽  
Amy L. Daitch ◽  
Pedro Pinheiro-Chagas ◽  
Josef Parvizi
Keyword(s):  
Word Processing ◽  
Past Research ◽  
Theoretical Models ◽  
Small Region ◽  
Neuronal Population ◽  
Number Word ◽  
Number Words ◽  
Electrophysiological Responses ◽  
The Difference ◽  
Number Form

Past research has identified anatomically specific sites within the posterior inferior temporal gyrus (PITG) and the intraparietal sulcus (IPS) areas that are engaged during arithmetic processing. Although a small region of the PITG (known as the number form area) is selectively engaged in the processing of numerals, its surrounding area is activated during both digit and number word processing. In eight participants with intracranial electrodes, we compared the timing and selectivity of electrophysiological responses in the number form area-surround and IPS regions during arithmetic processing with digits and number words. Our recordings revealed stronger electrophysiological responses in the high-frequency broadband range in both regions to digits than number words, with the difference that number words elicited delayed activity in the IPS but not PITG. Our findings of distinct profiles of responses in the PITG and the IPS to digits compared with number words provide novel information that is relevant to existing theoretical models of mathematical cognition.

DENSITY DISCONTINUITIES AT THE CRITICAL TEMPERATURE

1933 ◽  
Vol 9 (6) ◽  
pp. 613-629 ◽  
Author(s):  
C. A. Winkler ◽  
O. Maass
Keyword(s):  
Critical Temperature ◽  
Small Region ◽  
Density Difference ◽  
Experimental Investigations ◽  
Sharp Change ◽  
Two Component System ◽  
Medium Increase ◽  
The Difference ◽  
Temperature Equilibrium ◽  
Continuous Relation

A technique for measuring densities in various parts of a one- or two-component system, raised above its critical temperature, is described. Considerable improvements over a method for this purpose recently described by one of the writers consist in greater flexibility of manipulation and in making possible a variation in the volume of space confining the medium during the experiment. Propylene and methyl-ether were the two media examined. From the results the following generalizations regarding aberrations from the continuity of state were found to hold for both.When either liquid was heated above the temperature at which the visible meniscus disappeared, the density below this point of disappearance was found to be greater than that above. The density was uniform throughout each portion, undergoing a relatively sharp change in the small region where the meniscus was last seen. After one hour of temperature equilibrium, the difference in density between top and bottom became constant and remained unaltered for six hours. Constant stirring or temperature fluctuations of the order of 0.02 °C. do not alter this density difference. A decrease in the volume available for the medium increases the density difference between the top and bottom, a continuous relation existing between available space and density difference. With decrease in available space, the densities of both upper and lower portions of the medium increase, the density of the lower more rapidly than that of the upper. These results were reproducible quantitatively in the experiments carried out to date. The density difference for a fixed available space decreases with rise in temperature and is measurable up to at least 10 °C. above the critical temperature. A number of miscellaneous experiments are described which form the basis of work now being carried out. The theoretical significance of aberrations from the continuity of state is discussed to the extent warranted by the present stage of the experimental investigations, and tentative conclusions are drawn.

scholarly journals Evaluation of the Vertical Producing Degree of Commingled Production via Waterflooding for Multilayer Offshore Heavy Oil Reservoirs

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2428 ◽  
Author(s):  
Fei Shen ◽  
Linsong Cheng ◽  
Qiang Sun ◽  
Shijun Huang
Keyword(s):  
Heavy Oil ◽  
Flow Model ◽  
Dynamic Method ◽  
Theoretical Models ◽  
Oil Reservoirs ◽  
Sweep Efficiency ◽  
One Dimensional ◽  
Heavy Oil Reservoirs ◽  
The Difference ◽  
Important Form

Recently, commingling production has been widely used for the development of offshore heavy oil reservoirs with multilayers. However, the differences between layers in terms of reservoir physical properties, oil properties and pressure have always resulted in interlayer interference, which makes it more difficult to evaluate the producing degree of commingled production. Based on the Buckley–Leverett theory, this paper presents two theoretical models, a one-dimensional linear flow model and a planar radial flow model, for water-flooded multilayer reservoirs. Through the models, this paper establishes a dynamic method to evaluate seepage resistance, sweep efficiency and recovery percent and then conducts an analysis with field data. The result indicates the following: (1) the dynamic difference in seepage resistance is an important form of interlayer interference during the commingled production of an offshore multilayer reservoir; (2) the difference between commingled production and separated production is small within a certain range of permeability ratio or viscosity ratio, but separated production should be adopted when the ratio exceeds a certain value.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals The association between number magnitude and space is dependent on notation: Evidence from an adaptive perceptual orientation task

2019 ◽  
Vol 5 (1) ◽  
pp. 38-54
Author(s):  
Tianwei Gong ◽  
Baichen Li ◽  
Limei Teng ◽  
Zijun Zhou ◽  
Xuefei Gao ◽  
...  
Keyword(s):  
Judgment Task ◽  
Snarc Effect ◽  
Number Word ◽  
Reaction Time Difference ◽  
Number Words ◽  
Number Magnitude ◽  
Spatial Response ◽  
Orientation Task ◽  
Arabic Digits ◽  
Perceptual Orientation

Research on adults' numerical abilities suggests that number representations are spatially oriented. This association of numbers with spatial response is referred to as the SNARC (i.e., spatial–numerical association of response codes) effect. The notation-independence hypothesis of numeric processing predicts that the SNARC effect will not vary with notation (e.g., Arabic vs. number word). To test such assumption, the current study introduced an adaptive experimental procedure based on a simple perceptual orientation task that can automatically smooth out the mean reaction time difference between Arabic digits and traditional Chinese number. We found that the SNARC effect interacted with notation, showing a SNARC effect for Arabic digits, but not for verbal number words. The results of this study challenged the commonly held view that notation does not affect numerical processes associated with spatial representations. We introduced a parallel model to explain the notation-dependent SNARC effect in the perceptual orientation judgment task.

Construction and Experimental Study of an Elevation Linear Fresnel Reflector

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
J. D. Nixon ◽  
P. A. Davies
Keyword(s):  
Heat Loss ◽  
Thermal Efficiency ◽  
Theoretical Models ◽  
Loss Coefficient ◽  
Heat Transfer Fluid ◽  
Stagnation Temperature ◽  
Model Predictions ◽  
The Difference ◽  
Predicted Values ◽  
Linear Fresnel Reflector

This paper outlines a novel elevation linear Fresnel reflector (ELFR) and presents and validates theoretical models defining its thermal performance. To validate the models, a series of experiments were carried out for receiver temperatures in the range of 30–100 °C to measure the heat loss coefficient, gain in heat transfer fluid (HTF) temperature, thermal efficiency, and stagnation temperature. The heat loss coefficient was underestimated due to the model exclusion of collector end heat losses. The measured HTF temperature gains were found to have a good correlation to the model predictions—less than a 5% difference. In comparison to model predictions for the thermal efficiency and stagnation temperature, measured values had a difference of −39% to +31% and 22–38%, respectively. The difference between the measured and predicted values was attributed to the low-temperature region for the experiments. It was concluded that the theoretical models are suitable for examining linear Fresnel reflector (LFR) systems and can be adopted by other researchers.

Research in Information Systems

2012 ◽  
pp. 51-75
Keyword(s):  
Information Systems ◽  
Organizational Context ◽  
Past Research ◽  
Theoretical Models ◽  
Research Community ◽  
Nature Of Information ◽  
Is Design ◽  
Substantial Extent ◽  
Outer Environment

Information Systems (IS) are complex artifacts which could be viewed as playing the role of an interface between the organizational structure and processes and the technological capabilities. IS design is influenced by—and has an influence on—its outer environment: organizational context. Much of past research in IS is of explanatory nature and has largely focused on the processes and functions of outer environment, including organizations and individuals. There is not sufficient theoretical elaboration on the organizational and technological connections of the IS artifacts. Some of the most prominent theoretical models of IS do not incorporate the very nature of information systems to a substantial extent. The information content of these models is also questionable. IS research has been criticized by some members of the research community for lack of identity and lack of relevance.

scholarly journals Mean-Variance Analysis of Alternative Hedging Strategies

1972 ◽  
Vol 4 (1) ◽  
pp. 123-128 ◽  
Author(s):  
David Holland ◽  
Wayne D. Purcell ◽  
Terry Hague
Keyword(s):  
Futures Markets ◽  
Market Price ◽  
Theoretical Models ◽  
Spot Price ◽  
Hedging Strategies ◽  
Optimum Position ◽  
Futures Price ◽  
The Difference ◽  
Mean Variance ◽  
Over Time

Much of the research in commodity hedging has concentrated upon the development of theoretical models describing the optimum position in cash and futures markets. Other studies have shown that the difference between current spot price and futures price represents the market price for storage, processing services, or both. The revenue stabilizing potential of futures markets for commodities with continuous as opposed to noncontinuous inventories has also received attention. However, very little work or literature is publicly available on how different hedging strategies actually would have performed for a particular commodity over time.

scholarly journals Inversion effects on mental arithmetic in English- and Polish-speaking adults

2019 ◽  
Vol 73 (1) ◽  
pp. 91-103
Author(s):  
Carolin Annette Lewis ◽  
Julia Bahnmueller ◽  
Marta Wesierska ◽  
Korbinian Moeller ◽  
Silke Melanie Göbel
Keyword(s):  
Mental Arithmetic ◽  
Word Formation ◽  
Place Value ◽  
Number Word ◽  
Problem Size ◽  
Number Range ◽  
Number Words ◽  
Language Groups ◽  
Addition Problem ◽  
The Cost

In some languages the order of tens and units in number words is inverted compared with the symbolic digital notation (e.g., German 23 → “ dreiundzwanzig,” literally: “ three-and-twenty”). In other languages only teen-numbers are inverted (e.g., English 17 → “ seventeen”; Polish 17 → “ siedemnaście” literally “ seventeen”). Previous studies have focused on between group comparisons of inverted and non-inverted languages and showed that number word inversion impairs performance on basic numerical tasks and arithmetic. In two independent experiments, we investigated whether number word inversion affects addition performance within otherwise non-inverted languages (Exp. 1: English, Exp. 2: Polish). In particular, we focused on the influence of inverted ( I; English: teen-numbers ⩾ 13, Polish: numbers 11–19) and non-inverted ( N) summands with sums between 13 and 39. Accordingly, three categories of addition problems were created: N + N, N + I, and I + I with problem size matched across categories. Across both language groups, we observed that problems with results in the 20 and 30 number range were responded to faster when only non-inverted summands were part of the problems as opposed to problems with one or two inverted summands. In line with this, the cost of a carry procedure was the largest for two inverted summands. The results support the notion that both language-specific and language-invariant aspects contribute to addition problem-solving. In particular though, regarding language-specific aspects, the results indicate that inverted number word formation of teens influences place-value processing of Arabic digits even in otherwise non-inverted languages.

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