38,309 research outputs found
YeĆilçam Film Posters of the 60s and 70s: Representing Romance
Cinema and movie poster have the most powerful potential of establishing the ethos and mythology of people, and both assume an audience on the premises of a cultural context within which they are produced. So a movie poster contributing to mass communication through designed visual means contains a lot of information about film industry, evolution of design, craftsmanship, and the taste of the artists and society as well as standing for a strong evidence of its time.
The decade 1965-1975 is important for Turkish cinema for being the golden years of this industry. Besides all the good memories associated with these posters, they indeed involve the history of Turkish cinema, graphic design as well as Turkish society. The great deal of labour involved, resulting from the poor resources of the period; design elements, typography, composition, the mistakes; all reflect the characteristics of then-YeĆilçam. Going over an archive of posters and with the help of interviews with designers, cinema historians and labourers, the article focuses on the relationship of design with the industry, technology and society.
The YeĆilçam movie posters are analyzed through the methods of iconography as well as reception theory. And therefore as well as exploring their graphic and visual characteristics they would be placed in the context of the social life, the conditions of the movie industry in Turkey, the character of YeĆilçam Melodrama and evolution of Turkish movie poster.
After a detailed research and observation, four categories are revealed as the most frequently seen types among the Turkish melodrama posters, according to the kind of images in relation to specific themes and concepts and the design schemas they use. These are âstar postersâ, âbeefcake postersâ, âphallic woman postersâ, and âposters of movementâ. The paper goes in detail how these categories are formed and their significance and their relation to the creation of the concept of romance.
Keywords:
YeĆilçam melodrama; film poster; graphic design; romance</p
Spherical collapse of supermassive stars: neutrino emission and gamma-ray bursts
We present the results of numerical simulations of the spherically symmetric
gravitational collapse of supermassive stars (SMS). The collapse is studied
using a general relativistic hydrodynamics code. The coupled system of Einstein
and fluid equations is solved employing observer time coordinates, by foliating
the spacetime by means of outgoing null hypersurfaces. The code contains an
equation of state which includes effects due to radiation, electrons and
baryons, and detailed microphysics to account for electron-positron pairs. In
addition energy losses by thermal neutrino emission are included. We are able
to follow the collapse of SMS from the onset of instability up to the point of
black hole formation. Several SMS with masses in the range are simulated. In all models an apparent horizon
forms initially, enclosing the innermost 25% of the stellar mass. From the
computed neutrino luminosities, estimates of the energy deposition by
-annihilation are obtained. Only a small fraction of this energy
is deposited near the surface of the star, where, as proposed recently by
Fuller & Shi (1998), it could cause the ultrarelativistic flow believed to be
responsible for -ray bursts. Our simulations show that for collapsing
SMS with masses larger than the energy deposition is
at least two orders of magnitude too small to explain the energetics of
observed long-duration bursts at cosmological redshifts. In addition, in the
absence of rotational effects the energy is deposited in a region containing
most of the stellar mass. Therefore relativistic ejection of matter is
impossible.Comment: 13 pages, 11 figures, submitted to A&
Business strategy and firm performance: the British corporate economy, 1949-1984
There has been considerable and ongoing debate about the performance of the British economy since 1945. Empirical studies have concentrated on aggregate or industry level indicators. Few have examined individual firmsâ financial performance. This study takes a sample of c.3000 firms in 19 industries and identifies Britainâs best performing companies over a period of 35 years. Successful companies are defined as a) those that survive as independent entities, b) that outperform peer group average return to capital for that industry, and c) that outperform other firms in the economy according to return on capital relative to industry average. Results are presented as league tables of success and some tentative explanations offered concerning the common strategies of successful firms. A broader research agenda for British business history is suggested
Using Synthetic Data to Train Neural Networks is Model-Based Reasoning
We draw a formal connection between using synthetic training data to optimize
neural network parameters and approximate, Bayesian, model-based reasoning. In
particular, training a neural network using synthetic data can be viewed as
learning a proposal distribution generator for approximate inference in the
synthetic-data generative model. We demonstrate this connection in a
recognition task where we develop a novel Captcha-breaking architecture and
train it using synthetic data, demonstrating both state-of-the-art performance
and a way of computing task-specific posterior uncertainty. Using a neural
network trained this way, we also demonstrate successful breaking of real-world
Captchas currently used by Facebook and Wikipedia. Reasoning from these
empirical results and drawing connections with Bayesian modeling, we discuss
the robustness of synthetic data results and suggest important considerations
for ensuring good neural network generalization when training with synthetic
data.Comment: 8 pages, 4 figure
Overcoming data scarcity of Twitter: using tweets as bootstrap with application to autism-related topic content analysis
Notwithstanding recent work which has demonstrated the potential of using
Twitter messages for content-specific data mining and analysis, the depth of
such analysis is inherently limited by the scarcity of data imposed by the 140
character tweet limit. In this paper we describe a novel approach for targeted
knowledge exploration which uses tweet content analysis as a preliminary step.
This step is used to bootstrap more sophisticated data collection from directly
related but much richer content sources. In particular we demonstrate that
valuable information can be collected by following URLs included in tweets. We
automatically extract content from the corresponding web pages and treating
each web page as a document linked to the original tweet show how a temporal
topic model based on a hierarchical Dirichlet process can be used to track the
evolution of a complex topic structure of a Twitter community. Using
autism-related tweets we demonstrate that our method is capable of capturing a
much more meaningful picture of information exchange than user-chosen hashtags.Comment: IEEE/ACM International Conference on Advances in Social Networks
Analysis and Mining, 201
Transfer Learning for OCRopus Model Training on Early Printed Books
A method is presented that significantly reduces the character error rates
for OCR text obtained from OCRopus models trained on early printed books when
only small amounts of diplomatic transcriptions are available. This is achieved
by building from already existing models during training instead of starting
from scratch. To overcome the discrepancies between the set of characters of
the pretrained model and the additional ground truth the OCRopus code is
adapted to allow for alphabet expansion or reduction. The character set is now
capable of flexibly adding and deleting characters from the pretrained alphabet
when an existing model is loaded. For our experiments we use a self-trained
mixed model on early Latin prints and the two standard OCRopus models on modern
English and German Fraktur texts. The evaluation on seven early printed books
showed that training from the Latin mixed model reduces the average amount of
errors by 43% and 26%, respectively compared to training from scratch with 60
and 150 lines of ground truth, respectively. Furthermore, it is shown that even
building from mixed models trained on data unrelated to the newly added
training and test data can lead to significantly improved recognition results
Bridging the gap: building better tools for game development
The following thesis is about questioning how we design game making tools, and how developers may build easier tools to use. It is about the highlighting the inadequacies of current game making programs as well as introducing Goal-Oriented Design as a possible solution. It is also about the processes of digital product development, and reflecting on the necessity for both design and development methods to work cohesively for meaningful results. Interaction Design is in essence the abstracting of key relations that matter to the contextual environment. The result of attempting to tie the Interaction Design principles, Game Design issues together with Software Development practices has led to the production of the User-Centred game engine, PlayBoard
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