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Not Available ; Agricultural time-series data concerning production, prices, export and import of several agricultural commodities is published by Indian government along with other private agricultural sectors every year. The analysis of these factors is necessary to formulate and apply several policies regarding food acquisition and its distribution, quality and quantity of import and export products, pricing structure, MSP of agricultural commodities etc. Box – Jenkins's Autoregressive integrated moving average (ARIMA) model is broadly utilized in the field of time-series. In the field of time-series analysis, it is assumed by most of the researchers that the data points of different time lags do not depend on each other, i.e. absence of long memory process. But in agriculture, market price data exhibits that the observation are dependent on distant past. This is the possible indication of long memory process or long range dependency in the mean model. Autoregressive fractionally integrated autoregressive moving average (ARFIMA) model is generally used to portray the characteristic features of the long memory time series models as well as for the forecasting purposes. In this study wavelet decomposition is used for increasing the forecasting accuracy of the ARFIMA model. Daily wholesale data of wheat of Rewari market of Haryana for the period of January, 2010 to November, 2017 is used for the demonstration of our approach. ; Not Available

International audience ; This paper extends the results of Byers, Davidson and Peel (1997) on long memory in support for the Conservative and Labour Parties in the UK using longer samples and additional poll series. It finds continuing support for the ARFIMA(0,d,0) model though with somewhat smaller values of the long memory parameter. We find that the move to telephone polling in the mid-1990s has no apparent effect on the estimated value of d for either party. Finally, we find that we cannot reject the hypotheses that the parties share a common long memory parameter which we estimate at around 0.65.

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.

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.

In Northern Ireland, parades have long been important carriers of politico-cultural identities and collective memories, as well as arenas of struggle and conflict. Taking as its starting point that these contests over meaning are always framed by their contexts of articulation both in temporal and spatial terms, this article examines the role of parades in the current 'post-conflict' phase of the peace process as it plays out in a particular location, namely North Belfast. Using theories of cultural and collective memory and examples from republican and loyalist parades in North Belfast, it is argued that there is fear of memory and identity collapse in particular communities on the margins of the peace process, leading to a conscious doubling of efforts to (re)articulate the hidden recesses of memory in the current transition. In this, the patterns of 'competitive commemoration' in parades should be understood both horizontally: as majority memory traditions move to minority memory positions, and vertically: in relation to the increasing dissonance between vernacular practices of conflict and the official post-conflict discourses in Northern Ireland. Central to these arguments is the recognition that parading traditions are at once presentist, competitive instruments and also emotional and embodied practices to ensure the continuity of identity. It follows that both dimensions must be recognised together, if cognitive and visceral templates of conflict are to be explained and shifted. This article applies a wide-angle memory studies lens to capture the two together and explore the changing parade-scape.

Producción Científica ; Dataflow programming consists in developing a program by describing its sequential stages and the interactions between them. The runtime systems supporting this kind of programming are responsible for exploiting the parallelism by concurrently executing the different stages as soon as their dependencies are met. In this paper we introduce a new parallel programming model and framework based on the dataflow paradigm. It presents a new combination of features that allows to easily map programs to shared or distributed memory, exploiting data locality and affinity to obtain the same performance than optimized coarse-grain MPI programs. These features include: It is a unique one-tier model that supports hybrid shared- and distributed-memory systems with the same abstractions; it can express activities arbitrarily linked, including non-nested cycles; it uses internally a distributed work-stealing mechanism to allow Multiple-Producer/Multiple-Consumer configurations; and it has a runtime mechanism for the reconfiguration of the dependences and communication channels which also allows the creation of task-to-task data affinities. We present an evaluation using examples of different classes of applications. Experimental results show that programs generated using this framework deliver good performance in hybrid distributed- and shared-memory environments, with a similar development effort as other dataflow programming models oriented to shared-memory. ; 2019-01-01 ; MICINN (Spain) and ERDF program of the European Union: HomProg-HetSys project (TIN2014-58876- P), PCAS project (TIN2017-88614-R), CAPAP-H6 (TIN2016-81840-REDT), and COST Program Action IC1305: Network for Sustainable Ultrascale Com- puting (NESUS). By Junta de Castilla y Le on, project PROPHET (VA082P17). And by the computing facilities of Extremadura Research Centre for Advanced Technologies (CETA- CIEMAT), funded by the European Regional Develop- ment Fund (ERDF). CETA-CIEMAT belongs to CIEMAT and the Govern- ment of Spain.

The article is aimed at substantiating the choice of a conceptual historical memory model, transition from analytical models, descriptive models and unsubstantiated prognostics to the subject-activity model as a conceptual tool. This tool is aimed at consolidating the subjects of regional society in working out a common outline of actions and goals in the context of innovative development. According to the comparative analysis of the existing historical memory resource models, we concluded that in modern conditions there is a demand for understanding the resource of historical memory as a cognitive map of stability and consistency, with the possibility of decision-making at the level of regional society. We arrived at the conclusion that the subject-activity model of historical memory resource is the most adequate in terms of parameters focused on changes in regional society in relation to the tendency of mutual influence of historical experience, determined by the logic of everyday life, and the official historical discourse, formed according to political, ideological, legal and socio-orientation goals.

Collective memory research examines how the process of individual memory formation is a social and collective experience, rather than one that is wholly psychological and individual. The stories that societies tell about themselves are an important part of this process, as they seek to socialize new members into the national community. But sometimes that national history is very difficult to deal with. Most collective memory research is based on a single case study approach. What is lacking in collective memory research, although not absent, are broader comparative studies. This article develops a general model for the process of collective memory formation, which I can then use in my ongoing empirical research into how several different authoritarian and democratic societies with Eastern and Western cultural traditions have dealt with their violent histories. The cases include Germany (East and West), Japan, Turkey, Yugoslavia and Spain. In this article, I develop a general model of collective memory formation while drawing upon these five cases to illustrate different points. While democratic societies have a greater potential for dealing more fully with their difficult histories, it is far from guaranteed that they will do so.

State-space models are a popular choice in modelling voting intentions and election results by using poll data. The presented multivariate state-space model attempts to go beyond random-walk or Kalman-filter approaches (with comparable performance to simple weighted survey averages) to the problem by introducing a long-short term event memory effect. This effect serves as reasonable explanation to the observation that the voter's share partially tends to reverse to the party's long-term trend after larger short term movements. Any event influencing the voter's share of a party is presumed to have a convex shaped effect decomposable into a short term effect due to e.g. media spreading and a smaller long term effect remaining despite overlay effects of new events and forgetting. This effect is modelled by a mixture of a random walk and two contrasting autoregressive processes. By also taking advantage of the widely observed effect that government parties tend to fall in voter's share, whereas the opposite effect is observed for opposition parties, mid- and long-term predictions of election outcomes can be considerably be improved. The Stan-model is fitted and evaluated on poll data from seven pollsters for the German national elections ("Bundestagswahl") from 1994 to 2017, where low double digits (out-of-sample) improvements in prediction performance can be seen between 3- and 18-months prior elections. By taking into account the pollsters house effects, their poll errors and even more importantly their correlations in poll errors, an appropriate and realistic estimation error can be propagated.

Operating systems have historically had to manage only a single type of memory device. The imminent availability of heterogeneous memory devices based on emerging memory technologies confronts the classic single memory model and opens a new spectrum of possibilities for memory management. Transparent data movement between different memory devices based on access patterns of applications is a desired feature to make optimal use of such devices and to hide the complexity of memory management to the end user. However, capturing memory access patterns of an application at runtime comes at a cost, which is particularly challenging for large-scale parallel applications that may be sensitive to system noise. In this work, we focus on the access pattern profiling phase prior to the actual memory relocation. We study the feasibility of using Intel's Processor Event-Based Sampling (PEBS) feature to record memory accesses by sampling at runtime and study the overhead at scale. We have implemented a custom PEBS driver in the IHK/-McKernel lightweight multi-kernel operating system, one of whose advantages is minimal system interference due to the lightweight kernel's simple design compared to other OS kernels such as Linux. We present the PEBS overhead of a set of scientific applications and show the access patterns identified in noise sensitive HPC applications. Our results show that clear access patterns can be captured with a 10% overhead in the worst-case and 1% in the best case when running on up to 128k CPU cores (2,048 Intel Xeon Phi Knights Landing nodes). We conclude that online memory access profiling using PEBS at large-scale is promising for memory management in heterogeneous memory environments. ; This work has been partially funded by MEXT's program for the Development and Improvement of Next Generation Ultra High- Speed Computer Systems under its subsidies for operating the Specific Advanced Large Research Facilities in Japan. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska- Curie grant agreement No 708566 (DURO). ; Peer Reviewed ; Postprint (author's final draft)

Operating systems have historically had to manage only a single type of memory device. The imminent availability of heterogeneous memory devices based on emerging memory technologies confronts the classic single memory model and opens a new spectrum of possibilities for memory management. Transparent data movement between different memory devices based on access patterns of applications is a desired feature to make optimal use of such devices and to hide the complexity of memory management to the end user. However, capturing memory access patterns of an application at runtime comes at a cost, which is particularly challenging for large-scale parallel applications that may be sensitive to system noise. In this work, we focus on the access pattern profiling phase prior to the actual memory relocation. We study the feasibility of using Intel's Processor Event-Based Sampling (PEBS) feature to record memory accesses by sampling at runtime and study the overhead at scale. We have implemented a custom PEBS driver in the IHK/-McKernel lightweight multi-kernel operating system, one of whose advantages is minimal system interference due to the lightweight kernel's simple design compared to other OS kernels such as Linux. We present the PEBS overhead of a set of scientific applications and show the access patterns identified in noise sensitive HPC applications. Our results show that clear access patterns can be captured with a 10% overhead in the worst-case and 1% in the best case when running on up to 128k CPU cores (2,048 Intel Xeon Phi Knights Landing nodes). We conclude that online memory access profiling using PEBS at large-scale is promising for memory management in heterogeneous memory environments. ; This work has been partially funded by MEXT's program for the Development and Improvement of Next Generation Ultra High- Speed Computer Systems under its subsidies for operating the Specific Advanced Large Research Facilities in Japan. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska- Curie grant agreement No 708566 (DURO). ; Peer Reviewed ; Postprint (author's final draft)

El pdf del artículo es el documento de trabajo. ; Although it is commonly accepted that most macroeconomic variables are non-stationary, it is often difficult to identify the source of the non-stationarity. Integrated processes and short-memory models with trending components, possibly affected by structural breaks, imply similar features in the data and, accordingly, are hard to distinguish. The goal of this article is to extend the classical testing framework of I(1) versus I(0) + trends and/or breaks by considering a more general class of models under the null hypothesis: fractionally integrated (FI) processes. The asymptotic properties of the proposed tests are derived and it is shown that they are very well-behaved in finite samples. An illustration using US inflation data is also provided. ; Financial support from the Spanish Government CICYT project no SEJ2006-00369, the BGSE Research Network and the Generalitat de Catalunya is gratefully acknowledged.

The study of memory, architecture, and urban space has been the interest ‎of ‎researchers ‎from the diverse fields around the world due to, the significance of dealing ‎with ‎memories ‎especially after the tragedy of the Second World War. Nations in Europe has chosen ‎not to ‎neglect ‎their past, moreover, overcoming it by strengthening the national identity. An ‎approach was clear in ‎the literature, art, further in the way of rebuilding their cities; that mainly ‎has reflected on the ‎value of urban spaces and their role in narrating the country's national ‎memory. Thanks to this ‎approach, which has supported the post-war European nations to invite ‎to an act of ‎ forgiveness rather than to forget. ‎ On the contrary, memory, in relation to architecture is a form of knowledge has been ‎neglected in Egypt, especially during the previous decades after the declaration of independence ‎from the colonial power, and since 1952 revolution. Recently, a rising debate about Egypt ‎national history and the need to renationalize the Egyptian historical consciousness has rapidly ‎grown up, due to the political transformation has occurred because of the 25th uprising, 2011, ‎which unveiled the power of public spaces in constituting the nation thoughts, especially Tahrir ‎square.‎ At the same time, this has unveiled the results of neglecting the past instead of overcoming it; unveiled a present carries the danger of conflict and repeating previous mistakes. Researchers, historians, politicians, governmental organization, have ‎worked in the purpose of revisiting the historical information, and have tried to document the ‎current transformation of the 25th uprising. There was a public demand for redesigning Tahrir square to reflect the ‎memory of the uprising as a symbol of the power of the public. However, after eight years, those ‎memories have faded as if the 25th uprising has never happened. ‎ Those circumstances are very relevant to the gap between urban design and the art of ‎memory-work, in the scientific field. Few studies in Egypt conducted the concept of memory in ‎relation to urban spaces, however, the matter requires more attention, to associate the need for renationalizing Egypt ‎memory, with viewing urban space as a mean of narrating the country's national memory and ‎reflecting the citizens' current thoughts, as a try of nearing the distances between ‎competing ‎narratives. Therefore, the research aims at developing a methodological framework that should ‎contribute to renationalizing memory through urban space. Further, benefiting from the German experience by investigating lessons to learn. That is based on the hypothesis that, although there is no fixed formula for all countries to renationalize the historical ‎consciousness of memory through urban spaces, lessons to be learned from Germany experience ‎could be a driving dimension when designing Egyptian urban spaces with a concept of memory ‎as an essential factor. To guide the validity of the study's hypothesis, a set of research questions are thus ‎formulated: Starting from why memory is an essential factor when designing urban spaces? ‎Regarding Egypt national memory, how it was constituted through history and how to read its ‎representation on urban spaces? Also, the study quests the means of nationalizing memory ‎through urban spaces? And What are the learned lessons from the German experience?‎ The study tries to answer those questions. Via an inductive ‎analytical ‎methodology ‎which ‎moves from the gap of knowledge and from a particular situation ‎in Egypt, to study the German ‎experience in renationalizing the concept of memory through urban spaces.‎ ‎ Within the scope of the study, exploring Egypt prevailing narratives and the inherited ‎concepts which influenced the national memory is essential. Moreover, the research develops ‎analytical political psychosocial model that could help reading memories in urban spaces, ‎memory's actors, and memory influences. To validate this model, case studies are analysed in ‎light of the concluded aspects. Consequently, the expected result is to infer broad general ‎learned ‎lessons for the Egyptian case. ‎ Research findings and conclusions answer the research questions, interpret literature ‎review, recommend some guide points to three target groups: first, practice field; to encourage ‎designers to value the national and collective memories when designing urban spaces. Second, to ‎ask policymakers to take the public participation into consideration, when taking decisions related to urban ‎development. Third, the thesis recommends future researches of urban memory that connect ‎theoretical information with the practice field. ‎ Finally, enhancing the memory-work in relation to the national narrative, conveying a meaningful message, when ‎designing urban spaces could encourage citizens to learn, to interact, and to dissolve boundaries ‎between the competing narratives in post-conflict societies.‎

This paper introduces an innovative social process model addressing population-wide measures of voter preferences that was tested on data from the 2016 US presidential election. Population-wide, "macroscopic" parameters are needed when privacy, ethics or regulatory constraints block "big data" techniques (e.g., in political contexts to counter "micro-targeting"). Confidence will be eroded if existing trend models and other macroscopic approaches frequently fail to predict outcomes, however campaign data reveal mathematical features that suggest a different possible approach. Given that the populations modelled exhibit self-organisation and memory when transmitting viewpoints, our model is based on mathematical representations of such processes. Its validation indicates the applicability and potential generalisability of this theoretical approach. In order to design a stochastic dynamics model of changing voter preferences, we evaluated probability models for transitions between possible system states (magnitudes of voter preferences), formulated the boundary task for probability density functions and derived a second-order non-linear differential equation incorporating self-organisation and memory. We find consistent dependencies between influences on the system and its reaction, and it is congruent with empirical data. The ability to use researchable global parameters indicates the potential for modelling electoral processes and wider applicability for complex social processes, avoiding dependence on "internal" variables. ; Post-print / Final draft