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The Triple Perils of Protectionism, Populism, and Authoritarianism -- No Longer a "Special" or Privileged Partnership -- Regaining a Competitive Advantage -- Dancing with the Chinese Dragon and the Indian Elephant -- Energy Development and Environmental Protection: The Elusive Search for "Balance" -- Democratic Alliances versus Authoritarians: Russia's and NATO's Future -- In Search of a Middle East Policy -- Finding Moorings in a Brewing Cyber Storm -- Immigration and Refugees -- Shaping Our Destiny.

Decision theory was developed to prescribe the consistent choice behavior under uncertainty of an ideal individual. The policy analysis context of organizational decision making, however, necessitates certain modifications to the fundamental decision theory in order to deal with the problems of group consensus, ill-defined objectives, & disparate information sources. The argument is presented that more attention must be given to the explicit formulation of judgment, & that, in particular, there has to be an integration of the methodology of forecasting into the decision-analytic framework. A consequence of adopting a decision-theoretic approach to forecasting is the apparent need to develop ways of synthesizing the set of available predictive methods in order to satisfy the subjectivist principle of total evidence utilization. The synthetic approach to forecasting is in contrast to the conventional selective method. A brief review of some operational methods of pursuing the synthetic approach is given. HA.

Part 1: GIS, GPS, RS and Precision Farming ; International audience ; In the course of analyzing and forecasting regional groundwater depth, its variation process complexity was ignored in the past, so that it was difficult to realize scientific management of groundwater resources. Aiming at the aforesaid defect, taking Jiansanjiang branch bureau as research platform, this paper diagnosed the complexity of each monthly groundwater depth series through using complexity measurement methods which include wavelet theory, fractal theory, Approximate Entropy and so on. The comprehensive measurement analysis results show that the complexity order of monthly groundwater depth series in the eighth district of Farm Nongjiang is highest in four farms of northern region. On that basis, the most complexity groundwater depth series combination stochastic forecasting model based on wavelet transform in northern region of Jiansanjiang branch bureau was set up. The model forecasting results show that local annual mean groundwater depth will be in a state of fluctuant lifting, and have considerable gap in comparison to groundwater ideal depth in the future. So, local government should reinforce the scientific management of groundwater. The research achievements break through the traditional study paradigm of hydrological forecasting, provide a research mode for studying regional hydrologic process, and provide scientific evidence for sustainable utilizing regional groundwater resources.

Abstract. We make use of a novel forecasting technique based on the Hotelling-Downs spatial framework to project vote outcomes in the second round of the two-round French presidential election system. In doing so we take advantage of the high degree of bimodality in the distribution of voter preferences to predict which candidates will make it into the second round. While our principal focus is on the 2007 election, we also look at the seven previous presidential elections in the French Fifth Republic, from 1965 through 2002.Résumé. Pour prédire le résultat du deuxième tour de scrutin des élections présidentielles françaises de 2007, nous avons fait appel à une nouvelle technique fondée sur le modèle spatial de Hotelling-Downs. En procédant ainsi, nous avons pris en compte le haut degré de bimodalité de la distribution des préférences pour pronostiquer lequel des deux candidats remporterait la victoire. Bien que nous ayons surtout centré notre attention sur l'élection présidentielle de 2007, nous avons aussi examiné les sept élections présidentielles antérieures de la Cinquième République, tenues de 1965 à 2002, afin de tester notre méthode et prédire ex ante les résultats de 2007.

The decarbonization and the climate change mitigation have become a priority for many countries and governments. One of the main tools for accomplishing these objectives is the growth of renewable generation sources in the power system, but their inclusion constitutes a great challenge for the network operation due to their high variability and their stochastic behavior. In this context, the management of the power system and microgrids can be treated as optimization problems in which the resources are operated with the aim of minimizing the cost function. This cost function and the corresponding operative restrictions depend on each specific situation, for example, on which are the power consumption requirements, how weak is the connection with the power grid, and how critical are the loads to be fed in the zone. In this sense, despite the large variety of optimization approaches, these have in common the importance of counting on a high-quality forecasting system for predicting the uncertainties of the microgrid (or network) to operate. The main existing approaches for predicting the uncertainties are deterministic and stochastic (which in many cases is also called probabilistic) forecasting. Considering the importance of forecasting systems for performing the optimization of microgrids and, in general, power networks, this doctoral thesis is focused on the design of a microgrid-oriented forecasting framework that includes a wide range of forecasting approaches, which makes possible its integration with other applications, for example, energy management optimization systems. This framework includes several deterministic and stochastic methods and is able to handle the training and selection of the models for performing the forecast according to the type of uncertainty representation that is required in each case. ; La descarbonización y la reducción del cambio climático se han convertido en una prioridad para muchos países y gobiernos. Una de las principales herramientas para lograr estos objetivos es aumentar ...

MODEL ESTIMASI WABAH DEMAM BERDARAH DAN PENANGANAN KADER JUMANTIK DI WILAYAH MALANG RAYA (KOTA MALANG, KABUPATEN MALANG DAN KOTA BATU)Estimation Model of DHF Epidemic and It's Handling of Jumantik Cadre at Malang Raya Region (Malang City, Malang District and Batu City)Moh. Hartono(1), Yoyok Heru P.I(2), Arif Rahman Hakim(3), Elief Yuniarti(4)(1,2,3)Politeknik Negeri Malang(4)Paramedis Puskesmas Dinoyo MalangEmail: 1)hartono@polinema.ac.idABSTRAKStudi tentang wabah DBD telah banyak dilaksanakan akan tetapi penelitian yang mengkombinasikan peramalan dan analisis multivariat yang berkaitan dengan penanganan DBD masih jarang dijadikan kajian. Penelitian ini mencoba mengkombinasikan kedua metode diatas dalam menekan wabah DBD khususnya di wilayah Malang Raya (meliputi Kota Malang, Kabupaten Malang dan Kota Batu). Sejauh ini kelemahan penanganan dari wabah DBD adalah masih kurang tepatnya waktu antisipasi dan cara penanganan pencegahan wabah DBD. Hasil yang diperoleh dari penelitian ini berupa model waktu antisipasi yang tepat dan cara penanganan mencegah berjangkitnya wabah DBD. Model peramalan dalam bentuk ARIMA musiman ( p , d , q ) ( P , D , Q )12 dengan berbagai variasi di setiap wilayah. Sedangkan hasil dari analisis multivariat yang melibatkan analisis faktor adalah terbentuknya 10 faktor baru yang berpengaruh terhadap kinerja Kader Jumantik. Diharapkan dengan kombinasi kedua metode ini dapat menjadi masukan bagi Pemerintah lokal khususnya di wilayah Malang Raya dalam menangani wabah DBD. Kata Kunci: Peramalan, Analisis Faktor dan Model ARIMA. ABSTRACTThe study of an epidemic of Dengue Hemorrhagic Fever ( DHF ) has been widely implemented , however, research on the combination of forecasting and factors analysis related to the handling of DHF is still small even rarely studied . This study tries to combine both methods in suppressing the development of dengue epidemic especially in Malang region which covers an area of Malang City, Malang District and Batu City . So far, Weakness of handling DHF is less precisely of anticipation timing and how to deal with dengue disease . The results of this study in the form of input anticipation appropiate time and the right way in preventing and combating dengue disease . Forecasting models in the form of seasonal ARIMA ( p , d , q ) ( P , D , Q )12 with diverse variations of each region . While the results of the factor analysis formed 10 new factors that affect the performance of its duties Jumantik cadres. Hopefully with this combination can be input for each Local Government in dealing with an epidemic of dengue feverKeywords: Forecasting, Factor Analysis, ARIMA Model

A new forecasting model, solved for Bayesian Perfect Equilibria, is introduced. It, along with several alternative models, is tested on data from the European Union. The new model, which allows for contingent forecasts and for generating confidence intervals around predictions, outperforms competing models in most tests despite the absence of variance on a critical variable in all but nine cases. The more proximate the political setting of the issues is to the new model's underlying theory of competitive and potentially coercive politics, the better the new model does relative to other models tested in the European Union context. [Reprinted by permission; copyright Sage Publications Ltd.]

We use a mean-adjusted Bayesian VAR model as an out-of-sample forecasting tool to test whether money growth Granger-causes inflation in the euro area. Based on data from 1970 to 2006 and forecasting horizons of up to 12 quarters, there is surprisingly strong evidence that including money improves forecasting accuracy. The results are very robust with regard to alternative treatments of priors and sample periods. That said, there is also reason not to overemphasize the role of money. The predictive power of money growth for inflation is substantially lower in more recent sample periods compared

This article presents a methodology for decomposing ex ante forecasting error into exogenous variable error, data revision error, model error and judgement error. This methodology is applied to the forecasts made by the National Institute in February 1975 and February 1976. The first section describes the methodology including the NIESR forecasting procedure. Then the NIESR model (with some of its problems) is discussed together with the data used in the study. The methodology for decomposing the forecasting error to 1975 is applied and a similar analysis presented for 1976. Some conclusions and a summary complete the article.

E The National Guard of Ukraine performs various combat-service missions. Their implementation complicates in the conditions of disturbances of social and political nature. An important function performed by the military management body of the National Guard of Ukraine in these conditions is to make a decision to perform combat-service missions during the conduct of operational and special actions. Among the main components of the decision-making process is the assessment and forecasting of the socio-political situation, which makes it possible to make an appropriate decision on a special operation. In the article it is determined a nature of assessment and forecasting of socio-political situation, its factors and conditions which impact on the NGU's activities either directly or indirectly. The levels of complexity of the socio-political situation and their content have been determined. The levels of variability of the socio-political environment have been established and the factors determining its essence have been established. The activities of the civil-military cooperation group are substantiated. The results of CIMIC team's activities during the table training exercises are provided in the article as follows: proposals on its activities were presented to deputy commander on personnel, performance results on estimation of civil environment which comprises of five tables "Estimation of civil environment" as well as results of constant monitoring of social and political situation. ; Національна гвардія України виконує різні за призначенням службово-бойові завдання. Виконання цих завдань ускладнюється в умовах виникнення масових заворушень суспільно-політичного характеру. Важливою функцією, яка виконується органом військового управління Національної гвардії України у цих умовах, є прийняття рішення на виконання службово-бойових завдань під час проведення оперативних і спеціальних дій (спеціальних операцій). Серед основних складових прийняття рішення є оцінювання і прогнозування суспільно-політичної обстановки, яке дозволяє прийняти адекватне до ситуації рішення на проведення спеціальної операції. У статті визначено сутність оцінювання та прогнозування суспільно-політичної обстановки, її чинники й умови, які безпосередньо або опосередковано впливають на діяльність Національної гвардії України. Визначено також рівні складності суспільно-політичної обстановки та їх зміст. Установлено рівні стабільності суспільно-політичної обстановки та встановлені чинники, які визначають її сутність. Обґрунтована діяльність групи цивільно-військового співробітництва. Наведено результати апробації роботи групи цивільно-військового співробітництва під час проведення командно-штабних навчань: створення нештатного складу групи, зміст пропозицій заступнику по роботі з особовим складом щодо діяльності групи, результати роботи групи щодо оцінки цивільного середовища, яка складається з п'яти таблиць, об'єднаних в формуляр «Оцінка цивільного середовища», та результати постійного моніторингу суспільно-політичної обстановки.

Women of childbearing age and pregnant women are susceptible to nutritional deficiencies of iron that can cause bleeding during childbirth. It is one of the causes of the high maternal mortality rate in Indonesia. The government, especially the Department of Health has a role in meeting the needs of the iron tablet, especially in the management of medicines. This study aims to estimate the amount of iron tablet needs for the period 2015, according to data distribution in 2013 and 2014; comparing needs iron tablet planned with the realization of the distribution in 2013 and 2014; as well as the correlations between the number of visits in the clinic by the number of prescriptions or the distribution of iron tablet needs. Quantitative research using the data distribution, transfer and planning proposals iron tablet, as well as the number of health center visits prescriptions. Data processing includes forecasting distributions based on the trend with seasonal index, forecasting needs with the method of consumption, and correlation test. The tools used are Microsoft Excel Data Analysis menu. The results of the estimated distribution in 2015 to 18 health centers with a buffer stock of 20% is 487 607 tablets that can be met from the stock early in 2015. The proportion of the distribution of the iron tablet planning for 18 health centers in 2013 was 57.48%, and in 2014 amounted to 53, 28% are caused not all pregnant women check-up and receive iron tablet in the clinic. Correlation coefficient values <0.4 indicate a weak correlation between the amount of iron tablet needs with the number of visits recipes

EU Horizon 2020 EuroSea project deliverable on identifying existing initiatives in foresight in ocean observation, emerging strategies and roadmaps. Led by European Marine Board. This report captures the major foresight initiatives and documents relevant for European ocean observation and forecasting. After introducing the definition of foresight and the scope of this report (chapter 1), more than 120 initiatives, strategies and roadmaps contributing to foresight in ocean observation are listed and briefly analysed (chapter 2). These include international frameworks and coordination efforts (chapter 2.1), European Union's frameworks and community coordination efforts (chapter 2.2), and ocean and sea basin relevant actors and efforts (chapter 2.3). Final remarks and opportunities are then provided (chapter 4).

Abstract. In this study, artificial neural networks, including both multilayer perception and the radial basis function neural networks, are applied for modeling and forecasting the maximum and time variation of storm surges at the Tanshui estuary in Taiwan. The physical parameters, including both the local atmospheric pressure and the wind field factors, for finding the maximum storm surges, are first investigated based on the training of neural networks. Then neural network models for forecasting the time series of storm surges are accordingly developed using the major meteorological parameters with time variations. The time series of storm surges for six typhoons were used for training and testing the models, and data for three typhoons were used for model forecasting. The results show that both neural network models perform very well for the forecasting of the time variation of storm surges.