Forecasting Inflation in Tunisia Using Dynamic Factors Model

This work presents a forecasting inflation model using a monthly database. Conventional models for forecasting inflation use a small number of macroeconomic variables. In the context of globalization and dependent economic world, models have to account a large number of information. This model is the goal of recent research in the various industrialized countries as well as developing countries. With Dynamic Factors Model the forecast values are closer to actual inflation than those obtained from conventional models in the short term. In our research we devise the inflation in to “free inflation and administered inflation” and we test the performance of the DFM in different types of inflation namely administered and free inflation. We found that dynamic factors model leads to substantial forecasting improvements over simple benchmark regressions

Forecasting Inflation in Tunisia Using Dynamic Factors Model

This work presents a forecasting inflation model using a monthly database. Conventional models for forecasting inflation use a small number of macroeconomic variables. In the context of globalization and dependent economic world, models have to account a large number of information. This model is the goal of recent research in the various industrialized countries as well as developing countries. With Dynamic Factors Model the forecast values are closer to actual inflation than those obtained from conventional models in the short term. In our research we devise the inflation in to “free inflation and administered inflation” and we test the performance of the DFM in different types of inflation namely administered and free inflation. We found that dynamic factors model leads to substantial forecasting improvements over simple benchmark regressions

Forecasting Inflation in Tunisia into instability: Using Dynamic Factors Model a two-step based on Kalman filtering

This work presents a forecasting inflation model using a monthly database. Conventional models for forecasting inflation use a small number of macroeconomic variables. In the context of globalization and dependent economic world, models have to account a large number of information. This model is the goal of recent research in the various industrialized countries as well as developing countries. With Dynamic Factors Model the forecast values are closer to actual inflation than those obtained from conventional models in the short term. In our research we devise the inflation in to “free inflation and administered inflation” and we test the performance of the DFM into instability (before and after revolution) in different types of inflation and trend inflation namely administered and free inflation. We found that dynamic factors model with factor instability leads to substantial forecasting improvements over dynamic factor model without instability factor in period after revolution

Forecasting Inflation in Tunisia into instability: Using Dynamic Factors Model a two-step based on Kalman filtering

This work presents a forecasting inflation model using a monthly database. Conventional models for forecasting inflation use a small number of macroeconomic variables. In the context of globalization and dependent economic world, models have to account a large number of information. This model is the goal of recent research in the various industrialized countries as well as developing countries. With Dynamic Factors Model the forecast values are closer to actual inflation than those obtained from conventional models in the short term. In our research we devise the inflation in to “free inflation and administered inflation” and we test the performance of the DFM into instability (before and after revolution) in different types of inflation and trend inflation namely administered and free inflation. We found that dynamic factors model with factor instability leads to substantial forecasting improvements over dynamic factor model without instability factor in period after revolution

IOT et Cloud Computing : état de l'art

International audienceInternet of things (IOT) rend les objets simples des objets intelligents capables de transférer des données sur un réseau sans interaction humaine. Les données générées par ces objets sont en temps réel et non structurées, ce qui nécessite une structure décentralisée permettant le stockage et l’analyse de cette grande quantité de données. L’intégration du Cloud Computing et IOT devient importante pour plusieurs raison : quantité de données générées, besoin d'avoir le privilège d'utilisation des ressources virtuelles et la capacité de stockage, aussi la possibilité de créer plus d'utilité à partir des données générées par IoT et le développement des applications intelligentes pour les utilisateurs. Dans cet article nous présentons une revue de littérature sur l’intégration de l’internet of things et le Cloud Computing et les défis de cette intégration

A one-dimensional polymeric cobalt(III)–potassium complex with 18-crown-6, cyanide and porphyrinate ligands

The reaction of CoII(TpivPP) {TpivPP is the dianion of 5,10,15,20-tetrakis[2-(2,2-dimethylpropanamido)phenyl]porphyrin} with an excess of KCN salts and an excess of the 18-crown-6 in chlorobenzene leads to the polymeric title compound catena-poly[[dicyanido-2κ2C-(1,4,7,10,13,16-hexaoxacyclooctadecane-1κ6O){μ3-(2α,2β)-5,10,15,20-tetrakis[2-(2,2-dimethylpropanamido)phenyl]porphyrinato-1κO5:2κ4N,N′,N′′,N′′′:1′κO15}cobalt(III)potassium] dihydrate], {[CoK(CN)2(C12H24O6)(C64H64N8O4]·2H2O}n. The CoIII ion lies on an inversion center, and the asymmetric unit contains one half of a [CoIII(2α,2β-TpivPP)(CN)2]− ion complex and one half of a [K(18-C-6]+ counter-ion (18-C-6 is 1,4,7,10,13,16-hexaoxacyclooctadecane), where the KI ion lies on an inversion center. The CoIII ion is hexacoordinated by two C-bonded axial cyanide ligands and the four pyrrole N atoms of the porphyrin ligand. The KI ion is chelated by the six O atoms of the 18-crown-6 molecule and is further coordinated by two O atoms of pivalamido groups of the porphyrin ligands, leading to the formation of polymeric chains running along [011]. In the crystal, the polymeric chains and the lattice water molecules are linked by N—H...O and O—H...N hydrogen bonds, as well as weak C—H...O, O—H...π and C—H...π interactions into a three-dimensional supramolecular architecture

Di-μ-azido-bis(μ-1,4,7,10,13,16-hexaoxacyclooctadecane)bis(5,10,15,20-tetraphenylporphyrinato)dicadmiumdisodium

The asymmetric unit of the title compound, [Cd2Na2(N3)2(C44H28N4)2(C12H24O6)2], consists of one half of the dimeric complex; the tetranuclear molecule lies about an inversion centre. The CdII atom is coordinated by the four pyrrole N atoms of the 5,10,15,20-tetraphenylporphyrinate ligand and one N atom of the axial azide ligand in a square-pyramidal geometry. The azide group is also linked to the NaI atom, which is surrounded by one 18-crown-6 molecule and additionally bonded to a second 18-crown-6 molecule trans to the azide group. The porphyrin core exhibits a major doming distortion (∼40%) and the crystal structure is stabilized by weak C—H...π interactions. The molecular structure features weak intramolecular hydrogen bonds: two O—H...O interactions within the 18-crown-6 molecule and one C—H(18-crown-6)...N(azido) contact

Effect of heat transfer on shear flow around an obstacle

The study of heat transfer on shear flows around an obstacle presents a great interest in determination of the influence of water on buildings and port infrastructures. The variation of the inlet temperatures and the influence of an obstacle placed at the bottom of a channel were analyzed. The obtained results supported by numerical simulations have shown that the doubling of the fluid inlet temperature significantly modifies all the dynamic characteristics of the shear flow. Pressure distribution, turbulent kinetic energy, dissipation rate, turbulent viscosity, and strain rate in the water channel were exposed. These results can help us to better exploit the flow of hot water discharged by power plants