scholarly journals Blurring the Boundaries between Real Worlds, Discourse Worlds and Text Worlds

2021 ◽  
Vol 21 ◽  
Author(s):  
Nelly Tincheva
Keyword(s):  
Real World ◽  
Article Title ◽  
Black Widow ◽  
Data Set ◽  
The Real ◽  
Theoretical Premise ◽  
Political Speeches ◽  
The Difference ◽  
World Concept

Blurring the Boundaries between Real Worlds, Discourse Worlds and Text WorldsWhat do the article title ‘Black Widow Breaks Up With Kylo Ren’ and a Twitter message saying ‘The scene in The Departed where Mark Wahlberg shoots Matt Damon is the blueprint for how to handle corrupt cops’ have in common? Clearly, they both combine references to actors and movies, but do they combine them through the same cognitive technique(s)? This paper starts by addressing the question of how these two instances of reference differ. The line of argumentation that is supported suggests that a world-building theory needs to be employed in order to understand the difference. In doing this, the paper aims and contributes to the theoretical advancement of world-building approaches by arguing for the introduction of the concept of ‘Real Worlds’ in research on Text Worlds and Discourse Worlds. Data set sample analyses employing the Real World concept are included to verify the main theoretical premise. The analyzed texts cover traditional genres such as political speeches as well as modern-day, boundary-blurring genres such as Twitter messages. Zacieranie granic między światem rzeczywistym, światem dyskursu i światem tekstu Co mają wspólnego artykuł zatytułowany Czarna wdowa zrywa z Kylo Renem i wiadomość na Twitterze o treści „Scena w The Departed, w której Mark Wahlberg strzela do Matta Damona, jest schematem postępowania ze skorumpowanymi gliniarzami”? Oczywiście oba łączą odniesienia do aktorów i filmów, ale czy łączą je za pomocą tych samych technik poznawczych? Artykuł rozpoczyna się od odpowiedzi na pytanie, czym różnią się te dwa przypadki odniesienia. Wynikiem zaprezentowanej argumentacji jest sugestia, aby w celu zrozumienia różnicy między nimi wyjść od teorii tworzenia światów. Opowiedzenie się za wykorzystaniem koncepcji „świata rzeczywistego” w badaniach nad światem tekstu i światem dyskursu ma na celu rozwój i wzmocnienie teorii tworzenia światów. W weryfikacji podstawowej przesłanki teoretycznej w artykule uwzględniono wyniki analizy próbek ze zbioru danych, w których wykorzystano koncepcję „świata rzeczywistego”. Analizie poddano zarówno teksty reprezentujące tradycyjne gatunki, takie jak przemówienia polityczne, jak również teksty, w których dochodzi do zacierania granic międzygatunkowych, na przykład wiadomości w serwisie społecznościowym Twitter.

scholarly journals Difference between the Real World and Virtual World

Proceedings ◽  
2020 ◽  
Vol 47 (1) ◽  
pp. 35
Author(s):  
Wei Wang
Keyword(s):  
Virtual Reality ◽  
Real World ◽  
Virtual World ◽  
Actual World ◽  
Scientific Representation ◽  
The Real ◽  
The Difference

The development of virtual reality brings an old and historic question on the difference between the real world and unreal world. In this paper, starting from the concept of representation, I argued that what we call “virtual reality” is a representation of an actual or non-actual world and the criterion of difference between the “real world” and “virtual reality” is whether we present it with the intention of using it as a representation. After that, the thesis is demonstrated again from different theories of scientific representation. Therefore, the intuitive distinction between the “real world” and “virtual reality” can be drawn on the epistemological criterion; that is to say, the virtual world is a representation while the real world is not.

Different Engines

2017 ◽  
Author(s):  
Gary Westfahl
Keyword(s):  
Science Fiction ◽  
Real World ◽  
The Real ◽  
Alternate History ◽  
Film Version ◽  
Bruce Sterling ◽  
Song Lyrics ◽  
The Difference ◽  
First Offers

This chapter examines William Gibson's The Difference Engine, a collaboration with Bruce Sterling, as well as his screenplays, poetry, song lyrics, and nonfiction. Sterling used an irresistibly marketable concept for The Difference Engine: a novel by what he could describe as the two leading cyberpunk authors that would appealingly blend three popular subgenres of science fiction—cyberpunk, alternate history, and “steampunk” literature. Despite the prominence of cyberspace in his Sprawl trilogy, Gibson claimed that he has “never really been very interested in computers themselves.” This chapter first offers a reading of The Difference Engine before discussing Gibson's screenplays written for Hollywood in the late 1980s, including one for a proposed Alien 3 film and another for the film version of Johnny Mnemonic. It also considers Gibson's poems such as “The Beloved: Voices for Three Heads,” his ventures into writing song lyrics, and the approach he used in some of his later nonfiction works: looking at the real world in terms of science fiction, conveying that we indeed live in a science fiction world.

Further Considerations of Classification-Oriented and Approximation-Oriented Rough Sets in Generalized Settings

2010 ◽  
Vol 4 (2) ◽  
pp. 12-34
Author(s):  
Masahiro Inuiguchi
Keyword(s):  
Real World ◽  
Rough Sets ◽  
Decision Rules ◽  
Point Of View ◽  
Inverse Relation ◽  
The Real ◽  
The Difference

Rough sets can be interpreted in two ways: classification of objects and approximation of a set. From this point of view, classification-oriented and approximation-oriented rough sets have been proposed. In this paper, the author reconsiders those two kinds of rough sets with reviewing their definitions, properties and relations. The author describes that rough sets based on positive and negative extensive relations are mathematically equivalent but it is important to consider both because they obtained positive and negative extensive relations are not always in inverse relation in the real world. The difference in size of granules between union-based and intersection-based approximations is emphasized. Moreover, the types of decision rules associated with those rough sets are shown.

Adjusting the Outputs of a Classifier to New a Priori Probabilities: A Simple Procedure

2002 ◽  
Vol 14 (1) ◽  
pp. 21-41 ◽  
Author(s):  
Marco Saerens ◽  
Patrice Latinne ◽  
Christine Decaestecker
Keyword(s):  
Real World ◽  
Classification Accuracy ◽  
A Priori ◽  
Training Set ◽  
Real World Data ◽  
Data Set ◽  
World Data ◽  
The Real ◽  
Trained Classifier ◽  
A Priori Probability

It sometimes happens (for instance in case control studies) that a classifier is trained on a data set that does not reflect the true a priori probabilities of the target classes on real-world data. This may have a negative effect on the classification accuracy obtained on the real-world data set, especially when the classifier's decisions are based on the a posteriori probabilities of class membership. Indeed, in this case, the trained classifier provides estimates of the a posteriori probabilities that are not valid for this real-world data set (they rely on the a priori probabilities of the training set). Applying the classifier as is (without correcting its outputs with respect to these new conditions) on this new data set may thus be suboptimal. In this note, we present a simple iterative procedure for adjusting the outputs of the trained classifier with respect to these new a priori probabilities without having to refit the model, even when these probabilities are not known in advance. As a by-product, estimates of the new a priori probabilities are also obtained. This iterative algorithm is a straightforward instance of the expectation-maximization (EM) algorithm and is shown to maximize the likelihood of the new data. Thereafter, we discuss a statistical test that can be applied to decide if the a priori class probabilities have changed from the training set to the real-world data. The procedure is illustrated on different classification problems involving a multilayer neural network, and comparisons with a standard procedure for a priori probability estimation are provided. Our original method, based on the EM algorithm, is shown to be superior to the standard one for a priori probability estimation. Experimental results also indicate that the classifier with adjusted outputs always performs better than the original one in terms of classification accuracy, when the a priori probability conditions differ from the training set to the real-world data. The gain in classification accuracy can be significant.

scholarly journals Effects of Background Color, Flash and Exposure Value on the Accuracy of Smartphone-Based Pill Recognition System Using Deep Convolutional Neural Network (Preprint)

2020 ◽  
Author(s):  
KyeongMin Cha
Keyword(s):  
Real World ◽  
Color Difference ◽  
Recognition System ◽  
Reference Image ◽  
White Background ◽  
Factors Affecting ◽  
The Real ◽  
Black Background ◽  
The Difference ◽  
World Image

BACKGROUND It is difficult to develop a drug image recognition system due to the difference of the pill color influenced by external environmental factors such as the illumination or presence of flash. OBJECTIVE In this study, we wanted to see how the difference in color between the reference image and the real-world image affects the accuracy in pill recognition under 12 real-world conditions according to the background colors, presence of flash, and exposure values (EV). METHODS We used 19 medications with different features of colors, shapes, and dosages. The average color difference was calculated based on the color distance between the reference image and the real-world image. RESULTS In the case of the black background, as the exposure value lowered, the accuracy of top-1 and top-5 increased independently of the presence of flash. The top-5 accuracy in black background increased from 26.8% to 72.6% with the flash on and from 29.5% to 76.8% with the flash off as EV decreased as well. On the other hand, top-5 accuracy was 62.1% to 78.4% in white background with the flash on. The best top-1 accuracy was 51.1 % in the white background, flash on, and EV+2.0. The best top-5 accuracy was 78.4% in the white background, flash on, and EV0. CONCLUSIONS The accuracy generally increased as the color difference decreased except in the case of black background and EV-2.0. This study reveals that the background colors, presence of flash, and exposure values in real-world conditions are important factors affecting the performance of a pill recognition model.

scholarly journals Translators as Well as Thinkers: Teaching of Journalistic Translation in Hong Kong1

2006 ◽  
Vol 51 (3) ◽  
pp. 611-619 ◽  
Author(s):  
Defeng Li
Keyword(s):  
Hong Kong ◽  
Empirical Evidence ◽  
Professional Practice ◽  
Real World ◽  
The Real ◽  
The World ◽  
Translator Training ◽  
The Difference ◽  
Translation Methods

Abstract Hong Kong is probably one of the most exciting places in the world to study translation as a student or a researcher. Seven out of the eight universities offer translation degrees. Among others, journalistic translation has always been one of the most popular courses for students. However, students have often felt underprepared in journalistic translation even after taking some related courses. This study argues, with the support of empirical evidence that one of the major reasons accountable for this is the gap between institutional translator training and the real world of professional translation, which, in the context of journalistic translation, manifests itself as the difference in translation methods taught in translation programs and used in professional practice. The author further contends that this gap needs to be bridged in order to better prepare student translators for the market. Recommendations are also made as to how the gap can be narrowed or bridged.

scholarly journals Sensitivity analysis for mistakenly adjusting for mediators in estimating total effect in observational studies

BMJ Open ◽  
2017 ◽  
Vol 7 (11) ◽  
pp. e015640 ◽  
Author(s):  
Tingting Wang ◽  
Hongkai Li ◽  
Ping Su ◽  
Yuanyuan Yu ◽  
Xiaoru Sun ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Real World ◽  
Observational Studies ◽  
Total Effect ◽  
Causal Relationships ◽  
The Real ◽  
Limited Knowledge ◽  
Causal Diagrams ◽  
The Difference

ObjectivesIn observational studies, epidemiologists often attempt to estimate the total effect of an exposure on an outcome of interest. However, when the underlying diagram is unknown and limited knowledge is available, dissecting bias performances is essential to estimating the total effect of an exposure on an outcome when mistakenly adjusting for mediators under logistic regression. Through simulation, we focused on six causal diagrams concerning different roles of mediators. Sensitivity analysis was conducted to assess the bias performances of varying across exposure-mediator effects and mediator-outcome effects when adjusting for the mediator.SettingBased on the causal relationships in the real world, we compared the biases of varying across the effects of exposure-mediator with those of varying across the effects of mediator-outcome when adjusting for the mediator. The magnitude of the bias was defined by the difference between the estimated effect (using logistic regression) and the total effect of the exposure on the outcome.ResultsIn four scenarios (a single mediator, two series mediators, two independent parallel mediators or two correlated parallel mediators), the biases of varying across the effects of exposure-mediator were greater than those of varying across the effects of mediator-outcome when adjusting for the mediator. In contrast, in two other scenarios (a single mediator or two independent parallel mediators in the presence of unobserved confounders), the biases of varying across the effects of exposure-mediator were less than those of varying across the effects of mediator-outcome when adjusting for the mediator.ConclusionsThe biases were more sensitive to the variation of effects of exposure-mediator than the effects of mediator-outcome when adjusting for the mediator in the absence of unobserved confounders, while the biases were more sensitive to the variation of effects of mediator-outcome than those of exposure-mediator in the presence of an unobserved confounder.

Evaluator as a Critical Participant in an Interagency Collaboration: A Case Study

2000 ◽  
Vol 22 (2) ◽  
pp. 18-22
Author(s):  
Barbara Knox-Seith
Keyword(s):  
Public Relations ◽  
Real World ◽  
Interagency Collaboration ◽  
Staff Time ◽  
Lead Agency ◽  
The Real ◽  
The Difference

The day after I presented an earlier version of this article (in the session "Landing on Your Feet in the Real World: Anthropologists as Evaluators" at the SfAA annual meetings in Seattle, March, 1997) I spoke by phone with Hilary Stern, the director of CASA Latina, the lead agency on the project discussed in the following pages. She summarized her experiences with evaluation: The evaluation you did for us was the first helpful evaluation we've had, and we've participated in many. Other agencies' experiences are similar to ours. I was really glad that I could tell other people about our experience [at a session on evaluation at a conference on ESLIadult education]. It was the only positive example anyone was able to provide. In most evaluations, evaluators have come from outside. They impose on staff time, and sometimes they don't even give the agency the results. When they do, the information isn't of value to the agency: they tell us what we already know; they don't tell us about things we want to know, things that matter to us. The difference with this evaluation is that it met our agenda. We decided we wanted the evaluation, and we selected the evaluator. It contributed to the success of our project and to our goals as an agency. Other evaluations were done to meet the agenda of the researchers. We agreed to participate in them as a matter of good public relations. Other than that, they're a waste of our time. I'm glad we had the experience of this evaluation. It shows that evaluation can be useful. I hope that you will publish your paper about it as a model and inspiration to others. — [paraphrase of] Hilary Stern, from phone conversation on March 8, 1997

Chiasm of Thought-and-Action

1993 ◽  
Vol 11 (3) ◽  
pp. 279-294 ◽  
Author(s):  
G Olsson
Keyword(s):  
Coordinate System ◽  
Real World ◽  
Double Helix ◽  
Three Dimensional ◽  
The Real ◽  
Human Thought ◽  
The World ◽  
Minimalist Approach ◽  
The Difference ◽  
Three Dimensional Coordinate

How do I know the difference between you and me and how do we share our beliefs in the same? How are we made so obedient and so predictable? As a minimalist approach to these questions I imagine human thought-and-action as a double helix, It is assumed firstly, that man is a semiotic animal, a species whose individuals are kept together and apart by their use of signs; secondly, that every sign within itself combines elements of drastically different ontologies. This invisible world is then captured in a three-dimensional coordinate system whose axes are those of identity, difference, and intentionality. While the resulting map is anchored in fix-points of silence, the real world of socialization and understanding is always in flux. The paper closes with a pastiche on Carl von Linné's Flora Suecica; in the current world of thought-and-action, signifier and signified are assigned the same ordering functions as stamina and pistil once were in the world of plants. How do I draw the invisible lines of the taken-for-granted? How do I project a dematerialized point onto a transparent plane?

scholarly journals Technical note: analytical estimation of the optimal parameters for the EOF retrievals of the IASI Level 2 Product Processing Facility and its application using AIRS and ECMWF data

2006 ◽  
Vol 6 (3) ◽  
pp. 831-846 ◽  
Author(s):  
X. Calbet ◽  
P. Schlüssel
Keyword(s):  
Standard Deviation ◽  
Linear Regression ◽  
Mean Difference ◽  
Training Data ◽  
Data Set ◽  
The Real ◽  
Atmospheric Profiles ◽  
The Mean ◽  
Atmospheric State ◽  
The Difference

Abstract. The Empirical Orthogonal Function (EOF) retrieval technique consists of calculating the eigenvectors of the spectra to later perform a linear regression between these and the atmospheric states, this first step is known as training. At a later stage, known as performing the retrievals, atmospheric profiles are derived from measured atmospheric radiances. When EOF retrievals are trained with a statistically different data set than the one used for retrievals two basic problems arise: significant biases appear in the retrievals and differences between the covariances of the training data set and the measured data set degrade them. The retrieved profiles will show a bias with respect to the real profiles which comes from the combined effect of the mean difference between the training and the real spectra projected into the atmospheric state space and the mean difference between the training and the atmospheric profiles. The standard deviations of the difference between the retrieved profiles and the real ones show different behavior depending on whether the covariance of the training spectra is bigger, equal or smaller than the covariance of the measured spectra with which the retrievals are performed. The procedure to correct for these effects is shown both analytically and with a measured example. It consists of first calculating the average and standard deviation of the difference between real observed spectra and the calculated spectra obtained from the real atmospheric state and the radiative transfer model used to create the training spectra. In a later step, measured spectra must be bias corrected with this average before performing the retrievals and the linear regression of the training must be performed adding noise to the spectra corresponding to the aforementioned calculated standard deviation. This procedure is optimal in the sense that to improve the retrievals one must resort to using a different training data set or a different algorithm.

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