Oil Exports and the Iranian Economy

This paper develops a long run growth model for a major oil exporting economy and derives conditions under which oil revenues are likely to have a lasting impact. This approach contrasts with the standard literature on the "Dutch disease" and the "resource curse", which primarily focus on short run implications of a temporary resource discovery. Under certain regularity conditions and assuming a Cobb Douglas production function, it is shown that (log) oil exports enter the long run output equation with a coefficient equal to the share of capital. The long run theory is tested using a new quarterly data set on the Iranian economy over the period 1979Q1-2006Q4. Building an error correction specification in real output, real money balances, inflation, real exchange rate, oil exports, and foreign real output, the paper finds clear evidence for two long run relations: an output equation as predicted by the theory and a standard real money demand equation with inflation acting as a proxy for the (missing) market interest rate. Real output in the long run is shaped by oil exports through their impact on capital accumulation, and the foreign output as the main channel of technological transfer. The results also show a significant negative long run association between inflation and real GDP, which is suggestive of economic inefficiencies. Once the effects of oil exports are taken into account, the estimates support output growth convergence between Iran and the rest of the world. We also find that the Iranian economy adjusts quite quickly to the shocks in foreign output and oil exports, which could be partly due to the relatively underdeveloped nature of Iran's financial markets.growth models, long run relations, Iranian economy, oil price, foreign output shocks, error correcting relations

Study on hydrophobic modification of basil seed gum-based (BSG) films by octenyl succinate anhydride (OSA)

The main objective of this study was to evaluate the changes in the characteristics of basil (Ocimum bacilicum L.) seed gum (BSG) films after modification with octenyl succinate anhydride (OSA) at different OSA:BSG weight ratios (WRs) of 0, 0.01 and 0.03. HPLC analysis revealed that the amount of added OS groups was 0%, 0.28%, and 1.01%, respectively. The introduction of OS groups along the BSG backbone was also confirmed by FT-IR and NMR analysis. XRD results revealed no significant change of physical state after modification. The contact angle (i.e., hydrophobicity) of modified BSG films was higher than that of control film. A decrease in the film solubility in water (29%) and water vapor permeability (50%), but an increase in density (14.28%) and opacity (21.37%) was observed after modification at the WR of 0.03. Also, the results showed that modification with OSA had no significant influence on the film thickness, moisture content and color properties. BSG modification with OSA at the WR of 0.03 significantly increased the flexibility and ultimate strength of respective films. The results of this study showed that OSA-modified BSG is a good candidate for developing edible films and coating with relatively high resistance to water

Oil Exports and the Iranian Economy

This paper develops a long run growth model for a major oil exporting economy and derives conditions under which oil revenues are likely to have a lasting impact. This approach contrasts with the standard literature on the "Dutch disease" and the "resource curse", which primarily focus on short run implications of a temporary resource discovery. Under certain regularity conditions and assuming a Cobb Douglas production function, it is shown that (log) oil exports enter the long run output equation with a coefficient equal to the share of capital. The long run theory is tested using a new quarterly data set on the Iranian economy over the period 1979Q1-2006Q4. Building an error correction specification in real output, real money balances, inflation, real exchange rate, oil exports, and foreign real output, the paper finds clear evidence for two long run relations: an output equation as predicted by the theory and a standard real money demand equation with inflation acting as a proxy for the (missing) market interest rate. Real output in the long run is shaped by oil exports through their impact on capital accumulation, and the foreign output as the main channel of technological transfer. The results also show a significant negative long run association between inflation and real GDP, which is suggestive of economic inefficiencies. Once the effects of oil exports are taken into account, the estimates support output growth convergence between Iran and the rest of the world. We also find that the Iranian economy adjusts quite quickly to the shocks in foreign output and oil exports, which could be partly due to the relatively underdeveloped nature of Iran’s financial markets.growth models, long run relations, Iranian economy, oil price and foreign output shocks, and error correcting relations

Modélisation intégratrice du traitement BigData

Nowadays, multiple actors of Internet technology are producing very large amounts of data. Sensors, social media or e-commerce, all generate real-time extending information based on the 3 Vs of Gartner: Volume, Velocity and Variety. In order to efficiently exploit this data, it is important to keep track of the dynamic aspect of their chronological evolution by means of two main approaches: the polymorphism, a dynamic model able to support type changes every second with a successful processing and second, the support of data volatility by means of an intelligent model taking in consideration key-data, salient and valuable at a specific moment without processing all volumes of history and up to date data.The primary goal of this study is to establish, based on these approaches, an integrative vision of data life cycle set on 3 steps, (1) data synthesis by selecting key-values of micro-data acquired by different data source operators, (2) data fusion by sorting and duplicating the selected key-values based on a de-normalization aspect in order to get a faster processing of data and (3) the data transformation into a specific format of map of maps of maps, via Hadoop in the standard MapReduce process, in order to define the related graph in applicative layer.In addition, this study is supported by a software prototype using the already described modeling tools, as a toolbox compared to an automatic programming software and allowing to create a customized processing chain of BigDataDans le monde d’aujourd’hui de multiples acteurs de la technologie numérique produisent des quantités infinies de données. Capteurs, réseaux sociaux ou e-commerce, ils génèrent tous de l’information qui s’incrémente en temps-réel selon les 3 V de Gartner : en Volume, en Vitesse et en Variabilité. Afin d’exploiter efficacement et durablement ces données, il est important de respecter la dynamicité de leur évolution chronologique au moyen de deux approches : le polymorphisme d’une part, au moyen d’un modèle dynamique capable de supporter le changement de type à chaque instant sans failles de traitement ; d’autre part le support de la volatilité par un modèle intelligent prenant en compte des données clé seulement interprétables à un instant « t », au lieu de traiter toute la volumétrie des données actuelle et historique.L’objectif premier de cette étude est de pouvoir établir au moyen de ces approches une vision intégratrice du cycle de vie des données qui s’établit selon 3 étapes, (1) la synthèse des données via la sélection des valeurs-clés des micro-données acquises par les différents opérateurs au niveau de la source, (2) la fusion en faisant le tri des valeurs-clés sélectionnées et les dupliquant suivant un aspect de dé-normalisation afin d’obtenir un traitement plus rapide des données et (3) la transformation en un format particulier de carte de cartes de cartes, via Hadoop dans le processus classique de MapReduce afin d’obtenir un graphe défini dans la couche applicative.Cette réflexion est en outre soutenue par un prototype logiciel mettant en oeuvre les opérateurs de modélisation sus-décrits et aboutissant à une boîte à outils de modélisation comparable à un AGL et, permettant une mise en place assistée d'un ou plusieurs traitements sur BigDat

Application of Arbuscular Mycorrhizal Fungi on Zinc and Iron Concentration in Wheat under Cadmium Stress

For evaluate the application of a bio-fertilizer on zinc and iron concentration in wheat, under cadmium stress, a greenhouse experiment was conducted in factorial design with three replications. Treatments included Arbuscular Mycorrhiza levels (Control, Glomus mosseae and Glomus intraradices) and cadmium with six levels (0, 5, 10, 20,40 and 80  mg.kg-1). The measured data showed that the effects of treatments were significant on zinc and iron concentration. Arbuscular mycorrhizal fungi increasing zinc and iron concentration in plant. Glomus intraradices species increased zinc concentration in shoot and root % 252 and %222, respectively.  But Glomus mosseae species increased iron concentration in shoot and root % 148 and %170, respectively

Pixel steganography method for grayscale image steganography on colour images

The process of hiding secret data within a host signal is known as steganography; its design parameters are imperceptibility, concealment capacity, and recovered data quality. A case of images, one of the existing methods based on modification of the host image pixels is called Block Pixel Hiding Method (BPHM), which has good imperceptibility and high-capacity concealment but does not guarantee the quality of the secret image recovered. This article proposes a method that improves results BPHM based on band selection and search algorithm global called Improved Pixel Hiding Method (IPHM). According to the simulations carried out, the results obtained with IPHM are better than those obtained with BPHM. They are similar to one of the more popular methods in imaging steganography known as Quantization Index Modulation (QIM). Steganography is the method of hiding hidden data within a host signal, with imperceptibility, concealment capacity, and retrieved data quality as design criteria. In the case of images, Block Pixel Hiding Method (BPHM) is one of the available methods based on modifying the host picture pixels, which has good imperceptibility and high-capacity concealment but does not guarantee the quality of the hidden picture recovered. Improved Pixel Hiding Method is a method proposed in this article that improves BPHM outcomes by using band selection and a global search algorithm (IPHM). The results obtained using IPHM are better than those achieved with BPHM, according to simulations. They're related to Quantization Index Modulation, which is one of the most widely used picture steganography techniques (QIM)

EDUCATION IN SCHOOLS OF CHRISTIAN DENOMINATIONS AND FOREIGN MISSIONS IN THE KARAK REGION DURING THE PERIOD OF OTTOMAN ORGANIZATIONS 1864-1918 A.D.

Attention to education in the schools of Christian denominations and foreign missionary missions formed the basis for the modern renaissance in eastern Jordan, and Ottoman reforms in the second half of the nineteenth century AD contributed to advancing education among members of the Christian denominations who were subjects of the Ottoman Empire in eastern Jordan to be They have their own educational institutions under their supervision and management. The system of Ottoman privileges allowed foreign countries to build educational institutions and spread missionary missions throughout the Ottoman Empire, including Karak.Attention to education in the schools of Christian denominations and foreign missionary missions formed the basis for the modern renaissance in eastern Jordan, and Ottoman reforms in the second half of the nineteenth century AD contributed to advancing education among members of the Christian denominations who were subjects of the Ottoman Empire in eastern Jordan to be They have their own educational institutions under their supervision and management. The system of Ottoman privileges allowed foreign countries to build educational institutions and spread missionary missions throughout the Ottoman Empire, including Karak

Risk assessment of noise pollution by analyzing the level of sound loudness resulting from central traffic in Shiraz

Background: Today, the effects of environmental pollution on human life and human needs, which reduces the level of community health caused by traffic noise in large cities, are clearly visible by creating irritation and pathogenic conditions. The aim of this study was to assess the risk of noise pollution resulted from central traffic in Shiraz by analyzing its indicators and related components. Methods: By specifying the high traffic jam in Shiraz, the sound and its frequency in 156 points of the city were analyzed using a sound analyzer (Tes-1358C model). The sound pressure levels (LA and LP) and the one and one-third octave band were continuously measured in A and C networks. Then, data were extracted and analyzed using Excel 2016 and Minitab 18.1. Eventually, phon and sone indexes were calculated for the heavy traffic jam in some of the central streets of Shiraz and the results were statistically calculated and their charts were prepared with comfort disturbance ranges. Results: The highest harmful frequency of traffic in Shiraz was 50 Hz and 83.3 dB. The sound pressure level ranged from 70 to 92.7 dB in network A and 87.8 dB in network C. The maximum sound level was 87 phon and the maximum sone was 26 at 14 stations. Conclusion: According to the results, the sound pressure levels exceeded the environmental standards of Iran and the values of phon and sone were higher than the standard of comfort at night and day. Keywords: Noise pollution, Environmental pollution, Loudness perception, Health risk assessment, Shiraz

An Effective Preprocessing Step Algorithm in Text Mining Application

Text mining was a process of mining the significant information from the text documents. Any text mining system was created its process by preprocessing step; which involve tokenization, stop words removal, stemming and finally creating term frequency and inverse document frequency matrix (TF-IDF matrix). These steps provide the highest time consuming stage in knowledge discovery. The proposed method tries to build effective preprocessing step to even win area of memory space and time requirements. That by proposed a method for improved stop words removal algorithm and improved stemming algorithm based porter stemming algorithm. The proposed method is tested in two levels, first level uses only vector space model which based on used traditional stop words removal and with traditional porter stemming and the second level uses vector space model with combined features of improved stop words removal algorithm and improved stemming algorithm. The results show that using second level as effective preprocessing step for text mining application achieves good performance from reducing storage space used in memory about 10% and the processing time become faster which achieves good performance to build the final TF-IDF matrix