Diachronic study of the floristic diversity of the Royal Mausoleum of Mauretania, Algeria

This study aimed to provide knowledge on the mural flora of the Royal Mausoleum of Mauretania. Through floristic surveys, we complied a catalog listing168 vascular plants belonging to 141 genera and 58 families. Asteraceae and Poaceae were the most dominant families, constituting 24.81% of the species. Dominant characteristics of this flora included therophytes (41.07%) and Mediterranean floristic elements (67.26%). To update the floristic list of the Mausoleum, we compared our data with 3 old lists from 1867, 1928 and 1985. The diachronic analysis reveals the persistance of 35 taxa representing 16.27% of 215 taxa listed since the first inventory, and the emergence of 30 new taxa (13.95%). The diversity of this wall flora is associated with changes in the landscape around the Mausoleum as well as its conservation status

PHARMACY STUDENTS’ OPINIONS OF USING MOCK QUESTIONS TO PREPARE FOR SUMMATIVE EXAMINATIONS

Objective: Mock questions are thought to benefit to students through help with learning, revealing specific areas of learning difficulties, practice examination timing and aiding a higher mark in the examination. The literature suggests practice questions have a direct impact on students’ academic performance and improving examination confidence. The aim of the study was to gather opinions of pharmacy students on using mock examinations and practice questions to prepare for summative examinations. Methods: Paper based questionnaires were distributed to all fourth year pharmacy students at the start of a university scheduled workshop session. The data was transcribed onto a Microsoft Excel™ spreadsheet and analysed. Results: Out of all fourth year pharmacy students 73% completed the questionnaire of which 91% had received access to mock questions but only 92% of those who had access used them. Common themes were identified; the benefits of using mock questions were ‘knowledge’, ‘examination style’ and ‘identification of weaknesses’. Furthermore, most participants chose ‘Year 3 Calculations exam’ (62%) as the most useful summative examination for which to use mock questions. Conclusion: Mock questions have a place in improving the performance of pharmacy students in examinations. The study results showed that the majority of participants who used mock questions found them to be useful in promoting learning, revealing specific areas of learning difficulties, improving awareness of examination structure, practicing their ability to apply knowledge to questions under examination conditions and to motivate students to revise more using better strategies

Day-ahead electricity price forecasting with emphasis on its volatility in Iran (GARCH combined with ARIMA models)

This paper provides a method to forecast day-ahead electricity prices based on autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedastic (GARCH) models. In the competitive power market environment, electricity price forecasting is an essential task for market participants. However, time series of electricity price has complex behavior such as nonlinearity, nonstationarity, and high volatility. ARIMA is suitable in forecasting, but it is not able to handle nonlinearity and volatility are existent in time series. Therefore, GARCH models are used to handle volatility in the in time series forecasting. The proposed method is computed using the daily electricity price data of Iran market for a five-year period from March 2013 to February 2018. The results reported in this paper illustrate the potential of the proposed ARMA-GARCH model and this combined model has been successfully applied to real prices in the Iranian power market

Day-ahead electricity price forecasting with emphasis on its volatility in Iran (GARCH combined with ARIMA models)

This paper provides a method to forecast day-ahead electricity prices based on autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedastic (GARCH) models. In the competitive power market environment, electricity price forecasting is an essential task for market participants. However, time series of electricity price has complex behavior such as nonlinearity, nonstationarity, and high volatility. ARIMA is suitable in forecasting, but it is not able to handle nonlinearity and volatility are existent in time series. Therefore, GARCH models are used to handle volatility in the in time series forecasting. The proposed method is computed using the daily electricity price data of Iran market for a five-year period from March 2013 to February 2018. The results reported in this paper illustrate the potential of the proposed ARMA-GARCH model and this combined model has been successfully applied to real prices in the Iranian power market

Software Architecture Design on National Level for Vaccination Planning and Dispensing System

This paper describes the software architecture design for vaccination planning and dispensing system to be used nationwide in public health-care departments and hospitals in response to the immunization improvement program in underdeveloped and poor countries. The system will help in managing all activities of child vaccination right from their birth by sending alerts to their parents via SMS or voice call in their local language. This automation will help keeping track of particular vaccination against which majority of children are not getting proper vaccination in time and analyze how many chances will be there that the particular disease will spread in that area based on different trends listed in Knowledge base of the health-care system

Non-Linearities in the relation between oil price, gold price and stock market returns in Iran: a multivariate regime-switching approach

Iran Stock Exchange is the most important component of Iran capital market and more attention has been paid to it in recent years. Many factors affect the Iran stock exchange. In this paper, the effects of oil price and gold price on stock market index are investigated and a three regime Markov Switching Vector Error Correction model is used to examine the nonlinear properties model during the period January 2003 to December 2014. The results of the study shows that the relationships between variables can be analyzed in three different status, so that the three regimes, respectively, represents the “great depression”, “mild depression” and “expansion” period. The results of the model show that the impact of oil price on stock returns is negative and significant in all three regimes; this means that with rising oil price, stock market returns are reduced. But the relationship between gold price and stock market returns varies during the period, according to market conditions. It means that positive shock inflicted on the price of gold in the short-run (10 months) leads to reduce the stock returns and in the medium-term and long-run, it leads to increase the stock returns

Modeling and forecasting the electricity price in Iran using wavelet-based GARCH model

The restructuring of Iranian electricity industry allowed electricity price to be determined through market forces in 2005. The main purpose of this paper is to present a method for modeling and forecasting the electricity prices based on complex features such as instability, nonlinear conditions, and high fluctuations in Iran during the spring 2013 and winter 2018. For this purpose, time series data of the daily average electricity price was decomposed into one approximation series (low frequency) and four details series (high frequency) utilizing the wavelet transform technique. The approximation and details series are estimated and predicted by ARIMA and GARCH models, respectively. Then, the electricity price is predicted by reconstructing and composing the forecasted values of different frequencies as a proposed method (Wavelet-ARMA-GARCH). The results demonstrated that the proposed method has higher predictive power and can forecast volatility of electricity prices more accurately by taking into consideration different domains of the time-frequency; although, more errors are produced if the wavelet transform process is not used. The mean absolute percentage error values of the proposed method during spring 2017 to winter 2018 are significantly less than that of the alternative method, and the proposed method can better and more accurately capture the complex features of electricity prices

Non-Linearities in the relation between oil price, gold price and stock market returns in Iran: a multivariate regime-switching approach

Iran Stock Exchange is the most important component of Iran capital market and more attention has been paid to it in recent years. Many factors affect the Iran stock exchange. In this paper, the effects of oil price and gold price on stock market index are investigated and a three regime Markov Switching Vector Error Correction model is used to examine the nonlinear properties model during the period January 2003 to December 2014. The results of the study shows that the relationships between variables can be analyzed in three different status, so that the three regimes, respectively, represents the “great depression”, “mild depression” and “expansion” period. The results of the model show that the impact of oil price on stock returns is negative and significant in all three regimes; this means that with rising oil price, stock market returns are reduced. But the relationship between gold price and stock market returns varies during the period, according to market conditions. It means that positive shock inflicted on the price of gold in the short-run (10 months) leads to reduce the stock returns and in the medium-term and long-run, it leads to increase the stock returns