From the temporal perspective, this article examines shifts in the production of sociological knowledge. It identifies two kinds of rhythms of sociology: 1) that of sociological standpoints and techniques of investigation and 2) that of contemporary academic life and culture. The article begins by discussing some of the existing research strategies designed to “chase” high-speed society. Some, predominantly methodological, currents are explored and contrasted with the “slow(er)” instruments of sociological analysis composed of different, yet complementary, modes of inquiry. Against this background, the article stresses that it is through the tension between fast and slow modes of inquiry that sociology reproduces itself. The subsequent part explores the subjective temporal experience in contemporary academia. It is argued that increasing administration and auditing of intellectual work signifi cantly coshapes sociological knowledge production not only by requiring academics to work faster due to an increasing volume of tasks, but also by normalizing time-pressure. The article concludes by considering the problem as to whether the increasing pace of contemporary academic life has detrimental consequences for the more organic reproductive rhythms of sociology., Tento článek zkoumá proměny produkce sociologického vědění, a to z perspektivy temporality (časovosti). Odlišuje dva druhy sociologických rytmů: první souvisí se sociologickými hledisky and technikami zkoumání, druhý potom se současnou podobou akademické kultury. Článek se nejprve zabývá několika existujícími výzkumnými strategiemi určenými ke „stíhání“ vysokorychlostní společnosti. Některé, především metodologické proudy jsou podrobeny diskuzi a porovnány s „pomalými/pomalejšími“ nástroji sociologické analýzy, sestávajících se z odlišných, avšak komplementárních způsobů šetření. V této souvislosti článek zdůrazňuje, že napětí mezi rychlými a pomalými způsoby šetření tvoří reprodukční předpoklady sociologie. Následující část se zabývá subjektivní časovou zkušeností v podmínkách soudobého akademického světa. Článek tvrdí, že zvyšující se adp ministrativa a auditování intelektuální práce značně spoluutváří výrobu sociologického vědění; a to nejen proto, že akademičtí pracovníci jsou díky vzrůstajícímu počtu úkolů nuceni pracovat rychleji, ale také kvůli normalizaci časového tlaku. Závěrem je pojednáno o tom, do jaké míry lze tvrdit, že tempo současného akademického života má neblahé důsledky pro organické reprodukční rytmy sociologie., and Filip Vostal.
The 38th International Conference on Current Trends in Theory and Practice of Computer Science was held in Špindlerův Mlýn on January 21–27, 2012. SOFSEM (SOFtware SEMinar) is the annual international winter conference devoted to the theory and practice of computer science. Its aim is to present the latest developments in research for professionals from academia and industry, working in leading areas of computer science. In memory of Alan Turing, whose 100th anniversary is being observed during 2012, SOFSEM 2012 hosted a session on Turing machines. This session consisted of invited and contributed talks on Turing machines as the basic model of computability and complexity. SOFSEM 2012 was among the official Centenary Events of The Alan Turing Year. and Martin Řimnáč.
Link-capacity functions are the relationships between the fundamental traffic variables like travel time and the flow rate. These relationships are important inputs to the capacity-restrained traffic assignment models. This study investigates the prediction of travel time as a function of several variables V/C (flow rate/capacity), retail activity, parking, number of bus stops and link type. For this purpose, the necessary data collected in Izmir, Turkey are employed by Artificial Neural Networks (ANNs) and Regression-based models of multiple linear regression (MLR) and multiple non-linear regression (MNLR). In ANNs modelling, 70% of the whole dataset is randomly selected for the training, whereas the rest is utilized in testing the model. Similarly, the same training dataset is employed in obtaining the optimal values of the coefficients of the regression-based models. Although all of the variables are used in the input vector of the models to predict the travel time, the most significant independent variables are found to be V/C and retail activity. By considering these two significant input variables, ANNs predicted the travel time with the correlation coefficient R = 0.87 while this value was almost 0.60 for the regression-based models.
Historical comments about identification of solar X-emission of various events and recent examples, especially of long-range emission from active regions, are presented
This article deals with a neural network based on Min/Max nodes and its utilisation for image recognition purposes. The general concepts of the Min/Max nodes and the single-layer neural networks are outlined. The developed software systems for simulation are briefly introduced and the results of simulations with the various settings of a neural net are presented. The subject of simulations was the recognition of human faces. Finally, the hardware design of the neural network in VHDL is shown. The design demonstrates the ease of systems realisation and the achieving of high performance.