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The article deals with to the analysis of artistic models of memory in contemporary Ukrainian literature on the example of the novel "Echo" by Larysa Denysenko. The author describes the events of World War II in an unusual way: through the prism of the 21st century from the standpoint of the defeated people. The artistic form of the novel seeks to destroy the stereotypical image of the German, showing them through the prism of national trauma caused by events that are still unconscious collective experience, and therefore do not belong to the former, but are still in the paradigm of modernity. The research focuses on clarification of collective strategies for the reception of traumatic events of the past, which are carried by the characters of the novel. Models of memory are polyphonic and outlined through the number of major strategies for dealing with the events of World War II. They are as follows: to distance oneself from the past, as history can harm future generations; to accept historical facts and to abandon the socially constructed model of all-German guilt committed by the fascist party; history should be turned into culture, because only such a memory can be constructive, while real history produces social conflicts; to forgive – because all people were victims of the political system; forget the history and focus on the present; find out the truth about past events; identify the war criminals and punish them. The protagonist demonstrates a position of personal involvement in history, cultivating a sense of responsibility for the war crimes of the older generation, which are to be paid for, that is, World War II forms guilt as a model of behavior of the generation of grandchildren. This narrative aims to recode the socio-cultural reception of war from heroic to traumatic and to remove the "Friend or Foe" diachrony by socializing the private experience. Accordingly, the cultural construction of memory through the construction of a memorial as a symbolic sign of reconciliation takes place. It is worth ...

Brand alliances between the brands from different categories are increasingly becoming popular (Smarandescu, Rose and Wedell, 2013). This is particular relevant to the emerging countries context where multinational brands due to strong impact of cultural and country-specific political and economic governance policies are establishing cross-category brand alliances with local brands to gain brand success and customer loyalty. Existing studies investigated cross-category brand alliances according to the aspects of brand order, consumer ethnocentrism, the country of origin and brand familiarity. However, these studies primarily incorporate end-user impact factors in measuring and understanding the cross-category brand alliances performance. Brands as business perspective is required to understand the impacts of brand resources and attributes on the cross-category brand alliance. This study focuses on the cross-category brand alliances and attempts to develop a framework to measure the performance of cross-category brand alliances. The framework constructs are derived from Associative Network Memory (ANM) Model and Resource Based View (RBV) theories. The framework is developed by evaluating the interviews with the marketing managers of brands in the brand alliance case studies from an emerging country, Turkey.

AbstractThis experiment examined single‐process and dual‐process accounts of the development of visual recognition memory. The participants, 6–7‐year‐olds, 9–10‐year‐olds and adults, were presented with a list of pictures which they encoded under shallow or deep conditions. They then made recognition and confidence judgments about a list containing old and new items. We replicated the main trends reported by Ghetti and Angelini () in that recognition hit rates increased from 6 to 9 years of age, with larger age changes following deep than shallow encoding. Formal versions of the dual‐process high threshold signal detection model and several single‐process models (equal variance signal detection, unequal variance signal detection, mixture signal detection) were fit to the developmental data. The unequal variance and mixture signal detection models gave a better account of the data than either of the other models. A state‐trace analysis found evidence for only one underlying memory process across the age range tested. These results suggest that single‐process memory models based on memory strength are a viable alternative to dual‐process models for explaining memory development.

A model for visual recall tasks was presented in terms of visual information storage (VIS), scanning, rehearsal, and auditory information storage (AIS). It was shown first that brief visual stimuli are stored in VIS in a form similar to the sensory input. These visual "images" contain considerably more information than is transmitted later. They can be sampled by scanning for items at high rates of about 10 msec per letter. Recall is based on a verbal receding of the stimulus (rehearsal), which is remembered in AIS. The items retained in AIS are usually rehearsed again to prevent them from decaying. The human limits in immediate-memory (reproduction) tasks are inherent in the AIS-Rehearsal loop. The main implication of the model for human factors is the importance of the auditory coding in visual tasks.

"Long- and Short-term Memory Structure in Political Decision Making" published on by Oxford University Press.

Стаття присвячена удосконаленню технологій обчислювального інтелекту щодо розробки інтелектуальних машин, які використовуються в керуванні автономними технічними системами, у тому числі системами воєнного призначення з розвинутими сенсорами. Наведено формальну модель сенсорної пам'яті, яка підтримує наведений механізм узагальнення. Розглянуто комп'ютерні експерименти, які демонструють переваги технології обробки сенсорної інформації із застосуванням механізму узагальнення даних. ; Статья посвящена совершенствованию технологий вычислительного интеллекта по разработке интеллектуальных машин, которые используются в управлении автономными техническими системами, в том числе системами военного назначения с развитыми сенсорами. Представлена формальная модель сенсорной памяти, которая поддерживает приведенный механизм обобщения. Рассмотрены компьютерные эксперименты, демонстрирующие преимущества технологии обработки сенсорной информации с применением механизма обобщения данных. ; The paper is dedicated to the improvement of computational intelligence technology at developing intelligent machines that are used in autonomous driving technical systems, including military systems with advanced sensors. The sensory memory model with generalization processing is presented in the paper. We consider computer experiments, which demonstrate benefits of processing of sensory information using data generalization.